Betting MMA Over/Unders For Rounds Fought

Can Anyone can help me out this question, might sound dumb but with a Over 2.5 bet, it needs to pass 2.5 mins of the third round right? So does that mean has to go to a decision but what if there is a stoppage over the 2.5 mark in round 3 ?

submitted by joehowardddd to UFCbettingdiscussion3 [link] [comments]

ELI5: How does over-under betting work? (When people say the over-under on this is ___, what do those numbers mean?)

Over-under bets. How do they work?
submitted by BarbaBarber to explainlikeimfive [link] [comments]

Don't be fooled. This IS The Market Crash: My DD.

I've been researching this a LOT lately because I didn't want to get caught in it. Looking at trends and past data. I believe, strongly, that we're in the middle of the market crash. I used my knowledge and was able to fully exit my entire $500k portfolio on Tuesday, maintaining all my gains. I've even taken a sizeable position in SPY puts ($50k worth of Dec $260). I got my close friends out (well the ones who listened) on Friday at the first sign of positive movement.
First of all, a little history lesson on the Minksy Bubble. It's basically a theory for how market bubbles happen. It occurs in 5 steps. I will outline what they are in basic and how the current market looks in relation.
  1. Displacement: This is the beginning of a new paradigm where the market changes in a big way. For this, that was the Coronavirus. This took place between February to April.
  2. Boom: Increase in spending begins and major gains start to be made. Media attention and market involvement begin to increase. Currently, we've seen a HUGE increase in retail traders (who are extremely volatile) and massive media attention toward the stock market as it relates to corona news as well as stimulus and recovery speed gains. This took place between April and July.
  3. Euphoria: People stop caring about any sort of reasonable investment strategy and just start throwing money at stuff. Tesla is a fantastic example of this, but many other stocks in the tech sector are guilty of this. July was the beginning of this phase as Tesla saw insane growth within a few week period and other companies followed suit very quickly. This continued into late August with Apple and Tesla going to stupid prices after their splits, and all the other big tech names reaching wild valuations.
  4. Profit Taking: Smart money starts withdrawing funds from the market as they prepare for the crash. We are seeing record insider selling, but most publicly, it began with Tesla announcing they would sell $5bn in new shares. Their second biggest shareholder then announced they were conveniently "rebalancing" their portfolio to sell many Tesla shares as well. This was nothing more than a ploy to pull money out without crashing the market, even though it did anyway. I will get more in depth on this phase later. The biggest catalyst was Softbank, though, and that leads me to the final stage.
  5. Panic Selling: This is when people start to exit en masse in order to recoup whatever they can. We are currently witnessing this. The last few days have been a trainwreck on the market, wiping out August's gains entirely.
Now I know you want to say "well look at today. We're up 2% in the S&P!" This is par for the course on a crash. With the Corona crash, these were the rough day to day movement patterns (I'm using Corona as an example for its shortness/simplicity but all crashes have similar patterns):
Of those gain days, the first was a slowdown, but the second was a change of 4.8% in S&P/SPY from an open of 294 to a close of 309. Consecutive, positive days occurred during every major crash. We can see that being mirrored today and will likely see more upward mobility before more big money starts exiting. Don't be fooled by positive days. That does NOT indicate the crash is over. Novices tend to think crashes are a short event and that they should hold through them because they missed the boat. Crashes take weeks, minimum, but usually months, if not years, to become fully realized. Covid's crash is the fastest we've had at one month.
Another trend I've noticed is that these market bubbles are happening and recovering faster and faster. The late 80's Japanese market crash took 6 years to play out. The 2000 dotcom bubble was 4 years. The Chinese 2007 bubble took 2 years. The 2008 oil bubble took 1 year. On the flipside, the 2007 housing bubble took 5 years. The 2008 energy bubble took 3 years. We're about 6 months into this current bubble, but more if you account for any forming bubble from before covid. Maybe this means nothing, but I thought it was worth mentioning.
Bubble analysts always say there is a warning sign prior to a true collapse. I've been seeing these called "violent shake-offs." Most crashes get one, but some get two. We had one with the June mini-crash. One could argue that this current crash could be a violent shake-off. I'll get to the alternate scenario later. Assuming it's not, which I don't think it is, we move to the final trigger, the catalyst.
Catalysts: These are are things required to trigger a bubble collapse. Almost every bubble has had some notable catalyst(s) to trigger the rapid decline. As mentioned in Profit Taking, we've had three catalysts occur so far that triggered panic selling. New Tesla shares, secondary Tesla offloading, and Softbank. They are the big one and who I will focus on for a minute.
To those who don't know, Softbank bought $4 billion in options during the early days of the market post-covid. These options are worth a fortune right now ($30bn estimated), but they have to be sold in order to be fully capitalized on. What everyone is afraid of is Softbank doing just that, or worse, for shareholders: holding through a market crash and losing it all. In the movie, Margin Call (great movie), a hedge fund got wind of the housing market crash before everyone else and ultimately sold EVERYTHING they had in order to get ahead of it, single handedly beginning the inevitable market crash. To be fair, this is a fictional movie and they had a portfolio of like a trillion, but it's really just mentioned to illustrate my point. Softbank has to exercise these options, which have strike prices likely WAY below market value. If they sell those shares, they could easily double their investment, even through a crash. The problem is that people got so spooked by this revelation that Softbank lost over $15 billion in market cap (currently at $112bn). Had this not happened, the speed at which we decline would've been much slower. They have to make those losses up now. You know what would do that? Exercising all their options and selling them for market gains.
They can't keep those options forever, either. At best they have 2 years. Softbank will try very hard to sell all those off without crashing the market, but if it keeps dipping, they will become more desperate and start selling them more frantically, promoting a panic selling cycle. And what are we in? A panic selling cycle.
If this cycle continues with Softbank, more will tack on and we'll see this bubble continue to collapse. If it can hold a recovery this week, it might survive, but of course, I don't think it will. The end of day today really showed that people are afraid and that given any opportunity, selloff will occur. I think this IS the crash. But, I could be wrong. That brings me to the second and third catalysts.
Commercial Real Estate Crash: The eviction crisis is a real threat to our economy. It's brushed under the rug pretty heavily, pointing to the home real estate market and its gains, but the damage is done. Most major commercial real estate buildings, especially apartments, are in disarray. Go look around and see the kinds of deals your local apartments are offering. Where I am, I'm seeing up to 2 months of free rent in some places. I've never seen that before. Everyone is desperate for paying tenants. Most commercial properties can weather a bit of this kind of thing, but we haven't seen anything like this. Small businesses are shutting down, new businesses are not opening. No one is shopping. Who replaces those lost tenants? All these properties are heavily in debt. That's how the industry works, for the most part. Entrepreneurs and builders finance all projects because they are seen as very safe and it's a rule of thumb to never use your own money for investment. The margins had become abysmal before corona. I once looked into buying commercial real estate and found that I would only cover the expenses and have to solely rely on the property value increasing, to make anything worthwhile. This will cause properties to bleed out extremely fast. There is a commercial real estate collapse coming, likely within 6 months, and it will compound any damage the tech bubble has done. Don't forget that this isn't strictly a US problem. This is a worldwide problem.
Vacation Industry Crash: Many countries around the world rely on a steady influx of visitors in order to keep their businesses afloat. This, in turn, boosts GDP. Malaysia, for instance, is a place I personally visited, during Covid, and it was a desolate wasteland. Most shops had employees literally standing outside waiting for a single customer. It was like this for blocks and blocks. Huge tourist attractions were completely devoid of people. It's only a matter of time before our lack of flying catches up to these already poor and extremely hard to maintain businesses. The country in Malaysia I visited had a notoriously low success rate for new restaurants, during the best of times. Now, they are lucky to get any customers. That affect will bleed into the second catalyst. More businesses going under, causing commercial real estate to lose tenants with no one to replace them, causing those buildings to go under, causing banks to be stuck with a boat load of vacant, unprofitable properties, causing them to go under.
Even with a vaccine, we won't go back to normal fast enough to recover the losses. The airline industry is reporting that they don't estimate returns to normal until late 2021, early 2022. Do you think a random Joe has enough liquidity to keep his business running that long at extreme drought? The people at the bottom of the chain, consumers and small business owners, were never prepared to have a cash supply on hand for this kind of hit to their lives. That is going to trickle up to the top and when it does, goodbye market.
Of course, there's also the US election, but that will be a small catalyst as far as I'm concerned.
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Other notable indicators/insights that things don't look good:
  1. Market cap to GDP was 2:1 at peak. The dotcom crash was 1.4 and the recession was 1.1. Currently 1.77:1.
  2. Google trend results for "Market Crash" are trending up. Last week, which only accounted for 3 days, really, already topped the June mini-crash.
  3. An analyst who witnessed the Japanese crash of the 1980's believes this will be the biggest crash we've ever seen.
  4. EVs are the new dotcom company. Many will fail as car creation proves to be more difficult than anticipated.
  5. High growth, high revenue companies do not automatically equate to sustainable companies, despite stock prices pretending they do. For example, Sea Ltd. doubled revenue but also doubled expenses in Q2 2020. eToys is a prime example of this, from the dotcom bust era. Had huge revenue, but their expenses could not be lowered to a sustainable level and went out of business, despite the business model making sense and the revenue stream looking really good.
  6. The PE ratio of the market is above 30, which has historically always resulted in a market crash.
  7. Apple saw 12 million shares exited at the bell today. Prior to that was around 600k peak. This happened for MOST tech stocks.
  8. If you bought Microsoft at peak dotcom bust, you would have to wait 10 years to breakeven (longer if you account for inflation losses). That kind of stagnation is what we're looking at, even today.
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This does NOT mean the entire market will crash. Quite the contrary. Yes, most stocks will go down as the market collapses in overvalued sectors (TECH) brings down the whole thing, but they will stay high if priced fairly. Most epicenter is priced within a reasonable area, for instance, and will weather the storm quite well. At least, until the commercial real estate market collapse catches up to them.
Plan accordingly, set stop losses, and do your own research. I don't expect you to just follow my information blindly. I may have gotten things wrong or mixed some wires. You need to figure this out on your own and make your own judgement call. I simply hope to raise awareness for what I believe is a market crash so that people don't lose their shirt during this. I hope I'm wrong, though I'm literally betting with my money that I'm not.
Good luck.
submitted by ItsAllJustASickGame to stocks [link] [comments]

This week 12 yrs ago--Lehman Bros collapsed......(Best Interest) Explaining the Big Short and the 2008 Crisis

edit: thanks for the awards. I'd be a dick to take credit. Go check out the one-man-band who actually wrote it---I've been reading for a couple months, good stuff https://bestinterest.blog/explain-the-big-short/
(Best Interest) This post will explain the Big Short and the 2008 subprime mortgage collapse in simple terms.
This post is a little longer than usual–maybe give yourself 20 minutes to sift through it. But I promise you’ll leave feeling like you can tranche (that’s a verb, right?!) the whole financial system!
Key Players
First, I want to introduce the players in the financial crisis, as they might not make sense at first blush. One of the worst parts about the financial industry is how they use deliberately obtuse language to explain relatively simple ideas. Their financial acronyms are hard to keep track of. In order to explain the Big Short, these players–and their roles–are key.
Individuals, a.k.a. regular people who take out mortgages to buy houses; for example, you and me!
Mortgage lenders, like a local bank or a mortgage lending specialty shop, who give out mortgages to individuals. Either way, they’re probably local people that the individual home-buyer would meet in person.
Big banks, such as Goldman Sachs and Morgan Stanley, who buy lots of mortgages from lenders. After this transaction, the homeowner would owe money to the big bank instead of the lender.
Collateralized debt obligations (CDOs)—deep breath!—who take mortgages from big banks and bundle them all together into a bond (see below). And just like before, this step means that the home-buyer now owes money to the CDO. Why is this done?! I’ll explain, I promise.
Ratings agencies, whose job is to determine the risk of a CDO—is it filled with safe mortgages, or risky mortgages?
Investors, who buy part of a CDO and get repaid as the individual homeowners start paying back their mortgage.
Feel lost already? I’m going to be a good jungle guide and get you through this. Stick with me.
Quick definition: Bonds
A bond can be thought of as a loan. When you buy a bond, you are loaning your money. The issuer of the bond is borrowing your money. In exchange for borrowing your money, the issuer promises to pay you back, plus interest, in a certain amount of time. Sometimes, the borrower cannot pay the investor back, and the bond defaults, or fails. Defaults are not good for the investor.
The CDO—which is a bond—could hold thousands of mortgages in it. It’s a mortgage-backed bond, and therefore a type of mortgage-backed security. If you bought 1% of a CDO, you were loaning money equivalent to 1% of all the mortgage principal, with the hope of collecting 1% of the principal plus interest as the mortgages got repaid.
There’s one more key player, but I’ll wait to introduce it. First…
The Whys, Explained
Why does an individual take out a mortgage? Because they want a home. Can you blame them?! A healthy housing market involves people buying and selling houses.
How about the lender; why do they lend? It used to be so they would slowly make interest money as the mortgage got repaid. But nowadays, the lender takes a fee (from the homeowner) for creating (or originating) the mortgage, and then immediately sells to mortgage to…
A big bank. Why do they buy mortgages from lenders? Starting in the 1970s, Wall St. started buying up groups of loans, tying them all together into one bond—the CDO—and selling slices of that collection to investors. When people buy and sell those slices, the big banks get a cut of the action—a commission.
Why would an investor want a slice of a mortgage CDO? Because, like any other investment, the big banks promised that the investor would make their money back plus interest once the homeowners began repaying their mortgages.
You can almost trace the flow of money and risk from player to player.
At the end of the day, the investor needs to get repaid, and that money comes from homeowners.
CDOs are empty buckets
Homeowners and mortgage lenders are easy to understand. But a big question mark swirls around Wall Street’s CDOs.
I like to think of the CDO as a football field full of empty buckets—one bucket per mortgage. As an investor, you don’t purchase one single bucket, or one mortgage. Instead, you purchase a thin horizontal slice across all the buckets—say, a half-inch slice right around the 1-gallon mark.
As the mortgages are repaid, it starts raining. The repayments—or rain—from Mortgage A doesn’t go solely into Bucket A, but rather is distributed across all the buckets, and all the buckets slowly get re-filled.
As long as your horizontal slice of the bucket is eventually surpassed, you get your money back plus interest. You don’t need every mortgage to be repaid. You just need enough mortgages to get to your slice.
It makes sense, then, that the tippy top of the bucket—which gets filled up last—is the highest risk. If too many of the mortgages in the CDO fail and aren’t repaid, then the tippy top of the bucket will never get filled up, and those investors won’t get their money back.
These horizontal slices are called tranches, which might sound familiar if you’ve read the book or watched the movie.
So far, there’s nothing too wrong about this practice. It’s simply moving the risk from the mortgage lender to other investors. Sure, the middle-men (banks, lenders, CDOs) are all taking a cut out of all the buy and sell transactions. But that’s no different than buying lettuce at grocery store prices vs. buying straight from the farmer. Middle-men take a cut. It happens.
But now, our final player enters the stage…
Credit Default Swaps: The Lynchpin of the Big Short
Screw you, Wall Street nomenclature! A credit default swap sounds complicated, but it’s just insurance. Very simple, but they have a key role to explain the Big Short.
Investors thought, “Well, since I’m buying this risky tranche of a CDO, I might want to hedge my bets a bit and buy insurance in case it fails.” That’s what a credit default swap did. It’s insurance against something failing. But, there is a vital difference between a credit default swap and normal insurance.
I can’t buy an insurance policy on your house, on your car, or on your life. Only you can buy those policies. But, I could buy insurance on a CDO mortgage bond, even if I didn’t own that bond!
Not only that, but I could buy billions of dollars of insurance on a CDO that only contained millions of dollars of mortgages.
It’s like taking out a $1 million auto policy on a Honda Civic. No insurance company would allow you to do this, but it was happening all over Wall Street before 2008. This scenario essentially is “the big short” (see below)—making huge insurance bets that CDOs will fail—and many of the big banks were on the wrong side of this bet!
Credit default swaps involved the largest amounts of money in the subprime mortgage crisis. This is where the big Wall Street bets were taking place.
Quick definition: Short
A short is a bet that something will fail, get worse, or go down. When most people invest, they buy long (“I want this stock price to go up!”). A short is the opposite of that.
Certain individuals—like main characters Steve Eisman (aka Mark Baum in the movie, played by Steve Carrell) and Michael Burry (played by Christian Bale) in the 2015 Oscar-nominated film The Big Short—realized that tons of mortgages were being made to people who would never be able to pay them back.
If enough mortgages failed, then tranches of CDOs start to fail—no mortgage repayment means no rain, and no rain means the buckets stay empty. If CDOs fail, then the credit default swap insurance gets paid out. So what to do? Buy credit default swaps! That’s the quick and dirty way to explain the Big Short.
Why buy Dog Shit?
Wait a second. Why did people originally invest in these CDO bonds if they were full of “dog shit mortgages” (direct quote from the book) in the first place? Since The Big Short protagonists knew what was happening, shouldn’t the investors also have realized that the buckets would never get refilled?
For one, the prospectus—a fancy word for “owner’s manual”—of a CDO was very difficult to parse through. It was hard to understand exactly which mortgages were in the CDO. This is a skeevy big bank/CDO practice. And even if you knew which mortgages were in a CDO, it was nearly impossible to realize that many of those mortgages were made fraudulently.
The mortgage lenders were knowingly creating bad mortgages*.* They were giving loans to people with no hopes of repaying them. Why? Because the lenders knew they could immediately sell that mortgage—that risk—to a big bank, which would then securitize the mortgage into a CDO, and then sell that CDO to investors. Any risk that the lender took by creating a bad mortgage was quickly transferred to the investor.
So…because you can’t decipher the prospectus to tell which mortgages are in a CDO, it was easier to rely on the CDO’s rating than to evaluate each of the underlying mortgages. It’s the same reason why you don’t have to understand how engines work when you buy a car; you just look at Car & Driver or Consumer Reports for their opinions, their ratings.
The Ratings Agencies
Investors often relied on ratings to determine which bonds to buy. The two most well-known ratings agencies from 2008 were Moody’s and Standard & Poor’s (heard of the S&P 500?). The ratings agency’s job was to look at a CDO that a big bank created, understand the underlying assets (in this case, the mortgages), and give the CDO a rating to determine how safe it was. A good rating is “AAA”—so nice, it got ‘A’ thrice.
So, were the ratings agencies doing their jobs? No! There are a few explanations for this:
  1. Even they—the experts in charge of grading the bonds—didn’t understand what was going on inside a CDO. The owner’s manual descriptions (prospectuses) were too complicated. In fact, ratings agencies often relied on big banks to teach seminars about how to rate CDOs, which is like a teacher learning how to grade tests from Timmy, who still pees his pants. Timmy just wants an A.
  2. Ratings agencies are profit-driven companies. When they give a rating, they charge a fee. But if the agency hands out too many bad grades, then their customers—the big banks—will take their requests elsewhere in hopes of higher grades. The ratings agencies weren’t objective, but instead were biased by their need for profits.
  3. Remember those fraudulent mortgages that the lenders were making? Unless you did some boots-on-the-ground research, it was tough to uncover this fact. It’s hard to blame the ratings agencies for not catching this.
Who’s to blame?
Everyone? Let’s play devil’s advocate…

To explain further, there are two things going on here.
First, Goldman Sachs bankers were selling CDOs to investors. They wanted to make a commission on the sale.
At the same time, other bankers ALSO AT GOLDMAN SACHS were buying credit default swaps, a.k.a. betting against the same CDOs that the first Goldman Sachs bankers were selling.
This is like selling someone a racehorse with cancer, and then immediately going to the track to bet against that horse. Blankfein’s defense in this video is, “But the horse seller and the bettor weren’t the same people!” And the Congressmen responds, “But they worked for the same stable, and collected the same paychecks!”
So do the big banks deserve blame? You tell me.
Inspecting Goldman Sachs
One reason Goldman Sachs survived 2008 is that they began buying credit default swaps (insurance) just in time before the housing market crashed. They were still on the bad side of some bets, but mostly on the good side. They were net profitable.
Unfortunately for them, the banks that owed Goldman money were going bankrupt from their own debt, and then Goldman never would have been able to collect on their insurance. Goldman would’ve had to payout on their “bad” bets, while not collecting on their “good” bets. In their own words, they were “toast.”
This is significant. Even banks in “good” positions would’ve gone bankrupt, because the people who owed the most money weren’t able to repay all their debts. Imagine a chain; Bank A owes money to Bank B, and B owes money to Bank C. If Bank A fails, then B can’t collect their debt, and B can’t pay C. Bank C made “good” bets, but aren’t able to collect on them, and then they go out of business.
These failures would’ve rippled throughout the world. This explains why the US government felt it necessary to bail-out the banks. That federal money allowed banks in “good” positions to collect their profits and “stop the ripple” from tearing apart the world economy. While CDOs and credit default swap explain the Big Short starting, this ripple of failure is the mechanism that affected the entire world.
Betting more than you have
But if someone made a bad bet—sold bad insurance—why didn’t they have money to cover that bet? It all depends on risk. If you sell a $100 million insurance policy, and you think there’s a 1% chance of paying out that policy, what’s your exposure? It’s the potential loss multiplied by the probability = 1% times $100 million, or $1 million.
These banks sold billions of dollars of insurance under the assumption that there was a 5%, or 3%, or 1% chance of the housing market failing. So they had 20x, or 30x, or 100x less money on hand then they needed to cover these bets.
Turns out, there was a 100% chance that the market would fail…oops!
Blame, expounded
Ratings agencies—they should be unbiased. But they sold themselves off for profit. They invited the wolves—big banks—into their homes to teach them how to grade CDOs. Maybe they should read a blog to explain the Big Short to them. Of course they deserve blame. Here’s another anecdote of terrible judgment from the ratings agencies:
Think back to my analogy of the buckets and the rain. Sometimes, a ratings agency would look at a CDO and say, “You’re never going to fill up these buckets all the way. Those final tranches—the ones that won’t get filled—they’re really risky. So we’re going to give them a bad grade.” There were “Dog Shit” tranches, and Dog Shit gets a bad grade.
But then the CDO managers would go back to their offices and cut off the top of the buckets. And they’d do this for all their CDOs—cutting off all the bucket-top rings from all the different CDO buckets. And then they’d super-glue the bucket-top rings together to create a field full of Frankenstein buckets, officially called a CDO squared. Because the Frankenstein buckets were originally part of other CDOs, the Frankenstein buckets could only start filling up once the original buckets (which now had the tops cut off) were filled. In other words, the CDO managers decided to concentrate all their Dog Shit in one place, and super glue it together.
A reasonable person would look at the Frankenstein Dog Shit field of buckets and say, “That’s turrible, Kenny.”
BUT THE RATINGS AGENCIES GAVE CDO-SQUAREDs HIGH GRADES!!! Oh I’m sorry, was I yelling?!
“It’s diversified,” they would claim, as if Poodle shit mixed with Labrador shit is better than pure Poodle shit.
Again, you tell me. Do the ratings agencies deserve blame?!
Does the government deserve blame?
Yes and no.
For example, part of the Housing and Community Development Act of 1992 mandated that the government mortgage finance firms (Freddie Mac and Fannie Mae) purchase a certain number of sub-prime mortgages.
On its surface, this seems like a good thing: it’s giving money to potential home-buyers who wouldn’t otherwise qualify for a mortgage. It’s providing the American Dream.
But as we’ve already covered today, it does nobody any good to provide a bad mortgage to someone who can’t repay it. That’s what caused this whole calamity. Freddie and Fannie and HUD were pumping money into the machine, helping to enable it. Good intentions, but they weren’t paying attention to the unintended outcomes.
And what about the Securities & Exchange Commission (SEC), the watchdogs of Wall Street. Do they have a role to explain the Big Short? Shouldn’t they have been aware of the Big Banks, the CDOs, the ratings agencies?
Yes, they deserve blame too. They’re supposed to do things like ensure that Big Banks have enough money on hand to cover their risky bets. This is called proper “risk management,” and it was severely lacking. The SEC also had the power to dig into the CDOs and ferret out the fraudulent mortgages that were creating them. Why didn’t they do that?
Perhaps the issue is that the SEC was/is simply too close to Wall Street, similar to the ratings agencies getting advice from the big banks. Watchdogs shouldn’t get treats from those they’re watching. Or maybe it’s that the CDOs and credit default swaps were too hard for the SEC to understand.
Either way, the SEC doesn’t have a good excuse. If you’re in bed with the people you’re regulating, then you’re doing a bad job. If you’re rubber stamping things you don’t understand, then you’re doing a bad job.
Explain the Big Short, shortly
You’re about 2500 words into my “short summary.” But the important things to remember:

And with that, I’d like to announce the opening of the Best Interest CDO. Rather than invest in mortgages, I’ll be investing in race horses. Don’t ask my why, but the current top stallion is named ‘Dog Shit.’ He’ll take Wall Street by storm.
If you don’t mind my cussing but you do like this content, consider subscribing to the email list to get these articles (and nothing more) sent to your inbox every week.
I hope this post helped if you were looking for someone to explain the Big Short. Thanks for reading the Best Interest.

Source: https://bestinterest.blog/explain-the-big-short/
submitted by CrosscourtFade to investing [link] [comments]

I help someone get revenge on their gold-digging ass of an SO

This happened some years ago but was just reminded of it, so here you go Reddit!
I worked as a front desk agent in a large luxury hotel chain for some years. One particular hotel I worked at was located really close to the downtown area and so we got a large number of young, very wealthy, business people who loved to party. I usually worked the 2nd & 3rd shifts which meant I got to see loads of drunken hookups, breakups, cheating, hookers, and more.
This particular one though...this is one I will never forget.
I was working at the desk when a group of young, well-dressed men come walking in. They've all clearly been drinking, but aren't so drunk that they can't walk right and hold a conversation.
One of them comes up to me and tells me that while he and his friends were at the bar, a woman was hitting on him, and even though he told her no multiple times she wouldn't stop. So he and his friends left and it wasn't until they got in the Uber that he realized he didn't have his room key anymore. He thinks she took it and he's concerned that she may come up to his room, he asked that I deactivate his keys and if she does come up to the hotel to not let her in.
When he was telling me all of this, it didn't sit right with me. He and his friends were all grinning about it and snickering amongst one another. Then he gave a clear description of her, without being asked. Told me height, body shape, hair color, and style, the kind of dress she was wearing. All while saying it in a mocking tone.
Now, this could have easily been because he thought the whole thing was ridiculous or was too drunk to take it seriously, but it really didn't sound right to me. Either way, I did as I was trained in that situation. I pulled up his reservation, deactivated the keys as requested, made him a new set when he showed me his ID, and even offered to move him to a new room if that would make him feel more comfortable. He and his buddies all laughed a little at that and he declined, took the keys and they went to their room.
About an hour or so later, the woman he described showed up. Now, by this point, my relief for the night had also shown up and was sitting at the front desk while I was in the back office counting down my cash drawer. I hadn't had a chance to tell him about the woman. Just as I'm walking out of the back office with my bag and about to leave, I see my coworker buzz the doors open and the woman comes rushing in, cuts through the lobby and down the hall to the elevators. She was barefoot, holding her heels in her hands, and knew exactly where she was going.
I rushed up to him and told him what the man from before had told me about her. My coworker looked at me confused. He then pointed to the screen that had the reservation pulled up and told me that when the woman arrived, she went to use the room keys and they didn't work. So he asked for her room number and last name, she gave both and her name is on the reservation. I looked at the reservation and down in the notes, there was a woman's name listed. The man from before was listed as the primary, but her name was listed as secondary with his consent to be in the room.
I was confused, I thought maybe she wasn't the same woman he was talking about. But, to be on the safe side I called the man in his room and told him the situation and that we allowed a woman, fitting that description he gave, to enter the building because she confirmed her name was on the room. He laughed, said he forgot her name was on the room and asked that I remove it. I was now super confused, I asked to make sure:
Me: "Sir...just to be clear, the woman you met at the bar tonight was with you at check-in hours ago and was allowed keys then, but now she is not?"
Him: (laughs to all his friends in the room) "Awww....guys I confused the poor girl." (gets back on the phone with me) "Yeah sweetheart, she's banned from the room. Don't worry about the other details, just take her name off."
Me: "...I see. Then, if she isn't going to be on the room anymore, would you like us to call the police and have her removed from the property?"
Him: "Hahaha...woah! That's too far there. Don't worry, she'll get the hint soon enough."
We ended the call there and I got really suspicious of this. I told my coworker to not do anything and that I was going to stick around for a bit to see if anything happened.
A short time later the woman came off the elevator, pouring tears, sobbing while on the phone with someone. She sat down in our lobby and my coworker and I tried to look busy while eavesdropping hard on her phone call.
She was sobbing on the phone to her mom and sister. From what she told them, she was invited out to spend the week with her boyfriend meeting all of his old college buddies. This being their first-night they all met up for dinner and drinks. After a bit, she went to the restroom and when she came back she caught her boyfriend hitting on another woman. His friends all bet that he wouldn't do it. When she confronted him pissed off, he called her a bunch of names and humiliated her in front of his friends and the entire bar. All of his friends joined in on mocking her and he threw in her face that she was "nothing without him" and dumped her right there. He and his friends then took an Uber back and left her stranded at the bar with no money and no way back. She then had to use her phone's GPS and walk back to the hotel from the bar, barefoot (she had heels, and walking 2 miles in those was not going to cut it). She was asking her mom and sister for help as he wouldn't let her in the room to get her luggage or her wallet.
My heart broke. I felt horrible. I helped this guy treat this poor woman like crap and now he and all his friends were up there laughing at her while she's sitting in our lobby sobbing and with nothing. I went over to our snacks area in the lobby, grabbed her a bottled water, and brought it to her. I told her that I couldn't help but overhear the conversation and was very sorry for her situation and asked if she would like us to help. I informed her that if he was keeping her from getting to her things, we could call the police and have them force him to hand over her things so she could leave if she'd like. Or if she wanted to let her mom or sister pay for a room we'd be happy to give her a very low rate in a room far from him.
She thanked me, took the water, and tried to calm down and talk to me about what all was happening and what her options were. Eventually, we decided on her staying in the hotel for the night and figuring out the rest in the morning. As we make it to the desk, she asks me to try and run her credit card to see if it has enough on it for another room. I ask her what she means by "another room" and she tells me that she's actually paying for the room he's in. That his name is on the room because he booked it, but it's her card paying for everything.
This intrigued me. I asked why she was paying for the room if it was in his name. She told me that she's the one with a job, not him. That he hasn't been able to find a job in his field since graduating from college and is essentially living off of his parents' money. But just after they started dating, his parents cut him off, so he's been living off of her money. That's why she was so upset and confused by how he had been acting all night, he was sweet and doing everything for her back home, but since he met up with his friends he did a 180 and hasn't been the same guy the entire time.
I wanted to tell her that it was obvious he was using her for the money and that he would probably blame his friends for all of this and try to get back with her later on. But I doubted she would have listened to me or cared for a complete stranger to butt in on her personal life like that. So instead, I offered up a sweet piece of revenge.
I informed her that, considering she's the one paying for the room, if she can confirm that it is her card on file with some sort of photo ID and verify the last 4 digits of the card number (That's honestly all this hotel company required) then she could, if she wanted to, kick him out of the room and keep it all to herself. But, considering how poorly her night has been, if she were indeed able to prove she is the one paying for the room, then I'd be more than happy to provide for her the biggest luxury upgrade we offered at our property. Largest suite we had, full hotel ammenity access, I'd even have my coworker fish out a bottle of champagne and some fresh strawberries for her to have sent to her room. All free of charge.
She was taken aback by the offer and was very sincerely tempted, she looked like she was about to say no. Then I told her that since she would be upgrading her room, that would require moving her things from that room and into her new one. Which mean the room that she is currently listed in would need to be vacated immediately, if anyone were to remain in the room after we have demanded it be vacated, we are required to have them escorted off the property or they pay for the room. Their choice.
She then thought about it, pulled up her card's banking app and showed me the screen. It had a photo of her, her full name, the card's full number, and the hold from our hotel for the room. She asked if that worked. It was good enough for me.
I quickly upgraded her, moved everything over in the system and before I could say a word to my coworker he was already grabbing a set of master keys, a bell cart and was asking her what her luggage looked like since he would be the one retrieving it for her to deliver to her room. He didn't want her to have to deal with her ex again. She smiled and told him which ones were hers and that she hadn't unpacked yet.
My coworker runs down to the elevators and up to fetch her things. While I make her a new set of keys and send her off to her new room. Once she's on the elevator, my phone at the desk starts ringing. It's the ex-boyfriend and he's very angry about why my coworker has entered the room and is taking her things. I calmly explain that I cannot give out the private information of any of our guests and that if he would like to remain in his room he will need to pay for it as there is no longer a method of payment on his room.
He. Blew. Up.
He's making a ton of demands and at the same time yelling at my coworker to stop what he's doing, but its obvious from the way he's yelling at him that my coworker isn't listening to him. I can even hear the guy's friends telling him to chill out and just pay for the room.
I then explain that we will give him a courtesy 10 mins to make a decision. At which point, if he doesn't have payment ready then he must vacate the building or we will be forced to call the authorities and have him evicted. He continues to yell at me. He screams, swears, threatens, and yells for a solid minute before taking a breath. I then tell him he has 9 mins remaining and asks if he has come to a decision yet. He hangs up on me.
9 minutes later I call the room and he doesn't answer. I call again, no answer. I call a third time, he picks up, then immediately hangs up. I call the police and tell them what's going on and they said they're on their way.
The officers arrive, I tell them what's going on, we go up to the room together and the man and his friends are all white as ghosts when they see the cops. The cops explain to the ex-boyfriend and his friends that they're being evicted. The ex-bf starts trying to talk to me but the cops stop him and tell him to only talk to them (I told him about his attitude on the phone before). The friends are all offering to pay for the room at this point and the cops look to me and ask if that would be acceptable. I smile very sweetly and say "no" and the cops nod and start rushing all of the guys to grab their things and leave the room. The ex-bf is the last one out the door carrying his 2 bags and complaining that he isn't even given a luggage cart and has to carry his own things. His friends all look pissed at him.
I go with the officers to escort all of them out of the building and run into my coworker in the lobby. He waits until they're all outside in the parking lot to tell me that the woman is in her new room, loves it, and said no to the champagne, she just wanted to sleep.
I didn't get to see her before she left town the next day, but the ex-bf did try calling our hotel to complain a number of times and even tried leaving some bad reviews of us online and lied through all of it. I hope she doesn't have to ever deal with him again.
Edit: Thank you all so much for the awards! It's only been 1 day and I'm blown away by how much this story was loved! I normally do post my hotel stories to talesfromthefrontdesk but felt that this one would work here too so I posted it here first. Glad I did and I plan to repost there as well. Thank you all again for the love! I have a lot of asshole stories from working in that industry, very few wholesome stories, but this is my one and only revenge story. So really happy you all loved it! Thank you!
Edit 2: Wanted to address some things you guys brought up in the comments:
  1. I have no idea why she didn't use Uber instead of walking, probably due to the distress of the moment and didn't think of it. Honestly, if you're ever in that situation, despite being publicly humiliated like that, ask the staff for help. Either they think of something you're too panicked to think of or they'll be nice and pay for an uber for you. I've done it for people plenty when working in hotels. There's no shame in asking for help.
  2. The credit card company is Capital One. I wasn't going to mention it since some subs immediately flag your story for listing major company names and didn't want to fuss with that. But yeah, their app lets you post a picture on your profile and, on most banking and credit card apps, you are able to pull up the full card number by clicking on the account information. Yes, technically I shouldn't have accepted this as a form of ID however, given how shit her night was, I didn't care.
submitted by Anonymous_Annie5523 to ProRevenge [link] [comments]

How I applied Buffet's strategies to my own portfolio, +70% networth, beat SP500 by 40%

I believe I did pretty well in the market this year. My networth increased ~65% since its lowest point in March, ~350k to 620k. 20k from the car I bought in March. I rolled over a 401k and it messed up Mint's reporting, hence the spike from Jul -> Aug.
I beat the SP500 by 40% in my YOLO account, my FAANG account went from 180->300
I did this by following some basic investing principles, buying and holding for the most part, being patient, and only investing in areas which I have expertise in.
I did not buy into the TSLA hype, nor do I play options, nor do I play crypto.

High level advice:

I picked the 7 I agree with.
  1. Invest in what you know…and nothing more.
  2. Never compromise on business quality
  3. When you buy a stock, plan to hold it forever
  4. Diversification can be dangerous
  5. Most news is noise, not news (don't read articles about investing)
  6. The best moves are usually boring (buy and hold)
  7. Only listen to those you know and trust
I firmly believe that anyone who follows those concepts, they will find success in investing.

General mindset:

Application:

I was very specific in the types of companies I would choose to invest in within tech. I decided to follow my strengths. As a data engineer, I'm very intimate with cloud technologies, and I think I generally have pretty sharp business acumen and good strategic direction.
As a result, my day to day work had me using a ton of technologies in the cloud space. I've used Splunk, NewRelic, Twilio, AWS, GCP, Hortonworks/Cloudera, Oracle, Tableau, Datadog, Sendgrid (bought by Twilio), Dropbox/box, Slack, Salesforce, Marketo, Databricks, Snowflake, HP Vertica, just to name a few. I was familiar with CDN services like Fastly and Cloudflare because sometimes, I worked with the DevOps and IT guys.
Based on industry hearsay, day to day work, eventually, I got a good "feel" of what technologies were widely adopted, easy to use, and had a good reputation in the industry. Similarly, I also got a feel for what tech were being considered 'dated' or not widely used (HP, Oracle, Cloudera, Dropbox, Box).
I tend to shy away from companies that I don't understand. In the past, most times I've done that-- I got burned. My biggest losers this year was betting on $NAT and $JMNA (10k total loss). After learning from those mistakes, I decided to only focus on investing in companies that either I or my peers have intimate first hand experience with using. Because of this rationale, the majority of stocks in my portfolio are products which I believe in, I thoroughly enjoy using, and I would recommend to my friends, family, and colleagues.
Post COVID, due to the shift to remote work and increase in online shopping I decided to double down on tech. I already knew that eCommerce was the next big thing. I made very early investments into SHOP and Amazon in 2017 for that reason.
My hypothesis was that post-COVID, the shift on increased online activity, remote work, and eCommerce would mean that companies which build tools to support increased online activity should also increase. I decided to choose three sectors within tech to narrow down-- these were three sectors that I had a good understanding of, due to the nature of my work and personal habits.
  1. eCommerce + AdTech
  2. IT/DevOps (increased online activity means higher need for infra)
  3. FinTech (increased shopping activity means more transactions)
These are the points I consider before I consider jumping into a stock:
  1. Do I feel good about using the company? Do I believe in the company's vision?
  2. Where do I see this company in 5 years? 10 years? Do I see my potential children being around to use these companies?
  3. What does YoY, QoQ growth look like for this company?
  4. Is/Will this product be a core part of how businesses or people operate?
  5. Who are their customers and target demographic?
  6. (SaaS) Customer testimonials, white papers, case studies. If it's for a technology, I'm going to want to read a paper or use case.
In March, I took what I believe to be an "educated gamble". When the market crashed, I liquefied most of my non tech assets and reinvested them into tech. Some of the holdings I already had, some holdings were newly purchased.
EDIT ^ this isn't called timing the market you /wsb imbeciles. Timing the market would be trying to figure out when to PULL OUT during ATH and then buying the dip. I SOLD at the lowest point, and I with the cash I sold AT A LOSS, I reinvested that cash and doubled down into tech. If I sold in Feb, and bought back in March, that would be calling timing the market. What I am doing is called REINVESTING/REBALANCING... not timing the market.
I have 50% of my networth in AMZN, MSFT, AAPL, GOOG, FB, NFLX, and the rest in individual securities/mutual funds. I have 3 shares of TSLA that I got in @1.5.
Here are the non FAANGs I chose.
  1. $SQ. I had already been invested in SQ since 2016. I made several bad trades, holding when it first blew past 90 until I sold it at 70... bought in again last year at 60s, after noticing that more and more B&M stores were getting rid of their clunky POS systems and replacing it with Square's physical readers. After COVID, I noticed a lot of pop up vendors, restaurants doing take out. A Square reader made transactions very easy to make post-COVID.
  2. $ATVI. Call of Duty and Candy Crush print money for them. I've been a Blizzard fanboy since I was a kid, so I have to keep this just out of principle.
  3. $SHOP. They turned a profit this year, and I think there is still a lot more room to grow. It's become somewhat of a household name. I've met quite a few people who mentioned that they have a Shopify site set up to do their side hustle. I've tried the product myself, and can definitely attest that it's pretty easy to get an online shop up and running within a day. I 5.5xed my return here.
  4. $BIGC. I bought into this shortly after IPO. I'm very excited to see an American Shopify. BigC focuses on enterprise customers right now, and Shopify independent merchants, so I don't see them directly competing. I'm self aware this is essentially a gamble. I got in at 90, sold at 140, and added more in 120s. I def got lucky here... it's not common for IPOs to pop so suddenly. I honestly wasn't expecting it to pop so soon.
  5. $OKTA. Best in class SSO tool. Amazing tool that keeps tracks of all of my sign-ons at work.
  6. $DDOG. Great monitoring tool. Widely adopted and good recommendations throughout the industry. Always had a nice looking booth at GoogleNext.
  7. $ZM. Zoom was the only video conf tool at work which I had a good time using. Adoption had blown up pre-COVID already in the tech world, and post-COVID, they somehow became a noun. "Zoom parties" and "Zoom dates" somehow became a thing interwoven into peoples' day to day lives.
  8. $TWLO. Twilio sells APIs which allow applications to send messages like text, voice, and video chat. For example, when DoorDash sends you a text at 1 AM reminding you that your bad decision has arrived, that text is powered by Twilio. In March, New York announced that they were going to use Twilio to send SMS notifs for COVID contact tracing.
  9. $NET/$FSTY. These two two seem like the ones best poised for growth in the CDN space. This is based off of industry exposure and chatting with people who work in DevOps.
  10. $DOCU. people aren't going to office to sign stuff, super easy to use, I like their product.
  11. $WMT. eComm, streaming, and a very substantial engineering investment makes me think they have room to grow. Also I really need to diversify.
  12. $COST. When is the last time you heard someone say "Man I hate going to Costco and paying $1.50 for a hotdog and soda?" Diversification. Also cheap hotdogs.
  13. $NVDA/AMD. GPUs are the present and the future. Not only are they used for video games, but Machine Learning now uses GPU instead of CPU to do compute (Tensorflow for example). Crypto is still a thing as well, and there will always been a constant need for GPUs.
Mutual funds/ETFs 1. $FSCSX. MF which focuses on FinTech.
  1. $VTSAX Pretty much moves with the SP500.
  2. $WCLD. Holdings include Salesforce, Workday, Zuora, Atlassian, Okta, New Relic, Fastly...
Titanvest: I was an early access user, and I was able to secure 0% fees for my accout. 36% gains so far. I like them, because their portfolio happens to include shares of tech giants that I either don't have individual stocks for or my stake is low (CRM, PPYL). It nicely complements my existing portfolio.

Some things I do that that are against the grain:

One example was how I applied the above principle was to WalMart. In 2018 I noticed that I was getting targeted by a lot of Data engineering job listing for WalMartLabs-- WarMart's tech division. The role was to build out a big data pipeline to support their eCommerce platform. WalMart's online store released in Q3 of 2019. Post COVID, I used their online store and it was a seamless experience. They even offer a 5% cash back card like Amazon. They reported strong Q4 sales last year, and they did very well post COVID. Why did I choose to invest in $WMT? Because I believe that Wal-Mart has room to grow for their online platform.
Lastly... remember that wealth isn't accrued over time. It takes years to build. The quickest way to increase your wealth is by investing in yourself-- your career and earning potential. The sooner my income increased, the quicker I had more capital to buy into stocks.
Also, if you've gotten this far, the point of my post isn't to say that you should invest into tech. The message I'm trying to get across is-- when picking companies, pick companies in fields or verticals you have good knowledge in. Heed Buffet's advice to only pick companies you believe in and understand. Play to your strengths, don't mindless toss money based on one person's posts on Reddit-- always do your own due diligence. Use DD as a guide and use personal research and experience to drive your decision.
submitted by fire_water76 to stocks [link] [comments]

Do you guys use the word "Ya" in your countries?

Edit: So it looks like there is no other region that uses “Yaaa” like they do in Bolivia (La Paz) such as in the examples below. But there are a few countries that do use “Ya” as “ok, alright, go on” such as Peru, Chile and D.R sort of.
Here is a video that contains some short ways it is used.
I thought it was just a word we used in Bolivia until I found out some people in Peru and Chile use it as well.
-"Ya" is like saying "Ok" or "alright". It's used A LOT. (E.g -"Want to do something tonight?" - "Ya")
-"Yaaa" is hard to explain and is also used a lot. It could be used for a lot of things lol. When someone makes an exaggerated statement, sarcastic joke or a joke that contains a statement of what they are going to do or what they did which would be pretty funny. If the original person with the statement said something that the other person(s) don't believe what the original person said, then that original person or the friend/friends/crowd around them usually says/shouts "Yaaa". It could also be used by someone else, when someone does something unexpected but in a good show off way. I'm probably missing a lot of other scenerios and not explaining this all the way, so feel free to elaborate.
(E.g. Group of friends are camping during a hike and everyone has their own tent to sleep in. Girl says to guy “yea it’s so cold I wish I could sleep next to this campfire all night.” Guy responds “You know you can always come over to my tent so that we can both stay warm...yaaaa” and then chuckles. (Yaaa means he said something funny and he was joking, or was he?)
-(E.g. Girl secretly like Guy 1 and ask him in front of Guy 2, what Guy 1's favorite food is. Guy 1 responds Lomo montado. Girls say "Me too!". Guy 2 laughs and says "Yaaa". Guy 2 doesnt beleive the girls statement that she likes that food and she prob only said that b/c she wants to be with Guy 1. Guy 2 saying "Yaa" makes it awkward for the girl, but funny for him and other friends that are around who would be teasing them.
-(E.g. Large groups of people have been waiting outside a rock & roll night club late at night for over an hour drinking alcohol and waiting for people inside to get out as the club is'nt letting anyone in as it's at full capacity. -Drunk guy takes a shot with friends looks at his watch and notices it's 1:30 am. He shouts to everyone that is waiting outside too "¡Ya chicos, continuaremos el farreo, doy casa....Yaaaa!" (Yaaa means he was joking around)
-(E.g A group of young kids are betting that their slightly overweight friend can't do more then 30 pushups, Then the overweight kid starts doing pushups and not only passes 30 but gets to 50 and keeps on going. Kids surpisingly say "Yaaa".
-(E.g Person 1 explaining to Person 2 how to use the word "Ya" in Bolivia.
Person 1: "You need to know when a Yaa is warrented and needed and when it is'nt. You need to execute the word at exactly the right scenerio and at exactly the right time. Misuing the word Yaa and miscalculating the timing of the word even by a second would be detrimental to the whole situation and..”
Person 2: *interrupts* “Yaaa" while smiling.
submitted by thedayisred to asklatinamerica [link] [comments]

Mam, that's a faraday cage.

This one happened to me today and I can not stop laughing at it.
Phone call regarding wifi not working in a lady's room but works everywhere else in the house.
$Me = Zach from campfire stories (look it up) People keep asking, I am not him. Just read my lines in his voice. $CU = Clueless User or some snooty art girl
$Me - Thanks for calling IT may I have your name please? $CU - Its Clueless User.
I input her name into the thing and it pops up red indicating a VIP who expects to be given whatever she wants. She usually gets it too.
$ME - So how may I help you today? $CU - So this will sound really weird and crazy, but I swear my wifi does not work right. Everywhere else I can work just fine, but as soon as I bring it home, it just stops working.
Oh fun one of THESE calls. Probably an all metal house or an old as dirt house.
$Me - So is it everywhere in your house? $CU - Yes... NO actually last night I worked while watching netflix on the tv in the living room and had zero issues. $Me - Well thats a good place to start. Lets go into your living room and test the wifi. $CU - Sure thing.
We test the wifi in every room in her house and find that the signal degrades significantly the instant she steps into her room.
$Me - OK this is going to sound like some James Bond scifi stuff but I bet something in your room is causing EM interference. Have you moved anything new into the room? I mean anything. A lamp, a microwave, coffee maker, mini fridge, or even non electronic stuff like metal? $CU - Who has a mini fridge in their room? (Laughs) $Me - I actually keep drinks in mine by my desk while I work. $CU - Oh. Well there is nothing like that. Plus the router is in the other room. Only thing over there are my art projects. $Me - OK. I am reaching WAY out there now. Is there a lot of metal content in that wall? $CU - No but there is a lot of metal on it. $Me - How so? You do metal work for your art? $CU - No I use it to hang my art. $Me - Its probably not it, but lets go ahead and send me a picture of it. I doubt that is whats causing it but might as well send me a picture.
She takes the picture and sends it to me. In a roughly 6x8 foot section of her wall is a mounted chain link fence with these little cut up coke cans as art hanging off of it. It took me a full minute looking at the absurdity of the picture in front me when the light came on.
$Me - Mam, that's a faraday cage. Well... sort of. $CU - What is a faraday cage.
I hear from the background. "I TOLD YOU!"
$CU - Ignore that, thats my son. We keep yelling at him to move the modem and router into our room but he says the fence is the problem. $Me - Well to be honest, it kinda is. No its not kinda, it definitely is. $CU - Huh? $Me - So a faraday cage is what is used to block signals. Basically any linked metal cage can create a field where signals have trouble passing through. $CU - This is that James Bond crap you were talking about? $Me - I mean kinda? Its not a full faraday cage because its just 1 side. Its why your wifi works but constantly cuts out and stays at half strength. A faraday cage has to actually enclose something to properly shield it from radio and em waves. But that chain link fence is in direct line of sight with the router. $CU - I... don't see how that is possible. It makes no sense. But you, my husband, and my 16 year old son all say the same thing. They all say moving that to the garage will solve my problems. $Me - I agree with your assessment. $CU - Are you willing to put your job on it?
She had me stay on hold for 30 minutes as she got her husband and son to move the art and fence to the garage.
$CU - Ok I am back. Pulling the ethernet cable... Huh that was fast. It instantly connected to the wifi. $Me - OK lets get connected again.
Ran ping test with -t -l 1400 and had zero dropped pings. Before it was every 3rd one. Speed test gave her the full speed for her area.
$CU - That was strange, well it is working now. How often you think this happens? $Me - I can legitimately state that I have never once run into this issue in my entire career. $CU - Seriously? $Me - Yup. Now I have run into weird things before. $CU - Like what? $ME - (All true stories.) In my parent's house, if you stand in the laundry room on wifi and I open both the fridge and freezer door in the kitchen, your phone will lose wifi connection. I had a friend who had to move his router 5 feet because a new lamp his mom loved was causing line of sight interference with his laptop. And my uncle decided to build an all metal house. Metal beams, metal roofing, and metal doors. He gets zero reception inside his house and has to run ethernet cables all over his home. $CU - So would running this ethernet cable through the wall be a better solution? $Me - Infinitely better.
I thanked her and immediately shared the picture with everyone on my team. Only 3 had to be told what a faraday cage was. I am so proud of my team.
submitted by TheLightningCount1 to talesfromtechsupport [link] [comments]

General Election Polling Discussion Thread (August 30th, 2020)

Introduction

Welcome to the /politics polling discussion thread for the general election. As the election nears, polling of both the national presidential popular vote and important swing states is ramping up, and with both parties effectively deciding on nominees, pollsters can get in the field to start assessing the state of the presidential race. Please use this thread to discuss polling and the general state of the presidential or congressional election. Below, you'll find some of the most recent polls, but this is by no means exhaustive, as well as some links to prognosticators sharing election models.
As always though, polls don't vote, people do. Regardless of whether your candidate is doing well or poorly, democracy only works when people vote, and there are always at least a couple polling misses every cycle, some of which are pretty high profile. If you haven't yet done so, please take some time to register to vote or check your registration status.

Polls

Below is a collection of recent polling of the US Presidential election. This is likely incomplete and also omits the generic congressional ballot as well as Senate/House/Gubernatorial numbers that may accompany these polls. Please use the discussion space below to discuss any additional polls not covered. Additionally, not all polls are created equal. If this is your first time looking at polls, the FiveThirtyEight pollster ratings page is a helpful tool to assess historic partisan lean in certain pollsters, as well as their past performance.
Several polls are in the field, so we won't have a full picture of the field until next week when more are expected to be released. Until then, here are the polls since August 16th.
Poll Date Type Biden Trump
USC Dornsife 8-30 National 54 39
YouGov 8-29 National 47 41
Morning Consult 8-29 National 50 44
Morning Consult 8-29 National 52 42
USC Dornsife 8-29 National 52 40
Emerson College 8-28 Massachusetts 69 30
Trafalgar Group 8-28 Michigan 45 46
Redfield & Wilton Strategies 8-28 National 48 38
Franklin & Marshall College 8-27 Pennsylvania 49 42
Harris Insights & Analytics 8-26 National 47 38
Ipsos 8-26 National 44 37
Benenson Strategy Group 8-26 National 50 39
Rasmussen Reports 8-26 National 46 45
YouGov 8-26 National 50 41
Roanoke College 8-26 Virginia 53 39
Ipsos 8-26 National 47 40
Change Research 8-26 Wisconsin 49 44
Change Research 8-26 Arizona 49 47
Change Research 8-26 Michigan 50 44
Change Research 8-26 Florida 49 46
Change Research 8-26 National 51 43
Change Research 8-26 North Carolina 48 47
Change Research 8-26 Pennsylvania 49 46
Trafalgar Group 8-25 Wisconsin 45 46
Public Policy Polling 8-25 Delaware 58 37
Public Policy Polling 8-25 New York 63 32
Public Policy Polling 8-25 Florida 48 44
Morning Consult 8-24 National 51 43
Morning Consult 8-24 National 52 43
Morning Consult 8-24 National 52 42
Morning Consult 8-24 National 51 43
Morning Consult 8-24 National 51 43
Morning Consult 8-24 National 52 42
Léger 8-24 National 49 40
Morning Consult 8-24 National 52 42
Morning Consult 8-24 North Carolina 49 46
Public Policy Polling 8-24 Texas 48 47
Trafalgar Group 8-24 Louisiana 37 54
YouGov 8-24 National 50 39
TargetSmart 8-24 Ohio 47 46
YouGov 8-23 National 52 42
Morning Consult 8-22 National 52 43
Morning Consult 8-22 National 51 43
Redfield & Wilton Strategies 8-22 National 49 39
Redfield & Wilton Strategies 8-21 Pennsylvania 48 41
Redfield & Wilton Strategies 8-21 Florida 49 41
Redfield & Wilton Strategies 8-21 North Carolina 44 46
Redfield & Wilton Strategies 8-21 Michigan 50 38
Redfield & Wilton Strategies 8-21 Wisconsin 49 39
Redfield & Wilton Strategies 8-21 Arizona 47 38
Harris Insights & Analytics 8-21 National 46 38
Civiqs 8-21 Wisconsin 51 45
Civiqs 8-21 Pennsylvania 51 44
Civiqs 8-21 Michigan 49 46
Civiqs 8-21 Ohio 47 47
DKC Analytics 8-21 New Jersey 52 33
Saint Anselm College 8-20 New Hampshire 51 43
Muhlenberg College 8-20 Pennsylvania 49 45
Global Strategy Group 8-20 Texas 47 45
Echelon Insights 8-20 National 51 38
Echelon Insights 8-20 National 53 39
Data for Progress 8-20 National 50 41
Morning Consult 8-20 National 47 36
Morning Consult 8-20 National 49 39
Trafalgar Group 8-19 Minnesota 46 46
Ipsos 8-19 National 48 40
Ipsos 8-19 National 45 36
ALG Research 8-19 Louisiana 43 50
Rasmussen Reports 8-19 National 48 44
YouGov 8-19 National 50 40
Harris Insights & Analytics 8-18 National 45 39
OnMessage Inc. 8-18 Wisconsin 47 47
OnMessage Inc. 8-18 Florida 49 49
OnMessage Inc. 8-18 Pennsylvania 50 46
OnMessage Inc. 8-18 Arizona 48 51
GQR Research (GQRR) 8-18 Michigan 52 43
Léger 8-17 National 51 35
Morning Consult 8-17 National 50 43
Morning Consult 8-17 National 51 43
Morning Consult 8-17 National 51 43
Morning Consult 8-17 National 51 43
Morning Consult 8-17 National 51 43
Morning Consult 8-17 National 51 42
Morning Consult 8-17 National 51 42
Morning Consult 8-17 Wisconsin 49 43
Redfield & Wilton Strategies 8-17 National 48 40
Landmark Communications 8-17 Georgia 44 47
YouGov 8-17 National 49 38
YouGov 8-17 National 50 41
YouGov 8-17 Texas 40 47
ABC News 8-17 National 54 44
ABC News 8-17 National 53 41
ABC News 8-17 National 53 41
SSRS 8-16 National 50 46
YouGov 8-16 National 52 42
East Carolina University 8-16 North Carolina 46 46
NBC News 8-16 National 50 41

Election Predictions

Prognosticators

Prognosticators are folks who make projected electoral maps, often on the strength of educated guesses as well as inside information in some cases from campaigns sharing internals with the teams involved. Below are a few of these prognosticators and their assessment of the state of the race:

Polling Models

Polling models are similar to prognosticators (and often the model authors will act like pundits as well), but tend to be about making "educated guesses" on the state of the election. Generally, the models are structured to take in data such as polls and electoral fundamentals, and make a guess based on research on prior elections as to the state of the race in each state. Below are a few of the more prominent models that are online or expected to be online soon:

Prediction Markets

Prediction markets are betting markets where people put money on the line to estimate the likelihood of one party winning a seat or state. Most of these markets will also tend to move depending on polling and other socioeconomic factors in the same way that prognosticators and models will work. Predictit and Election Betting Odds are prominent in this space, although RealClearPolitics has an aggregate of other betting sites as well.
submitted by _mr0 to politics [link] [comments]

How to be Wrong and Still Make Money: A comprehensive guide to selling credit spreads

So I first dipped my toes into options trading a few years ago. I had previously been swing trading stocks so I had a couple years of experience before that, but the leverage and potential returns that options provided really piqued my interest. After it was all said and done, I lost almost $20,000 buying options. After realizing that someone was getting all of this money I was losing, I learned about option selling and haven’t looked back since.
I recently posted my YTD performance here, and received a lot of questions about how I did it. My strategy changed over time, but I first started with credit spreads, which may be applicable to more people since it’s a strategy that works with smaller accounts too. I got a lot of questions about how I played credit spreads and it’s tough to completely explain what I do through a comment here and a comment there so I created this guide explaining my exact approach to trading credit spreads. Here you go:
This is a wall of text, so if you're a more visual learner, here's a link to videos explaining all four parts:
Part One
Part Two
Part Three
Part Four

Part One: The Basics

So what is a spread? A high level conceptual explanation is that you’re essentially betting on a stock to finish above or below a certain price upon expiration. One of the advantages here is that you can set this number out of the money, so if a stock is trading at $100, you can bet that it’ll remain below $110 by a certain date. This is a bearish position, so if you’re correct and it goes down, you’ll make max profit. The catch though is that even if you’re wrong, you basically have a 10% upward cushion before you start to lose any money. So the easiest way to describe it is a strategy that lets you make money if you’re right, but also make money if you’re slightly off.
How does it work? So in the above example, if we were bearish on a stock we would open what’s called a call credit spread. We could set it up where we sell a 110c for a credit of $1.50, and buy a 115c for a debit of $0.50. This means that in this transaction we receive $1.50, and pay $0.50 for a net credit of $1. That credit is your max profit on the play. If you’re familiar with options you’ll know that if the stock finishes at or below $110 upon expiration, both of these calls will be worthless. That’s great news for us because the long leg we bought (115c) for 0.50 will be a loss, but we’ll get to keep the full $1.50 from the short leg (110c) that we sold, resulting in us realizing our max gain on the trade of $1.
Why not just sell the 110c and collect the full $1.50? While it cuts into our profits, the reason we buy the 115c in this example for $0.50 isn’t to cut into our profits when we’re correct, but rather protect us when we’re wrong. If the stock in the example stays below $110, we’re good to go and we’ll hit max profit. But what if it goes to $120, $150, or something crazy happens and it hits $200. If the stock hits $150 upon expiration, that 110c that we sold for $1.50 will be worth $40, meaning that we’ll incur a $3,875 loss in pursuit of a $150 gain. We’ve seen crazy run ups from the likes of TSLA and ZM lately, and people who sold what we call “naked options” got absolutely killed. With our spread, yes our 110c will be worth $40 meaning we’re down $4,000 on that position, but the 115c we bought behind it will be worth $35 meaning we’re up $3,500 there for a net loss of $500. Additionally, we get to keep that $1.00 credit we received up front no matter what, so our loss with this spread is actually $500-$100=$400 as opposed to the $3,875 loss that we would’ve seen had we sold the 110c by itself. THAT is the value in selling a spread as opposed to a naked option.
Why are you multiplying everything by 100? Each options contract is worth 100 shares, so a contract that is trading for $1.50 actually costs $150 to purchase.
Another high level point I like to make is that there are really 5 different things that can happen when you make a play. Let’s say you think a stock will go up. It can (1) go up a ton and you’d be correct, (2) go up a little and you’d be correct, (3) trade flat and you’d be incorrect, (4), go down a little and you’d be incorrect, or (5) go down a lot and you’d be incorrect. With a bullish spread, you’d hit max profit on 4/5 , or 80% of the possible outcomes, whereas if you bought stock or purchased an option you’d only be profitable on (1) or (2). Obviously the actual outcomes are a little more complex, but for a base-level understanding of the advantages a spread provides, I think this is a good way to look at it.
So that’s the value of a spread. A lot of traders are introduced to option selling and are scared of the prospect of incurring a huge loss like we mentioned above, but using credit spreads is a great way of receiving the benefits that selling has to offer while limiting a lot of the risks. So let’s move onto actually opening a spread.

Part Two: Making the Trade

So for actually opening a spread up, we have a four-step approach we take: Pick a Stock Pick a Direction Pick a Strike Price Execute the Trade
1: Picking a Stock:
One of the most important things I tell people is to trade what you know. I have a watchlist of 25-30 stocks that I watch and get familiar with during the day. That way if I recognize a good opportunity, I’ll have a decent base of knowledge to rely on to make what I feel is a smart play. It’s super easy to get caught up in the “stock of the week” and try to jump in on a play because a ticker is in the news. If you’re not familiar with a stock, don’t trade it.
For this example (the one used in the video), Wayfair was trading in a 195-210 range for a little bit and then had a big day where it broke up out of that range and up towards $220. This was an unusual move that I noticed since it was on my watchlist, so I decided to make a play.
STOCK: WAYFAIR
2: Picking a direction:
So if we look at Wayfair’s YTD chart, it has exploded this year. A clear upward trend, but a recent trend that I noticed from following the stock was that every time it broke out like this, there would be a little bit of a pullback afterwards. Additionally, I felt the stock was overvalued on a fundamental basis (had a negative book value at the time of the trade) so I wanted to play this stock back down. This is probably the quickest and easiest step of the four, since you’ll likely already have an opinion on most of the stocks that you follow.
DIRECTION: DOWN
3:Picking a Strike Price:
So we know that we’re going to be playing Wayfair back down, but now the question is what spread are we going to set up to do that. In this example Wayfair was trading at $218.42 at the time that we decided to make this trade. In the video we illustrate a trading channel that Wayfair was at the top of. It was also approaching the ATH of $221.54. A lot of the time that will act as resistance for a stock, meaning it’ll bounce down off of it. So in order to give ourselves a bit of a cushion we decided to set our short leg at 222.50, meaning that we’re playing the stock to stay below $222.50 by the end of that week.
So with this play it means in plain English that if we’re correct and the stock goes down, we hit max profit. But if we’re wrong and it goes up, we still have a $4.08 cushion before we’re not hitting max profit anymore. So we could be a little wrong, have the stock go up a few dollars, and still walk away with max profit.
STRIKE PRICE OF SHORT LEG: $222.50
4: Executing the Trade:
I’ll be the first to tell you that when I started trading spreads I didn’t realize you could open both legs of the spread at once. I was stupid. I would like to think I’m at least a little bit smarter now. If you look at the options screen for most brokers, you’ll just see single legs. Switching over to “vertical” allows you to set up the entire spread in one trade. If you use something like RH, there’s a feature that allows you to select multiple options, so you’ll select the one you wish to sell (short leg) and the one you wish to buy (long leg).
In this example we selected the 222.5/227.5c spread, meaning that we sold the short leg of 222.5 and the long leg of 227.5. The net credit was 1.45, which is our max gain on the trade. A wider spread gives a larger credit but also increases max loss. This is a $5 wide spread but we could have made it a tighter spread with a $2.5 width. Typically the best risk to reward ratio is on the tightest spreads, but a slightly wider spread will raise your breakeven price and studies have shown that it actually results in better expected value long term.
Circling back to the credit we received of $1.45, this means that our max profit was $145 and our max loss was $355 for each spread that we sold. We know that because our broker tells us that, but a quick way to calculate it is the width of the spread minus the credit. A $1.45 credit on $5 wide spread means a $5-$1.45=$3.55 max loss.
When I evaluate trades like this I look for a max profit to max loss ratio of 1:2 to 1:4. Based on different scanners I’ve seen, the best expected values tend to fall on spreads within that risk/reward ratio. The ratio on this trade is 1:2.44.
So we put our order in for a credit of $1.45, it filled, and now we get to sit back and watch. Sometimes your order won’t fill right away. In fact, most of the time it won’t fill right away. It’s important to be patient with your fill price and not chase it downwards. We want the highest credit possible. So if the credit on these spreads dropped to 1.30 when I was trying to place an order, it usually isn’t a great idea to drop my order price down to 1.30 just to get a fill. The only time I would recommend that is if you’re trying to open a spread right before the market closes. Otherwise, hang tight. Patience pays.

Part 3: Managing the Trade

So now that we’ve made the trade, it’s time to manage it. In my opinion one of the best parts about trading spreads is that they don’t require active management. You get to sit back and watch the price. Once the trade has been opened, which is also quick, it takes very little effort.
So with the Wayfair example we used, our analysis turned out perfectly, as Wayfair touched the ATH and dipped back down to end the week safely at $214. We hit max profit on that trade, but what if the trade goes against us? That’s what we’ll take a look at in this section.
One thing we didn’t address in part two is when to open the trade. We like opening spreads on Mondays and Tuesdays, and monitoring them during the week. This is the part of my strategy that is a little bit controversial, as there is a (legitimate) school of thought that selling spreads about 45 DTE is better value. I like that idea and if you would rather do that then absolutely go for it. It’s important to trade what you’re comfortable with. All of the lessons in here still apply to that strategy. With that said though, I stick with the weekly strategy of opening them at the beginning of the week and look to close them throughout the week.
The way I see it, your % of max profit should be the metric you’re looking at when deciding what to do with a spread. Divided up equally, that means if you progressed through the week to max profit in a linear fashion, you would be at 20% of max profit on Monday, 40% on Tuesday, and so forth. A good rule of thumb I use is that if you’re ever on the fence about whether or not to close something out, do so if your return exceeds the linear return for that day of the week. The market can move quickly and I’ve had several times where I have regretted not closing a spread out. It’s important to take profit.
Another thing I’ll add to this is that this weekly strategy gets a little risky on Thursday afternoon headed into Friday. If your spread is remotely close to being in the money on Thursday afternoon, close it out. Now that I type that out I realize that may all sound a little convoluted, but it’s better visualized in the video I’ve linked for this section.
Now let's get into what happens if a trade really starts to move against you. With the strategy we use there are really two options: (1) Close the trade for a loss and move on, or (2) Roll the strikes higher.
The first option is pretty self explanatory, but a quick note I want to add here is that you can have a stock move way against you but still be able to close the trade for less than max loss. The example I use in my video is I played FB earnings, thought it would go down, but it shot way above my spread and well into max loss territory. We opened a 245/247.5c spread for a credit of $0.54. FB was reporting earnings on a Thursday night and we sold this spread that expired the following day, so there wasn’t a ton of time to manage it. Long story short, FB killed earnings and shot up to $256 that morning. Really not a prayer that it would come back down to the spread I opened by the end of the day. But despite the fact that this trade went way against us and we had almost no time to manage it since it was a Friday play, we were still able to close out for a debit of $1.90. Yes that’s a loss of $1.36 per spread, but we SAVED an additional $0.60 cent loss by avoiding a max loss debit of $2.50. That’s another benefit of spreads.
Let’s talk about option two. This is the best option to use if you’re confident that you’re correct about the ultimate price action on a stock, but you need a little extra wiggle room on the trade. For this example we’ll look at a TSLA call spread that I opened. TSLA was trading at $1542 after an incredible run, so I figured I would play it below 1600 with a 1600/1610c spread that offered a credit of $2.52. As is the theme with this section, TSLA exploded the following morning (Tuesday) and went all the way up to $1794 at one point. My spread was literally almost $200 out of the money. One of the biggest possible moves against myself that I had ever seen. Despite this crazy move, it was only Tuesday and we were able to close the first spread for a debit of only $5.25 (as opposed to a $10 max debit). We opened 6 of these off the bat so this was a loss of $1638. From there we “rolled” our strikes higher, opening 10 1750/1760c spreads for a credit of $3.45. So the closing and subsequent opening of a spread like we did here is what we are referring to when we say we “rolled the strikes higher”.
By the end of the week TSLA had finally crashed a bit and it finished at $1506. This meant the second of spreads we opened were easily max profit. And while we lost $1,638 on the first set of spreads we opened here, we profited $3,450 on the second set of spreads so we were able to still finish the week with a $1,812 profit on TSLA. The funny thing with this one is that the original spread would have hit max profit since it dropped all the way back down to 1500, but we would have had the same result had TSLA finished anywhere below 1750.
Rolling the strikes higher gave me extra breathing room and turned a potential disaster into a profitable trade. One thing I’ll add though is that with this method you do run the risk of increasing your potential max loss. Because of that, I’ll only roll my strikes higher ONCE. Anything past that is chasing a losing trade. If I roll my strikes higher and it’s still going against me, I’m at the point where I need to accept the fact that I don’t fundamentally understand a stock as well as I thought I did and move on. There is always another trade out there.
The final point I’ll add to this is ALWAYS CLOSE OUT YOUR SPREADS. The only time I’ll let a spread expire worthless is if my spread is OTM by a crazy amount and it would quite literally take a historic after-hours move on Friday to take me back ITM. Other than that, close your spreads out. Even if it’s just for a $0.05 debit. It may seem annoying but I’ll tell you why in the following section.

Part 4: Additional Risks and Considerations

I will start this section by saying I’ve never been impacted by any of the following risks, but it’s important to be aware of 100% of the possible outcomes of your trade before you enter it. They’re infrequent but this really wouldn’t be a comprehensive guide if I omitted them. They are as follows: (1) Early Assignment, (2) Dividend Risk, (3) Pin Risk.
1: Early Assignment:
The best way to start this section is by talking about why your max loss is actually your max loss. We know it’s quickly calculated as the width of your spread minus the credit, but why is that?
Let’s use a 110/115c spread as an example. We’ll say we received a credit of $1. We know that if the stock finishes anywhere below 110 then both legs are worthless and we’ll hold onto that $1 credit. But what happens if we’re in a max loss position. Let’s say the stock finishes at $120.
In this situation the short leg (110c) we sold would be worth $10 (120-110), meaning that we would owe $1,000 on that position. The long leg we bought would be worth $5 (120-115), meaning we are holding a position worth $500. The net effect is a $500 loss, but remember that’s netted against the $100 credit you received, so it’s a max loss of $400. That math checks out as the width of the spread is $5, the credit is $1, so the max loss is 5-1=$4*100=$400.
So that’s how it works upon expiration. But lets say this position moved against you, you still have a few days until expiration, but the stock is at $120. Since there are a few days left, you probably could close the contract for a debit of $3.50 rather than the max loss debit of $5. However, since your short leg is ITM the person you sold the option to may choose to exercise their option. As a result, that would require you to take on a short position of $110*100=$11,000 per contract sold. You may not be able to afford to cover that, or your broker may not let you hold that position. So what happens is your long leg gets exercised as well resulting in you taking a max loss early. So while on paper you received a credit of $1 that could have been closed for a debit of $3.50 and your loss was only $2.50, early assignment results in you prematurely taking a max loss.
When does this happen? It typically doesn’t, since it requires the buyer sacrificing the remaining extrinsic value on the option, but it’s more likely with certain stocks. There are three different classifications of a stock that relate to it’s borrowing ability: Easy to Borrow (ETB), Hard to Borrow (HTB), and Not Available to Borrow (NTB). The harder a stock is to borrow, the more likely it is that a call is exercised early because it gives the buyer a way to acquire a stock which may not be available to them through their broker. So if you’re selling call spreads that are close to being ITM, make sure to check out the borrowing status of the stock.
2: Dividend Risk:
This risk relates to the first one discussed, as it’s just another way you risk early assignment. If a company is announcing a dividend, there will be something known as an “ex-div” date, which means that all shareholders as of that date are entitled to receive the divident, which will be distributed usually at a later date. Because of this, call buyers may exercise an out of the money call option in an effort to acquire those shares.
Remembering that exercising an option means that you sacrifice all remaining extrinsic value, another reason a buyer may exercise a call option before an ex-dividend date is that the value of the dividend announced is greater than the extrinsic value remaining in the option. Say a 100c is trading at $2 and the underlying (stock) is currently at 101. The extrinsic value is the value of the option in excess of what it would be worth upon expiration. So the extrinsic value in this situation is $1, since the 100c trading for $2 is just $1 in excess of the current strike price. If the company in question here announced a $2 dividend, an option buyer would likely exercise their call option because the $2 dividend is greater than the $1 of extrinsic value.
3: Pin Risk:
We know that if your spread finishes out of the money it’s a max gain and if both legs of your spread finish in the money it’s a max loss. But what happens when the price of a stock finishes between the two legs of your spread? Let’s take a look.
So using a 100/110c spread as an example, let’s say that the stock finishes at 105. Your long leg, which is there to protect you, is worthless so you wouldn’t exercise it. However the short leg at 100 that you sold will be exercised by the buyer since it’s ITM. As a result, you’re now short 100 shares at a price of 100 and you’ll be holding that position over the weekend. This can go both ways from here, but since we’re focused on risk let’s say that this stock you’re now short shoots up over the weekend and some sort of news/event brings it up to $120.
With this short position of 100 shares at $100 you’re borrowing $10,000 worth of stock. Now that the stock is worth $120 this position is now worth $12,000. Over the weekend you’ve sustained a $2,000 loss. If we received a credit of $3 when we opened this spread, we may have thought that our max loss was 10-3=$7*100=$700. Since we failed to close the spread out, this position has now resulted in a $2,000 loss net of the $300 credit that you received when you opened the position. So on a trade where you thought you could lose at most $700, you’re now down almost $2k.
I can’t repeat it enough, but THIS IS WHY WE CLOSE OUT SPREADS BEFORE EXPIRATION. That is the single most important takeaway I can give you here. Spreads are great since they’re defined risk and defined gain. When you’re buying options you have a defined loss but a potentially infinite gain. This can make it really easy to get greedy and I’ve seen countless traders lose big profits because they keep holding out for more. When you have a defined gain and defined loss it makes it easier to make smart decisions, take profits, and continuously build on those profits over time.
That was an enormous wall of text but I hope it helps explain, from a base level, what spreads are and how they work. Switching from buying options to selling options has dramatically changed my performance in the market so I hope sharing this can do the same for someone else. If you have any questions let me know and I’d be happy to answer them.
submitted by fuzz11 to StockMarket [link] [comments]

The story I'm about to tell you is true. 100% documented and proven.

Marc Dutroux The story I'm about to tell you is true.
Perhaps the most intriguing part of this story is that every single person reading this post - every single one of you - was alive when this story became news in 2004.
That fact is intriguing because everyone reading this post has either never heard this story, or forgot about it (I'm betting on the first one, because it is truly unforgettable).
Furthermore, once you hear this story in its entirety, I can promise it will be seared into your memory forever.
Our main character is a man named Marc Dutroux. He was born in Belgium in 1956. He was twice convicted of kidnapping and raping underage children. The first time was in 1989. The second time occurred in 1996.
That was not a typo - you read that correctly. He was convicted and served a (much too brief) sentence in 1998. He served only 3 and a half years of his 13 year sentence because he was released for good behavior. Less than 10 years later, he was arrested again on the same charges (different victims).
In the second round of charges, he was convicted of kidnapping, torturing and abusing victims, some of them to the point of death.
What I am about to tell you comes from the statements made by his surviving victims (called the X Files), Marc Dutreox himself, and evidence from law enforcement. I've also added references/citations at the very end of this post.
Here we go.
Marc confessed to kidnapping, raping, drugging, torturing and filming children for many years. He also claimed he was doing it at the behest of a political elite who financed his career as a professional trafficker.
Not only did this political elite finance his efforts - they made specific requests of him. Sometimes they requested specific types of children (they were called "party favors" and he was asked to deliver kids of certain age, sex, race). Sometimes they requested specific means of torturing the children to fulfill their desires (orgies, satanic rituals involving sacrifices, torture games).
And sometimes they requested he film certain influential people engaged in these acts, for later use as blackmail.
He claimed many of his customers and financiers were world leaders. This was not a stretch of the imagination because he lived in Belgium, where the EU and NATO headquarters were located. This statement was also corroborated by victims who were able to identify specific politicians.
Anneke Lucas was one of his victims who testified against him. She claimed she was 6 years old when the cleaning lady hired by her mother sold her to the pedophile network in 1969. Her claims were extraordinary:
-She was raped over seventeen hundred hours before turning 12 years old. -She was 6 years old when she was forced to participate in her first orgy, which included wearing an iron dog collar and eating human excrement. -She would actually be delivered back to her parents from time to time. However, her parents themselves were complicit in the crimes and always sent her back to her abusers. -Torture included being strapped to a butchers block used to execute other children. Other victims were forced to torture her for hours as part of their initiation. -She was considered attractive and that made her preferred by her abusers. She claimed that she tried to use that to her survival advantage to the best of her ability, but by the age of eleven, she had become so broken that she was slated to be executed and disposed of. -She said she was saved when one of her abusers negotiated for her freedom. That abuser would later sit as a defendant in the trial.
Other witnesses and victims would soon come forward, describing such things as “Black Masses,” with child and adult sacrifices taking place in front of observers and participants, which included prominent politicians and figures. This would be corroborated by a note found by police at the house belonging to Bernard Weinstein—a man who previously worked with Dutroux, but whom Dutroux had murdered. The letter contained very specific requests for certain types of victims for satanic sacrifices.
The letter was signed by a man who called himself 'Anubis'. It turned out 'Anubis' was the high priest of a satanic cult called 'Abrasax' whose real name was Francis Desmet. Police obtained a warrant and seized computers, documents, mail, actual human skulls, jars of blood, and all sorts of Satanic items - but none of this was enough to make an arrest.
As the Dutroux trial went public, other victims stepped forward and confirmed the testimony, offering up descriptions of sexual abuse and human sacrifice.
They also described “hunting parties” where elites would release naked children into the woods to hide, so that the elites themselves could hunt them down and slaughter them. Many of the stories from victims contained so many similarities, they were impossible to deny. For example, the hunting parties were often held at castles, where victims could not escape and were hidden from the public eye. Those not killed in the hunt were usually chased down and mauled/killed by Dobermans.
All of these victims echoed the testimonies of other, older survivors of ritual Satanic abuse from around the world.
It is also notable that Dutroux owned 10 homes valued at 6 million dollars.
It is also notable that Dutroux was not employed.
It is also notable that Dutroux received $1,200 per month in public assistance.
It is also notable that documents released by Wikileaks show large sums of money in various currencies were deposited into his wife's bank account.
It is also notable that those deposits coincided with reported kidnappings and missing children reports.
It is also notable that before his removal, judge Jean-Marc Connerotte was on the verge of publicly disclosing the names of high level government officials who had been recognized on video-tapes of sexual torture that took place in Dutroux's dungeon.
It is also notable that 20 potential witnesses for this case have died without explanation.
Does any of this sound familiar? Are there any headlines today that sound like history is repeating itself?
Guys, not one single thing in this post is theory. It's all proven and on record.
You see the pictures attached to this post? Those are images of hunting games. They're paintings that people like Tony Podesta buy, and hang in his home, and invite others over to enjoy.
We all know Epstein was a sick sob who had friends in high places - the same friends that hang out with Tony Podesta.
You think Epstein was the only one? That he's somehow unique? Or was he the low level one they were willing to sacrifice to protect everyone else involved at a higher level?
Do you realize now that when it comes to trafficking, satanism, pedophilia, human sacrifices, organ harvesting, adrenachrome - that it is art imitating life? That these people who are so obsessed with the art that glorifes these things might actually, themselves, be engaged in these things?
Do you think normal, non-pedo, non-cannibal, average Joes would hang that garbage up in their homes?
Suddenly the claims that world leaders and governments being involved in this satanic horror show isn't so far fetched after all.
Suddenly its not so crazy to say that world agencies who claim to stop these crimes (WHO, UN) are actually facades that cover up the real work of procuring and enabling - yes, even participating - in these crimes.
Suddenly the whole house of cards comes crashing down.
With this one case, all the unbelievers are silenced.
For crying out loud, this trial was in 2004! Did you remember it? If not, do you wonder why it was not front page news across the world?
And if you're asking yourself HOW DO THESE PEOPLE GET AWAY WITH THIS - have you not yet figured out that the very people who are supposed to end it, are doing it?
Most everyone has watched an Epstein documentary on Netflix - I think there's been maybe 3 or 4 made since his death. And the one thing I heard people say over and over and over again was this: "Where is Epstein's girlfriend and why hasn't she been arrested yet?"
Did anyone asking that question even try to find the answer? Or did you just shrug your shoulders and say, "Well, it is what it is and there's nothing I can do about it" and go on with your life?
Let me help you out.
Did you hear the news story from two weeks ago that President Trump fired federal prosecutor Geoffrey Berman? He was the prosecutor in charge of the Epstein case.
AG Barr requested Berman step down, and Berman refused. So Trump fired him and Berman was replaced with prosecutor Audrey Strauss. And then suddenly BAM! Maxwell is in custody.
You now get a front row seat for the horror show that is about to come out.
You will not believe who is involved and how deep it goes. And you will not believe the lengths they'll go to in order to protect their secrets.
https://cwasu.org/wp-content/uploads/2016/07/Confronting-An-Atrocity.pdf?fbclid=IwAR1iFppDKV9fKTovmv9zLfWBQduNSavsSNA4_4fuavxF6Y5u0n8tB7JfI60
http://archive.is/SFRGD
http://archive.is/jxiLV#selection-3715.53-3715.70
https://www.euronews.com/amp/2019/10/27/explainer-paedophile-marc-dutroux-and-the-horror-case-that-united-a-divided-belgium
submitted by Fantastic-Reply to conspiracy [link] [comments]

"No one is above the rules, and I mean no one call me if he pulls rank"

I used to work for a marketing company that serviced small and medium-sized businesses across America. It was a multi-billion dollar revenue company. The CEO was a true rags to riches story. He joined the company right after he got out of jail in his early 20s for a small drug charge and worked his way up over 20 years to eventually become the CEO of the company.
The CEO strongly believed that the success of the company did not come from the brilliant and intelligent minds that he hired for his executive team, but the hard work, sweat and tears of the infield sales reps, service reps (made sure the customer services where properly installed), collection reps (chased after customers who fell behind on their payments), and sales managers.
He would often say, without sales we don't have the revenue to pay your salaries
Without customer service customers will drop us faster then we can bill them
Without collection reps we'd lose too many accounts due to non-payment
And without sales managers to hold it all together we'd fall apart
And he had a rule
EVERY SINGLE EXECUTIVE team member would spend 1 full week of each quarter in the field with a Sales Manager, Customer Service Rep, Collections Rep, or Sales rep. In addition when they are in the field they are to SUBMIT to whoever they've been assigned too and they may not pull rank.
This rule applied to EVERYONE to include the CEO. I know this, cause the CEO personally road along with me for 5 days in the field. He was a legit cool guy (I got a story at the end about this)
So...apparently we had hired a new VP Of Marketing from a major brand that I'm sure everyone in this sub would know of. Anyway apparently the first time he went in the field the VP Of Marketing pulled rank on a sales manager and the sales manager reported this directly to the CEO.
A new quarter went by, and I got an email stating that the VP Of Marketing will be joining me in the field on such and such week. Ok cool, not the first time I had some higher up come out and ride with me.
But about an hour later I got a call from my CEO.
CEO: PJ the VP Of Marketing is going in the field with you
Me: Yes sir, I got the email...
CEO: PJ I picked you cause when I was in the field with you, you seemed like the kinda guy that wouldn't be bullied or let someone run all over you
Me: Ok, well thank you
CEO: This VP is new to the company, and the last time he went in the field he pulled rank. I've told him not to pull rank again, and if he does I want you to call me as soon as you can.
PJ: I understand
CEO: Thank you
The VP meets me up, honestly for the first two days everything was fine. However on the 3rd day I was meeting with an existing client. This client was a difficult to please customer, he would always say we weren't worth the money, but I knew we were cause I could see his results, and over the years this clients business had grown alot. Said client would beat us up over pricing I'd stand firm, give him a 3% price increase, and offer him upgrades on top he'd haggle me down to a 1.5% price increase and we'd sign the contract.
Now I told the VP what would happen, that it would be a long sales call, and a difficult high tense one. But to let me handle it, I've dealt with the client quite a bit and was well prepared.
Now this meeting with the client lasted 2 1/2 hours but I'll get to the point. The client wanted a discount and was threatening to go to our competitor, he wouldn't. That's when the VP spoke up and said "I'm the VP and I'll personally give you a 15% discount on your current plan if you agree to sign a 1 yr contract" the customer said "20%" the VP said "Spilt the difference 17.5% and we have a deal" they agreed I was mad as hell.
One thing to mention my commissions depended on me generating MORE REVENUE and this VP just fucked me over.
We get in my car, and I go "You pulled rank you shouldn't have done that" he said "I got the deal done" I said "Had you kept your mouth shut I'd have gotten more money, not given 20% back" he goes "We got the contract signed" I said "We gave away tens of thousands of dollars that we didn't need to" he goes "Look I'm the VP..."
I then called my CEO, he saw the name pop up on my cars bluetooth
CEO answered
CEO: PJ, how are you doing?
PJ: The VP pulled rank on me and gave my customer a 17.5% discount on his current plan right as I was about to close him for more money
CEO: That's not right, where is the VP?
PJ: Your on speaker, he can hear you
CEO: Excellent, hey VP
VP: Yes sir
CEO: Tell me what happend
VP: Told his side of the story, which he admitted the truth but also admitted to pulling rank and giving the customer a discount
CEO: Ok, thanks for your honesty. Your fired.
VP: Excuse me?
CEO: Your fired, you have a 1 yr probation clause your done you don't pull rank when in the field
VP: You can't do this
CEO: I just did, you are to get on a plane come back to your office and clean it out, PJ take Mr. VP back to his hotel and drop him off.
PJ: Sure, no problem
And for the next 20 minutes I had an awkward car ride back to my former VPs hotel.
Later in a all hands on meeting, the CEO made sure to talk about how if an executive is in the field and pulls rank its a firable offense for the executive and he wants all the sales reps, sales managers, customer service reps, and collection reps to know that.
Side Story on this CEO
The company had a data plan, which gave us 4G on our Ipads, Phones, and Laptops. Well the company changed the service plan, and our data plan went down to ONLY our phones and we had to hotspot off that. They said this move would save us $80,000 a month (we had like 4,000~ employees in the field)
Well 2 months later we had a conference (we had 3 conferences a year) and after the conference, everyone went to the hotel bar. That's when I approached my CEO with another sales rep and talked to him about how much of a PITA it was to hotspot all our devices and how much it drained our phone batteries and blah blah and that I get it saves money, but it also costs producitiy.
The CEO nodded and said "Tell you what, in 2 weeks the CIO is supposed to go in the field, I'll have him to go in the field with you and if he agrees that its costing our reps productivity and causing to many workflow issues I'll bring back 4G data to all devices
The CIO was there and said "CIO, your going to XYZ area and you will be riding with PJ, pay attention to how he uses his 4G data and if you think we should go back to the old plan where all devices had 4G"
The CIO went into the field with me, on the 3rd day at breakfast he said "Last night I called the CEO" and I said "yea?" and he said "I made a recommendation that we go back to our old data plan and ensure all your devices have 4G data, its obviously creating productivity issues and when you look at the cost per user, its not that great" FAQ
Do you still work there? If so why not?
No I do not work there I was much better at maintaining and growing existing clients than acquiring new ones. The company ended up buying another company and started laying people off, and made acquiring new business more important then maintaining the current business meaning I was going be let go so I quit and switched jobs before ethey fired me.
Sounds like a great CEO/he's what I wish all CEOs would be comments
He's still a ruthless business person, I'll give you an example of what he did to a lot of managers. When he bought out his competitor. He had a lot of redundancy and a lot of managers on rock-solid employment contracts which he couldn't just "lay off" so he took the managers with those contracts and turned them into phone reps. Imagine being a sales manager or even a VP and getting a call and being told you are no longer a manager or a VP and your demoted, not even an outside sales rep but an inside phone rep.
Those managers obviously didn't perform very well after being demoted and would be written up for poor performance and let go. I know of a VP in the company who was demoted to a phone rep position. And literally got written up for poor performance for his first month. O and he was still getting his VP salary (per the contract, they could change his position/duties but they could not pay him less and the only way they could fire him would be through poor performance)
Also another thing he did, he invested a lot in automation during this time so he could lay off even more people. I had a talk with my manager one day, and he said the CEO was obsessed with revenue/per employee number and was determined to drive that number up.
I want to work for them, can give me the company name/etc
No, for two reasons
First reason, the company is currently not hiring and actively laying people off. Their primary revenue comes from small, and medium-sized businesses. As you can imagine due to the economic circumstance those small businesses can no longer afford to pay their bills, which includes my former employer. As a result, they've had to downsize. I'm sure the company will survive, they had crazy healthy margins, and I heard right before the economic downfall they had a lot of cash on hand for another acquisition of some competitors which they didn't go through with cause I bet they are using that cash to survive.
Secondly, I don't want to be doxxed.
What's my opinion of this CEO
Honestly nothing but fucking respect. The dude is inspiring. He is also not someone I would not want to be, he's an obvious work alcoholic, his personal net worth is in excess of $100+ million and he doesn't need to work ever again but according to all the VPs/Managers I spoke to the dude literally works 7 days a week at all hours of the day.
Put it this way, he travels SO MUCH in his biggest markets he keeps a car that he bought since its cheaper then buying a rental everytime he flys in
What did I take away from my time with them?
Honestly, I think a lot of companies could learn a lot from this company. Seriously why more companies don't force their top leadership to work within the ranks on a regular basis is beyond me. Its one gripe I have with my current employer.
This is how he reduced his sales staff
When he bought out the competitor he removed all sales objectives. He then made maintaining current/growing current client worth 1x he made acquiring new clients worth 5x. Also losing revenue cost you 1.5x Everyone was ranked against everyone, and he placed everyone in quadrants if you fell in the bottom 25% for 2 months in a row you got laid off.
And this created for some interesting results. Example I had a family emergency. I took off for one week. For that one week I did $0 in business. however because people who were ranked ABOVE me lost revenue I rose in ranking. And the first week I came back I closed on a new business, increased revenue, and fell in rank because others around me did more.
It created for some depressing performance reviews, a co-worker of mine closed decent sized new business and he thought for sure that'd save his job. It didn't, because another person sold more then he did, and it kept him in the bottom 25% and he was fired. Thursday evening he was so excited about his new account, thinking it saved his job. Friday afternoon he let go.
submitted by PJExpat to MaliciousCompliance [link] [comments]

General Election Polling Discussion Thread (September 2nd, 2020)

Introduction

Welcome to the /politics polling discussion thread for the general election. As the election nears, polling of both the national presidential popular vote and important swing states is ramping up, and with both parties effectively deciding on nominees, pollsters can get in the field to start assessing the state of the presidential race. Please use this thread to discuss polling and the general state of the presidential or congressional election. Below, you'll find some of the most recent polls, but this is by no means exhaustive, as well as some links to prognosticators sharing election models.
As always though, polls don't vote, people do. Regardless of whether your candidate is doing well or poorly, democracy only works when people vote, and there are always at least a couple polling misses every cycle, some of which are pretty high profile. If you haven't yet done so, please take some time to register to vote or check your registration status.

Polls

Below is a collection of recent polling of the US Presidential election. This is likely incomplete and also omits the generic congressional ballot as well as Senate/House/Gubernatorial numbers that may accompany these polls. Please use the discussion space below to discuss any additional polls not covered. Additionally, not all polls are created equal. If this is your first time looking at polls, the FiveThirtyEight pollster ratings page is a helpful tool to assess historic partisan lean in certain pollsters, as well as their past performance.
With the conclusion of both major parties’ nominating conventions, pollsters scrambled into the field to conduct polls of swing states and the national race. The result has been a slew of high quality pollsters releasing their numbers on Wednesday as well as today, which paint a picture of the electorate right after the candidates are expected to have received a temporary convention bounce.
Poll Date Type Biden Trump
Quinnipiac University 9-3 Florida 48 45
Quinnipiac University 9-3 Pennsylvania 52 44
Monmouth University 9-3 North Carolina 48 46
Monmouth University 9-3 North Carolina 47 45
Monmouth University 9-3 North Carolina 48 46
Rasmussen Reports 9-3 Pennsylvania 47 48
Harper Polling 9-3 Minnesota 48 45
USC Dornsife 9-3 National 50 42
USC Dornsife 9-3 National 51 42
Morning Consult 9-2 Wisconsin 52 42
Morning Consult 9-2 Wisconsin 52 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 52 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 53 42
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 52 41
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 49 42
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 49 42
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 50 40
Morning Consult 9-2 Wisconsin 51 40
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 47 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 46
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 50 40
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 48 46
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 42
Morning Consult 9-2 Wisconsin 47 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 47 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 49 42
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 47 44
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 47 45
Morning Consult 9-2 Wisconsin 47 45
Morning Consult 9-2 Wisconsin 47 45
Fox News 9-2 Wisconsin 49 41
Fox News 9-2 North Carolina 49 45
Fox News 9-2 Wisconsin 50 42
Fox News 9-2 North Carolina 50 46
Fox News 9-2 Arizona 49 40
Fox News 9-2 Arizona 49 39
Ipsos 9-2 National 43 38
SSRS 9-2 National 51 43
Harris Insights & Analytics 9-2 National 46 40
Morning Consult 9-2 National 51 43
Morning Consult 9-2 National 51 43
Morning Consult 9-2 National 50 43
Morning Consult 9-2 National 51 44
Morning Consult 9-2 National 52 42
Morning Consult 9-2 National 51 43
Quinnipiac University 9-2 National 52 42
Qriously 9-2 National 46 41
Opinium 9-2 Florida 50 43
Opinium 9-2 Wisconsin 53 39
IBD 9-2 National 49 41
YouGov 9-2 National 51 40
Rasmussen Reports 9-2 National 48 45
Monmouth University 9-2 Pennsylvania 49 46
Monmouth University 9-2 Pennsylvania 49 45
Monmouth University 9-2 Pennsylvania 48 47
Suffolk University 9-2 National 46 41
Ipsos 9-2 National 47 40
USC Dornsife 9-2 National 51 42
USC Dornsife 9-2 National 51 41
Opinium 9-2 National 53 39
Suffolk University 9-2 National 49 43
Selzer & Co. 9-2 National 49 41
Redfield & Wilton Strategies 9-1 National 49 40
Landmark Communications 9-1 Georgia 40 47
East Carolina University 9-1 North Carolina 46 48
Public Policy Polling 9-1 Michigan 48 44
Expedition Strategies 9-1 Montana 44 48
University of Nevada, Las Vegas 9-1 Nevada 44 38
Morning Consult 9-1 National 52 43
Morning Consult 9-1 National 51 43
Morning Consult 9-1 Texas 47 48
Morning Consult 9-1 Florida 49 47
Morning Consult 9-1 Pennsylvania 49 45
Morning Consult 9-1 National 51 43
Morning Consult 9-1 North Carolina 49 47
Morning Consult 9-1 Ohio 45 50
Morning Consult 9-1 Minnesota 50 43
Morning Consult 9-1 Florida 50 45
Morning Consult 9-1 Georgia 49 46
Morning Consult 9-1 Michigan 50 44
Morning Consult 9-1 Georgia 46 47
Morning Consult 9-1 Colorado 51 41
Morning Consult 9-1 Wisconsin 52 43
Morning Consult 9-1 Michigan 52 42
Morning Consult 9-1 Arizona 52 42
Morning Consult 9-1 Colorado 51 41
Morning Consult 9-1 Texas 46 47
Morning Consult 9-1 Minnesota 50 42
Morning Consult 9-1 Ohio 45 49
Morning Consult 9-1 North Carolina 49 46
Morning Consult 9-1 Pennsylvania 50 44
Morning Consult 9-1 Arizona 45 47
USC Dornsife 9-1 National 51 41
USC Dornsife 9-1 National 51 41
Léger 9-1 National 49 42
AtlasIntel 9-1 National 49 46
Emerson College 8-31 National 51 48
RMG Research 8-31 National 48 44
Global Strategy Group 8-31 Pennsylvania 53 43
Global Strategy Group 8-31 Pennsylvania 50 42
Public Policy Polling 8-31 Georgia 47 46
Harris Insights & Analytics 8-31 National 47 38
GQR Research (GQRR) 8-31 Pennsylvania 52 43
Trafalgar Group 8-31 Missouri 41 51
USC Dornsife 8-31 National 53 40
USC Dornsife 8-31 National 52 40
John Zogby Strategies 8-30 National 45 42
John Zogby Strategies 8-30 National 48 42
USC Dornsife 8-30 National 54 39
USC Dornsife 8-30 National 53 39

Election Predictions

Prognosticators

Prognosticators are folks who make projected electoral maps, often on the strength of educated guesses as well as inside information in some cases from campaigns sharing internals with the teams involved. Below are a few of these prognosticators and their assessment of the state of the race:

Polling Models

Polling models are similar to prognosticators (and often the model authors will act like pundits as well), but tend to be about making "educated guesses" on the state of the election. Generally, the models are structured to take in data such as polls and electoral fundamentals, and make a guess based on research on prior elections as to the state of the race in each state. Below are a few of the more prominent models that are online or expected to be online soon:

Prediction Markets

Prediction markets are betting markets where people put money on the line to estimate the likelihood of one party winning a seat or state. Most of these markets will also tend to move depending on polling and other socioeconomic factors in the same way that prognosticators and models will work. Predictit and Election Betting Odds are prominent in this space, although RealClearPolitics has an aggregate of other betting sites as well.
submitted by TheUnknownStitcher to politics [link] [comments]

How to Make Money Betting Sports - Basic Sports Betting ... Over Under Bet Explained - SportsBetting3.com - YouTube 1x2 in Sports Betting Explained Betting strategy: How To Bet on Goal Totals Over / Unders ... Guide to Moneyline Betting: How & When to Use this Popular Betting Concept

Total (Over/Under) Bets Definition of bet: A total bet focuses on how many points are scored, regardless of who wins the game. After a total point score has been set, bettors can wager on whether the actual score of the game will be over or under the set point score. A look at how to read spreads, moneylines and odds. Chicago Bears linebacker Khalil Mack is a very strong human being, which isn't breaking news at all. Now that you know what rollover means in sports betting and how to calculate it and turn it into actual monetary value, let's make a few points. First, you must understand that when we mention wagering requirements, it simply means the amount that must be wagered, not lost. In other words, if the rollover shows that the wagering requirement is ... Before a game begins betting over or under the total points scored is usually a -110 wager. Bettors will wager $110 to win $100 for a pre-game totals bet. If bettors wager a lot more on one side of the total, the moneyline might change before the actual point total moves. At a certain point, the sportsbook will reset the total and the moneyline ... What does Over/Under mean? The Over/Under is a set of odds in which you bet on whether the combined score will add up to more or less than the projected total number set by oddsmakers.

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How to Make Money Betting Sports - Basic Sports Betting ...

Complete over-under total bet overview. This bet is fun and easy! Why do totals contain 1/2 points? Learn what all the numbers mean. See how the juice affect... Under/over bets are becoming increasing popular, and here are our tips to get the most out of them. 1) Go further back. Don’t just judge teams on their last ... How to make money betting sports and basic sports betting strategy and tips direct from Las Vegas and professional sports handicappers Marco D’Angelo, Ralph ... Explaining what the 1x2 oddstype and bettype is and how it works in sports betting. Using the UEFA Champions League game between Porto and Liverpool as an example. The 1x2 is also known as 3-way ... Learn how to understand and read the most popular kinds of betting odds found on sports betting sites. What do the numbers mean, and how can you determine wh...

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