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When developing a stock trading strategy, it is important that the backtest be as accurate as possible. In some of my previous strategies, I have noted that the backtest did not account for survivorship bias.
Survivorship bias is a form of selection bias caused by only focusing on assets that have already passed some sort of selection process. In this post we will look at a few improvements we can make to the strategy so we can start live trading!
In this post we will look at the long term performance of leveraged ETFs, as well as simulate how they may have performed in time periods before their inception.
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Should we trust our gut feelings or rely on probabilities and careful analysis when making important decisions?
In this quick talk, professional poker player Liv Boeree shares three strategies she's learned from the game and how we can apply them to real life.
Meet Lucy. She was a math major in college, and aced all her courses in probability and statistics. Which do you think is more likely: that Lucy is a portrait artist, or that Lucy is a portrait artist who also plays poker?
How do we know which statement is more likely to be true? Alex Gendler explores our tendency to look for shortcuts and the p For when you need to stop biting your nails and just pick a direction.
What happens when technology knows more about us than we do? Poppy Crum studies how we express emotions -- and she suggests the end of the poker face is near, as new tech makes it easy to see the signals that give away how we're feeling.
In a talk and demo, she shows how "empathetic technology" can read physical signals like body temperature and Liv Boeree investigates how we make better decisions in an uncertain world.
Would you negotiate with someone you knew to be evil, to save lives? Samantha Power tells a story of a complicated hero, Sergio Vieira de Mello.
This UN diplomat walked a thin moral line, negotiating with the world's worst dictators to help their people survive crisis. It's a compelling story told with a fiery passion.
Those traits do not necessarily include his skill at the poker table, which spoiler alert lead to Mike McDermott taking Teddy to school by the end of the movie.
Using the size of the current pot to inform your bets is one of the most fundamental parts of poker strategy, but Teddy KGB does not seem to do that.
Teddy rarely seems to bet less than the size of the pot in the entire movie. Top-tier poker players do mix in overbets on occasion, but Teddy seems to fire massive wagers into the pot in every hand he plays.
The first hand of the movie is a good example of this. You may remember it as the hand in which Mike McDermott plays over his head and loses his entire bankroll to Teddy.
Versus such a huge bet, Mike could be hesitant to raise with trip nines or a flush. A smaller bet size will also make it more likely Mike raises with a hand like a flush or even a bluff, which would obviously be a welcome sight for Teddy.
But suppose Mike was holding anything other than a full house. He's gonna be hustlin' till the day he dies. Even though this was created Feb 17th Iceman just retweeted it himself today Aug 18th New World Order.
No Winning Orbits? In celebration of this monumental launch, Teddy got himself suspended from the Red Rock for 30 days, involving an altercation with another player.
Sounds a bit like he's selling the poker version of how to find gold in the Yukon after it was picked over by every two-bit prospector with a sluice pan and a dream.Before the build, Savage recaps an earlier project in which he recreated Teddy KGB’s poker chips (see video below). The latest instructional is a follow-up to that project and the next stage in. Plot. New York City law student and gifted poker player Mike McDermott dreams of winning the World Series of followstamps.com an underground Texas hold 'em game run by Russian mobster Teddy "KGB" (John Malkovich), an overconfident Mike loses his entire $30, bankroll in a single hand. Buss is widely considered one of the biggest rocks in the game of poker. 7. Teddy Monroe: The Iceman, a cash game grinder for nearly three decades, told Card Player, “If I go up early in a. Posts. Nov 11, Performers: The Kernel Trick, Random Fourier Features, and Attention Google AI recently released a paper, Rethinking Attention with Performers (Choromanski et al., ), which introduces Performer, a Transformer architecture which estimates the full-rank-attention mechanism using orthogonal random features to approximate the softmax kernel with linear space and time. TeddyPaw - Dinslaker Str, Oberhausen, Germany - Rated based on 11 Reviews "War gestern zum ersten mal dort hab direkt den ersten.
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