Sammy
@sammy_capital • 2,205 subscribers
ml + quant / reverse engineering markets, models & decision-making
Videos
When Hitler invaded Poland, John Templeton borrowed money and told his broker to buy $100 of every stock trading below $1. There were 104 of them. The broker called back with a problem: 37 were already bankrupt. Templeton told him to buy those too. He believed that if America entered a major war, even companies considered nearly worthless could return to production. One of the positions was Missouri Pacific preferred stock. It had fallen from $7 to 12 cents and had not paid a dividend in years. Templeton bought roughly 800 shares for $100. When the position reached 40 times his purchase price, he sold. The stock later climbed to $105. That trade became an early version of the philosophy behind the Templeton Growth Fund, where $10,000 invested at its 1954 launch reportedly grew to roughly $2 million by the time he sold the business in 1992. In this rare Charlie Rose interview, Templeton explains that bargains do not appear because the market calmly calculates fair value. They appear because frightened owners are desperate to sell. His job was to determine whether the pessimism had pushed the price below what the business could eventually earn. He compared earnings, growth, dividends, book value, and competitors. If similar companies traded at 25 times earnings while one credible business traded at five, that was where the research began. Templeton became a billionaire by buying assets other investors were emotionally unable to hold. This interview explains the arithmetic beneath the contrarian mythology.
Sammy1,604,791 görüntüleme • 1 ay önce
When one young Chicago trader first heard people were making $50,000 to $100,000 in a day He told himself he would quit the moment he ever made that kind of money. Then he had his first five-figure day. He was back in the pit the next morning. “After a while, the money becomes just a way of keeping score.” By the late 1980s, a seat on the exchange could cost more than $300,000, and the trading floors were said to hold more millionaires per square inch than anywhere else on earth. But the footage shows what that money did to people. Traders carried live quote machines on dates, practiced screaming so they could be heard above the crowd, wore the same clothes after winning days, and came back even after they had already made enough to leave. The technology looks ancient now. The psychology does not. This rare documentary captures the exact moment trading stops being about money and turns into identity, competition, and addiction to the game. Bookmark it and watch as a lesson from the past Especially now that markets are once again rewarding speed, hype, and risk-taking.
Sammy940,314 görüntüleme • 2 ay önce
One Chicago trader made $2.5 million in five days. Another explained how a five-tick move could put you up $1 million or wipe out the same amount before lunch. That was the world a young Chicago worker walked into for the first time. Paper was flying. Thousands of traders were screaming prices, throwing hand signals, and risking their own money in a room that looked more like a riot than a workplace. He went back to his job that same day and gave two weeks’ notice He just knew: “This was where I needed to be.” At its peak, Chicago had roughly 9,000 pit traders across its exchanges. Some were making $20,000 to $30,000 a day. But the most revealing line had nothing to do with getting rich: “It’s not what you make. It’s what you don’t lose.” Because the same aggression that made traders fortunes could keep them trapped inside a losing position while a car, then a house, disappeared in real time. Bookmark it and watch this piece of market history Before the next generation forgets what trading looked like when every emotion was visible.
Sammy114,859 görüntüleme • 2 ay önce
A senior quant at an $18.4 billion fund showed his team a study of 50 US stocks and asked: “why are we trading volume when the order book explains price better?” the answer led them into level 3 data during the same 30 seconds that an opening candle printed five values the exchange produced more than 215,000 messages hidden inside them were market makers adding liquidity, canceling bids, and stepping away before a move worth $120,000 appeared on the chart level 3 records every order added, modified, filled, or canceled, along with its price, size, side, and location in the book the team turned that stream into rates of additions, cancellations, and trades per second then they built two signals the continuation model looked for bids entering much faster than asks while the spread stayed tight and activity remained high the reversal model waited until price became stretched then watched bid cancellations jump above the 95th percentile of the previous 60 seconds while new buyers stopped replacing them the candle could still look bullish but the market makers underneath it had already started backing away they do not want thousands of bids filled as price falls and leaves the desk holding millions in unwanted long exposure so they cancel first the visible reversal comes later with $30 million positioned around the open, a 0.4% move equals roughly $120,000 the edge was not predicting every tick it was noticing the exact moment liquidity stopped supporting the price this is the skill firms pay six figures for: turning hundreds of thousands of invisible market events into one signal worth risking capital on I broke down how to build that skill from zero in 16 weeks bookmark this lesson then read the full quant roadmap below ↓
Sammy76,266 görüntüleme • 2 ay önce
A Nobel Prize-winning volatility model was turned into a trading filter with a reported 72% hit rate. The original framework came from economist Robert Engle. The new version answers one question before a trader risks any money: “Will tomorrow have enough price movement to trade?” On the example shown, GARCH predicted a true range near $306. The market realized roughly $311. The model takes true range, adjusts for its skew, removes the trailing average, and forecasts the remaining volatility. Then it compresses everything into a binary state: green chart = conditions are active normal chart = stay out That is closer to how professional risk systems think. They do not begin by searching for an entry. They first ask whether the current market regime is compatible with the strategy. A breakout strategy needs expansion. Without it, the setup can look perfect and still go nowhere. Most indicators tell you when to trade. This one may be more valuable because it tells you when the opportunity is not there.
Sammy63,498 görüntüleme • 2 ay önce
a portfolio manager running $8.4 billion once paid a quant researcher $410,000 a year to answer one question: “can you tell me which breakouts are real before we risk the money?” the researcher started with an idea traders had repeated for decades a breakout is stronger when the tape becomes “twitchy” everyone understood what that looked like nobody could define it precisely enough to code so he measured the speed at which trades forced price to update not raw volume because one million orders hitting the same price can create activity without moving the market the difference was enormous during lunch, price changed around 4 times per second near the closing bell, it jumped to almost 70 a 17.5x increase in the speed of price discovery then he built the test: breakout = 5-minute close beyond the previous 30-minute high or low signal = normalized price-update speed success = profit barrier reached before the equal-distance loss barrier now imagine the fund puts $25 million behind each breakout basket filtering out one false 0.8% move protects roughly $200,000 that is why the manager did not care whether the chart looked convincing he cared whether “twitchy” could be turned into a number most traders protect their intuition from being tested quants turn it into code and make it fight for capital and this is exactly the skill firms pay six figures for: taking a vague market idea, defining it mathematically, then testing whether it deserves real money I broke down how to build that skill from zero in 16 weeks bookmark this lesson then read the full quant roadmap below ↓
Sammy54,858 görüntüleme • 2 ay önce
Warren Buffett turned $10,000 into roughly $15 million without a computer, a Wall Street office, or an army of analysts Almost nobody watches the interview where he explains how Buffett was already worth more than $2 billion when Adam Smith visited him in Omaha His financial empire was run by seven people He spent most of the day reading and thinking, then occasionally made a decision large enough to matter for decades The numbers were already absurd $9.7 million invested in The Washington Post had become $370 million $46 million invested in GEICO had become $849 million A Berkshire share bought for $12 in 1965 was trading above $3,900 The interviewer asks why everyone does not simply copy the strategy Buffett’s answer has nothing to do with secret research or superior technology The principles were public. The undervaluations were visible. Everyone could see the same prices Most people would rather be promised they can get rich next week than accept that getting rich slowly may require years of doing almost nothing Bookmark this for the next time the market gives you a lower price and your emotions call it danger Then watch the section where Buffett says the New York Stock Exchange could close for two years and he would not care He was not buying lines moving across a screen He was buying businesses whose value could keep growing while nobody was allowed to trade them The footage is old, slightly blurry, and buried on YouTube The capital allocation lesson has aged better than nearly everything filmed since
Sammy31,831 görüntüleme • 2 ay önce
a kid still at university just tested inverse fair value gaps more seriously than most traders do before funding a $100,000 account he coded five-minute IFVGs on NQ, marked the first one-minute tap after each setup formed, then measured what price did next at first, the setup looked profitable average forward returns were positive, which is usually enough for someone online to call it an edge and start risking real money on it but there was a catch IFVGs do not appear in random conditions they often form during stronger trends, higher volatility, and more active parts of the session so the return might be coming from the environment, not the gap itself to test that, he matched every real IFVG tap with another market moment that had similar volatility, similar trend direction, and a similar time of day then he compared both groups the edge disappeared returns stayed slightly positive, but the 95% confidence intervals crossed zero in other words, there was no reliable evidence that the IFVG itself predicted anything better than a similar market moment he removed previously mitigated gaps and ran the test again same result ICT traders will probably say it needs a liquidity sweep, displacement, session filters, or higher-timeframe alignment maybe one of those conditions matters but each one has to be defined before looking at the result otherwise you can keep adding confluences until noise finally looks like a strategy that is the part most traders skip and it is exactly the skill quant firms pay six figures for: turning a trading belief into code, building the right baseline, and finding out whether the edge survives after the story is removed bookmark this test because it shows the exact point where a convincing chart pattern stops being a measurable edge then read article below if you want to learn how people actually build this kind of research skill from scratch ↓
Sammy22,054 görüntüleme • 2 ay önce
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