Quantocracy

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Recent Quant Links from Quantocracy as of 07/23/2025

This is a summary of links recently featured on Quantocracy as of Wednesday, 07/23/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Validation framework [Trading the Breaking]

    Look, anyone can show you a backtest with a nice Sharp. I've seen a thousand of them. The question I always ask is simple: Is this real, or did you just get lucky? Did you find a genuine edge, or did you just curve-fit the hell out of the last ten years of data? A pretty equity curve from the past tells you what happened. It tells you nothing about whether it will keep happening. So, we stop
  • Why the Last Few Minutes of Trading Might Matter More Than You Think [Alpha Architect]

    This paper reveals a striking pattern in U.S. stock markets: the prices of individual stocks often reverse direction at the very end of the trading day. Using high-frequency data, the authors find that the last few minutesparticularly the closing auctionare dominated by large institutional flows that cause temporary price pressure. This is followed by a reversal the next day. This
  • Weekly Research Recap [Quant Seeker]

    News Sentiment and Commodity Futures Investing (Yeguang, El-Jahel, and Vu) While momentum and carry strategies are well-known in commodities, this paper shows that weekly news sentiment from financial media also predicts returns. Using Refinitivs MarketPsych indices, the authors construct long-short portfolios that deliver strong risk-adjusted returns, even after accounting for costs. Combining

Recent Quant Links from Quantocracy as of 07/20/2025

This is a summary of links recently featured on Quantocracy as of Sunday, 07/20/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Carlson’s “Defense First” [Allocate Smartly]

    This is a test of Thomas Carlsons Defense First strategy from his paper Defense First: A Multi-Asset Tactical Model for Adaptive Downside Protection. Strategy results from 1971 follow. Results are net of transaction costs see backtest assumptions. Learn about what we do and follow 90+ asset allocation strategies like this one in near real-time. Logarithmically-scaled. Click for
  • When your strategy works, is it just dumb luck? How to stack the odds in your favour [Robot Wealth]

    Recently, we had an excellent question on the Trade Like a Quant Discord server: How do you know if your strategy is working out of coincidence rather than actual edge? The strategy might work over a long period just because of blind luck. Damn good question. It hits right in the insecurity because the honest answer is: you can never know for sure. I remember when I first started trading. I
  • The Memorization Problem: Can We Trust LLMs Forecasts? [Quantpedia]

    Everyone is excited about the potential of large language models (LLMs) to assist with forecasting, research, and countless day-to-day tasks. However, as their use expands into sensitive areas like financial prediction, serious concerns are emergingparticularly around memory leaks. In the recent paper The Memorization Problem: Can We Trust LLMs Economic Forecasts?, the authors
  • Behavioral Biases and Retail Options Trading [Relative Value Arbitrage]

    Why Do Investors Lose Money? Behavioral finance is the study of how financial behavior affects economic decisions and market outcomes, and how those decisions and outcomes are affected by psychological, social, and cultural factors. Behavioral finance research has shown that people do not always make rational decisions when it comes to money. Factors such as emotion, social pressure, and cognitive
  • Do Smart Machines Make Smarter Trades? [Alpha Architect]

    Can machine learning models help us exploit stock market anomalies more effectively? This paper says yesbut with a few important caveats. By applying gradient boosting algorithms to a wide array of established anomalies (like value, momentum, and quality), the authors show that machine learning methods can significantly improve the performance of long-short strategies. These models capture

Recent Quant Links from Quantocracy as of 07/15/2025

This is a summary of links recently featured on Quantocracy as of Tuesday, 07/15/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Unintended Consequences of Rebalancing [Quantitativo]

    I picked up one or two pieces and examined them attentively… I then collected four or five pieces and went to Mr. Scott… I said, I believe this is gold. James W. Marshall. He found gold and died broke. James W. Marshall unintentionally sparked one of the greatest migrations in American history. In 1848, while building a sawmill on the American River, he noticed a few glimmers in
  • Weekly Research Recap [Quant Seeker]

    In-Sample and Out-of-Sample Sharpe Ratios for Linear Predictive Models (Jacquier, Muhle-Karbe, and Mulligan) Combining many weak signals can raise a models in-sample Sharpe ratio, but this paper shows it often backfires out of sample due to overfitting. Even if the combined model looks better in backtests, it tends to perform worse in live trading than simpler models built on fewer, stronger
  • How Fragile is Liquidity Across Asset Classes? [Quantpedia]

    The paper Through Stormy Seas: How Fragile is Liquidity Across Asset Classes? is a very interesting examination of how liquidity properties have evolved over the past decade. Although the average bidask spread has declined, the kurtosis and skewness of the spread distribution have increased. What does this imply? On average, markets appear more liquid; however, liquidity evaporates more
  • The Rise of 0DTE Options: Cause for Concern or Business as Usual? [Relative Value Arbitrage]

    Zero DTE (Days to Expiration) options are contracts that expire on the same day they are traded. They were introduced in 2022 and have been gaining popularity. In this post, I discuss their impact on the market and how options traders use them. Impact of Zero DTE Options on the Market Zero DTE (0DTE) options, also known as same-day expiration options, are financial derivatives with

Recent Quant Links from Quantocracy as of 07/14/2025

This is a summary of links recently featured on Quantocracy as of Monday, 07/14/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The 10 Most Popular TAA Strategies Ranked [Allocate Smartly]

    Were in a unique position to analyze the behavior of Tactical Asset Allocation (TAA) investors. We track 90+ TAA strategies. Members combine these strategies into what we call Model Portfolios. By analyzing how members form these Model Portfolios, we can understand the choices that TAA investors make when strategies are presented objectively (no marketing mumbo jumbo) and technical
  • Testing Strategies [Trading the Breaking]

    Introduction. Risks and method limitations. Circular-shift (lag-invariant) permutation test. Random sign-flip (direction-neutral) test. Stationary bootstrap of returns. White's reality check and Hansen's superior predictive ability. Jittered-entry (temporal perturbation) test. Parameter stability test. Noise injection test. Synthesis Introduction The true starting point for any
  • Research Review | 11 July 2025 | Risk Factors [Capital Spectator]

    Factoring in the Low-Volatility Factor Amar Soebhag (Erasmus University Rotterdam), et al. June 2025 Low-volatility stocks have historically delivered higher risk-adjusted returns than their high-volatility peers. Despite extensive evidence and widespread adoption in the investment industry, the so-called low-volatility factor is absent from standard asset pricing models. This paradox is
  • Volatility is a Reliable and Convenient Proxy for Downside Risk [Alpha Architect]

    Javier Estrada, author of the June 2025 study Volatility: A Dead Ringer for Downside Risk tackled a longstanding debate in finance: Is volatility (the standard deviation of returns) a good measure of the risk that investors actually care about? While volatility is the most widely used risk metric in investing, it is also heavily criticized, especially by those who argue that investors are

Recent Quant Links from Quantocracy as of 07/08/2025

This is a summary of links recently featured on Quantocracy as of Tuesday, 07/08/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Lumber-Gold Strategy [Allocate Smartly]

    The Lumber-Gold Strategy was first published a decade ago, won the 2015 NAAIM Wagner Award, and continues to be cited today. The strategy trades based on the relative strength of lumber as a leading economic indicator, versus gold. How has the strategy performed since publication? Strategy results from 1987 follow. Results are net of transaction costs see backtest assumptions. Learn about what
  • Backtesting [Trading the Breaking]

    Introduction You know, after more than a decade in this business, I've come to think of backtesting as the ultimate paradox of our profession. It's like being handed the top one lie detector in the world, only to discover it's been calibrated exclusively on your own personal brand of self-deception. Let me tell you something about that momentand every quant knows exactly which
  • Weekly Research Recap [Quant Seeker]

    Hi there. Its time for this weeks recap of top investing research, with direct links to the original sources for easy access. As mentioned last week, there wont be a Thursday post this week as Im away on holiday. Normal posting resumes next week. Commodities Political Uncertainty and Commodity Markets (Hou, Tang, Tao, and Zhang) Commodity markets often respond sharply to political
  • Should Investors Combine or Separate Their Factor Exposures? [Alpha Architect]

    If youre a factor investor, there will come a time when you will have to choose between mom and dad: Should you combine or separate your factor exposures? And make no mistake: You will have to make a decision! While theres no right answer, the way you structure your portfolio can have significant implications for returns, costs, and even your own behavior as an investor. Lets walk through
  • How Machine Learning Enhances Market Volatility Forecasting Accuracy [Relative Value Arbitrage]

    Machine learning has many applications in finance, such as asset pricing, risk management, portfolio optimization, and fraud detection. In this post, I discuss the use of machine learning in forecasting volatility. Using Machine Learning to Predict Market Volatility The unpredictability of the markets is a well-known fact. Despite this, many traders and portfolio managers continue to try to

Recent Quant Links from Quantocracy as of 07/03/2025

This is a summary of links recently featured on Quantocracy as of Thursday, 07/03/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • PCA analysis of Futures returns for fun and profit, part 1 [Investment Idiocy]

    I know I had said I wouldn't be doing any substantive blog posts because of book writing (which is going well, thanks for asking) but this particular topic has been bugging me for a while. And if you listened to the last episode of Top Traders Unplugged you will hear me mention this in response to a question. So it's an itch I feel I need to scratch. Who knows, it might lead to a
  • Testing 87 Different Stop Loss Strategies [Paper to Profit]

    Stop losses are a way of life for a trader. They are often do or die in situations of intraday and leverage trading. However, we think that the gold standard is the average trailing stop. Maybe we add an ATR band to it if we are feeling fancy. But the reality is that there are much more effective stop loss strategies that exist. And, these strategies are not part of the mainstream.
  • Learn from the Source [Anton Vorobets]

    This newsletter gives you the last opportunity to get access to the Applied Quantitative Investment Management course at the best price. I will share the first lecture on Thursday, July 3rd. After that, the subscription price will increase from the current 100 per year. The subscription will give you access to video lectures, their slides, and a chat where you can ask me questions about the
  • Weekly Research Recap [Quant Seeker]

    How Efficient are Static Multi-Asset Portfolios? Evidence from Institutional Capital Market Expectations (Bni, Bruggermann, and Kroencke) Many investors rely on fixed-weight portfolios like the 60/40 split or equal-weighted, assuming these simple approaches are efficient. This paper challenges that belief, showing that they can be improved using forward-looking data. The authors incorporate

Recent Quant Links from Quantocracy as of 06/30/2025

This is a summary of links recently featured on Quantocracy as of Monday, 06/30/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • An Empirical Analysis of Conference-Driven Return Drift in Tech Stocks [Quantpedia]

    Corporate conferences have long been recognized as pivotal events in financial markets, serving as catalysts that signal upcoming innovations and strategic shifts. Scheduled corporate events induce market reactions that can be systematically analyzed to reveal predictable return patterns. In this work, we focus on examining the return drift exhibited by technology stocks in the days surrounding
  • The Derivative Payoff Bias [Quantitativo]

    You're nothing but a pack of cards! Alice, standing up to the Queen of Hearts. I used to think Alice in Wonderland was just a goofy kids story. After re-reading it as an adult, I actually think its brilliant. Its satire dressed up as nonsense. A dream disguised as a joke. A mirror hiding in plain sight. The White Rabbit? Thats obsession and urgency. The Queen of Hearts?
  • Mastering the Tri-Timeframe Trend-Following System [Alina Khay]

    Most losing trades happen for one reason: traders fight the trend on the wrong timeframe. You see a beautiful setup on the 15-minute chart, but the daily is turning, and the 4-hour is in no man's land. The result? You get chopped, faked out, or stopped at the exact top. Thats where Tri-Timeframe Trend-Following comes in. This strategy aligns three layers of market structure macro,
  • Can We Profit from Disagreements Between Machine Learning and Trend-Following Models? [Quantpedia]

    When using machine learning to forecast global equity returns, its tempting to focus on the raw predictionwhether some stock market is expected to go up or down. But our research shows that the real value lies elsewhere. What matters most isnt the level or direction of the machine learning models forecast but how much it differs from a simple, price-based benchmarksuch as a naive
  • A Cheat Code for Crypto? [Robot Wealth]

    The best trading edges are often found in places most people dont think to look. Its why being a bit of a pirate zigging when others zag and finding opportunities in the markets blind spots is such an effective approach. Today, I want to share something that has me genuinely excited. Its a little like finding a cheat code in a video game that gives you special powers the other
  • Insider Trading Increases Market Efficiency [Alpha Architect]

    The empirical research (for example, here, here, here and here) on insider trading demonstrates that insider transactions have significant predictive power for future stock returns as they reveal helpful information that may affect the price of stocks. George Jiang and Yun Ma contribute to the literature with their November 2023 study, Does Insider Trading Correct Mispricing? which examined
  • Predicting Corrections and Economic Slowdowns [Relative Value Arbitrage]

    Being able to anticipate a market correction or an economic recession is important for managing risk and positioning your portfolio ahead of major shifts. In this post, we feature two articles: one that analyzes indicators signaling a potential market correction, and another that examines recession forecasting models based on macroeconomic data. Predicting Recessions Using The Volatility Index And

Recent Quant Links from Quantocracy as of 06/25/2025

This is a summary of links recently featured on Quantocracy as of Wednesday, 06/25/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Navigating Economic Downturns with Survey-Based Recession Indicators [Allocate Smartly]

    This test was inspired by Yulong Suns paper Navigating Economic Downturns: Insights from Survey-Based Recession Indicators. Strategy results from 1970 follow. Results are net of transaction costs see backtest assumptions. Learn about what we do and follow 90+ asset allocation strategies like this one in near real-time. Logarithmically-scaled. Click for linearly-scaled results. These results
  • I Tuned the Radio on My Stock Returns [Paper to Profit]

    Its dated technology. The radio. But underpinning its humble origins is an electrical engineering field known as signal processing that has applications in literally everything around us: WiFi routers, making music sound better, and even detecting earthquakes. While many readers may assume that I built my system with bespoke approaches tuned specifically for financial applications, the reality
  • Weekly Research Recap [Quant Seeker]

    Genetic Mimicking Portfolios for ETF Arbitrage (Crego, Kvaerner, Sommervoll, Sommervoll, and Stevens) Many ETFs trade at a premium or discount to their net asset value (NAV). This paper targets corporate bond ETFs trading at a premium by shorting them and hedging the position with a portfolio of other liquid ETFs that replicate the NAV. Even after accounting for trading costs, the strategy

Recent Quant Links from Quantocracy as of 06/24/2025

This is a summary of links recently featured on Quantocracy as of Tuesday, 06/24/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Model: Advances in clustering [Trading the Breaking]

    Look, heres the thingweve all been drinking the correlation Kool-Aid for decades, right? Its elegant, sure. Clean math. Easy to explain to the PMs. But lets get real: relying on a correlation matrix in todays markets is like trying to sail a speedboat with an anchor chained to your hull. Its not just simplisticits dangerously misaligned with how the game actually works.
  • Experimental Control for Machine Learning of Temporal Effects in Quantitative Trading [Hanguk Quant]

    Experimental control is one of the foundational principles of sound scientific experimentation. Its importance lies in ensuring that the conclusions drawn from an experiment are valid and attributable to the factor(s) being investigated, rather than to confounding variables. Experimental control allows researchers to manipulate only the independent variable(s), establishing causal relationships by
  • Comprehensive Comparison of Algorithmic Trading Platforms [Jonathan Kinlay]

    This comprehensive analysis examines three leading algorithmic trading platformsBuild Alpha, Composer, and StrategyQuant Xacross five critical dimensions: comparative reviews and rankings, asset class applicability, ensemble strategy capabilities, walk-forward testing and robust optimization, and strategy implementation with broker connectivity. Through extensive research of platform
  • Rethinking Leveraged ETFs and Their Options [Relative Value Arbitrage]

    A leveraged Exchanged Traded Fund (LETF) is a financial instrument designed to deliver a multiple of the daily return of an underlying index. Despite criticism, LETFs are frequently used by institutional investors. In this post, I discuss the practicality of LETFs and show that they are not as risky as they may seem. Information Content of Leveraged ETFs Options Leveraged ETFs, or exchange-traded

Recent Quant Links from Quantocracy as of 06/22/2025

This is a summary of links recently featured on Quantocracy as of Sunday, 06/22/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Science and Practice of Trend-following Systems: paper and presentation [Artur Sepp]

    I would like to introduce the updated draft of my paper co-authored with Vladimir Lucic and entitled The Science and Practice of Trend-following Systems. Trend-following systems have been employed by many quantitative and discretionary funds, also known as commodity trading advisors (CTAs), or managed futures, since the early 1980s. Richard Dennis, a commodity trader on the CME, organised
  • Ask Me Anything with Euan Sinclair [Robot Wealth]

    In this Ask Me Anything, Euan addressed the following questions: Key lessons from wacky genius Victor Niederhoffer Euans journey from market maker to sports bettor to options trader What are the most important predictors for options trades? Where can we find good long vol trades? What is the minimum viable tech stack for an options beginner? Is it reasonable to harvest a VRP with ETPs vs
  • The Surefire Ratio: My Custom Risk Ratio that Supercharged My Investing [Paper to Profit]

    Weve all used it. Its seen as the gold standard of investment metrics. But the Sharpe ratio is a dated formula that takes a naive assumption on the market and runs us into walls. It has no concept of prolonged drawdowns or causality, and those that continue to use it as the gospel are quantitative luddites handicapping their own success. But get this: With a simple financial ratio, we