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Recent Quant Links from Quantocracy as of 08/05/2025

This is a summary of links recently featured on Quantocracy as of Tuesday, 08/05/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quantamental Catch-Up [Anton Vorobets]

    Many of you have undoubtedly enjoyed the summer holidays, so you might have missed out on the first five lectures of the Applied Quantitative Investment Management course. So far, we have been through the first four chapters of the Portfolio Construction and Risk Management book, reaching a point where we understand stylized market facts, the investment simulation framework, and multi-asset
  • Cultural Calendars and the Gold Drift: Are Holidays Moving GLD ETF? [Quantpedia]

    Financial markets exhibit persistent calendar anomalies, which often defy the efficientmarket hypothesis by generating predictable return patterns tied to institutional or cultural events. In this paper, we document a novel, globally pervasive drift in gold prices surrounding major wealth-oriented festivals across the four principal cultural and religious domains: Christianity, Islam, Hinduism,
  • Weekly Research Recap [Quant Seeker]

    Commodities and Conundrums: Decoding Behavioural Finance in Market Dynamics (Till) Investors often underestimate the influence of psychological biases in trading, particularly in commodity markets. This paper examines real-world cases, such as the collapse of MF Global, where overconfidence, loss aversion, and confirmation bias led to significant failures. It also explores common commodity trading
  • The Limits of Out-of-Sample Testing [Relative Value Arbitrage]

    In trading system design, out-of-sample (OOS) testing is a critical step to assess robustness. It is a necessary step, but not sufficient. In this post, Ill explore some issues with OOS testing. How Well Overfitted Trading Systems Perform Out-of-Sample? In-sample overfitting is a serious problem when designing trading strategies. This is because a strategy that worked well in the past may not

Recent Quant Links from Quantocracy as of 08/03/2025

This is a summary of links recently featured on Quantocracy as of Sunday, 08/03/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • We interrupt this service for an important message [Klement on Investing]

    Hi everyone Usually, I dont comment too much on current affairs on this substack. Still, Trump firing the Head of the BLS, Erika McEntarfer, because he didnt like the labour market data, is extremely dangerous for investors everywhere. If you have investments in the US, you should be highly concerned about this because having truthful data about the state of the US economy is the foundation
  • A Quant’s Guide to Covariance Matrix Estimation [OS Quant]

    In this article, we explore three techniques to improve covariance matrix estimation: evaluating estimates independently of backtests, decoupling variance and correlation, and applying shrinkage for more robust outputs. Author Adrian Letchford Published 2 August 2025 Length 12 minutes Like what you see? Follow Adrian on Twitter to be notified of new content. Follow Estimating a covariance matrix
  • Overnight Crypto Returns [Falkenblog]

    On Monday, I examined the flaw in capturing the overnight equity return anomaly. The basic issue was that the anomaly shrank considerably after the 2008 bear market, and given that one has to turn over the entire portfolio twice a day, the minuscule transaction costs eliminate any alpha. The guys who created the overnight ETFs were also plagued by incredibly bad luck, but that just did them a
  • A Different Way of Looking at Returns [Mark Best]

    It would be nice if it were possible to trade a moving average cross. The problem with this is always that the data lags. Its not possible to trade the current value of a moving average since it requires trading prices in the past. The advantage to doing so is that, due to the smoothing, forecasts are less noisy. The good thing is than many moving averages are finite impulse response (FIR)

Recent Quant Links from Quantocracy as of 08/01/2025

This is a summary of links recently featured on Quantocracy as of Friday, 08/01/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 100 Papers an Hour: 10x’ing Your Strategy Research Speed With AI [Paper to Profit]

    As much as LLMs and AI seem to be writing our code, creating our art, and potentially replacing (or at least supplementing) our own artistic souls, they also still excel at pretty mundane tasks. When applied correctly, they can chew through hundreds of research papers at a time and give you deeper insights, inspiration, and clarity that you can use to apply to your own research process. So, if
  • Weekly Research Recap [Quant Seeker]

    The Actual Retail Price of Equity Trades (Schwarz, Barber, Huang, Jorion, and Odean) Contrary to conventional wisdom, payment for order flow (PFOF) isnt systematically linked to worse execution. This paper finds large cost differences across brokers for identical orders, not explained by PFOF or commissions. Market makers like Citadel treat each brokers flow differently, possibly due
  • First trading day of the month has generally been strong except August [Quantifiable Edges]

    Ive shown the chart below several times over the years. It breaks down by month the performance of the first trading day of the month. July has long had the strongest Day 1. But August is also notable for its lack of Day 1 performance. As you can see it is the only month with a negative Day 1 return. Below is a look at how it has played out over time. This doesnt appear to be a bearish

Recent Quant Links from Quantocracy as of 07/28/2025

This is a summary of links recently featured on Quantocracy as of Monday, 07/28/2025. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Options: Iron Condor Strategy [Trading the Breaking]

    The iron condors appeal is statistically seductive: a high-probability, defined-risk structure promising steady income from time decay and volatility erosion. Yet beneath its deceptively flat payoff profile lies a quantitatively intricate realityone where theoretical win rates often mask a negative expected value. This isnt a flaw in the strategy itself, but a consequence of its dynamic
  • The Equity Overnight Anomaly ETFs [Falkenblog]

    TL;DR The overnight return anomaly became much less anomalous around 2009 The failed ETFs designed to capture it suffered from horrible timing, but also transaction costs Transaction costs are much greater than fees, and also greater than fees + (ask-bid)/2 The overnight equity anomaly is that most of the total equity returns are generated from the opening to the close. When I was an active
  • From Defense to Offense: A Tactical Model for All Seasons [Quantitativo]

    Basketball is a game of adjustments. Bob Knight. Bob Knight was the last coach to lead an NCAA team to a perfect season: 32 wins, zero losses. That record still stands nearly half a century later. His secret? He was a masterful tactician. Obsessed with preparation, relentless on fundamentals, and unmatched in making in-game adjustments. Knight believed basketball wasnt about memorizing
  • How to Identify Ponzi Funds? [Quantpedia]

    Can we spot a Ponzi scheme before it collapses? That question haunts regulators, investors, and journalists alike. But what if some modern investment funds operate on dynamics that, while not technically illegal, closely resemble Ponzi-like behavior? A new paper by Philippe van der Beck, Jean-Philippe Bouchaud, and Dario Villamaina examines whether certain actively managed funds inflate their own
  • The Risks of Passive Investing Dominance [Alpha Architect]

    Fueled by the persistent failure of active management (as evidenced, for example, by the annual SPIVA scorecards), passive investing now commands the majority of assets under management. This structural shift is not without consequence. Chris Brightman and Campbell Harveys May 2025 paper Passive Aggressive: The Risks of Passive Investing Dominance, along with recent academic and industry
  • Sentiment as Signal: Forecasting with Alternative Data and Generative AI [Relative Value Arbitrage]

    Quantitative trading based on market sentiment is a less developed area compared to traditional approaches. With the explosion of social media, advances in computing resources, and AI technology, sentiment-based trading is making progress. In this post, I will explore some aspects of sentiment trading. Using ChatGPT to Extract Market Sentiment for Commodity Trading A Large Language Model (LLM) is

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