“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

In-Sample and Out-of-Sample Sharpe Ratios for Linear Predictive Models (Jacquier, Muhle-Karbe, and Mulligan) Combining many weak signals can raise a model’s 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

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 bid–ask spread has declined, the kurtosis and skewness of the spread distribution have

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

We’re 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

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

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

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

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

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

Hi there. It’s time for this week’s recap of top investing research, with direct links to the original sources for easy access. As mentioned last week, there won’t be a Thursday post this week as I’m away on holiday. Normal posting resumes next week. Commodities Political Uncertainty and

If you’re 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 there’s no right answer, the way you structure your portfolio can have

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

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

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

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

How Efficient are Static Multi-Asset Portfolios? Evidence from Institutional Capital Market Expectations (Böni, 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

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

“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 it’s brilliant. It’s satire dressed up as nonsense. A dream disguised as a joke. A

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. That’s where

When using machine learning to forecast global equity returns, it’s tempting to focus on the raw prediction—whether some stock market is expected to go up or down. But our research shows that the real value lies elsewhere. What matters most isn’t the level or direction of the machine learning

The best trading edges are often found in places most people don’t think to look. It’s why being a bit of a pirate – zigging when others zag and finding opportunities in the market’s blind spots – is such an effective approach. Today, I want to share something that has me genuinely

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

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

This test was inspired by Yulong Sun’s 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

It’s 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

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

Look, here’s the thing—we’ve all been drinking the correlation Kool-Aid for decades, right? It’s elegant, sure. Clean math. Easy to explain to the PMs. But let’s get real: relying on a correlation matrix in today’s markets is like trying to sail a speedboat with an anchor chained to your

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

This comprehensive analysis examines three leading algorithmic trading platforms—Build Alpha, Composer, and StrategyQuant X—across five critical dimensions: comparative reviews and rankings, asset class applicability, ensemble strategy capabilities, walk-forward testing and robust optimization,

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

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

In this Ask Me Anything, Euan addressed the following questions: Key lessons from wacky genius Victor Niederhoffer Euan’s 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

We’ve all used it. It’s 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

Alright, let’s establish first principles. Before deploying capital into algorithmic strategies, one must confront the paradigm shift that distinguishes durable firms from those erased by structural blind spots: financial markets are not monolithic stochastic processes but non-stationary systems

As traders, we scour the internet, books, and articles for industry specific information to create our new fancy algorithms. The Black-Scholes model, Markowitz Mean-Variance portfolio optimization, the Capital Asset Pricing Model (CAPM)… These are all systems designed for investment purposes

We wrote a lot about transformers in the last three blog posts. Their sole purpose was for feature transformation / importance weighting. These transformed and attention-weighted features will be used as input to downstream applications. In this blog post, we will discuss one such application:

Decoding the Bond Market (Haghani and White) Investors often look to bonds for clues about future interest rates and inflation. This paper explains how to extract such signals from current market yields. After adjusting for convexity and risk premia, the authors find that markets expect long-term

Over the past decade and a half, the US equities have set the hard-to-beat performance benchmark. Nearly all of the other countries, no matter if small or big, emerging or developed, have lagged behind. However, what are the forces behind this outperformance? Why did most of the other markets and

Skewness is a measure of the asymmetry of a return distribution. In this post, I’ll discuss the skewness risk premium and how skewness can be used to forecast realized volatility. Skewness Risk Premium in the Options Market Skewness of returns is a statistical measure that captures the asymmetry

Valuation models for equity indexes are essential tools for investors seeking to assess long-term market conditions. Traditional models like the CAPE ratio, introduced by Robert J. Shiller, or the Buffett Indicator often rely on macroeconomic variables such as corporate earnings or GDP. While

When I sat down recently with Cesar Alvarez of Alvarez Quant Trading, I knew I'd be tapping into a deep reservoir of quantitative trading wisdom. Cesar’s journey into systematic trading began similarly to many of us—starting with discretionary trades, dabbling in mutual funds, and

Recently on QuantStart we have begun looking at generating synthetic asset price paths using Stochastic Differential Equation models such as the Brownian Motion, Geometric Brownian Motion (GBM), Ornstein-Uhlenbeck and Vasicek Models. Historically, we have also considered more sophisticated models

Someone sent me their trading technology blueprint. It was a thing of beauty: timeseries databases, Grafana dashboards, message queues, and all sorts of fancy architecture. My first question: “What are you currently trading?” Their answer: “Nothing yet. But I’m planning a medium frequency

Paul Calluzzo, Fabio Moneta, and Selim Topaloglu, authors of the April 2025 study “Momentum at Long Holding Periods” investigated a key aspect of how academic momentum strategies are typically constructed when forming a portfolio. Specifically, at the end of each month t−1, the standard 12-2

“A single hair from the head of a woman is worth more than all the books of Galen and Avicenna.” Paracelsus. Paracelsus (1493–1541) was one of the most radical and influential physicians and philosophers of the Renaissance. A restless traveler, alchemist, and fierce critic of medical

The Reaction of Corn Futures Markets to US and Brazilian Crop Reports (Silveira, Silva, Mattos, Junior, and Capitani) Crop reports from the US and Brazil inform markets about expected corn production, but not all reports have the same impact. The authors find that US reports prompt sharp price

Standard portfolio allocation algorithms like Markowitz mean-variance optimization or Choueffati diversification ratio optimization usually take in input asset information (expected returns, estimated covariance matrix…) as well investor constraints and preferences (maximum asset weights, risk

An easy, practical way to harness an edge in the face of trading costs is the “no trade region” technique. It nearly always improves after-cost performance. Here’s a real example: And it does so with only one-tenth of the trading of the baseline strategy! Uncertain edge vs certain costs A good