Quant Mashup

Should Investors Combine or Separate Their Factor Exposures? [Alpha Architect]

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(...)

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(...)

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(...)

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(...)

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(...)

Weekly Research Recap [Quant Seeker]

How Efficient are Static Multi-Asset Portfolios? Evidence from Institutional Capital Market Expectations (B?ni, 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(...)

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(...)

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 it��s brilliant. It��s satire dressed up as nonsense. A dream disguised as a joke. A(...)

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. That��s where(...)

Can We Profit from Disagreements Between Machine Learning and Trend-Following Models? [Quantpedia]

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(...)

A Cheat Code for Crypto? [Robot Wealth]

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 �C zigging when others zag and finding opportunities in the market��s blind spots �C is such an effective approach. Today, I want to share something that has me genuinely(...)

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(...)

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(...)

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

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 �C see backtest assumptions. Learn about what we do and follow 90+ asset allocation strategies like(...)

I Tuned the Radio on My Stock Returns [Paper to Profit]

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(...)

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(...)

Model: Advances in clustering [Trading the Breaking]

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 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(...)

Comprehensive Comparison of Algorithmic Trading Platforms [Jonathan Kinlay]

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,(...)

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(...)

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(...)

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 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(...)

The Surefire Ratio: My Custom Risk Ratio that Supercharged My Investing [Paper to Profit]

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(...)

Model: Clustering [Trading the Breaking]

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(...)

I Used a Thermostat��s Logic to Control My Portfolio��And Achieved 24% CAGR [Paper to Profit]

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(...)

Deep Reinforcement Learning for Portfolio Optimization [Gatambook]

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:(...)

Weekly Research Recap [Quant Seeker]

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(...)

Why Most Markets and Styles Have Been Lagging US Equities? [Quantpedia]

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(...)

Using Skewness and Kurtosis to Enhance Trading and Risk Management [Relative Value Arbitrage]

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(...)

Absolute Valuation Models for the Stock Market: Are Indexes Fairly Priced? [Quantpedia]

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(...)

Cesar Alvarez - A Novel Way to Combine Trend, Reversion, ETFs, Volatility & More [Algorithmic Advantage]

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(...)

Generating Synthetic Equity Data with Realistic Correlation Structure [Quant Start]

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(...)

Don\'t Over-Engineer your Trading Business�� Make Money Instead [Robot Wealth]

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(...)

Enhancing Momentum Strategies [Alpha Architect]

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(...)

Research Review?| 13 June 2025 | Analyzing And Monitoring Risk [Capital Spectator]

Short-Term Basis Reversal [Quantitativo]

��A single hair from the head of a woman is worth more than all the books of Galen and Avicenna.�� Paracelsus. Paracelsus (1493�C1541) was one of the most radical and influential physicians and philosophers of the Renaissance. A restless traveler, alchemist, and fierce critic of medical(...)

Weekly Research Recap [Quant Seeker]

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(...)

Supervised Portfolios: A Supervised Machine Learning Approach to Portfolio Optimization [Portfolio Optimizer]

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(...)

Reduce Trading Costs and Boost Profits with the "No-Trade Region" Strategy [Robot Wealth]

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(...)

Cross-Attention for Cross-Asset Applications [Gatambook]

In the previous blog post, we saw how we can apply self-attention transformers to a matrix of time series features of a single stock. The output of that transformer is a transformed feature vector r of dimension 768 �� 1. 768 is the result of 12 �� 64: all the lagged features are concatenated /(...)

Gold Ratios as Stock Market Predictors [Relative Value Arbitrage]

The ratio of gold prices to other asset classes has been shown to be a useful predictor of stock market returns. In this post, we discussed several gold-based ratios and how they can be used to forecast equity market performance. Gold Oil Price Ratio As a Predictor of Stock Market Returns Analyzing(...)

Pre-Announcement Drift for BoE, BoJ, SNB: Do Markets Move Before the Word Is Out? [Quantpedia]

We��ve previously examined how central bank policy decisions��particularly those by the Federal Reserve and the European Central Bank (ECB)��impact stock market behavior. The price drift in U.S. equities around the Federal Open Market Committee (FOMC) meetings is a well-documented phenomenon.(...)

Off to the Races: A Universal Metastrategy [Paper to Profit]

We often have baskets of assets that we turn into trading strategies. But also, we have baskets of trading strategies that we need to allocate our capital into. In my last post (here), I demonstrated how to use generative AI to create a theoretically limitless supply of trading strategies. But, this(...)

Weekly Research Recap [Quant Seeker]

Anomaly Persistence and Nonstandard Errors (Coqueret and Perignon) Many investing anomalies seem compelling, but their performance often depends on how they're tested. This paper demonstrates that overlapping design choices, such as holding periods and weighting, create strong correlations(...)

Quickies #1: Overfitting and EWMAC forecast scalars [Investment Idiocy]

I'm now in full book writing mode, so I don't have the time to do full blog posts. Instead I plan to do a series of quick posts where I share some research I did for the book. Cynically, there is also a chance it will encourage you to buy the book, as long as I don't overshare like(...)

Data: Range, Renko, Filter and Volatility bars [Trading the Breaking]

You are observing the markets in real-time��thousands of price ticks cascading across your screen, each reflecting a momentary shift in supply, demand, and sentiment. At first glance, the data appears evenly spaced, structured, and regular. Yet beneath this surface lies a deeper asymmetry: the(...)

Explaining overnight returns in the US [Joachim Klement]

Older people among my readers will remember the time when there was �C for a while �C a discussion about how the US stock market had significantly higher returns between yesterday��s close and today��s open (when there were no trades at all) than during the day. Those were the innocent days of(...)

Volatility of Volatility: Insights from VVIX [Relative Value Arbitrage]

The volatility of volatility index, VVIX, is a measure of the expected volatility of the VIX index itself. In this post, we will discuss its dynamics, compare it with the VIX index, and explore how it can be used to characterize market regimes. Dynamics of the Volatility of Volatility Index, VVIX(...)

Quantpedia Awards 2025 �C Winners Announcement [Quantpedia]

Hello all, Welcome to the Quantpedia Awards 2025 winners announcement. This is the moment we all have been waiting for, and today, we would again like to acknowledge the accomplishments of the researchers behind innovative studies in quantitative trading. So, what do the top five look like, and what(...)

164 Profitable Trading Strategies [Paper to Profit]

As mentioned in my last post (here), I designed and developed a way to quickly produce trading systems with the help of generative AI. And while this sounds like a recipe for disaster, because I constrained the problem to a very specific subset and I focused on only a few factors, the results were(...)

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