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Explore our collection of free quantitative research tools, interactive platforms, and trading applications covering factor investing, macroeconomic data, news sentiment, systematic strategies, and bias-free backtesting.

Man AHL has recently published a research piece titled “A Trend Following Deep Dive: Cash (Equities) Is King” (Panjabi, Bordigoni, and Buchanan, 2026) which has resonated not only with researchers in the trend-following space but also with those specializing in equity markets. The authors show that timing equity factors with momentum can provide meaningful diversification […]

If you have ever worked on quant-trading desks, or been involved in advisory work, you already know that portfolio managers and institutional clients are always keen to know whether a signal can support a certain amount of capital in production and real-world trading settings. With this new follow-up piece, we would like to present some […]

Most trading systems fail in production for reasons that have nothing to do with the strategy itself. The code works, the backtests look good, and paper trading passes, but the infrastructure around the system quietly breaks in ways most people never expect. From stale market data and rejected MOC orders to pacing violations, clock drift, and paper trading mismatches, these are some of the real production issues traders keep running into when automating through broker APIs like Interactive Brokers. Based on real conversations and production experience, here are a few lessons worth knowing before you go live.

Identical trading strategies can produce vastly different results depending on the data provider. In this study, the same backtest ranges from $226k to $726k, highlighting how intraday data quality can materially affect performance.

When Intraday Trades are carried overnight Quantitative research is, at its core, about following rules. As in any other STEM discipline (science, technology, engineering, and mathematics), precise frameworks give research rigor, discipline, and comparability. Yet, because such frameworks often remain unquestioned, challenging one of their constraints on purpose can sometimes be an informative experiment. In […]

Compounding is most often interrupted by investor reactions to volatility rather than by weak long-term returns. Volatility targeting seeks to stabilize portfolio risk over time, reducing behavioral errors and helping preserve long-term compounding.

This article examines whether intraday trend-following strategies are effective in Bitcoin and whether trend strength varies across the trading week. Using a high-frequency, volatility-targeted long–short benchmark, we identify a pronounced performance pickup starting Sunday evening New York time and extending into Monday, aligned with the Asian market open. We refer to this pattern as the Monday Asia Open Effect and discuss potential liquidity-driven explanations.

Volatility is fundamental to modern finance, yet it remains intrinsically unobservable. What we call “volatility” is not a directly measured quantity, but an estimate constructed from market data using a chosen methodology. Because volatility forecasts are evaluated against these constructed proxies rather than the latent volatility itself, model performance depends as much on how volatility is defined and measured as on the forecasting model used. Understanding this dependence is essential for interpreting volatility forecasts, comparing models, and applying them effectively across trading horizons and use cases.

In short-term trading systems, delaying the execution of a signal can lead to a meaningful deterioration in performance. Many systematic traders design strategies under the assumption that any signal computed at the market close should be executed on the next day’s open. This workflow has a clear and important advantage: it keeps the live trading […]

In the evaluation of new signals and trading strategies, a common practice is to initiate the research process by analyzing a full set of trade statistics. The rationale behind this approach is simple: strategies exhibiting attractive trade-level metrics are considered eligible for further due diligence, whereas those that do not can be quickly rejected. While […]

Intraday trading strategies have gained significant recognition for their ability to capture short-term market inefficiencies and extract uncorrelated returns. From time-tested opening-range breakouts (ORB) to volatility-based approaches, these strategies can deliver strong results when executed correctly. However, the speed, precision, and scale required to implement them effectively are nearly impossible to achieve manually. This underscores […]

Introduction Trend-following strategies are widely regarded for their long-term returns and diversification benefits. Yet, much of the literature often highlights entry and exit signals, leaving position sizing relatively underexplored. How positions are sized and managed can profoundly affect the shape and stability of a strategy’s equity curve, influencing not only total returns but also drawdowns, […]

Traditional financial theory asserts that higher risk should be accompanied by higher expected returns, with risk commonly measured by the volatility of an asset’s daily log returns. This principle suggests that investors who endure greater uncertainty should be rewarded with superior performance over the long run. However, empirical evidence challenges this notion. Over the past […]

In the world of investing, stories of traders achieving extraordinary returns often make headlines. These “market wizards” are celebrated, inspiring many to emulate their strategies. But how much of their success is due to skill, and how much is simply luck? While it’s challenging to answer this question definitively, we conducted an experiment to help […]

In the world of finance, a long-standing belief persists: trading is a game best left to large institutional investors. This myth suggests that retail investors lack the resources, technology, and market influence to compete effectively. However, recent developments challenge this notion, revealing that retail traders are not only capable but may sometimes be better positioned […]

Introduction: Carlo Zarattini is actually a trained mathematician. However, his family history suggests that the markets were already in his blood. After completing his math studies in Padua, the native Italian earned a Master’s degree in Quantitative Finance from USI Università della Svizzera italiana and Imperial College Business School in London. He also worked as […]

Shorting US equity markets has always been a challenge for active traders due to the positive long-term drift, commonly referred to as the equity risk premium. One common method to avoid the headwind from this long-term market drift is either to completely bypass the short side of a trading signal or to add a market […]

Learn how to evaluate a trading strategy using p-values, Monte Carlo simulations, and bootstrapping methods to distinguish real edge from randomness.