Quant Mashup The Sharpe Ratio of Pure Noise [Quantt]This week we backtested 2,000,000 trading strategies. Every one of them was pure noise. We generated the returns ourselves with a random number generator, so we know, with complete certainty, that the true Sharpe ratio of every single strategy is exactly zero. The best ones still looked brilliant.(...) Dual vs. Single Momentum in Commodities: Enhancing Risk-Adjusted Returns [Quantpedia]Commodities represent a vital but highly volatile asset class, characterized by pronounced cyclicality, lack of yield, and susceptibility to severe macroeconomic drawdowns. While cross-sectional (relative) momentum is a well-documented anomaly, its application in commodities often forces portfolios(...) Automating a Volatility Strategy With Python and Interactive Brokers [Concretum Group]It won 5th place at the Quantpedia Awards 2026. The strategy compounds at 16.3% per year over a 17-year backtest, delivers a Sharpe ratio of 1, and keeps equity market correlation near 15%. This article shows how to build an automated VIX volatility trading strategy using Python and Interactive(...) FIFA* (*Fitting and Forecasting Actual data) Portfolio Optimisation competition with real returns [Investment Idiocy]This is my fourth post in my summer 2026 mini series on portfolio optimisation. It will very much follow the format of (also with a sports alluding title) blog post number two, so it might be worth rereading that. A reminder if you can't be bothered, I used random data to compare some(...) Feature selection: Filter-based methods [Trading the Breaking]Financial markets produce mountains of data, spanning simple price movements to limit order book dynamics. A common misconception assumes a larger dataset guarantees superior predictions. Reality proves the opposite. Excessive variables introduce noise, and invite to overfitting. Every input added(...) A Common Sense Guide to Volatility Trading [Quant Galore]It’s a Tuesday morning, you pull up a name you’ve been watching, and its 30-day implied vol is printing 48, sitting right near the top of where it’s traded all year. Vol is mean-reverting, everyone knows that, so you do the obvious thing. You sell the straddle, perhaps even an iron condor. Two(...) Market Effect Research: Turnaround Tuesday Effect [TradeQuantiX]This is the fourth article in the small market effect research series. The first looked at the holiday effect on SPY. The second looked at the turn of the month effect, also on SPY. The third looked at the holiday effect on gas and energy assets All three sets of research resulted in tradable(...) Why System Validation Matters More Than Ever [Relative Value Arbitrage]Today, AI and machine learning techniques are evolving at a rapid pace, making the development of trading systems increasingly accessible. Generating signals, building models, and testing ideas is easier than ever. As a result, the challenge is no longer simply developing a trading strategy, but(...) Dividend Timing and Global Dividend Premium [Alpha Architect]Asset pricing research often focuses on risk, valuation, and macroeconomic forces. But this paper highlights another surprisingly powerful driver of returns: the timing of dividend payments. Across 44 international equity markets, the authors uncover a large and persistent “dividend premium.”(...) A Hidden Trade Around SpaceX IPO? [Concretum Group]The piece we present today stems from some internal exchange within the Concretum team ahead of the highly anticipated SpaceX IPO, an offering that has dominated headlines for a string of firsts in recent market history, from its record valuation (~$1.75 trillion) to the one that interests us most:(...) The Factor Zoo Has Hundreds of Animals — But Only a Handful of Species [Alpha Architect]Academics have identified hundreds of factors that supposedly explain stock returns. New research shows most of them are telling the same story in different words — and only a few truly distinct forces actually drive the market. The problem: too many factors, too little meaning. Over the past few(...) The Right Way to Use AI in Trading (This Week) [Algorithmic Advantage]Yes, this is my first article without a podcast attached. The first of many, I hope. In time, I’d also like to produce more YouTube content that isn’t strictly interview-based. I’ll admit it: I’ve been biting off more than I can chew. Courses, podcasts, trading, farming (yep!). As you know,(...) I Audited 30 Years of SPY Candlesticks and the Variance Risk Premium [Peter Olayemi]Every retail trader eventually asks the same question: do candlestick patterns predict where price goes next? I decided to measure instead of believe. I built a small pipeline on SPY that discretizes each bar into one of twelve candle states, tests whether the next bar’s direction depends on that(...) Fast Option Pricing using Fourier Transform [Vertox Quant]Monte-Carlo Simulation is the most straightforward way to price an option, and if you don’t care about speed, it’s a solid choice. The moment you care about speed, like when quoting live, or when calibrating a pricing model where you need to reprice options thousands of times, Monte Carlo(...) Forecasting statistical estimates when data gets real [Investment Idiocy]This is my third post in a series about optimisation and fitting. In my previous post I used random data to calibrate and evaluate many portfolio optimisation techniques. It's worth quoting in full from that post: Random data is not real data: Well duh. But why is this important? Because random(...) Resourcing a Triangulated Stat Arb Operation as a Solo Trader [Robot Wealth]A Tale of Two Prices (the core idea of stat arb) Moneyball (finding undervalued pairs using unconventional metrics) The Winter of our Pairs Trading Discontent (problems, limitations, frustrations) The Metamorphosis (from pairs to portfolio) When is a Mispricing Not a Mispricing? (something(...) What Trend Following Actually Adds to a Risk-Premia Core [Beyond Passive]Combine a three-asset risk-premia portfolio with a trend-following program and the Sharpe ratio jumps from 1.1 to nearly 1.5. It looks like free diversification. But a trend program is long equities, bonds and metals — and a risk-premia core is equities, bonds and metals. So before we accept the(...) UFC - Ultimate Fitting Championships [Investment Idiocy]As I said in my last post I'm currently in the process of a mega-sized research project on fitting. In the first post I examined the correct way to cluster combinations of trading rules and instruments. This next post is rather meatier, and is about evaluating and calibrating some portfolio(...) When the insiders and the news disagree: a first look at the cross-signal [Tommi Johnsen]Two different sources each tell you something about where a stock is going. The first is insider trading filings: SEC Form 4, which executives, directors, and large shareholders are required to submit within two business days of buying or selling shares in their own company. The second is the news(...) Reconstructing a Century of U.S. Corporate Bonds [Quantpedia]How much do we really know about corporate bond returns before the modern data era? Until recently, the answer was: not enough. Most empirical work in corporate bond pricing has relied on relatively short samples, especially the post-2002 TRACE period, leaving open the question of whether observed(...) The crossword puzzle of fitting - why across and then down? [Investment Idiocy]This will be the first in a series of posts about portfolio optimisation. Main reason being I'm planning to write a book about backtesting, and that will include a big chunk of material on optimisation. Yes, I know, my latest book isn't out yet (it's out in December - in time for(...) The Non-Linear Costs of Trading [Concretum Group]At Concretum Group, a relevant part of our research effort goes into developing strategies for external clients, each arriving with different requirements about what market behavior to model and, just as importantly, about how much capital a given strategy is meant to run on. This brings us to a(...) How Wise is the Crowd in Prediction Markets [Quantpedia]If you’ve ever scrolled through Polymarket or Kalshi wondering whether the “wisdom of crowds” is actually wisdom—or just organized noise—you’re not alone. A new paper, “How Wise is the Crowd? Bias and Edge in Prediction Markets,” tears into the microstructure of modern prediction(...) Research Review | 5 June 2026 | Risk Management [Capital Spectator]Measuring Bubbles via Put-Call Disparity: A Model-Free Approach Robert A. Jarrow (Cornell U.) and Simon Kwok (U. of Sydney) May 2026 This paper introduces simple, model-free lower and upper bounds for measuring the size of asset price bubbles. Assuming only that the market satisfies(...) The software side of replication [Implementing QuantLib]Hello again! Today’s post was originally published in the November 2025 issue of Wilmott Magazine. What if you could make it a lot easier for readers to replicate your paper? That was the idea I followed when Wilmott called for articles to be published in a special issue on the replication crisis.(...) Does Regression Still Work in Modern Markets? [Relative Value Arbitrage]Regression is one of the oldest and widely used statistical techniques. It has found applications across the social sciences, engineering, natural sciences, and finance. Despite the rapid rise of machine learning and AI, regression remains a useful tool for modeling relationships, making forecasts,(...) New Feature: Return Contribution Analysis [Allocate Smartly]Every strategy and Model Portfolio now includes a Return Contribution analysis, showing each asset’s contribution to overall annual return. We further aggregate results by asset category and risk on/off, as well as estimate the drag from “trading friction” (transaction costs + slippage).(...) Trend following (2/4): Sector-by-sector replication [Beyond Passive]Part 1 left a gap. Regressing the synthetic backtrack against the whole universe at once recovered the program in ten contracts at a Sharpe of 0.84, against the program’s 1.03 — a fifth of a Sharpe unaccounted for. I argued there that the gap lived in the regression’s blindness to the(...) When Is a Mispricing Not a Mispricing? [Robot Wealth]Last time, I showed you a pattern in energy spreads and asked what it meant. The answer seemed obvious: XOM is the outlier. Every spread involving XOM is stretched. The spreads not involving XOM are near zero. But on this seemingly obvious map of mispricings, XOM may not mark the spot… The name(...) AI Overfitting in Trading Systems [Wisdom Trading]In-sample looks great. Live trading is where the truth lives. A few weeks ago we wrote about how we use AI alongside Trading Blox — what it does well, what it doesn’t, and the workflow we run. The single biggest risk we flagged was overfitting — specifically, the way AI overfitting in trading(...) New Feature: Model Portfolio Withdrawal Rates [Allocate Smartly]We’ve added Safe and Perpetual Withdrawal Rates to your custom Model Portfolios. New here? Learn more: What is a Model Portfolio? What are Withdrawal Rates? The Safe Withdrawal Rate (SWR) measures the max amount that could have been withdrawn each year in retirement (with an annual adjustment for(...) Market Effect Research: Holiday Seasonality - Part 2 [TradeQuantiX]Welcome to the “Systematic Trading with TradeQuantiX” newsletter, your go-to resource for all things systematic trading. This publication will equip you with a complete toolkit to support your systematic trading journey, sent straight to your inbox. Remember, it’s more than just another(...) Institutions’ return expectations across assets and time [Alpha Architect]Asset prices are often viewed through a simple lens. Investors form expectations, discount future cash flows, and determine prices accordingly. But in reality, expectations themselves are complex. They vary across institutions, across asset classes, and over time. This paper introduces a new(...) How to Build a Reliable Algo Trading Infrastructure [Concretum Group]More and more traders are using Claude Code, ChatGPT, Cursor, and other LLMs to build and automate their trading systems. It works. You can go from strategy idea to a working bot in a day. The code compiles, the backtest looks good, orders fire on paper trading, and you move to production. Then(...) Trend following (1/4): Replicating your own program [Beyond Passive]The published literature on trend-following replication treats the program being copied as a black box. When the program is your own, this is the wrong way around — and fixing it changes the result more than I expected. The story of trend following as a systematic strategy reaches back to the(...) When Short Sellers Create Overnight Alpha [Concretum Group]Last week, we shared some findings of an intraday short-selling signal taken from our internal research archives. Today, picking up on the same theme, we present some evidence behind an effect we believe stems from the very presence of short sellers in stocks with the same characteristics(...) Trend-Following Filters – Part 10 [Alpha Architect]Two previous articles, “Trend-Following Filters – Part 7” [1] and “Trend-Following Filters – Part 9” [2], examined, from a digital signal processing (DSP) time domain perspective, digital filters commonly used by technical analysts to aid in making trading decisions. The filters examined(...) The Sharpe stability ratio of trading strategies [Macrosynergy]The Sharpe stability ratio measures the consistency of risk-adjusted PnL value generation. It divides the mean Sharpe ratio over sequential overlapping lookback periods by its estimated standard error. Thereby, it quantifies significance and intertemporal stability. Both are critical for selecting(...) Quantpedia Awards 2026 – Winners Announcement [Quantpedia]Welcome to the Quantpedia Awards 2026 winners announcement. For the third time, we are proud to celebrate excellence in quantitative research and recognize the researchers behind innovative studies in quantitative trading. We are also pleased to see that the Quantpedia Awards have become an(...) Martyn Tinsley - Walk Forward Correlation: A New Tool for Robust Strategy Design [Algorithmic Advantage]That line, usually pinned to Einstein, fits this article rather well. In trading strategy research, we can spend a long time counting the wrong thing: like, as Martyn Tinsley says - whether the single best in-sample parameter set survives out-of-sample testing. Martyn Tinsley’s novel new approach,(...) Most of the insider trading alpha is gone by the time you see the filing: poof! [Tommi Johnsen]The academic literature on legal insider trading is unusually mature. Sixty years of work, replicated across multiple samples and methodologies, has converged on a few consistent claims: insider purchases carry information, insider sales mostly do not, cluster buying by multiple insiders is stronger(...) The Metamorphosis [Robot Wealth]Pairs trading remains a feasible approach for the indie trader. But, as we saw last time, there are inherent limitations. Trading both legs eats a lot of buying power and limits the number of pairs you can trade. Trading only the mispriced leg helps, but introduces a ton of variance. Essentially,(...) Active Dual Momentum GTAA Strategy [Quantpedia]Our study explores a weekly-rebalanced dual-momentum-based Global Tactical Asset Allocation (GTAA) strategy applied to a diversified set of ETFs. The strategy selects assets based on relative momentum and applies an absolute momentum filter to avoid declining investments. Ultimately, a single(...) Identifying Stocks to Fade [Concretum Group]Without a shade of doubt, Market Wizards books have been a staple in the upbringing of whole generations of traders and investors, and rightfully so… we ourselves have been inspired by the exceptional stories within them. The series, authored by Jack Schwager, began in 1989: what has made it so(...) A Faster Monotone Implied Volatiltty Solver [Chase the Devil]Choi, Huh and Su have a very good paper entitled Tighter uniform bounds for Black–Scholes implied volatility and the applications to root-finding. What’s particularly great is that it gives both a decent lower bound and a proof a monotone convergence using Newton’s method starting from this(...) When Everyone Trades the Same Factor Playbook [Alpha Architect]For decades, academic researchers have catalogued hundreds of patterns in the stock market — statistical regularities linking firm characteristics to future returns. These persistent return patterns, unexplained by standard risk models, are known as anomalies. They now form the intellectual(...) How to Manage an Intraday Trend Trade [Concretum Group]In managing our book, we run trend strategies across multiple asset classes and at different speeds, with exposure ranging from slower multi-day systems to faster intraday signals. Regardless of model specifications, we keep observing the same pattern: small implementation details can produce(...) A Century Without Data: Reconstructing Emerging Markets Equity History [Quantpedia]For U.S. equities, fixed income, and commodities, reconstructing long-term historical datasets is relatively straightforward, and we have already explored these challenges in several previous studies, including 100 Years of Multi-Asset Trend Following, Extending Historical Daily Bond Data to 100(...) Market Effect Research: Turn of the Month Effect [TradeQuantiX]Welcome to the “Systematic Trading with TradeQuantiX” newsletter, your go-to resource for all things systematic trading. This publication will equip you with a complete toolkit to support your systematic trading journey, sent straight to your inbox. Remember, it’s more than just another(...) Nine Pounds of Ore for an Ounce of Gold [Tommi Johnsen]Last night the pipeline pulled 1,199 financial news articles tagged across nine GICS sectors. It started at 9 PM Mountain Time and finished around 1 AM. By morning we had sorted the catch. One hundred and six articles carried direction. The other one thousand ninety-three were ore. Thanks for(...)