Quant Mashup Envision Your Financial Future and Plan How to Get There with a Portfolio of Portfolios [Engineered Portfolio]How much money do you aim to have by when and why? How will you achieve that goal? In this post I will share my vision and plan with specific investment strategies while posing questions to you to help you envision your own financial future and take steps to get there. At the age of 28 when I(...) Cryptocurrency as an Investable Asset Class – 10 Lessons [Quantpedia]Cryptocurrencies have matured from experimental curiosities into a viable investable asset class whose return-generation and risk characteristics merit treatment within empirical asset pricing. A recent paper by Nicola Borri, Yukun Liu, Aleh Tsyvinski, Xi Wu summarizes ten facts from the literature(...) Where Factors Speak Loudest: Why Size Matters in Factor Investing [Alpha Architect]The Curious Case of the Disappearing Size Premium The size effect was first documented by Rolf Banz in his 1981 paper “The Relationship Between Return and Market Value of Common Stocks,” which was published in the Journal of Financial Economics. After the 1992 publication of Eugene Fama and(...) Research Review | 24 October 2025 | Risk Analysis [Capital Spectator]The case for low-risk equity investing: evidence from 2011-2025 Raul Leote de Carvalho (BNP Paribas), et al. July 2025 This paper investigates the performance of equity low-risk strategies since 2011, highlighting their ability to deliver strong risk-adjusted returns across diverse market(...) The End-Of-Month Effect in Value–Growth and Real‑Estate–Equity Spreads [Quantpedia]The clustering of excess returns on the final trading days of the month constitutes a robust empirical regularity with significant implications for portfolio construction. We document a month-end premium that is both statistically and economically significant, distinct from the canonical(...) Optimization: Adaptive regret for regime-shifting markets [Trading the Breaking]In our preceding discourse, we talked about the features of parameter-free optimization, a methodology designed to liberate quantitative strategists from the sinister task of parameter tuning. The allure was undeniable: escape the perilous cycle of tweaking lookback windows, volatility thresholds,(...) Weekly Research Recap [Quant Seeker]Cryptocurrency as an Investable Asset Class: Coming of Age (Borri, Liu, Tsyvinski, and Wu) This paper describes 10 stylized facts about cryptocurrencies, including their 5× higher volatility but similar Sharpe ratios to equities, a rising correlation with stocks (2% to 37% post-2020) yet strong(...) Effectiveness of Covered Call Strategy in Developed and Emerging Markets [Relative Value Arbitrage]Covered call strategies are often promoted as an income-generation tool for investors seeking steady returns with reduced risk. But how effective are they in practice? In this post, we take a closer look at their real-world performance across different markets. Do Covered Calls Deliver Superior(...) Can Machine Learning Predict Factor Returns? [Alpha Architect]Nusret Cakici, Christian Fieberg, Carlos Osorio, Thorsten Poddig, and Adam Zaremba, authors of the study “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” published in the April 2025 issue of The Journal of Portfolio Management, set out to answer a(...) Can Technology Sector Leadership Be Systematically Exploited? [Quantpedia]The U.S. equity market has periodically been dominated by a few technology-driven stocks, most recently the so-called “Magnificent Seven.” Historically, similar dominance occurred during the Nifty Fifty era in the 1960s–1970s and the dot-com boom in the 1990s. These periods of concentrated(...) The crucial difference in price momentum vs. earnings momentum [Klement on Investing]Sometimes, you don’t know what you know until somebody spells it out crystal clear for you. At least that’s how I felt when I read the analysis of Kewei Hou and his colleagues on price momentum and earnings momentum. Most investors know that both price momentum and earnings momentum are factors(...) Why You Can’t Tell if Your Strategy “Stopped Working” (Statistically Speaking) [Robot Wealth]Traders love the illusion of precision. A few bad weeks go by, and you think, “Let’s run a t-test and see if the strategy stopped working.” It sounds rigorous. It isn’t. Imagine a strategy that, in truth, earns 10% per year with 20% volatility – roughly the S&P’s long-term profile.(...) The Points-and-Line Chart [Financial Hacker]-and-Line Chart Traders like special bars on a chart, since they let the price curve appear smoother and more predictable as it really is. Some types of bars, such as Renko bars, even use fake prices for generating curves that appear to move straight upwards or downwards. In the TASC November issue,(...) Weekly Research Recap [Quant Seeker]Analyzing over 1,500 bond funds (2015–2024) shows that active returns, performance relative to benchmarks, are driven mainly by systematic risk exposures, not manager skill. For Aggregate and Corporate funds, about 55% of active returns come from underweighting duration and overweighting credit(...) Identifying and Characterizing Market Regimes Across Asset Classes [Relative Value Arbitrage]Identifying market regimes is essential for understanding how risk, return, and volatility evolve across financial assets. In this post, we examine two quantitative approaches to regime detection. Hedge Effectiveness Under a Four-State Regime Switching Model Identifying market regimes is important(...) Asset Embeddings [Quantitativo]“You shall know a word by the company it keeps.” John Rupert Firth. John Rupert Firth was a British linguist and one of the pioneers of modern semantics. In the 1950s, he proposed a simple yet revolutionary idea: “You shall know a word by the company it keeps.” More than half a century(...) Is the degradation of trend following performance a cohort effect, instrument decay or environmental problem? [Investment Idiocy]It's probably bad luck to say this, but the most recent poor performance of CTAs and trend following managers this year appears to have been reversed. My own system is up over 12% since the nadir of the summer drawdown, and is now up for year; admittedly by only by 5.5%. Nevetheless, it's(...) Weekly Research Recap [Quant Seeker]Music as an Asset Class (Stoikov, Singla, Cetin, Cendra Villalobos) Analyzing 1,295 transactions from the Royalty Exchange, a marketplace for music royalties, the authors calibrate three discounted cash flow models to value music rights. The best-fitting model shows that “Life of Rights” assets(...) Book and Workshop Introduction: Generative AI for Trading and Asset Management [EP Chan]The world of finance is no stranger to artificial intelligence. Most quantitative asset managers are already familiar with discriminative models, for example, given yesterday’s return, what is the probability that today’s return will be positive? Many are also familiar with reinforcement(...) Gold’s Rally and the Gold Mining Stocks Trap [Quantpedia]Gold has been in the headlines lately as it climbs to new highs, prompting many investors to look for ways to benefit from the rally. However, many institutional investors – such as mutual funds and pension funds – face restrictions on buying physical gold or gold-backed ETFs. Instead, they(...) The Role of Data in Financial Modeling and Risk Management [Relative Value Arbitrage]Much emphasis has been placed on developing accurate and robust financial models, whether for pricing, trading, or risk management. However, a crucial yet often overlooked component of any quantitative system is the reliability of the underlying data. In this post, we explore some issues with(...) Employing volatility of volatility in long-term volatility forecasts [Outcast Beta]We demonstrate how simple long-term volatility forecasts can be improved by incorporating the volatility of short-term volatility into forecasting models. The theoretical framework for modelling volatility of short-term volatility, along with its role in long-term forecasts, will be outlined.(...) Weekly Research Recap [Quant Seeker]State-Dependent Market (In)Efficiency in Cryptocurrency Markets (Barak, Razmi, and Mousavi) Cryptocurrency return predictability is regime-dependent. This paper tests strategies based on “Directional Change events”, where a new trend is confirmed only once price moves a fixed percentage from the(...) Hedging Tail Risk with Robust VIXY Models [Quantpedia]Extreme market events, once perceived as statistical outliers, have become a central concern for investors. The persistence of sharp drawdowns and volatility spikes demonstrates that the cost of ignoring tail risks is not tolerable for long-term portfolio resilience. While diversification can(...) Parameter-free optimization [Trading the Breaking]Let’s talk plainly. Quant finance has spent years chasing complexity—layering indicators, stacking models, scaling clusters—anything that might tease out an edge. We’ve built whole infrastructures around that chase: faster data, bigger grids, deeper nets. Yet under all that polish sits an(...) Cross-Sectional and Dollar Components of Currency Risk Premia [Quantpedia]Currency strategies often appear simple on the surface – go long high-yielding currencies, short low-yielding ones, or take a position on the U.S. dollar. But these trades actually mix two distinct components: a Dollar component, which bets on broad movements of the U.S. dollar against all others,(...) A scorecard for global equity allocation [Macrosynergy]Macro-quantamental scorecards are systematic enhancements of discretionary portfolio management. They offer (a) information efficiency by structuring and condensing key macroeconomic data series, and (b) empirical validation of predictive power and trading value using historic point-in-time(...) Volatility Risk Premium Across Different Asset Classes [Relative Value Arbitrage]The volatility risk premium has been studied extensively in the equity space, but less so in other asset classes. In this post, we are going to examine the VRP across different asset classes. Volatility Risk Premium Across Different Asset Classes The volatility risk premium (VRP) is the compensation(...) Refining The 0DTE SPX Breakout Strategy with Evidence-Based Exclusions [Quantish]Every quant has been there. You’re backtesting a strategy, the overall results look good, but something feels off when you dig into the day-by-day breakdown. You keep digging while your gut says “this feels like data mining,” but the statistics keep pointing to the same uncomfortable truth –(...) Weekly Research Recap [Quant Seeker]The Term Structure of European Carbon Futures and the Predictive Power of Speculators and Hedgers (Lautner, Dudda, and Klein) Shifts in the carbon futures term structure are driven by hedgers, not speculators. Using ESMA Commitment of Traders data, the authors show that a 1% increase in commercial(...) Intelligent Concentration: A Synopsis of Warren Buffett and Diversification [Alpha Architect]Warren Buffett’s diversification practices have been back in the spotlight over the past few years. Specifically, the level of concentration in his portfolio has come under scrutiny due to the size of the largest stock holding in Berkshire Hathaway’s marketable equities portfolio. A historical(...) A Golden Opportunity to Upgrade a 60/40? [Alpha Architect]Our friends Corey Hoffstein and Rodrigo Gordillo over at Return Stacked have done some interesting research on the potential for gold to improve your run-of-the-mill 60/40. You’ll need to hit them directly on their site to get their full report. However, I read their very detailed white paper, and(...) Leveraged ETFs in Low-Volatility Environments [Quantpedia]Leveraged ETFs (such as SPXL – (Direxion Daily S&P 500 Bull 3X Shares) offer amplified exposure to the S&P 500, promising high returns but exposing investors to volatility drag caused by daily rebalancing. This effect can significantly erode performance over longer horizons, particularly(...) When Trading Systems Break Down: Causes of Decay and Stop Criteria [Relative Value Arbitrage]Decay and Stop Criteria Subscribe to newsletter A key challenge in system development is that trading performance often deteriorates after going live. In this post, we look at why this happens by examining the post-publication decay of stock anomalies, and we address a practical question faced by(...) What Drives the Excess Bond Premium? [Quantpedia]The Excess Bond Premium (EBP – the portion of corporate bond spreads not explained by default risk), a key metric in quantitative finance for gauging credit spreads, has long been a subject of intense scrutiny. Recent research sheds new light on its dynamics, moving beyond traditional(...) Robust optimization protocol [Trading the Breaking]Parameter optimization is where good ideas go to either earn their keep or quietly fail. Given a fixed modeling recipe, the optimizer will always return a winner; what it cannot tell you—unless you force it to—is whether that winner is real. Financial data are dependent, heteroskedastic,(...) Weekly Research Recap [Quant Seeker]News Sentiment and Commodity Futures Investing (Yeguang, El-Jahel, and Vu) Media news sentiment is a priced factor in commodity futures. A weekly long–short strategy, buying commodities with the most positive sentiment and shorting those with the most negative, delivers an 8.3% annualized return(...) Macro trading factors: dimension reduction and statistical learning [Macrosynergy]Macro trading factors are information states of economic developments that help predict asset returns. A single factor is typically represented by multiple indicators, just as a trading signal often combines several factors. Like signal generation, factor construction can be supported by(...) Volatility Targeting Across Asset Pricing Factors and Industry Portfolios [Relative Value Arbitrage] Profitably Trading the SPX Opening Range. Code Included. [Quantish]This promising strategy comes from Option Alpha’s comprehensive research on trading SPX breakouts with zero-day-to-expiration (0DTE) credit spreads – selling one option while buying a further OTM option for protection, collecting premium with defined risk. If you’re not famliar with Option(...) Weekly Research Recap [Quant Seeker]The trade imbalance network and currency returns (Hou, Sarno, and Ye) While past work links a country’s trade balance to predictability of FX returns, this study shows that its position in the global network of deficits and surpluses matters too. The authors create a centrality-based measure(...) Surprisingly Profitable Pre-Holiday Drift Signal for Bitcoin [Quantpedia]Cryptocurrency markets have matured into a distinct asset class characterized by extreme volatility, deep liquidity pools, and worldwide retail participation. Traditional equity and commodity markets exhibit a well-documented pre-holiday effect, where returns on trading days immediately preceding(...) A Better Stock Rotation System [Financial Hacker]A stock rotation system is normally a safe haven, compared to other algorithmic systems. There’s no risk of losing all capital, and you can expect small but steady gains. The catch: Most of those systems, and also the ETFs derived from them, do not fare better than the stock index. Many fare even(...) PCA analysis of Futures returns for fun and profit, part deux [Investment Idiocy]In my previous post I discussed what would happen if you did the crazy thing of doing a PCA on the whole universe of futures across assets, rather than just within US equities or bonds like The Man would want you to. In this post I explore how we could do something useful with them. There is some(...) Skewness Premium in Managed Futures: A Practitioner's Guide [Invest ReSolve]Skewness-based managed futures strategies offer a unique opportunity to enhance portfolio performance by exploiting the asymmetry of return distributions across diverse asset classes. By focusing on the third moment of return distributions—skewness—these strategies seek to capitalize on the(...) Conditional Value at Risk [OS Quant]Value at Risk (VaR) is the industry’s go-to portfolio risk metric. But, it’s a cutoff completely ignoring tail risk. It tells you how often you’ll breach a threshold, not how bad losses are when you do. Conditional Value at Risk (CVaR) looks at that damage. It measures the average of your(...) Equity duration and predictability [Alpha Architect]Since 1945, a silent revolution has taken place in the way equity markets move. The classic view of stock prices responding mainly to changes in expected dividends no longer holds. Instead, expected returns now dominate. This paper digs into the reason: equity duration has increased dramatically. As(...) Tail Risk Hedging Using Option Signals and Bond ETFs [Relative Value Arbitrage]Tail risk hedging plays a critical role in portfolio management. I discussed this topic in a previous article. In this post, I continue the discussion by presenting different techniques for managing tail risks. Hedging with Puts: Do Volatility and Skew Signals Work? Portfolio hedging remains a(...) Bitcoin ETFs in Conventional Multi-Asset Portfolios [Quantpedia]Understanding how Bitcoin-related instruments can fit into traditional portfolios is increasingly relevant for investors. Some risk-averse investors do not like to hold cryptocurrencies in their portfolios strategically; however, they may be open to investing in crypto-linked assets on a tactical(...) Weekly Research Recap [Quant Seeker]Global News Networks and Return Predictability (Freire, Moin, Quaini, and Soebhag) News sentiment, extracted from a massive global article dataset, predicts daily equity index returns across 14 developed markets. Local sentiment strategies nearly double buy-and-hold Sharpe ratios (e.g., U.S. 1.34(...)