Quant Mashup - Quantpedia Cultural Calendars and the Gold Drift: Are Holidays Moving GLD ETF? [Quantpedia]Financial markets exhibit persistent calendar anomalies, which often defy the efficient‐market hypothesis by generating predictable return patterns tied to institutional or cultural events. In this paper, we document a novel, globally pervasive drift in gold prices surrounding major(...) How to Identify Ponzi Funds? [Quantpedia]Can we spot a Ponzi scheme before it collapses? That question haunts regulators, investors, and journalists alike. But what if some modern investment funds operate on dynamics that, while not technically illegal, closely resemble Ponzi-like behavior? A new paper by Philippe van der Beck,(...) The Memorization Problem: Can We Trust LLMs’ Forecasts? [Quantpedia]Everyone is excited about the potential of large language models (LLMs) to assist with forecasting, research, and countless day-to-day tasks. However, as their use expands into sensitive areas like financial prediction, serious concerns are emerging—particularly around memory leaks. In the recent(...) How Fragile is Liquidity Across Asset Classes? [Quantpedia]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(...) 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(...) 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(...) 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(...) 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(...) 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.(...) Quantpedia Awards 2025 – 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(...) Can We Finally Use ChatGPT as a Quantitative Analyst? [Quantpedia]In two of our previous articles, we explored the idea of using artificial intelligence to backtest trading strategies. Since then, AI has continued to develop, with tools like ChatGPT evolving from simple Q&A assistants into more complex tools that may aid in developing and testing investment(...) Is Machine Learning Better in Prediction of Direction or Value? [Quantpedia]Building machine learning models for trading is full of nuances, and one important but often overlooked question is: what exactly should we try to predict—the direction of the next market move or the actual value of the asset’s return? A recent paper by Cheng, Shang, and Zhao, titled(...) What Can We Expect from Long-Run Asset Returns? [Quantpedia]What can we realistically expect from investing across different asset classes over the long run? That’s the kind of big-picture question the “Long-Run Asset Returns“ paper tackles—offering a sweeping look at how stocks, bonds, real estate, and commodities have performed over the past 200(...) Are Sector-Specific Machine Learning Models Better Than Generalists? [Quantpedia]Can machine learning models better predict stock returns if they are tailored to specific industries, or is a one-size-fits-all (generalist) approach sufficient? This question lies at the heart of a recent research paper by Matthias Hanauer, Amar Soebhag, Marc Stam, and Tobias Hoogteijling. Their(...) Revisiting Pragmatic Asset Allocation: Simple Rules for Complex Times [Quantpedia]Pragmatic Asset Allocation (PAA) represents a portfolio construction approach that seeks to balance the benefits of systematic trend-following with the realities faced by semi-active investors (mainly taxes and lack of time to manage positions). Building upon the insights presented in Quantpedia’s(...) Quantpedia Awards 2025 – Countdown [Quantpedia]Hello all, Just little over 24 hours remain until the end of the deadline for QUANTPEDIA AWARDS 2025 – April 30th, 2025, at 23:59 UTC. Join the competition now, and don’t miss out on this chance to showcase your skills! Alternatively, if you can’t (or don’t want) to join, then please help us(...) Short-Term Correlated Stress Reversal Trading [Quantpedia]Short-term reversal strategies in U.S. large-cap equity indexes, such as the S&P 500, are well-documented and widely followed. These reversals often occur in response to brief periods of market stress, where sharp declines are followed by quick recoveries (as we have experienced in the last few(...) Uncovering the Pre-ECB Drift and Its Trading Strategy Applications [Quantpedia]As the world’s attention shifts from the US-centric equity markets to international equity markets (which strongly outperform on the YTD basis), we could review some interesting anomalies and patterns that exist outside of the United States. In the world of monetary policy, traders have long(...) Trump’s Executive Orders and Their Impact on Financial Markets [Quantpedia]In recent months, financial markets have experienced heightened volatility as Donald Trump, in his second term as President of the United States, increasingly uses executive orders to steer economic policy. While he also made use of this presidential power during his first term (2017–2021), the(...) Fear, Not Risk, Explains Asset Pricing [Quantpedia]With financial markets increasingly whipsawed by geopolitical tensions and unpredictable policy shifts from the Trump administration—investors are once again questioning how to understand risk, fear, and the true drivers of returns. A recent and compelling paper dives into this debate with a(...) Front Running in Country ETFs, or How to Spot and Leverage Seasonality [Quantpedia]Understanding seasonality in financial markets requires recognizing how predictable return patterns can be influenced by investor behavior. One underexplored aspect of this is the impact of front-running—where traders anticipate seasonal trends and act early, shifting returns forward in time. We(...) How Mega Tech Stocks Impact Factor Strategies [Quantpedia]The dominance of mega-tech stocks, particularly the “Magnificent 7,” in both U.S. and global equity indexes has a profound impact on factor portfolios. When constructing value-weighted smart beta strategies, these portfolios often end up heavily concentrated in a few individual stocks. This(...) How Global Neutral Rates Impact Currency Carry Strategies? [Quantpedia]Market practitioners often rely on experience-based wisdom to navigate currency markets, and one such widely held belief is that low dispersion in global bond yields signals weak future returns for carry trades (and high dispersion implies high future carry returns). While this intuition makes(...) Trading the Spread: Bitcoin ETFs vs. Cryptocurrencies Infrastructure ETFs [Quantpedia]In this study, we explore the application of simple spread trading strategies using Bitcoin ETFs and cryptocurrency infrastructure ETFs—two highly correlated asset classes due to the broader influence of cryptocurrency market movements. Given their strong relationship, this setup provides a(...) The Impact of the Inflation on the Performance of the US Dollar [Quantpedia]Inflation is one of the key macroeconomic forces shaping financial markets, influencing asset prices across the board. In our previous analysis, we examined how gold and Treasury prices react to changes in the inflation rate, uncovering patterns that suggested inflation dynamics also impact the US(...) Can Margin Debt Help Predict SPY’s Growth & Bear Markets? [Quantpedia]Navigating the financial markets requires a keen understanding of risk sentiment, and one often-overlooked dataset that provides valuable insights is FINRA’s margin debt statistics. Reported monthly, these figures track the total debit balances in customers’ securities margin accounts—a key(...) Using Inflation Data for Systematic Gold and Treasury Investment Strategies [Quantpedia]Inflation significantly impacts the prices of gold and treasury bonds through various mechanisms. Gold is often viewed as a hedge against inflation, while treasury bonds exhibit a more complex relationship influenced by interest rates and investor behavior. This relationship between inflation, gold,(...) Dangers of Relying on OHLC Prices – the Case of Overnight Drift in GDX ETF [Quantpedia]Can we truly rely on the opening price in OHLC data for backtesting? While the overnight drift effect is well-documented in a lot of asset classes, we investigated its presence in gold using the GLD ETF and then extended our analysis to the GDX – Gold Miners ETF, where we observed an unusually(...) Join the Race Once Again: Quantpedia Awards Competition Is Back! [Quantpedia]Hello everyone, Over the last few months, we have received numerous messages asking us if we plan to continue with our successful quant research competition in 2025. Last year, we promised our readers that the Quantpedia Awards would be back! And now it’s again time to unveil what we have prepared(...) Seasonality Patterns in the Crisis Hedge Portfolios [Quantpedia]Building upon the established research on market seasonality and the potential for front-running to boost associated profits, this article investigates the application of seasonal strategies within the context of crisis hedge portfolios. Unlike traditional asset allocation strategies that may falter(...) Out-of-Sample Test of Formula Investing Strategies [Quantpedia]Can we simplify the complexities of the stock market and distill them into a simple set of quantifiable metrics? A lot of academic papers suggest this, and they offer formulas that should make the life of a stock picker easier. Some of the most compelling methodologies within this realm are the(...) Detecting Wash Trading in Major Crypto Exchanges [Quantpedia]The general acceptance of cryptocurrencies, especially Bitcoin, was a blessing from Wall Street, which institutionalized them as ETFs for comprehensive access by the general public and institutional investors. There is little to no denying now that this new asset class is becoming more traditional,(...) Refining ETF Asset Momentum Strategy [Quantpedia]Today’s research introduces a refined ETF asset momentum strategy by combining a correlation filter with selective shorting. While traditional long-short momentum strategies usually yield suboptimal results, the long leg proves effective on its own, and the correlation filter demonstrates(...) Top Ten Blog Posts on Quantpedia in 2024 [Quantpedia]The year 2024 is nearly behind us, so it’s an excellent time for a short recapitulation. In the previous 12 months, we have been busy again (as usual) and have published over 70 short analyses of academic papers and our own research articles. The end of the year is a good opportunity to summarize(...) Front-Running Seasonality in US Stock Sectors [Quantpedia]Seasonality plays a significant role in financial markets and has become an essential concept for both practitioners and researchers. This phenomenon is particularly prominent in commodities, where natural cycles like weather or harvest periods directly affect supply and demand, leading to(...) Can We Use Active Share Measure as a Predictor? [Quantpedia]Active Share is a metric introduced to quantify the degree to which a portfolio differs from its benchmark index. It is expressed as a percentage, ranging from 0% (fully overlapping with the benchmark) to 100% (completely different). The concept gained popularity because it was believed that higher(...) Trader’s Guide to Front-Running Commodity Seasonality [Quantpedia]Seasonality is a well-known phenomenon in the commodity markets, with certain sectors exhibiting predictable patterns of performance during specific times of the year. These patterns often attract investors who aim to capitalize on anticipated price movements, creating a self-reinforcing cycle. But(...) How To Profitably Trade Bitcoin’s Overnight Sessions? [Quantpedia]As interest in cryptocurrencies continues to surge, driven by each new price rally, crypto assets have solidified their position as one of the main asset classes in global markets. Unlike traditional assets, which primarily trade during standard working hours, cryptocurrencies trade 24/7, presenting(...) How to Build Mean Reversion Strategies in Currencies [Quantpedia]Our article explores a simple mean reversion trading strategy applied to FX futures, focusing on identifying undervalued and overvalued currencies to generate returns. Using FX futures rather than spot rates allows for the inclusion of interest rate differentials, simplifying the analysis. The(...) Pre-Holiday Effect in Commodities [Quantpedia]Our research will explore the intriguing phenomenon of the Pre-Holiday effect in commodities, particularly crude oil and gasoline. Historical data reveals a short-term price drift prior to major U.S. holidays, suggesting a trend in these markets. We hypothesize that this anomaly may be driven by(...) How to Improve ETF Sector Momentum [Quantpedia]In this article, we explore the historical performance of sector momentum strategies and examine how their alpha has diminished over time. By analyzing the underlying causes behind this decline, we identify key factors contributing to the underperformance. Most importantly, we introduce an enhanced(...) How to Improve Commodity Momentum Using Intra-Market Correlation [Quantpedia]Momentum is one of the most researched market anomalies, well-known and widely accepted in both public and academic sectors. Its concept is straightforward: buy an asset when its price rises and sell it when it falls. The goal is to take advantage of these trends to achieve better returns than a(...) Revisiting Trend-following and Mean-reversion Strategies in Bitcoin [Quantpedia]Over the past few years, significant shifts in the financial landscape have reshaped the dynamics of global markets, including the cryptocurrency sector. Events such as the ongoing war in Ukraine, rising inflation rates, the soft landing scenario in the US economy, and the recent Bitcoin halving(...) Insights from the Geopolitical Sentiment Index made with Google Trends [Quantpedia]Throughout history, geopolitical stress and tension has been ever-present. From ancient civilizations to today’s world, global dynamics have been largely shaped by wars, terrorism, and trade disputes. Financial markets, as always, have keenly observed and been significantly influenced as a result.(...) Overnight Reversal Effects in the High-Yield Market [Quantpedia]High-yield bond ETFs represent a unique financial vehicle: they are highly liquid instruments that hold inherently illiquid securities, creating a fertile ground for predictable market behaviors. Our latest research uncovers an intriguing anomaly within these ETFs, similar to those observed in the(...) Lunch Effect in the U.S. Stock Market Indices [Quantpedia]In the complex world of financial markets, subtle patterns often reveal themselves through careful observation and analysis. Among these is the intriguing phenomenon we can call the “Lunch Effect,” a pattern observed in U.S. stock indexes where market performance tends to exhibit a distinct(...) A Few Thoughts on Pragmatic Asset Allocation [Quantpedia]One of the main reasons why the Pragmatic Asset Allocation Model was designed is to give investors a tax-efficient possibility to invest in a global equity portfolio with a lower risk than the passive buy&hold approach. Therefore, the PAA model is not the “absolute return” model but rather(...) The Art of Financial Illusion: How to Use Martingale Betting Systems to Fool People [Quantpedia]The Internet (and especially the part related to finance, trading, and cryptocurrencies) can be dangerous and full of offers of guaranteed returns, pictures of forever-growing bank accounts, and guys with golden rings swimming in the bathtub filled with cash. The truth is usually less rosy.(...) Investigation of Lead-Lag Effect in Easily-Mistyped Tickers [Quantpedia]Our new study aims to investigate the lead-lag effect between prominent, widely recognized stocks and smaller, less-known stocks with similar ticker symbols (for example, TSLA / TLSA), a phenomenon that has received limited attention in financial literature. The motivation behind this exploration(...) Quantpedia Composite Seasonality in MesoSim [Quantpedia]The Efficient Market Hypothesis (EMH), theory developed in the 1960s, states that stock prices reflect all available information, making it impossible to consistently earn above-average returns using this information. Nevertheless, numerous studies challenge this view by documenting anomalies that(...)