Zaremba, Adam
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Zaremba, Adam
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Zaremba, Adam
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Item-typ:Veröffentlichung, Non-standard errors in the cryptocurrency worldMotivated by recent findings from the equity market, we investigate non-standard errors in cryptocurrency research. We examine ten prevalent decisions related to data sources, sample preparation, and portfolio construction, generating 20,736 research designs for 43 sorting variables. Our findings reveal remarkable variation in portfolio performance tied to seemingly trivial choices. The non-standard errors in cryptocurrency studies not only surpass those in the stock market but also clearly exceed standard errors—though varying considerably across coin characteristics. Notwithstanding the above, the most prominent cryptocurrency factors, such as size and momentum, remain consistently robust across numerous specifications. Lastly, we find that reducing the influence of the smallest coins effectively decreases the non-standard errors.Wissenschaftlicher ArtikelHeft:9234 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Machine learning goes global: Cross-sectional return predictability in international stock marketsWe examine return predictability with machine learning in 46 stock markets around the world. We calculate 148 firm characteristics and use them to feed a repertoire of different models. The algorithms extract predictability mainly from simple yet popular factor types—such as momentum, reversal, value, and size. All individual models generate substantial economic gains; however, combining them proves particularly effective. Despite the overall robustness, the machine learning performance depends heavily on firm size and availability of recent information. Furthermore, it varies internationally along two critical dimensions: the number of listed firms in the market and the average idiosyncratic risk limiting arbitrage.Wissenschaftlicher ArtikelHeft:15579 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Pockets of Predictability: A Replication(Wiley, 2025-08); ; Farmer, Schmidt, and Timmermann (FST) document time-variation in market return predictability, identifying “pockets” of significant predictability through kernel regressions. However, our analysis reveals a critical discrepancy between the method outlined by FST and the code actually implemented. Instead of using a one-sided kernel, which guarantees out-of-sample forecasts, they perform in-sample estimation with a two-sided kernel. As a result, future information leaks into the forecasting model, undermining its reliability. Rectifying this error qualitatively alters the findings, invalidating most conclusions of the FST study. Thus, attempts to exploit such “pockets”—should they exist—offer little help in forecasting market returns.Wissenschaftlicher ArtikelBand:80Heft:617 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Cross-country factor momentumWe study a new class of the momentum effect: cross-country factor momentum. We document a persistent international pattern: factors in winning countries consistently outperform those in losing countries. The effect holds across most anomalies and is robust to many considerations.Wissenschaftlicher ArtikelHeft:23532 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, A Trend Factor for the Cross Section of Cryptocurrency Returns(Cambridge University Press, 2025-07); ; ; ; We propose CTREND, a new trend factor for cryptocurrency returns, which aggregates price and volume information across different time horizons. Using data on more than 3,000 coins, we employ machine learning methods to exploit information from various technical indicators. The resulting signal reliably predicts cryptocurrency returns. The effect cannot be subsumed by known factors and remains robust across different subperiods, market states, and alternative research designs. Moreover, it survives the impact of transaction costs and persists in big and liquid coins. Finally, an asset pricing model that incorporates CTREND outperforms competing factor models, providing a superior explanation of cryptocurrency returns.Wissenschaftlicher ArtikelBand:60Heft:751 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns(With Intelligence, 2025-04); ; ; The article examines the cross-sectional predictability of factor returns. Using machine learning techniques, the authors extract information from a comprehensive set of factor characteristics measuring their past returns, risks, and spreads. Applying this method to a repertoire of US stock market anomalies, they find robust predictability in their performance. The decile of factors with the highest expected return outperforms those with the worst outlook by up to 1.39% per month. The alphas are robust to many considerations but gradually decline over time. Predictability is mainly driven by factor momentum, which captures most of the cross-sectional variation in anomaly returns.Wissenschaftlicher ArtikelBand:51Heft:678 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Cryptocurrency factor momentumIs there a momentum effect in cryptocurrency anomalies? To answer this, we analyze data from over 3900 coins spanning the years 2014 to 2022 and replicate 34 anomalies in the cross-section of cryptocurrency returns. We document a discernible pattern in factor premia: past winners consistently outperform losers. The effect persists across subperiods, withstands various methodological approaches, and its magnitude parallels that of its stock market counterpart. However, the autocorrelation in factor returns is not widespread and primarily stems from size and volatility anomalies. Additionally, unlike in stocks, cryptocurrency factor momentum originates from price momentum, which subsequently transfers to the factor level.Wissenschaftlicher ArtikelBand:23Heft:12134 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Factor momentum versus price momentum: Insights from international marketsDoes factor momentum drive stock price momentum? We examine this relationship across 51 countries. Factor momentum proves strong across many markets and international portfolios, independent of typical return predictability drivers. However, its ability to capture stock momentum profits depends on methodological and dataset choices. Empirical factor momentum cannot entirely subsume stock or industry momentum globally. Conversely, price momentum often better explains its factor counterpart than vice versa. Notably, factor momentum based on principal components is more robust, capturing a major share of price momentum gains in developed and emerging markets. Our findings challenge the view that momentum merely times other factors rather than constituting a distinct.Wissenschaftlicher ArtikelBand:17012 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Cryptocurrency anomalies and economic constraintsThe asset pricing literature documents a growing list of predictable patterns in the cross-section of cryptocurrency returns. But can they be forged into viable trading profits? We answer this question by examining the interplay between economic restrictions and return predictability in cryptocurrency markets. We find that size and volume anomalies originate from micro-cap coins of negligible economic importance. Conversely, the momentum effect prevails in larger cryptocurrencies but incurs substantial trading costs and extracts alphas largely from short positions. Most abnormal returns occur primarily in bull markets and fade over time. Therefore, protocols for identifying tradable cryptocurrency anomalies should focus on long positions, account for transaction costs, consider hard-to-trade coins, and emphasize performance in recent years.Wissenschaftlicher ArtikelHeft:9469 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Factor momentum versus price momentum: Insights from international marketsDoes factor momentum drive stock price momentum? We examine this relationship across 51 countries. Factor momentum proves strong across many markets and international portfolios, independent of typical return predictability drivers. However, its ability to capture stock momentum profits depends on methodological and dataset choices. Empirical factor momentum cannot entirely subsume stock or industry momentum globally. Conversely, price momentum often better explains its factor counterpart than vice versa. Notably, factor momentum based on principal components is more robust, capturing a major share of price momentum gains in developed and emerging markets. Our findings challenge the view that momentum merely times other factors rather than constituting a distinct anomaly.Wissenschaftlicher ArtikelHeft:170102