Quantpedia Premium Update – February 8th

New Strategies:

#1093 – Downside Risk Premium in US Stocks

Period of rebalancing: Quarterly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 1963-2022
Indicative performance: 6.29%
Estimated volatility: 15.4%

Source paper:

Li, Frank Weikai and Niu, Zilong: Resurrecting the Downside Risk Premium – a Geographic Perspective
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5019010
Prior studies document a downside risk premium where by stocks with greater sensitivities to downside market movements earn higher average returns contemporaneously, but the downside risk premium disappears with ex-ante downside beta. In this paper, we resurrect the downside risk premium by showing that stocks with higher sensitivities to local stock market downturns earn significantly higher future returns. The return predictability of local downside beta is distinct from other risk measures and stock anomalies. Furthermore, the local downside risk premium is more pronounced for stocks headquartered in regions with stronger local bias and where local labor income is highly correlated with local market return, and during periods when investors are less concerned about aggregate economic risks. Stocks with higher local downside betas are eschewed more by local investors than by non-local investors. Collectively, our findings suggest that local investors perceive stocks with higher local downside beta as riskier and demand additional compensation for holding such stocks.

#1094 – Intraday Drift in Crude Oil Price

Period of rebalancing: Intraday
Markets traded: commodities, equities
Instruments used for trading: CFDs, futures
Complexity: Moderately complex strategy
Backtest period: 2010-2021
Indicative performance: 6.29%
Estimated volatility: 18.14%

Source paper:

Ewald, Christian Oliver and Haugom, Erik and Ouyang, Ruolan and Smith-Meyer, Erik and Størdal, Ståle: Intra-day Seasonality and Abnormal Returns in the Brent Crude Oil Futures Market
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5037563
Abstract:
We investigate intra-day seasonal patterns in Brent crude oil futures traded at the Intercontinental Exchange in London. Our data cover tick data for futures of various maturities from January 2010 to October 2021, a database covering 130 Gigabytes of oil transactions. We convert these data into one-minute data and observe statistically significant intra-day seasonal patterns with peaks and bottoms at particular times of the day, depending on maturities and whether or not spreads are considered. In the second part of our analysis, we explore whether these systematic patterns can be exploited to create arbitrage-like long-short strategies, going long and short at particular times during the day. The answer is yes; even when accounting for realistic transaction costs and margin requirements, some of the proposed strategies can create consistent positive and significant CAPM alphas.

#1095 – Front-Running Sector ETF Seasonality Strategy

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: ETFs
Complexity: Moderately complex strategy
Backtest period: 1998-2024
Indicative performance: 10.99%
Estimated volatility: 16.81%

Source paper:

Beluská, Soňa and Vojtko, Radovan: Front-Running Seasonality in US Stock Sectors
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5119553
Abstract:
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 predictable price movements. However, seasonality also plays a role in equity markets, influencing stock prices based on recurring calendar patterns, such as month-end effects or holiday periods. Recognizing these patterns can provide investors with an edge by identifying windows of opportunity or risk in their investment strategies. In this study, we combine our knowledge obtained from articles such as Trader’s Guide to Front-Running Commodity Seasonality (how front-running affects commodity seasonality patterns), Market Seasonality Effect in World Equity Indexes (calendar-based anomalies across global equity markets), January Effect Filter and Mean Reversion in Stocks (well-known phenomenon where small-cap stocks often outperform in January) or 12-Month Cycle in Cross-Section of Stock Returns (the cyclical nature of returns across stocks over a yearly horizon). These insights underline the importance of understanding seasonality in both commodities and equities, offering investors the tools to refine their strategies and capitalize on predictable market behaviors.

#1096 – Risky Words and Returns

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Backtest period: 2000-2023
Indicative performance: 7.44%
Estimated volatility: 11.93%

Source paper:

Seyfi, Sina: Risky Words and Returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5043708
Abstract:
To discover dynamic risks that determine the expected stock returns, I develop a method to predict returns through the text of firms’ risk disclosures. By cross-sectionally regressing returns on the text of risk disclosures, I find certain words in the risk discussions (defined as “risky words”) that have independent predictive power for the cross-section of stock returns: an out-of-sample strategy that times ”risky words” earns up to 22% annual alpha between 2005-2023. Then I group risky words into 14 orthogonal clusters that are jointly eminent determinants of expected returns. Firm characteristics, industries, sentiments, and previously discovered text features do not explain the results.

#1097 – Intraday Option Momentum

Period of rebalancing: Intraday
Markets traded: equities
Instruments used for trading: options
Complexity: Very complex strategy
Backtest period: 2010-2018
Indicative performance: 22.71%
Estimated volatility: 3.67%

Source paper:

Da, Zhi and Goyenko, Ruslan and Zhang, Chengyu: Intraday Option Return: A Tale of Two Momentum
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5018430
Abstract:
Intraday returns on option straddles display the same persistent seasonality pattern as its underlying stock, even though straddles are delta-neutral. Specifically, straddle return in a given half-hour interval today positively predicts the return in the same intraday interval tomorrow. Such a continuation pattern is most prominent at the market open and close, which we label as morning and afternoon momentum, respectively. We find that morning momentum reflects investors’ underreaction to volatility shocks, while afternoon momentum is driven by persistent inventory management by option market makers.

New research papers related to existing strategies:

#465 – Equity Momentum Leads Corporate Bonds
#528 – Equity Factors and Corporate Bonds
#694 – Carry in Corporate Bonds
#696 – Fair Spread Value Factor in Corporate Bonds
#697 – Multifactor Corporate Bond Strategy

Nteventzis, Dimitrios: The cross-section of corporate bond returns
https://ssrn.com/abstract=5031438
Abstract:
We study the cross-section of corporate bonds utilizing a large set of financial statement, equity and bond characteristics. We use a predictive regression framework and the adaptive Lasso to choose the most relevant characteristics for the cross-section of corporate bonds. Applying the adaptive Lasso to the full dataset, we find a ten-factor model, with value, bond reversal, and equity momentum spillover being the dominant factors. Contrary to equity studies, financial variables from Compustat do not appear to have strong power in predicting corporate bond returns. We validate our initial results by running an out-of-sample exercise using an expanding window approach. Out of the 60 months utilized in the out-of-sample, the adaptive Lasso consistently chooses value, bond reversal, and equity momentum spillover. Finally, we evaluate the economic benefits of investing according to the predictions of the adaptive Lasso and find significant benefits in terms of absolute and risk-adjusted returns.

#5 – FX Carry Trade
#8 – Currency Momentum Factor
#9 – Currency Value Factor – PPP Strategy

Castro, Pedro and Hamill, Carl and Harber, John and Harvey, Campbell R. and van Hemert, Otto: The Best Strategies for FX Hedging
https://ssrn.com/abstract=5047797
Abstract:
The question of whether, when, and how to hedge foreign exchange risk has been a vexing one for investors since the end of the Bretton Woods system in 1973. Our study provides a comprehensive empirical analysis of dynamic FX hedging strategies over several decades, examining various domestic and foreign currency pairs. While traditional approaches often focus on risk mitigation, we explore the broader implications for expected returns, highlighting the interplay between hedging and strategies such as the carry trade. Our findings reveal that incorporating additional factors-such as trend (12-month FX return), value (deviation from purchasing power parity), and carry (interest rate differential) – into hedging decisions delivers significant portfolio benefits. By adopting a dynamic, active approach to FX hedging, investors can enhance returns and manage risk more effectively than with static hedged or unhedged strategies.

#963 – Why Do US Stocks Outperform EM and EAFE Regions?

Chen, Zefeng and He, Yintao and Shao, Zhiquan and Yu, Changhua: The US as the Global Equity Safe Haven
https://ssrn.com/abstract=5100501
Abstract:
We systematically document a flight-to-US phenomenon in the global equity market when global volatility soars, using portfolio holdings of globally investing active equity mutual funds with total size of over 2 trillion USD. We find that at the fund-stock level, a fund would on average rebalance to a US stock by 2% of this position relative to a non-US stock contemporaneously under one unit increase of the log VIX index, before reaching its peak of 9.1% after 4 quarters. The rebalance to US is mostly offset by withdraw from the emerging markets. Funds experience better ex-post return by engaging in rebalancing than hypothetically not rebalancing in the short run, but this effect diminishes after 8 quarters. We interpret the empirical findings using a stylized model featuring asymmetric balance sheet capacity between US and non-US liquidity providers that generate a convenience value of US stocks. When volatility rises, mutual funds rebalance to US to lower their potential fire sale cost, thanks to the better balance sheet capacity of US liquidity providers leading to a lower haircut for US stocks.

#97 – Half-Day Reversal
#118 – Time Series Momentum Effect
#160 – Long-Term PE Ratio Effect in Stocks
#207 – Value Factor – CAPE Effect within Countries
#247 – Value Effect within Countries v2
#424 – Long-Run Reversal in Commodity Returns
#609 – Intraday Reversal in US
#794 – 24-Hour Reversal in Cryptocurrencies
#922 – Price-Based Quantitative Strategy for Country Valuation
#944 – Overnight-Intraday Reversal in Futures

Safari, Sara A. and Schmidhuber, Christof: Trends and Reversion in Financial Markets on Time Scales from Minutes to Decades
https://doi.org/10.48550/arXiv.2501.16772
Abstract:
We empirically analyze the reversion of financial market trends with time horizons ranging from minutes to decades. The analysis covers equities, interest rates, currencies and commodities and combines 14 years of futures tick data, 30 years of daily futures prices, 330 years of monthly asset prices, and yearly financial data since medieval times.
Across asset classes, we find that markets are in a trending regime on time scales that range from a few hours to a few years, while they are in a reversion regime on shorter and longer time scales. In the trending regime, weak trends tend to persist, which can be explained by herding behavior of investors. However, in this regime trends tend to revert before they become strong enough to be statistically significant, which can be interpreted as a return of asset prices to their intrinsic value. In the reversion regime, we find the opposite pattern: weak trends tend to revert, while those trends that become statistically significant tend to persist.
Our results provide a set of empirical tests of theoretical models of financial markets. We interpret them in the light of a recently proposed lattice gas model, where the lattice represents the social network of traders, the gas molecules represent the shares of financial assets, and efficient markets correspond to the critical point. If this model is accurate, the lattice gas must be near this critical point on time scales from 1 hour to a few days, with a correlation time of a few years.

And several interesting free blog posts that have been published during the last 2 weeks:

It’s About the Price of Oil, Not ESG

The growing urgency of climate change has increased scrutiny of companies’ ESG (Environmental, Social, and Governance) practices. Investors are now more inclined to support firms that demonstrate strong ESG commitments, often willing to pay a green premium for sustainable investments. However, is the spread in performance between the ‘Sin’ and ‘Saint’ stocks driven by the ESG factor or some other omitted variable? The recent study by Zhan Shi and Shaojun Zhang suggests that the hidden force that may be in play is the price of the oil.

Seasonality Patterns in the Crisis Hedge Portfolios

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 during market stress, crisis hedge portfolios are designed to provide downside protection. We examine whether incorporating seasonal timing into these portfolios can enhance their performance and return-to-risk ratios, potentially offering superior risk-adjusted returns compared to static or non-seasonal approaches.

Join the Race Once Again: Quantpedia Awards Competition Is Back!

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 for you.

For a quick recapitulation (for those who were not around in 2024, when we started this activity for the first time), our Quantpedia Awards 2025 aims to be the premier competition for all quantitative trading researchers. If you have an idea in your head about systematic/quantitative trading or investment strategy, and you would like to gain visibility on the professional scene, then submit your research paper, and you can compete for an attractive list of prizes. All info about the prizes, submission process, expert committee, and our partners are described in detail on our dedicated subpage: Quantpedia Awards 2025. However, we will also give you a quick overview in this blog post.