Quantpedia Premium Post – October 4th

New Strategies

#1054 – Enhancing the High-Volume Return Premium

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 1964-2022
Indicative performance: 8.6%
Estimated volatility: 5.66%

Source paper:

Kang, Mhin: Enhancing the High-Volume Return Premium
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4934371
Abstract:
We suggest a novel trading strategy that can enhance the high-volume return premium (HVRP) in the US stock market. The key point is that by applying the HVRP strategy to stocks that have a negative contemporaneous correlation between return and volume changes (CCRV), the strategy takes advantage of additional returns generated during the trading volume mean reversion process. We show that the HVRP with negative CCRV stocks significantly exceeds the HVRP without CCRV restriction by over 30%. The enhanced premium consistently appears across different exchanges and size. This result suggests that the CCRV can be priced though the overall CCRV is not significant in the US stock market.

#1055 – Manager Uncertainty and the Cross-Section of Stock Returns

Period of rebalancing: Quarterly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Backtest period: 1993-2018
Indicative performance: 5.25%
Estimated volatility: 10.5%

Source paper:

Zhang, Tengfei: Manager Uncertainty and the Cross-Section of Stock Returns
https://ssrn.com/abstract=4854534
Abstract:
This paper evidences the explanatory power of managers’ uncertainty for cross-sectional stock returns. I introduce a novel measure of the degree of managers’ uncertain beliefs about future states: manager uncertainty (MU), defined as the count of the word “uncertainty” over the sum of the count of the word “uncertainty” and the count of the word “risk” in filings and conference calls. I find that managers’ level of uncertainty reveals valuation information about real options and thereby has significantly negative explanatory power for cross-sectional stock returns. Beyond existing market-based uncertainty measures, the manager uncertainty measure has incremental pricing power by capturing information frictions between managers’ reported uncertainty and investors’ perception of uncertainty. Moreover, a short-long portfolio sorted by manager uncertainty has a significantly positive premium and cannot be spanned by existing factor models. An application on COVID-19 uncertainty shows consistent results.

#1056 – Stocks Lead Corporate Bonds ETFs

Period of rebalancing: Daily
Markets traded: bonds
Instruments used for trading: ETFs
Complexity: Very complex strategy
Backtest period: 2012-2020
Indicative performance: 10.36%
Estimated volatility: –

Source paper:

Jiang, Hao and Li, Sophia Zhengzi and Xiao, Yuanyuan: Do Stocks Lead Bonds? New Evidence from Corporate Bond ETFs
https://ssrn.com/abstract=4938752
This paper studies the dynamic information flows between stocks and corporate bonds. Using accurately measured returns on corporate bond exchange-traded funds (ETFs), we find that returns on portfolios of bond-issuing firms’ stocks positively predict corporate bond ETF returns, but not vice versa. Inspired by these findings, we apply the adaptive LASSO to aggregate information from these bond-linked stocks, resulting in a signal with strong predictive power for ETF returns. By contrast, a randomly formed stock portfolio does not predict the ETF returns. These results provide fresh evidence on the notion of gradual information diffusion across different asset classes.

#1057 – Weighted Production Price Index Effect in Stocks

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Backtest period: 1999-2022
Indicative performance: 15.73%
Estimated volatility: 16.37%

Source paper:

Feng, Jian and Huang, Shiyang and Lee, Charles M.C. and Song, Yang: Inﬂation in the Cross-section: Separating Winners from Losers
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4907871
Abstract:
Using micro-level data behind headline inﬂation, we develop a monthly “Weighted Production Price Index” (WPPI) variable that captures the composite effect of multiple industry-level inﬂationary changes on each focal industry. We show: (a) WPPI explains cross-sectional variations in same-quarter earnings and same-month stock returns, (b) inﬂationary shocks captured by WPPI propagate across industries along supply chains and production complimentary networks, (c) WPPI has strong predictive power for industry and ﬁrm returns over the next 6 months, and (d) a WPPI-based hedge strategy yields a seven-factor alpha of 1% per month at the industry level. Further analyses of earnings forecast errors and information frictions point to sluggish price adjustment as the most likely driver of these return predictability patterns.

#1058 – Decision Tree Intraday Strategy

Period of rebalancing: Intraday
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Backtest period: 2023-2024
Indicative performance: 19.33%
Estimated volatility: 3.32%

Source paper:

Prajwal, Naga and Balivada, Dinesh and Nirmala, Sharath Chandra and Tiruveedi, Poornoday: Decision Trees for Intuitive Intraday Trading Strategies
https://ssrn.com/abstract=4838381
Abstract:
This research paper aims to investigate the efficacy of decision trees in constructing intraday trading strategies using existing technical indicators for individual equities in the NIFTY50 index. Unlike conventional methods that rely on a fixed set of rules based on combinations of technical indicators developed by a human trader through their analysis, the proposed approach leverages decision trees to create unique trading rules for each stock, potentially enhancing trading performance and saving time. By extensively backtesting the strategy for each stock, a trader can determine whether to employ the rules generated by the decision tree for that specific stock. While this method does not guarantee success for every stock, decision tree-based strategies outperform the simple buy-and-hold strategy for many stocks. The results highlight the proficiency of decision trees as a valuable tool for enhancing intraday trading performance on a stock-by-stock basis and could be of interest to traders seeking to improve their trading strategies.

#1059 – Teach Machine Asset Pricing

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Backtest period: 1972-2022
Indicative performance: 35.44%
Estimated volatility: –

Source paper:

Bai, Chengyu: Teach Machine Asset Pricing
https://ssrn.com/abstract=4598745
Abstract:
In this paper, I investigate how theories could collaborate with big data. I explore a promising framework of combining finance theories and data-driven approaches through transfer learning. Neural networks learn first from theories by the simulated data of structure models and then from real-world data. I conduct experiments on stock return predictions. The theory-guided neural networks demonstrate superior predictive power and profitability than the data-driven neural networks. The enhanced performance is attributed to the theoretical model’s effectiveness and the transfer learning procedure.

New research papers related to existing strategies:

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

Chernov, Mikhail and Dahlquist, Magnus and Lochstoer, Lars A.: An Anatomy of Currency Strategies: The Role of Emerging Markets
https://ssrn.com/abstract=4950551
Abstract:
We show that a small set of emerging markets with floating exchange rates expand the investment frontier substantially relative to G10 currencies. The frontier is characterized by an out-of-sample mean-variance efficient portfolio that prices G10- and emerging markets-based trading strategies unconditionally as well as conditionally. Our approach reveals that returns to prominent trading strategies are largely driven by factors that do not command a risk premium. After real-time hedging of such unpriced risks, the Sharpe ratios of these strategies increase substantially, providing new benchmarks for currency pricing models. For instance, the Sharpe ratio of the carry strategy increases from 0.71 to 1.29. The unpriced risks are related to geographically-based currency factors, while the priced risk that drives currency risk premiums is related to aggregate consumption exposure.

#998 – Google Trends Sentiment as a Predictor for Cryptocurrency Returns

John, Kose and Li, Jingrui and Liu, Ruming: Sentiment in the Cross Section of Cryptocurrency Returns
https://ssrn.com/abstract=4941032
Abstract:
In this paper, we analyze sentiment in the cross-section of cryptocurrency returns. We construct a cryptocurrency sentiment index named “CryptoSent.” We find that cryptocurrencies with high absolute sensitivities to CryptoSent innovations tend to yield lower average returns in the following month and subsequent week. We introduce a sentiment factor as a common risk factor in the cross-sectional returns of cryptocurrencies, alongside market, size, and momentum factors. By including the sentiment factor, the four-factor model explains an additional 13% of the weekly expected cryptocurrency returns. The sentiment factor possesses both economic and statistical significance in explaining eleven cryptocurrency characteristics-based long-short strategies.

#605 – Momentum on Straddles
#925 – Option Factor Momentum

Beckmeyer, Heiner and Filippou, Ilias and Zhou, Guofu: A New Option Momentum: Compensation for Risk
https://ssrn.com/abstract=4404190
Abstract:
This paper introduces a novel momentum strategy in the options market based on the systematic component of option returns. Utilizing a latent factor model to decompose options returns, we demonstrate that the systematic component exhibits stronger momentum and subsumes the performance of conventional return-based momentum. With a six-month formation and one-month holding period, the strategy achieves an annualized Sharpe ratio of 2.23, compared to 1.08 for traditional momentum, and is highly profitable for various formation and holding periods. The superior performance is driven by time-varying risk compensation rather than investor biases, underscoring the economic rationale behind its success.

#956 – News-Linked Momentum in China

Ge, Shuyi and Li, Shaoran and Zheng, Hanyu: Diamond Cuts Diamond: News Co-mention Momentum Spillover Prevails in China
https://ssrn.com/abstract=4489005
Abstract:
We conduct a comprehensive study on momentum spillovers in the Chinese stock market using various types of economic linkages, with particular attention to momentum spillover via news co-mention linkages. We utilize millions of Chinese business news articles and develop a flexible and innovative algorithm to identify linkages among listed firms. We find that news co-mention momentum spillover is stronger than others, unifying various forms of momentum spillover effects in the Chinese market and replacing the role of analyst co-coverage seen in the U.S. News co-mention identifies a wide range of economically important linkages, particularly recovering more cross-industry linkages than other link identification methods, which could contribute to its strong performance.

Chen, Xin and Wang, Huaixin: News Links and Predictable Returns
https://ssrn.com/abstract=4889875
Abstract:
Exploiting financial news data, we construct news-implied linkages and document a strong lead-lag effect of firms with shared news coverage in China ’ s stock market. The news-link momentum generates a monthly return of 1.33%. While prior evidence on the attention dynamics among firms with joint news coverage is limited, we show that the momentum spillover of news-linked firms is largely driven by investor underreaction. The return predictability from news links is also robust to controlling for alternative economic linkages. The findings suggest that information diffuses sluggishly among news-connected firms, thereby providing new evidence for pricing efficiency.

#334 – Volatility-Adjusted Momentum in Corporate Bonds
#570 – Corporate Bond Value Strategy

Sidhu, Amritpal and Oyeniyi, Temi: Bonding with Style Investing: Value and Momentum in Corporate Bonds
https://ssrn.com/abstract=4924945
Abstract:
The application of ‘smart beta’ strategies is expanding into corporate bonds, beyond its equity roots. This paper explores value, momentum, and short-term reversal styles in fixed income, highlighting the potential to enhance returns and diversify portfolios. The analysis shows that value and momentum strategies in iBoxx U.S. investment-grade (USIG) and high-yield (USHY) bonds generated statistically significant alpha, with low correlations to the comparable equity styles and markets premia.

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

Valuing Stocks With Earnings

Today, we will venture a little into the fundamental analysis corner, and we will give you a glimpse of an intriguing paper (Hillenbrand and McCarthy, 2024) that discusses the advantages of using ‘Street’ earnings over traditional GAAP earnings. The paper suggests that ‘Street’ earnings provide better valuation estimates and improved financial analysis. Is this a way how to improve the performance of the struggling equity value factor?