Quantpedia Premium Update – 5th September

New strategies:

#778 – Absolute Delta Beta Strategy in Chinese Equities

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 2005-2019
Indicative performance: 8.23%
Estimated volatility: 54.87%

Source paper:

Xie, Jun and Zhang, Baohua and Gao, Bin and Tan, Chunzhi: Absolute delta beta and cross-sectional stock returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4109730
Abstract
This paper explores the predictive power of the absolute delta beta (ADB) on future cross-sectional stock returns. By univariate portfolio analysis, bivariate portfolio analysis, and decomposition of predictive power, we find that the ADB can produce an excess return in the next month. The predictive power of ADB is contributed to the information of the left tail risk and the noise. Furthermore, we disclose that the ADB defined in the paper may measure the framing effect in the stock market, it has no persistence feature which implies it is a short-term behavior of the investors. The stocks with high ADB are always concentrated in retail investors. The investment strategies based on the ADB are better than the benchmark—the CSI300 index.

#779 – Factor Momentum in the Chinese Stock Market

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 2002-2019
Indicative performance: 7.02%
Estimated volatility: 8.78%

Source paper:

Ma, Tian and Liao, Cunfei and Jiang, Fuwei: Factor Momentum in the Chinese Stock Market
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4148445
Abstract
Based on 10 commonly used non-momentum factors, we construct a novel factor momentum strategy and find that it earns an annualized return of 9.91% and a Sharpe ratio of 1.15 in the Chinese stock market, which lacks stock-level momentum. We also find that factor momentum has strong explanatory power in subsuming industry momentum and digesting its component factors and a variety of anomalies. Reversal effect absorbs the performance of factor momentum. Further, mispricing correction helps explain factor momentum, which produces stronger returns during higher aggregate idiosyncratic volatility and lower investor sentiment periods as well as among stocks with higher information asymmetry and short-sale constraints. The exposure to factor premiums and a manifestation of predictability determine factor momentum in China.

#780 – ESG Exclusion Premium Factor

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 2005-2022
Indicative performance: 8.99%
Estimated volatility: 12.47%

Source paper:

Berle, Erika Christie and He, Wangwei and Ødegaard, Bernt Arne: The Expected Returns of ESG Excluded Stocks
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4095395
Abstract:
What are the consequences of widespread ESG-based portfolio exclusions on the expected returns of firms subject to exclusion? We consider two possible theoretical explanations. 1) Short-term price pressure around the exclusions leading to correction of mispricing going forward. 2) Long term changes in required returns. We use the exclusions of Norwegian Government Pension Fund Global (GPFG -`The Oil Fund’) to investigate. GPFG is the world’s largest SWF, and its ESG decisions are used as a model for many institutional investors. We construct various portfolios representing the GPFG exclusions. We find that these portfolios have significant superior performance (alpha) relative to a Fama-French five factor model. The sheer magnitude of these excess returns (5\% in annual terms) leads us to conclude that short-term price pressure can not be the only explanation for our results, the excluded firms expected returns must be higher in the longer term.

#781 – Enhanced Returns of LGBT CEOs

Period of rebalancing: Daily
Markets traded: equities
Instruments used for trading: stocks
Complexity: Simple strategy
Backtest period: 2000-2021
Indicative performance: 16.35%
Estimated volatility: 34.88%

Source paper:

Shanaev, Savva and Skorochodova, Arina and Vasenin, Mikhail: LGBT CEOs and Stock Returns: Diagnosing Rainbow Ceilings and Cliffs
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4111210
Abstract:
This study is the first to investigate the implications of lesbian, gay, bisexual, and transgender chief executive officers (LGBT CEOs) for stock performance, using an exhaustive sample of 26 LGBT publicly listed company CEOs since 2000 to document statistically and economically significant financial outperformance of LGBT-led firms. Stocks of companies with openly LGBT CEOs generate a monthly alpha of 0.69%-1.08%, robust to portfolio weighting schemes, estimation frequency, multi-factor asset-pricing models, factor multicollinearity, sectoral allocation effects, and in subsamples both in the United States and globally. The results imply that a “rainbow ceiling” exists with regards to LGBT executives, and that firms they lead are persistently undervalued due to discrimination by investors. The rainbow ceiling effect is smaller for gay men CEOs than for CEOs with other LGBT identities. Further, LGBT CEOs on average represent small growth stocks with poor past performance, which supports the “rainbow cliff” hypothesis stating members of the LGBT community are overrepresented in precarious leadership positions. Portfolios formed of stocks with LGBT CEOs robustly outperform broad market indices in raw and risk-adjusted terms, evidencing potential attractiveness for ethical individual and institutional investment from both selfish and social perspectives.

New research papers related to existing strategies:

#132 – Dynamic Commodity Timing Strategy

Cotter, Eyiah-Donkor, Potì: Commodity Futures Return Predictability and Intertemporal Asset Pricing
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4095741
Abstract:
We find out-of-sample predictability of commodity futures excess returns using combination forecasts of 28 potential predictors. Such gains in forecast accuracy translate into economically significant improvements in certainty equivalent returns and Sharpe ratios for a mean-variance investor. Commodity return forecasts are closely linked to the real economy. Return predictability is countercyclical, and the combination forecasts of commodity returns have significant predictive power for future economic activity. Two-factor models featuring innovations in each of the combination forecasts and the market factor explain a substantial proportion of the cross-sectional variation of both commodity and equity returns. The associated positive risk prices are consistent with the intertemporal capital asset pricing model (ICAPM), given how the predictors forecast an increase in future economic activity in the time-series. Overall, combination forecasts act as state variables within the ICAPM, thus resurrecting a central role for macroeconomic risk in determining expected returns on commodities.

#626 – Image Recognition in Stock Price Charts Predicts Stock Returns

Zhang, Lin, Zhao: Channel and Spatial Attention CNN: Predicting Price Trends from Images
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4173579
Abstract:
Deep learning has been successfully applied for predicting asset prices using financial time series data. However, image-based deep learning models excel at extracting spatial information from images and their potential in financial applications has not been fully explored. Here we propose a new model—channel and spatial attention convolutional neural network (CS-ACNN)—for price trend prediction that takes arbitrary images constructed from financial time series data as input. The model incorporates attention mechanisms between convolutional layers to focus on specific areas of each image that are the most relevant for price trends. CS-ACNN outperforms benchmarks on exchange-traded funds (ETF) data in terms of both model classification metrics and investment profitability, achieving out-of-sample Sharpe ratios ranging from 1.57 to 3.03 after accounting for transaction costs. In addition, we confirm that the images constructed based on our methodology lead to better performance when compared to models based on traditional time series data. Finally, the model learns visual patterns that are consistent with traditional technical analysis, providing an economic rationale for learned patterns and allowing investors to interpret the model.

#22 – Term Structure Effect in Commodities

Adams, Collot, Kirilenko: Measuring Financial Investor Presence through Term Structure Deflection
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4147678
Abstract:
We estimate the presence of financial investors in commodity futures markets from deflections in the term structure. We argue that large-scale inflows from financial investors cause systematic deviations in nearby futures contracts that reflect excessive buying pressure in commodities. We compare this new speculation indicator to popular existing measures including reported CFTC data and the Hamilton and Wu (2014) risk premium. We find substantial financial investor presence in commodity markets from 2004 to 2014. We show that our new speculation measure is better at explaining the variation in crude oil volatility than other existing measures.

#207 – Value Factor – CAPE Effect within Countries

Rajan Raju: Shiller’s CAPE and Forward Excess Returns in India
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4155788
Abstract:
We show an inverse relationship between elevated valuations (high CAPE) and forward excess returns over 1, 3, 5, and 10 years in India, similar to other international studies. At the end of June 2022, as measured by Shiller Barclays CAPE, valuation is at the 77th percentile of its historical distribution. There is a reasonable probability (40%) that 1-year forward returns are negative when CAPE is in its highest quintile. While “time in the market” reduces the chance of negative forward excess returns, these returns are still lower than entering at lower quintiles of CAPE. Longer-term, forward excess returns have significant variability. Therefore, CAPE on its own has limited use for market timing. However, the inverse relationship implies that investors should lower their forward excess return expectations and consider longer investment time horizons when starting CAPE is high without sound economic rationale.

#184 – Timing Carry Trade
#221 – Timing Carry Trade v2

Nakagawa, Sakemoto: Dynamic Allocations for Currency Investment Strategies
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4073980
Abstract:
This study conducts out-of-sample tests for returns on individual currency investment strategies and the weights on the universe of these strategies. We focus upon five investment strategies: carry, momentum, value, dollar carry, and conditional FX correlation risk. The performances of our predictive models are evaluated using both statistical and economic measures. Within a dynamic asset allocation framework, an investor adjusts investment strategy weights based upon results of the prediction models. We find that our predictive model outperforms our benchmark, which uses historical average information in terms of statistical and economic measures. When the Sharpe ratio of the benchmark model is 0.52, our predictive model generates economic gain of approximately 1.16% per annum over the benchmark. These findings are robust to the changes in investors’ risk aversion and target volatility for portfolio optimization.

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

Automated Trading Edge Analysis

Have you ever wondered if your trading asset trends or mean-reverts? Everyone involved in trading or investments daily solves the task of – What trading strategy should I apply to my assets to generate profits? As always, we at Quantpedia will try to help you a bit with this never-ending task with our new tool/report, which will be unveiled next week for all Quantpedia Pro subscribers. The following article serves as an introduction to the methodology we will use to find new trading edges for you automatically.

Should We Rebalance Index Changes Immediately?

Passive index funds are believed to offer low fees, nearly limitless liquidity, very low trading costs and (most of the time) they beat most active managers. Although not all of the above are accurate, there are still many arguments in favour of passive indexing. However, what is often left forgotten are avoidable travails linked to index funds. In general, after an index rebalances, traditional cap-weighted index funds buy high and sell low. Their tendency to add recent highfliers and drop unloved value stocks is what causes investors to lose. Arnott et al. (2022) target the stock selection problem around index rebalancing and propose several ideas on how to adjust index strategies in order to earn above-market returns. They present simple ways to construct an index, thanks to which it is possible to reduce both negative effects of buy-high/sell-low dynamic and the turnover costs of cap-weighted indices.

Are There Intraday and Overnight Seasonality Effects in China?

At the moment, there is a lot of attention surrounding overnight anomalies in various types of financial markets. While such effects have been well documented in research, especially in US equities and derivatives, there are other asset classes that are not as well addressed. A recent (2022) paper from Jiang, Luo, and Ye contributed appealing evidence in favor of validating these phenomena in the Chinese market. We highlight the finding that the market MKT factor beta premium is earned exclusively overnight and tend to reverse intraday (and in smaller potency also value HML and profitability RMW), which is the same finding as for the US equities. In contrast, the size SMB factor exhibit significantly opposite pattern: positive intraday premium and negative overnight premium (and the same for investment CMA factor).

How Retail Loses Money in Option Trading

Over the last few years, we may have noticed a significant growth in retail investing. No surprise, the COVID pandemic outbreak increased the numbers even more, and undoubtedly, options trading is no exception. According to the authors (de Silva, Smith, Co), retail traders seek options expecting spikes in volatility and, for that reason, incline toward firms with more media coverage. Furthermore, their trading increases around the time of firms’ earnings announcements. As a result, market makers benefit from the behavior mentioned above, which causes a large flow of money from retail to market makers.