Quantpedia Premium Update – 15th February 2022

New strategies:

#717 –Predicting the Delta-Hedged Option Returns Using LASSO

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: options, stocks
Complexity: Very complex strategy
Backtest period: 1996-2019
Indicative performance: 27.45%
Estimated volatility: 6.34%

Source paper:

Shafaati, Mobina and Chance, Don M. and Brooks, Robert E., The Cross-Section of Individual Equity Option Returns
https://ssrn.com/abstract=3927410
Abstract:
This paper examines the cross-section of delta-hedged equity option returns, which are found to be predictable by some characteristics of options and those of their underlying stocks. Using the LASSO method to evaluate the forecasting ability of a large set of predictor candidates, we identify the dominant characteristics that provide incremental information for delta-hedged option returns. These characteristics are robustly selected by different modifications of the LASSO method, using various tunning parameters, across hundreds of bootstrap samples, and over different time periods. The parsimonious models consisting of the dominant characteristics demonstrate superior performance in predicting delta-hedged option returns out-of-sample.

#718 –Geopolitical Risk and Commodities

Period of rebalancing: Monthly
Markets traded: commodities
Instruments used for trading: futures
Complexity: Moderately complex strategy
Backtest period: 1975-2011
Indicative performance: 8.21%
Estimated volatility: 8.61%

Source paper:

Daxuan Chenga, Yin Liaoa, Zheyao Pana: The pricing of geopolitical risk in cross-sectional commodity returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4009736
Abstract:
In this study, we investigate whether geopolitical risk is a pricing factor in cross-sectional commodity futures returns. By estimating the exposure of commodity futures returns on a geopolitical risk index, we find that commodities with high-risk beta generate 7.92% higher annual returns than those with low-risk beta. The results indicate that high geopolitical riskrelated commodity futures contracts require extra compensation. A moving average procedure shows that the geopolitical risk beta has a regular changing pattern that cycles every 10 years, and the relative risk premium tends to be higher than average before economic recessions and to further increase during the recession periods. Finally, we find that geopolitical threats better explain the variation of commodity futures return than do geopolitical actions.

#719 –Cross-sectional Momentum in Large Cryptos

Period of rebalancing: Weekly
Markets traded: cryptos
Instruments used for trading: cryptos
Complexity: Simple strategy
Backtest period: 2014-2021
Indicative performance: 144.06%
Estimated volatility: 22.13%

Source paper:

Cong, Lin and Karolyi, George Andrew and Tang, Ke and Zhao, Weiyi: Value Premium, Network Adoption, and Factor Pricing of Crypto Assets
https://ssrn.com/abstract=3985631
Abstract:
We document characteristic-based anomalies in over 4000 cryptocurrencies. We find that cryptocurrency returns exhibit momentum in the largest-cap group but reversal in other size groups. We identify strong crypto value and network adoption premia, from which we derive two novel factors to add to crypto market, size, and momentum factors. The resulting C-5 model outperforms extant models in pricing the cross-section of crypto assets, as revealed in most standard tests. We also provide the first comprehensive categorization of about 700 cryptocurrencies based on their economic functionality and use tools from international asset pricing to demonstrate strong segmentations across token categories.

#720 –Reversal in Small Cryptos

Source paper:

#721 –Growth of Addresses with Balance Factor in Cryptos

Source paper:

#722 –Price-based Value in Cryptocurrencies

Source paper:

New research papers related to existing strategies:

#35 – Insiders Trading Effect in Stocks

Bushee, Brian J. and Taylor, Daniel and Zhu, Christina: The Dark Side of Investor Conferences: Evidence of Managerial Opportunism
https://ssrn.com/abstract=3701977
Abstract:
While the shareholder benefits of investor conferences are well-documented, evidence on whether these conferences facilitate managerial opportunism is scarce. In this paper, we examine whether managers opportunistically exploit heightened attention around the conference to “hype” the stock. We find that managers increase the quantity of voluntary disclosure leading up to the conference; that these disclosures are more positive in tone and increase prices to a greater extent than post-conference disclosures; and that these disclosures are more pronounced when insiders sell their shares immediately prior to the conference. In circumstances where pre-conference disclosures coincide with pre-conference insider selling, we find evidence of a significant return reversal––large positive returns before the conference, and large negative returns after the conference––and that the firm is more likely to be named in a securities class action lawsuit. Collectively, our findings are consistent with some managers hyping the stock prior to the conference.

#42 – Alpha Cloning – Following 13F Fillings

Fleiss, Alexander and Kumaar, Amrith and Rida, Adam and Shin, Junsup and Lai, Xinying and Fang, Vivian and Chen, Jialiang and Li, Ang: Deep Reinforcement Learning & Feature Extraction For Constructing Alpha Generating Equity Portfolios
https://ssrn.com/abstract=3958478
Abstract:
The ambition of this paper is to catch hidden information inside the Securities and Exchange Commission’s (SEC)13F public holding data in order to construct an equity portfolio that maximizes returns. The 13F ling data give us the quarterly stock trading decisions of included funds, but we’re not given any insight on how they made their decisions or if information has been shared between funds. To remedy this lack of knowledge, this paper used feature extraction in order to lter out the best performing funds through several criteria. We propose a method employing powerful machine learning techniques (Deep Reinforcement Learning) to try to catch the missing pieces of information behind the decision process and use them as a prediction tool to construct quarterly equity portfolios. This approach reached an annualized return of 21% with a sharpe ratio of 1.8 outperforming the S&P 500 both in returns and stability through historical backtesting.

#659 – Robust Quality in Stocks
#623 – Quality Factor in Stocks

Otero, Luis: Redefining Quality Investing
https://ssrn.com/abstract=3952573
Abstract:
In this paper we evaluate the relationship between quality investing combined with Economic Moat, ESG (Environmental, Social and Governance) and analyst opinions over the period 2014-2020 (28 quarters) based on a dataset comprising 803 US stocks rated by Morningstar. Performance is evaluated mainly in terms of alphas (six factor model). Our results show that quality stocks measured by ROIC exhibit superior performance. The incorporation of competitive advantages (Morningstar’s Economic Moat) allows a better discrimination among the classic high-quality strategies. Investment in stocks with quality and high ESG entails the payment of a premium but buying quality companies with Economic Moat makes up for this negative aspect. The Morningstar Star Rating is not significant when we control the performance by, for instance, sector or size and considering Economic Moat, but it is the average Price-to-Price target (Analyst consensus). Our results show that conventional quality strategies can be improved via the incorporation of a company’s competitive advantages and, above all, by Analyst consensus regarding the potential for stock revaluation.

#460 – ESG Level Factor Investing Strategy

Crace, Logan and Gehman, Joel, What Really Explains ESG Performance? Disentangling the Asymmetrical Drivers of the Triple Bottom Line
https://ssrn.com/abstract=4011367
Abstract:
Why is there such great heterogeneity in environmental, social, and governance (ESG) performance between firms? Drawing inspiration from the locus of performance literature, we use variance partitioning methods to analyze the extent to which CEO, firm, industry, year, and state effects explain variation in ESG performance over recent decades. Our findings show that internal effects (i.e., CEO and firm) are the strongest determinants. Yet, disaggregation of the multidimensional ESG construct shifts the saliency of the factors significantly, revealing the importance of the external environment (i.e., industry and year) in explaining ESG concerns. Our research extends the locus of performance literature to our understanding of the triple bottom line and contributes to understanding the complex determinants of firm-level ESG performance across an array of positive and negative ESG indicators.

#497 – Monetary (FOMC) Momentum in Stocks

Cortes, Gustavo and Sethuraman, Mani and Silva, Felipe Bastos G.: Does Wall Street Understand Fed Speak? Monetary Policy Communication and Corporate Conference Calls
https://ssrn.com/abstract=3798794
Abstract:
Using short-time windows centered on FOMC communication days and a novel dataset comprising dialogues between managers and analysts during corporate conference calls, we uncover a tone transmission channel of monetary policy wherein the linguistic tone of Fed communication drives the linguistic tone of macro-related dialogues in conference calls. The tone of macro-related dialogues contemporaneously affects stock markets, and the semantics of such dialogues consistently conveys monetary policy content. Additional analysis suggests that the effect of monetary policy tone on corporate conference calls is stronger in more recent years. Our results shed light on how economic agents respond to“Fed Speak.”

#306 – Trading VIX ETFs v2
#256– Shorting Volatility During FOMC Meeting Days

Augustin, Patrick and Augustin, Patrick and Cheng, Ing-Haw and Van den Bergen, Ludovic: Volmageddon and the Failure of Short Volatility Products
https://ssrn.com/abstract=3819342
Abstract:
The rapid growth of exchange traded products (ETPs) has raised concerns about their implications for financial stability. A case in point is the abrupt market crash of short volatility strategies on February 5th 2018. In this paper, we describe this “Volmageddon” event and illustrate the risks associated with hedge and leverage rebalancing when markets are highly concentrated and volatile. The Volmageddon episode provides valuable risk management lessons because it illustrates the pitfalls of hedge and leverage rebalancing and is reminiscent of the losses incurred through portfolio insurance schemes.

#534 – Time Series Factor Momentum
#510 – Factor Momentum

Bessler, Wolfgang and Taushanov, Georgi and Wolff, Dominik and Wolff, Dominik: Factor-Investing and Asset Allocation Strategies: A Comparison of Factor Versus Sector Optimization
https://ssrn.com/abstract=3805855
Abstract:
Given the tremendous growth of factor allocation strategies in active and passive fund management, we investigate whether either asset allocation strategies based on factors or sectors provide investors with a superior portfolio performance. Our focus is on comparing factor versus sector allocation as some recent empirical evidence indicates the dominance of sector over country portfolios. We analyze the performance and performance differences of sector and factor portfolios for various weighting and portfolio optimization approaches including ‘equal-weighting’ (1/N), ‘risk-parity’ (RP), minimum-variance (MinVar), mean-variance (MV), Bayes-Stein (BS) and Black-Litterman (BL) by employing a sample-based approach in which the sample moments are the input parameters for the allocation model. For the period from May 2007 to November 2020, our results clearly reveal that, over longer investment horizons, factor portfolios provide relative superior performances. For shorter periods, however, we observe time varying and alternating performance dominances as the relative advantage of one over the other strategy depends on the economic cycle. We find that during “normal” times factor portfolios clearly dominate sector portfolios, whereas during crisis periods sector portfolios are superior offering better diversification opportunities.

#677 – Betting Against Uncertainty Beta in US Hedge Funds
#658 – Betting Against Uncertainty Beta in Australia

Yacine Aït-Sahalia, Felix Matthys, Emilio Osambela and Ronnie Sircar: When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance
https://www.nber.org/system/files/working_papers/w29195/w29195.pdf
Abstract:
We analyze an environment where the uncertainty in the equity market return and its volatility are both stochastic, and may be potentially disconnected. We solve a representative investor’s optimal asset allocation and derive the resulting conditional equity premium and risk-free rate in equilibrium. Our empirical analysis shows that the equity premium appears to be earned for facing uncertainty, especially high uncertainty that is disconnected from lower volatility, rather than for facing volatility as traditionally assumed. Incorporating the possibility of a disconnect between volatility and uncertainty significantly improves portfolio performance, over and above the performance obtained by conditioning on volatility only.

#206 – Trendfollowing Combined with Momentum in Commodity Futures

Han, Yufeng and Kong, Lingfei: A Trend Factor in Commodity Futures Markets: Any Economic Gains From Using Information Over Investment Horizons?
https://ssrn.com/abstract=3953845
Abstract:
This paper identifies a trend factor that exploits the short-, intermediate-, and long-run moving averages of settlement prices in commodity futures markets. The trend factor generates statistically and economically large returns during the post-financialization period 2004-2020. It outperforms the well-known momentum factor by more than nine times the Sharpe ratio and has less downside risk. The trend factor cannot be explained by the existing factor models and is priced cross-sectionally. Finally, we find that the trend factor is correlated with funding liquidity measured by the TED spread. Overall, the results indicate that there are significant economic gains from using the information on historical prices in commodity futures markets.

#14 – Momentum Factor Effect in Stocks

Vora, Premal P.: Trading and Market Efficiency in Summer
https://ssrn.com/abstract=3818169
Abstract:
The fall in stock-market trading during summer has real effects on stock-market efficiency. I examine the market efficiency of momentum, post-announcement earnings drift, and idiosyncratic volatility (IVOL). The profitability of a momentum winner-loser strategy is significantly enhanced in summer, thus accentuating momentum-related inefficiency. For positive unexpected earnings in summer, market inefficiency is attenuated, but for negative unexpected earnings market inefficiency is accentuated. The IVOL inefficiency is an exclusively summer effect. Once this effect is controlled for, a positive relation emerges between IVOL quintiles and alphas. Overall, market inefficiency appears to be accentuated in summer due to the fall in trading.

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

How to Utilize Anticipated ETF Rebalances

For many investors, passive investing can be a no-brainer and is suggested by many, especially those who think that the walk is random. However, it does not mean that the passive investors do not trade – the ETFs trade instead of them. The indexes that are being tracked are rebalanced to account for changes in the market cap, mergers, delistings, or IPOs. The novel research shows that it matters how the ETFs trade. Even though the differences are not that big, for a long-term horizon, the differences compound. For active traders, the paper shows that the rebalancing of the ETFs could be utilized by trading in advance.

Should Factor Investors Neutralize the Sector Exposure?

Factor investors face numerous choices that do not end even after picking the set of factors. For instance, should they neutralize the factor exposure? If the investor pursues sector neutralization, does the decision depend on a particular factor? Or are the choices different for the long-only investor compared to the long-short investor? The research paper by Ehsani, Harvey, and Li (2021) answers these questions and provides investors with an interesting insight on this topic.

Cryptocurrency Stablecoins – A Review of Recent Research

Since January 2020, the annualized volatility of Bitcoin stands around 70%, 6-times the volatility of commodities like Gold or Oil, more than twice the volatility of the S&P 500, and 10 times the volatility of the EURUSD exchange rate. Stablecoins represent a specific category of cryptocurrencies aiming to keep their value stable against a benchmark asset, usually a fiat currency like the US dollar. So how do stablecoins work, and do they really offer needed stability?