Quantpedia Premium Update – 15th April

New strategies:

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Moderately complex strategy
Backtest period: 1963-2014
Indicative performance: 56.27%
Estimated volatility: 17.05%

Source paper:

Brière, Marie and Szafarz, Ariane: When it Rains, it Pours: Multifactor Asset Management in Good and Bad Times
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3790816
Abstract:
We examine the profitability of multifactor portfolios on the U.S. stock market. Using passive sector investing as the benchmark, we assess the performances of factor-based asset management strategies in good and bad times. When short selling is unrestricted, factor investing outperforms sector investing in all respects. For long-only portfolios, our results reveal a trade-off between the risk premia associated with factors and the diversification potential of sectors. Multifactor investing tends to be more profitable than the benchmark during good times but less attractive during bad times, when diversification is needed the most.

#739 – Betting Against Beta in India

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Simple strategy
Backtest period: 2007-2021
Indicative performance: 18.88%
Estimated volatility: 16.02%

Source paper:

Raju, Rajan and Teli, Anish, ‘Long’ Factors, not ‘Short’ Change: Long Only Factor Portfolios in India
https://ssrn.com/abstract=4000418
Abstract:
We show that monthly rebalanced, equal-weighted, long-only winner portfolios, drawn from the top 200 stocks in India, built using systematic rules that underpin popular factors of momentum, low volatility and quality deliver alpha for the period under study. The market exposure is significant across all the style strategies we looked at. Therefore, correlations between the strategies are significantly higher than those observed for academic factor returns. We include alternate calculation methodologies for some factors and find that not all implementations of factor strategies are the same. Not all strategies have high turnover. Indeed, strategies like low volatility and quality show fairly low turnover. Factor exposure persistence over time varies across strategies and persistence should be considered when implementing factor-style strategies. We also find that size and sectoral preferences of factors are dynamic and could reduce perceived diversification benefits. Finally, we show that alpha for momentum, low volatility and quality strategies survives real-world implementation costs. While winner portfolios using momentum, low volatility, and quality rank higher than the broad S&P 200 Index over the period under study, there is not one factor-style that is a consistent winner.

#740 – Low Value Factor in India

Source paper:

#741 – Combination of the Long-term and the Short-term Reversal in China

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Simple strategy
Backtest period: 1997-2020
Indicative performance: 13.48%
Estimated volatility: 24.2%

Source paper:

Zhenya Liu, Bo Li, Shixuan Wang, The Evolvement of Momentum Effects in China: Evidence from Functional Data Analysis
https://ssrn.com/abstract=4011144
Abstract:
In comparison to developed securities markets, it is intriguing to observe that the Chinese stock market’s momentum or reversal effect is inconsistent. We address this controversy using a novel paradigm based on functional data analysis (FDA) with the goal of reconciling previous inconsistency. Compared with conventional approaches, the paradigm based on FDA can identify nonlinear cross-sectional patterns and dynamic time series evolvement. Our empirical findings provide compelling evidence that after the global financial crisis in 2008, mid-term momentum effects vanished and the market became dominated by reversal effects. Additionally, we find no evidence for permanent momentum effects in a variety of settings, but we do find significant evidence for short-(1-6 months) and long-term (3-year) reversal effects in China.

#742 – Risk-Reversal Options Strategy

Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: options
Complexity: Moderately complex strategy
Backtest period: 2005-2019
Indicative performance: 8.9%
Estimated volatility: 24.6%

Source paper:

Blair Hull, Euan Sinclair: The Risk-Reversal Premium
https://ssrn.com/abstract=3968542
Abstract:
We study the risk-reversal premium, where out-of-the-money puts are over-priced relative to out-of-the-money calls. This effect is driven by investors’ utility preferences which lead them to over-pay for the risk reduction benefits of long puts instead of valuing options on the basis of expected returns. Investors can exploit this implied skewness premium by trading standard, exchange-traded index options. We also show that including risk-reversals in an equity portfolio creates a better portfolio (as measured by Sharpe ratio) compared to a pure index position.

New research papers related to existing strategies:

#128 – Innovative Efficiency Effect in Stocks
#141 – Innovative Efficiency Effect in Stocks ver. 2

Drechsler, Katharina and Müller, Sebastian and Wagner, Heinz-Theo: Digital Innovation…And the Cross-Section of Stock Returns
https://ssrn.com/abstract=3972173
Abstract:
Based on validated word lists from the Information Systems literature, we use the MD&A section of annual firm reports to construct a text-based measure of digital innovation. In our sample period from 1996 to 2020, we find that firms with a high level of digital innovation are systematically different from low-level firms along several key characteristics like valuation, sales growth, and profitability. A digital innovation factor, which is long (short) stocks with high (low) digital innovation, earns an equally weighted (value-weighted) monthly six-factor alpha of 0.92% (0.50%) per month, both statistically significant at 1%. Differences in firm characteristics and abnormal returns are not explained by industry affiliation. Additional tests suggests that digital innovation is a priced risk factor, which should be added to existing asset pricing models.

#480 – Machine Learning-Based Financial Statement Analysis

Dyer, Travis and Guest, Nicholas M. and Yu, Elisha: New Accounting Standards and the Performance of Quantitative Investors
https://ssrn.com/abstract=3969442
Abstract:
Quantitative investing relies on historical data and limited day-to-day human involvement, which could create short-term inflexibility in the face of changing economic conditions. In this study, we examine quantitative investors’ ability to navigate a common and occasionally material change to the financial data generating process: new accounting standards. We find that returns of quantitative mutual funds temporarily decrease following the implementation of standards that change the definition of key accounting variables. The lower performance we document is relative to more traditional “discretionary” funds that rely heavily on human discretion to make investment decisions. Our result is stronger for value funds, which rely heavily on accounting data, and absent among funds slanted towards price-based strategies, including momentum and size. When we further investigate funds’ operations, we observe excess portfolio turnover following the implementation of accounting standards. Relatedly, quantitative underperformance is concentrated among funds holding more stocks. Overall, our results highlight a significant adjustment cost associated with accounting regulation that could become even more significant as more investors turn to quantitative strategies.

#505 – Systematic Investing in Emerging Market Debt

Li, Delong and Magud, Nicolas E. and Werner, Alejandro M. and Witte, Samantha Helen: The Long-Run Impact of Sovereign Yields on Corporate Yields in Emerging Markets
https://ssrn.com/abstract=4026333
Abstract:
We analyze the long-run impact of emerging-market sovereign bond yields on corporate bond yields, finding that the average pass-through is around one. The pass-through is larger in countries with greater sovereign risks and where sovereign bonds are more liquid. It is also greater for corporate bonds with lower ratings, shorter maturities, and for those issued by financial companies and government-related firms. Our results support theoretical arguments that corporate and sovereign yields are linked together through credit risks and liquidity premiums. Consequently, high sovereign risks may slowdown growth by persistently increasing private sector borrowing costs.

#381 – Blended Factors in Cryptocurrencies

Dobrynskaya, Victoria and Dubrovskiy, Mikhail, Cryptocurrencies Meet Equities: Risk Factors And Asset Pricing Relationships
https://ssrn.com/abstract=4042723
Abstract:
We consider a variety of cryptocurrency and equity risk factors as potential forces that drive cryptocurrency returns and carry risk premiums. In a cross-section of 2,000 biggest cryptocurrencies, only downside market risk, cryptocurrency size and policy uncertainty factors are systematically priced with significant premiums. Momentum premium has vanished in the recent years. Equity market risk, particularly equity downside market risk, appears to be more important than cryptocurrency market risk, suggesting greater linkages between cryptocurrency and equity markets than we used to think. Global and US equity factors are the most relevant for the cryptocurrency market.

#62 – Shorting Overvalued Stocks

Ling, Xiaoxu and Yan, Siyuan and Cheng, Louis T. W., Investor Relations Under Short-Selling Pressure: Evidence From Strategic Signaling by Company Site Visits
https://ssrn.com/abstract=4010128
Abstract:
Exploiting the staggered deregulation of short sales in China as a quasi-experiment, we investigate whether firms change investor relations (IR) strategy when they face short-selling pressure. We document significant increases in IR efforts as measured by the frequency of company visits when firms’ stocks become shortable in the market. Our cross-sectional tests further reveal that pilot firms’ engagements of such IR activities vary with their ex-ante operating performance, accounting quality, short-selling threat, and ownership structure. Moreover, we find that pilot firms with higher IR efforts experience fewer subsequent short sales. We further document that corporate IR efforts are associated with more positive media coverage and facilitate subsequent external financing and capital investment. In addition to the site visits, we also find that pilot firms increase their response rates on online IR platforms. Collectively, results are consistent with our prediction that firms take proactive IR actions as strategic signaling to assist investor communication and discourage short sellers. The findings also suggest that IR activities are effective to reconstruct market perceptions and mitigate downside impacts on firms’ operations produced by short sales.

#739 – Betting Against Beta in India

Agarwalla, Sobhesh Kumar and Jacob, Joshy and Varma, Jayanth Rama and Vasudevan, Ellapulli: BettingAgainst Beta in the Indian Market
https://ssrn.com/abstract=2464097
Recent empirical evidence from different markets suggests that the security market line is flatter than posited by CAPM. This flatness implies that a portfolio long in low-beta assets and short in high-beta assets would earn positive returns. Frazzini and Pedersen (2014) conceptualize a BAB factor that tracks such a portfolio. We find that a similar BAB factor earns significant positive returns in India. The returns on the BAB factor dominate the returns on the size, value and momentum factors. We also find that stocks with higher volatility earn relatively lower returns. These findings indicate overweighting of riskier assets by leverage constrained investors in the Indian market.

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

What’s the Best Factor for High Inflation Periods? – Part I

Another period of long sustained high inflation is probably right around the corner, as the Russia-Ukraine Conflict keeps evolving, and its end is nowhere to be seen. In this article, we analyzed the Consumer Price Index from the Federal Reserve Bank of Minneapolis, which includes the rate of inflation in the USA since 1913. We found multiple years during which the inflation was abnormally high and analyzed the performance of the known equity long-short factors. The factors with the highest average performance are HML (value stocks), long-term reversal, momentum, and energy stocks. On the other hand, tech stocks, bond-like assets, and the SMB factor should be avoided during the high inflation periods.

What’s the Best Factor for High Inflation Periods? – Part II

This second article offers a different look at high inflation periods, which we already analyzed in What’s the Best Factor for High Inflation Periods? – Part I. This second part looks at factor performance during two 10-year periods of high inflation. What’s our main takeaway? The best hedge for a high inflation period is the value or momentum factor. Other promising factors (energy sector, small-cap stocks, or long-run reversal) don’t perform as consistently as value and momentum.