New strategies:
#530 – Jump Risk in Stocks
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 1988-2011
Indicative performance: 8.9%
Estimated volatility: 17.21%
Source paper:
MARTIJN CREMERS, MICHAEL HALLING, and DAVID WEINBAUM: Aggregate Jump and Volatility Risk in the Cross-Section of Stock Returns
http://perpustakaan.unitomo.ac.id/repository/Aggregate%20Jump%20and%20Volatility%20Risk%20in%20the%20Cross-Section%20of%20Stock%20Returns.pdf
Abstract:
We examine the pricing of both aggregate jump and volatility risk in the cross-section of stock returns by constructing investable option trading strategies that load on one factor but are orthogonal to the other. Both aggregate jump and volatility risk help explain variation in expected returns. Consistent with theory, stocks with high sensitivities to jump and volatility risk have low expected returns. Both can be measured separately and are important economically, with a two-standard-deviation increase in jump (volatility) factor loadings associated with a 3.5% to 5.1% (2.7% to 2.9%) drop in expected annual stock returns.
#531 – Global Bond Portfolio Predicts Government Bonds Returns in Individual Countries
Period of rebalancing: Monthly
Markets traded: bonds
Instruments used for trading: bonds, ETFs, futures
Complexity: Simple strategy
Backtest period: 1970-2016
Indicative performance: 3.9%
Estimated volatility: 5.26%
Source paper:
Stig V. Møllery and Jesper Rangvidz: Global connectedness across bond markets
http://wp.lancs.ac.uk/fofi2018/files/2018/03/FoFI-2018-0177-Stig-Vinther-M%C3%B8ller.pdf
Abstract:
We provide frst tests of gradual difusion of information across bond markets. We show that excess returns on bond markets around the world react with a lag to excess returns on a global bond portfolio: high returns on the global bond portfolio signal high expected returns on bond markets in many countries. Results are strong in-sample and out-of-sample, and hold after controlling with variables often used to predict bond returns. Excess returns on a global bond portfolio also predict inflation rates around the world. Investors learn about fundamentals in di§erent countries (inflation rates) that ináuence expected returns around the world after observing returns on a global portfolio.
#532 – Minimum Idiosyncratic Returns in Stocks
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Moderately complex strategy
Backtest period: 1963-2014
Indicative performance: 7.83%
Estimated volatility: 15.63%
Source paper:
R. Jared DeLisle, Michael Ferguson, Haimanot Kassa: Hazard Stocks and Expected Returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3627669
Abstract:
Hazard stocks are opposite of lottery stocks. We proxy hazard stocks with the minimum daily idiosyncratic return over the past month, a negative shock labelled IMIN, and examine the relation between hazard stocks and expected returns. The literature on lottery-stocks implies that investors should discount hazard stocks. However, we find that investors underreact to hazard stocks, with negative return continuations for up to 24 months without subsequent reversals. An IMIN-based long-short arbitrage portfolio strategy generates monthly alphas of 0.52% to 0.75%. We find consistent results using Fama-MacBeth (1973) regressions and controlling for characteristics such as MAX (Bali et al., 2011), idiosyncratic volatility, and corporate events such as earnings announcements. Furthermore, we find that both firm-level information uncertainty and limits to arbitrage, but not limited investor attention, contribute significantly to the documented underreaction to hazard stocks.
#533 – FOMC Cycle and Credit Risk
Period of rebalancing: Weekly
Markets traded: bonds
Instruments used for trading: CDS
Complexity: Simple strategy
Backtest period: 2005-2017
Indicative performance: 8.89%
Estimated volatility: 14.87%
Source paper:
Difang Huang, Yubin Li, Xinjie Wang, Zhaodong Zhong: Does the FOMC Cycle Affect Credit Risk?
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3512662
Abstract:
This paper studies the returns of credit default swap (CDS) indices over the Federal Open Market Committee (FOMC) cycle from 2005 to 2017. We document that the CDS return is significantly higher in even weeks than in odd weeks of the FOMC cycle. This pattern is linked to the resolution of macroeconomic uncertainty by the biweekly schedules of the Fed Reserve internal Board of Governors meetings. We also provide evidence that the Fed affects the CDS market via unexpected information signal and monetary policy that lead to reductions in the risk premium. Finally, a simple trading strategy based on the biweekly pattern yields an annual return of 8.9%.
#534 – Time Series Factor Momentum
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Moderately complex strategy
Backtest period: 1965-2017
Indicative performance: 12%
Estimated volatility: 14.29%
Source paper:
Tarun Gupta and Bryan Kelly: Factor Momentum Everywhere
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3300728
Abstract:
In this article, the authors document robust momentum behavior in a large collection of 65 widely studied characteristic-based equity factors around the globe. They show that, in general, individual factors can be reliably timed based on their own recent performance. A time series “factor momentum” portfolio that combines timing strategies of all factors earns an annual Sharpe ratio of 0.84. Factor momentum adds significant incremental performance to investment strategies that employ traditional momentum, industry momentum, value, and other commonly studied factors. Their results demonstrate that the momentum phenomenon is driven in large part by persistence in common return factors and not solely by persistence in idiosyncratic stock performance.
New research papers related to existing strategies:
#14 – Investment Factor
#339 – Expected Investment Growth within the Cross-section of Stocks Returns
Rizova, Savina and Saito, Namiko: Investment and Expected Stock Returns
https://ssrn.com/abstract=3646575
Abstract:
Valuation theory predicts that, all else equal, expected investment should be negatively related to expected returns. We study the relation between expected investment and expected stock returns globally. We show that recent asset growth is a systematic proxy for future investment not only in the US, but also in developed ex US and emerging markets. Using this proxy, we find a negative investment effect across developed and emerging markets as well as across sectors in those regions, consistent with the prediction of valuation theory. Globally, the effect is much stronger among small caps than large caps and is mainly driven by the underperformance of high investment firms. Examining the different components of asset growth related to raising of capital as well as those related to use of capital, we find that all components contribute to the investment effect.
#49 – S&P 500 Index Addition Effect
Bennett, Benjamin and Stulz, Rene M. and Wang, Zexi: Does Joining the S&P 500 Index Hurt Firms?
https://ssrn.com/abstract=3656628
Abstract:
We investigate the impact on firms of joining the S&P 500 index from 1997 to 2017. We find that the positive announcement effect on the stock price of index inclusion has disappeared and the long-run impact of index inclusion has become negative. Inclusion worsens stock price informativeness and some aspects of governance. Compensation, investment, and financial policies change with index inclusion. For instance, payout policies of firms joining the index become more similar to the policies of their index peers. ROA falls following inclusion. There is no evidence of an impact of inclusion on competition.
#75 – Federal Open Market Committee Meeting Effect in Stocks
Gomez Cram, Roberto and Grotteria, Marco: Real-time Price Discovery via Verbal Communication: Method and Application to Fedspeak
https://ssrn.com/abstract=3613702
Abstract:
We advance the hypothesis and establish empirically that investors’ expectations underreact to Central Banks’ messages. From the videos of post-FOMC-meeting press conferences, we extract the words, and timestamp them at the millisecond. We align the transcripts with high-frequency data for several financial assets to provide granular evidence on the investors’ expectations formation process. When the Chairman discusses the changes between current and previous policy statement, price volatility and trading volume spike dramatically, and prices move in the same direction as they did around the statement release. Our approach allows us to quantify in monetary terms the value of information rigidity.
#233 – Using Straddles to Trade on Earnings Announcements
Adams, Thomas and Neururer, Thaddeus: Earnings Announcement Timing, Uncertainty, and Volatility Risk Premiums
https://ssrn.com/abstract=3598135
Abstract:
We examine the relationship between firms’ quarterly earnings report timing and uncertainty before quarterly earnings announcements. Prior research provides conflicting predictions on how investor uncertainty and report timing are related. Using implied volatilities from equity options and the realized returns to straddle positions, we find evidence that uncertainty and volatility risk premiums are higher for firms that report later in the quarter. Further tests show the increase in option premiums is unexplained by risk factors suggesting a mispricing by investors. These results are not associated with static firm-level factors and our findings are concentrated in high growth firms.
#420 – Geographical Country Momentum
JIN, Zuben and Li, Frank Weikai: Geographic Links and Predictable Returns
https://ssrn.com/abstract=3617417
Abstract:
Using detailed information of establishments owned by U.S. public firms, we construct a novel measure of geographic linkage between firms. We show that the returns of geography-linked firms have strong predictive power for focal firm returns and fundamentals. A long-short strategy based on this effect yields monthly value-weighted alpha of approximately 60 basis points. This effect is distinct from other cross-firm return predictability and is not easily attributable to risk-based explanations. It is more pronounced for focal firms that receive lower investor attention, are more costly to arbitrage and during high sentiment periods. In addition, we find sell-side analysts similarly underreact, as their forecast revisions of geography-linked firms predict their future revisions of focal firms. Our results are broadly consistent with sluggish price adjustment to nuanced news affecting firms with geographically overlapped establishmens.
#25 – Size Factor – Small Capitalization Stocks Premium
Chen, Qinhua and Chi, Yeguang and Qiao, Xiao: Follow the Smart Money: Factor Forecasting in China
https://ssrn.com/abstract=3636530
Abstract:
We present novel evidence of factor timing in the Chinese stock market. Actively managed Chinese stock mutual funds have larger exposure on the size factor when it performs well and smaller exposure when it performs poorly. By constructing a proxy for the size preference of active stock funds, we can forecast size factor returns in the subsequent periods. A one-standard deviation increase in the size factor loading of active stock funds is associated with an increase in the size factor return of 1.18% in the next month and 10.8% in the next year. The result is not driven by industry rotation, price impact of mutual funds, or factor momentum. Actively managed stock mutual funds do not appear to time value or momentum factors.
And two interesting free blog posts have been published during last 2 weeks:
Multi-Asset Skewness Trading Strategy
The best course of action for every quant researcher is to try to fundamentally understand anomalies and explore their functioning besides the original scope of the academic research papers. The goal of this article was to look for inspiration and further explore the Skewness affect – the tendency of assets with the lowest skewness to outperform assets with the highest skewness. It seems that this anomaly is present not only in commodities but also in currencies, fixed income and equities. Trading strategy that exploits the effect of skewness in the multi-asset setting would earn an annual return of 7.67% when leveraged to the 15% volatility.
Earnings announcement days are really important dates in a usual yearly corporate routine. The stock market usually reacts sharply on earnings announcement news and stocks on average earn statistically significant return excess of the market over the short window centred around the announcements. But how does the movement of stocks look before earnings announcement? The recent research paper written by Gao, Hu, and Zhang analyzes price action before and after earnings announcement and shows that a majority of the announcement month premium is realized during the pre-announcement period. Stocks with higher levels of uncertainty (stocks are sorted based on their option implied volatilities) experience larger pre-announcement returns and more uncertainty resolution during the pre-announcement period…
Plus, the following six trading strategies have been backtested in QuantConnect in the previous two weeks:
#397 – Accruals Momentum
#438 – US Equity Tail Risk and Currency Risk Premia
#451 – Growth Gap Factor in Fixed Income
#466 – Trend-Following and Spillover Effect
#494 – Pro-Cyclical Stocks and Expected Future Economic Conditions
#499 – ETF Momentum
Are you looking for more strategies to read about? Sign up for our newsletter or visit our Blog or Screener.
Do you want to learn more about Quantpedia Premium service? Check how Quantpedia works, our mission and Premium pricing offer.
Do you want to learn more about Quantpedia Pro service? Check its description, watch videos, review reporting capabilities and visit our pricing offer.
Are you looking for historical data or backtesting platforms? Check our list of Algo Trading Discounts.
Would you like free access to our services? Then, open an account with Lightspeed and enjoy one year of Quantpedia Premium at no cost.
Or follow us on:
Facebook Group, Facebook Page, Twitter, Linkedin, Medium or Youtube
