New strategies:
#429 – CAPE Sector Picking Strategy
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: funds, ETFs
Complexity: Simple strategy
Bactest period: 2002-2017
Indicative performance: 14.23%%
Estimated volatility: 17.98%
Source paper:
Farouk Jivraj,Robert J. Shiller: The Many Colours of CAPE
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3258404
Abstract:
Campbell & Shiller's [1988] Cyclically-Adjusted Price to Earnings ratio (CAPE) has both its advocates and critics. Currently, the debate is on the validity of the high CAPE ratio for US stock markets in forecasting lower future returns, with CAPE currently at 31.21. We investigate the efficacy and validity of CAPE from several different perspectives. First, we run multiple-horizon predictability regressions for CAPE versus its peers and find that CAPE consistently displays economic and statistical significance far better than any of its peers. Second, we explore alternative constructions of CAPE based on other proxies for earnings motivated by the work of findings by Siegel [2016] using NIPA profits. We find that original CAPE is still best when comprehensively and fairly reviewing the other proxies, even for NIPA profits. Third, we assess how to practically use CAPE in both an asset allocation and relative valuation setting. We demonstrate a novel use of CAPE for asset allocation programmes as well as discuss relative valuation exercises for country, sector and single stock rotation.
#430 – Volatility-Weighted Short-Term Reversal Strategy in Emerging Market Equities
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: funds, ETFs
Complexity: Simple strategy
Bactest period: 2005-2017
Indicative performance: 6.14%
Estimated volatility: 9.10%
Source paper:
Kaloyan Petkov, Plamen Patev: Maximize Market Timing Returns: Implementing Volatility-Weighted Bets
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339268
Abstract:
Market timing is preferred path to alpha because it is very simple to implement even by individual investors. In this paper we apply the Hallerbach (2014) methodology to emerging markets from Asia and Eastern Europe. We find that by using volatility-weighted bets we improve significantly the ex-post Information ratio of the strategy. This approach is even more important in emerging markets, where volatility is much higher than on traditional stock exchanges.In our research we select 15 leading emerging markets around the world. Examining volatility-weighted bets on emerging markets is even more interesting, because of the significantly higher volatility in comparison to developed markets. We develop the strategy on monthly basis in the period January, 2005 – March, 2017.
New research papers related to existing strategies:
#81 – Combining Value Stocks with Momentum and Volume Factors
Zhu, Sun: When Buffett Meets Bollinger: An Integrated Approach to Fundamental and Technical Analysis
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3330402
Abstract:
We study the portfolio performance of investment strategies that jointly apply both fundamental analysis and technical analysis. Compared with strategies that rely on one-dimensional fundamental or technical information, the integrated approach to fundamental and technical investing significantly improves portfolio performance. In addition, the joint strategies appear to perform better for stocks with higher idiosyncratic risks. We also find that when combined with fundamental signals, the Bollinger Bands, a reversal-type technical indicator, outperforms the moving average, which captures recent momentum in prices. Contrary to earlier findings from the literature, we show that moving average based strategies tend to incur higher volatility, lower Sharpe ratio, and larger tail risk. Our findings are consistent with the notion that, especially among small firms, the trading activities from investors with limited information capacity can lead to inefficient prices.
#4 – Overnight Anomaly
#97 – Half-Day Reversal
Abdi: Cycles of Declines and Reversals following Overnight Market Declines
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3287680
Abstract:
This paper uncovers and explains the emergence of cycles of intraday declines and overnight reversals in the U.S. stock market in the 21st century. Using quote midpoints for the past 24 years of common stocks traded in the three main exchanges, I show that the cross-sectional association between average intraday and overnight returns has steadily shifted from a direct association into a strong inverse association over the years. I explain this shift by showing that after 2001, consistent with theoretical models in which binding capital constraints lead to liquidity dry-ups, an overnight decline in the stock market is followed by a further intraday decline for volatile stocks and their reversal over the next overnight period. Moreover, I show that market liquidity of volatile stocks further deteriorates following an overnight market decline, which confirms my proposed explanation. Finally, I show that idiosyncratic volatility, compared with systematic risk, better explains the cross section of the documented systematic intraday declines and overnight reversals.
And two additional related research papers have been included into existing free strategy reviews during last 2 weeks:
Bill Gross is probably the most known fixed income fund manager. A new academic paper sheds more light on his track record and sources of his stellar performance …
Dewey, Brown: Bill Gross' Alpha: The King Versus the Oracle
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3345604
Abstract:
We set out to investigate whether ''Bond King" Bill Gross demonstrated alpha (excess average return after adjusting for market exposures) over his career, in the spirit of earlier papers asking the same question of ''Oracle of Omaha," Warren Buffett. The journey turned out to be more interesting than the destination. We do find, contrary to previous research, that Gross demonstrated alpha at conventional levels of statistical significance. But we also find that result depends less on the historical record than on whether we take the perspective of academics interested in market efficiency, investors picking a fund or someone (say a potential employer) asking whether a manager has skill or is throwing darts to pick positions. These are often thought to be overlapping or even identical questions. That's not completely unreasonable in equity markets, but in fixed income these are distinct. We also find quantitative differences, mainly that fixed-income securities have much higher correlations with each other than equities, make alpha 4.5 times as hard to measure for Gross than Buffett. We don't think our results will have much practical effect on attitudes toward Gross as an investor, but we hope they will advance understanding of what alpha means and appropriate ways to estimate it.
We present an interesting academic paper with a methodology that allows estimating VIX (volatility risk) since the year 1890 …
Manela, Moreira: News Implied Volatility and Disaster Concerns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2382197
Abstract:
We construct a text-based measure of uncertainty starting in 1890 using front-page articles of the Wall Street Journal. News implied volatility (NVIX) peaks during stock market crashes, times of policy-related uncertainty, world wars and financial crises. In US post-war data, periods when NVIX is high are followed by periods of above average stock returns, even after controlling for contemporaneous and forward-looking measures of stock market volatility. News coverage related to wars and government policy explains most of the time variation in risk premia our measure identifies. Over the longer 1890-2009 sample that includes the Great Depression and two world wars, high NVIX predicts high future returns in normal times, and rises just before transitions into economic disasters. The evidence is consistent with recent theories emphasizing time variation in rare disaster risk as a source of aggregate asset prices fluctuations.
