New strategies:
#266 – Skewness Effect in Country Equity Indexes
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: ETFs
Complexity: Moderately complex strategy
Bactest period: 1999 – 2014
Indicative performance: 13.76%
Estimated volatility: 25.66%
Source paper:
Zaremba, Nowak: Skewness Preference Across Countries
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2606180
Abstract:
The prospect theory implies that that assets with positively skewed returns should be traded at premium to assets with negative skewness. We hypothesize that in integrated financial markets this concept should also hold for entire country equity portfolios. The article examines the linkages between country-level expected returns and past skewness. We document a robust negative relationship between skewness and future returns. The phenomenon is strongest for large, liquid and developed stock markets and negligible for small, illiquid and undeveloped ones. Furthermore, additional sorts on skewness can improve performance of cross-country value and momentum strategies. The study is based on sorting and cross-sectional tests conducted within a sample 78 country equity markets for years 1999-2014.
New research papers related to existing strategies:
#99 – FX Carry Trade Combined with PPP (Value) Strategy
Cenadese: Safe Haven Currencies: A Portfolio Perspective
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2606662
Abstract:
Currency portfolios exhibit asymmetric correlations: during periods of bear, volatile world equity markets, currency portfolios provide different hedging benefits than in bull markets. I show how these time-varying hedging benefits depend on currency characteristics. This paper also illustrates how the presence of regime shifts in financial markets affects optimal portfolio choice across currency portfolios: during bear markets, investors are better off by unwinding carry trade positions, and by following currency momentum. Also, diversification benefits increase by holding undervalued currencies and currencies of countries with strong current accounts and international investment positions.
#118 – Time Series Momentum Effect
Levine, Pedersen: Which Trend Is Your Friend?
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2603731
Abstract:
Managed-futures funds (sometimes called CTAs) trade predominantly on trends. There are several ways of identifying trends, either using heuristics or statistical measures often called “filters.” Two important statistical measures of price trends are time series momentum and moving average crossovers. We show both empirically and theoretically that these trend indicators are closely connected. In fact, they are equivalent representations in their most general forms, and they also capture many other types of filters such as the HP filter, the Kalman filter, and all other linear filters. Further, we show how trend filters can be equivalently represented as functions of past prices vs. past returns. Our results unify and broaden a range of trend-following strategies and we discuss the implications for investors.
#210 – Adaptive Asset Allocation
Keller, Butler, Kipnis: Momentum and Markowitz: A Golden Combination
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2606884
Abstract
Mean-Variance Optimization (MVO) as introduced by Markowitz (1952) is often presented as an elegant but impractical theory. MVO is "an unstable and error-maximizing" procedure (Michaud 1989), and "is nearly always beaten by simple 1/N portfolios" (DeMiguel, 2007). And to quote Ang (2014): "Mean-variance weights perform horribly… The optimal mean-variance portfolio is a complex function of estimated means, volatilities, and correlations of asset returns. There are many parameters to estimate. Optimized mean-variance portfolios can blow up when there are tiny errors in any of these inputs…". In our opinion, MVO is a great concept, but previous studies were doomed to fail because they allowed for short-sales, and applied poorly specified estimation horizons. For example, Ang used a 60 month formation period for estimation of means and variances, while Asness (2012) clearly demonstrated that prices mean-revert at this time scale, where the best assets in the past often become the worst assets in the future. In this paper we apply short lookback periods (maximum of 12 months) to estimate MVO parameters in order to best harvest the momentum factor. In addition, we will introduce common-sense constraints, such as long-only portfolio weights, to stabilize the optimization. We also introduce a public implementation of Markowitz's Critical Line Algorithm (CLA) programmed in R to handle the case when the number of assets is much larger than the number of lookback periods. We call our momentum-based, long-only MVO model Classical Asset Allocation (CAA) and compare its performance against the simple 1/N equal weighted portfolio using various global multi-asset universes over a century of data (Jan 1915-Dec 2014). At the risk of spoiling the ending, we demonstrate that CAA always beats the simple 1/N model by a wide margin.
#264 – Dividend Risk Premium Strategy
Binsbergen, Koijen: The Term Structure of Returns: Facts and Theory
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2597481
Abstract:
We summarize and extend the new literature on the term structure of equity. Short-term equity claims, or dividend strips, have on average significantly higher returns than the aggregate stock market. The returns on short-term dividend claims are risky as measured by volatility, but safe as measured by market beta. These facts are hard to reconcile with traditional macro-finance models and we provide an overview of new models that can reproduce some of these facts. We relate our evidence on dividend strips to facts about other asset classes such as nominal and corporate bonds, volatility, and housing. We conclude by discussing the broader economic implications by linking the term structure of returns to real economic decisions such as hiring and investment.
Four additional related research paper have been included into existing free strategy reviews during last 2 week:
#2 – Asset Class Momentum – Rotational System
#3 – Sector Momentum – Rotational System
#8 – FX Momentum
#14 – Momentum Effect in Stocks
#15 – Momentum Effect in Country Equity Indexes
Geczy, Samonov: 215 Years of Global Multi-Asset Momentum: 1800-2014 (Equities, Sectors, Currencies, Bonds, Commodities and Stocks)
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2607730
Abstract:
Extending price return momentum tests to the longest available histories of global financial asset returns, including country-specific sectors and stocks, fixed income, currencies, and commodities, as well as U.S. stocks, we create a 215-year history of multi-asset momentum, and we confirm the significance of the momentum premium inside and across asset classes. Consistent with stock-level results, we document a large variation of momentum portfolio betas, conditional on the direction and duration of the return of the asset class in which the momentum portfolio is built. A significant recent rise in pair-wise momentum portfolio correlations suggests features of the data important for empiricists, theoreticians and practitioners alike.
#6 – Volatility Effect in Stocks – Long-Short Version
#7 – Volatility Effect in Stocks – Long-Only Version
#20 – Volatility Risk Premium Effect
Ilmanen: Do Financial Markets Reward Buying or Selling Insurance and Lottery Tickets?
https://www.aqr.com/~/media/files/papers/faj-do-financial-markets-reward-buying-or-selling-insurance-and-lottery-tickets.pdf
Abstract:
Selling financial investments with insurance or lottery characteristics should earn positive longrun premiums if investors like positive skewness enough to overpay for these characteristics. The empirical evidence is unambiguous: Selling insurance and selling lottery tickets have delivered positive long-run rewards in a wide range of investment contexts. Conversely, buying financial catastrophe insurance and holding speculative lottery-like investments have delivered poor longrun rewards. Thus, bearing small risks is often well rewarded, bearing large risks not.
#8 – FX Momentum
#14 – Momentum Effect in Stocks
#21 – Momentum Effect in Commodities
#118 – Time Series Momentum Effect
Goyal, Jegadeesh: Cross-Sectional and Time-Series Tests of Return Predictability: What Is the Difference?
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2610288
Abstract:
We analyze the differences between past-return based strategies that differ in conditioning on past returns in excess of zero (time-series strategy, TS) and past returns in excess of the cross-sectional average (cross-sectional strategy, CS). We find that the return difference between these two strategies is mainly due to time-varying long positions that the TS strategy takes in the aggregate market and, consequently, do not have any implications for the behavior of individual asset prices. However, TS and CS strategies based on financial ratios as predictors are sometimes different due to asset selection.
#237 – Dispersion Trading
Deng: Volatility Dispersion Trading
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1156620
Abstract:
This papers studies an options trading strategy known as dispersion strategy to investigate the apparent risk premium for bearing correlation risk in the options market. Previous studies have attributed the profits to dispersion trading to the correlation risk premium embedded in index options. The natural alternative hypothesis argues that the profitability results from option market inefficiency. Institutional changes in the options market in late 1999 and 2000 provide a natural experiment to distinguish between these hypotheses. This provides evidence supporting the market inefficiency hypothesis and against the risk-based hypothesis since a fundamental market risk premium should not change as the market structure changes.
