Buffett’s Asset Allocation Advice: Take it … With a Twist
October 26, 2015
One of the most important decisions retirees need to make is the asset allocation of their portfolios. They can have a static or a dynamic allocation, and simplicity usually favors the former. Warren Buffett recently added another vote for static allocations by revealing that he had advised a trustee to split the bequest his wife will receive 90% in stocks and 10% in short-term bonds. The evidence discussed here shows that, relative to other static allocations, a 90/10 split has a very low failure rate and provides investors with very good upside potential and downside protection. The evidence also shows that two minor twists to the 90/10 split result in two very simple dynamic strategies with even better upside potential and downside protection.
Momentum Investing & Asset Allocation
September 22, 2015
This paper highlights the use of a new strategic approach within a quantitative investment methodology in the context of making prudent asset allocation decisions. Three asset classes will frame the dynamic asset allocation discussion: Equities, Fixed Income, and Hedge Funds. The quantitative methodology used is an evolution of J. Welles Wilder’s Relative Strength Index (RSI) first published in New Concepts in Technical Trading Systems . The sample portfolio that was analyzed over several market cycles has demonstrated greater compound returns with less volatility. The result is a set of strategies that yield better risk-adjusted returns to the broad equity markets, broad bond markets, and broad returns of hedge funds. In fact, the portfolios we analyzed delivered significantly higher risk adjusted returns across multiple market cycles.
Value, Size, Momentum and the Average Correlation of Stock Returns
Christoph Becker and Wolfgang M. Schmidt
November 19, 2015
Dynamic average correlations of stock returns are predicted by the volatility of the market excess return and moving average returns of value, size and momentum portfolios. While the influence of market volatility on average correlation is well-known, the role of value, size and momentum appears to be underappreciated. Correlations of stock returns and stock returns share sources of risk like the market volatility, but there are other sources that are distinct. In particular, correlations are increased when value or momentum returns are roughly zero, while strongly negative returns of value or momentum are associated with lower correlations. Using the market volatility and a moving average return of the value portfolio as predictors of average correlation, we obtain a global minimum variance portfolio with a Sharpe ratio that is 1.5% higher relative to the one based on a Dynamic Equicorrelation Garch model, and the difference in portfolio volatility is statistically significant.
Has the Pricing of Stocks Become More Global?
Ivan Petzev, et al.
November 18, 2015
We show that in recent years global factor models have been catching up significantly with their local counterparts in terms of explanatory power (R2) for international stock returns. This catch-up is driven by a rise in global factor betas, not a rise in factor volatilities, suggesting that the effect is likely to be permanent. Yet, there is no conclusive evidence for a global factor model catch-up in terms of pricing errors (alpha) or a convergence in country-specific factor premia. These findings suggest that global financial markets have progressed surprisingly little towards fully integrated pricing, different from what should be expected under financial market integration. We discuss alternative explanations for these patterns and assess implications for practice.
Ninety Years of Media Coverage and the Cross-Section of Stock Returns
Alexander Hillert and Michael Ungeheuer
November 12, 2015
Using a novel dataset on New York Times coverage of U.S. firms from 1924 to 2013, we re-examine the relation between media coverage and stock returns. The relation between changes in media coverage and returns is consistent with an attention-driven price pressure effect: Top-quintile outperform bottom-quintile coverage-change stocks by 10.68% during the formation year. Over the next two years, these stocks underperform their counterparts by 5.04%. In contrast to previous findings, the level of media coverage positively predicts stock returns. Top-quintile outperform bottom-quintile coverage stocks by 2.76% per year. This strategy is investable, exhibits an annual portfolio turnover of only 33%, does not depend on illiquid stocks, and attains a Sharpe Ratio of 0.48 (Momentum: 0.49).
Trend Following: Expected Returns
November 12, 2015
This paper describes how to create ex-ante expectation for generalized trend-following rules. This report first study the effect of trend-following rules applied to random data with varying degrees of drift and autocorrelation. There is a positive relationship between drift, autocorrelation and the theoretically extractable Sharpe ratio for a trend following strategy. Drift is more important, since it is theoretically unbounded, but strong auto-correlation can create positive returns in the absence of long term drift.
The realized Sharpe ratio of a trend strategy is proportional to the absolute drift and auto-correlation of a market above a threshold. From a practical perspective, this means that anyone engaging in trend following strategies, should expect to generate positive returns if the drift is strong enough or if there is enough autocorrelation. Conversely, when there is no drift or auto-correlation, trend-following is not profitable. There is a strong preference for slower strategies under drift and transaction costs.
Returns are compared to actual markets and indices of active traders (managed futures) and a high correlation is detected to the results in this paper. Trend-following should never be applied to a single market on a stand-alone basis. That said, even portfolios of trend following strategies have low expected Sharpe, especially so when the systems generated correlated trades. In the end, trend-following does not necessarily need uncorrelated markets, but rather uncorrelated system-market returns. A nuance that is often lost.
Optimal Index Asset Allocation for Maximizing Risk Adjusted Performance Using Historical Returns
Giuseppe Palmiotti and Valentina Palmiotti
December 8, 2015
This paper seeks to determine an optimal allocation of index assets selected among classes commonly used for diversifying portfolios intended for long term investments, like those employed for retirement purposes (401(k) or IRA). The goal of this study, intended for risk adverse investors, is to obtain a risk adjusted performance which rewards returns and penalizes volatility. Nonlinear optimization techniques are employed to calculate the optimal allocation that maximizes risk adjusted performance. Results are compared against those of other traditional portfolios, and a parametric study is performed to investigate the impact of different rebalancing frequencies on portfolio performance.
The Global Financial Crisis and the Case for MEFA Strategic Asset Allocation
June 10, 2015
Major institutional investment managers, such as, major hedge funds and large university endowments, have based their investment portfolios upon tactical asset allocation among multiple asset classes with low correlation with the goal of achieving superior risk-adjusted returns. However, during the current financial crisis, many of these asset classes experienced high degrees of correlation as they all decreased in value. In addition, many alternative asset classes not only decreased in value but also were illiquid in nature, impeding asset class re-allocation efforts. This paper examines a new strategic asset allocation framework called Monetary Environmental Flow Analysis™ (MEFA™) which can offer downside protection in such environments using only extremely liquid investment vehicles. The result over time is long-term returns comparable to equities but lower draw-downs in financial crisis environments. These strategies are tested over the period 1996-2014 with live signals for them from 2006 and 2007. Several of the strategies have been tested back to the 1970’s.
Beta Investing in Periods of Rising Interest Rates
August 12, 2015
Beta investment strategies attempt to capture the long term appreciation in global asset prices with as little risk as possible. They remain invested in a broadly diversified pool of asset classes and manage risk principally by rebalancing their portfolio. These strategies often include a significant allocation to bonds, an asset class that may be entering a long cyclical downtrend. To assess the impact of bonds on beta strategies in times of rising interest rates, we construct pro-forma “strawman” portfolios that we show capture the essential features of beta investing, and review their performance history for the decade leading to the latest peak in interest rates in 1981. We find that a bond-heavy beta investment approach would have performed well in the 1970’s, principally as a result of the booming price of commodities in U.S. dollars.
Applying profit attribution analysis to the key asset classes of the “strawman” portfolios, we analyze the impact on beta strategies of various actions that could be used to manage bond exposure going forward in all-asset strategies. The best option, in keeping with a diversified investment approach that minimizes market timing, is to reduce the duration of the bond exposure. Such a portfolio can still perform well in periods of rising rates. Performance depends more on the economic environment that drives capital markets than on the sole performance of shorter duration bonds in the portfolio. While the cumulative profit contribution of the bond position may remain negative throughout a cyclical uptrend in interest rates, entirely removing bonds would land a portfolio in a tug of war between the stock and commodities markets which are both cyclical and highly volatile. The risk versus return profile of such a portfolio would be similar to what can be achieved using run-of-the-mill directional investment strategies.