The Trend is our Friend - Risk Parity Momentum and Trend Following in Global Asset Allocation

An examination of the effectiveness of applying a trend following methodology to global asset allocation between equities, bonds, commodities and real estate.

Investors today have a choice of a wide range of asset classes when seeking to invest their money. With electronic trading and the rapid expansion of the Exchange Traded Funds (ETFs) universe, the ability to invest in asset classes and instruments both domestically, and overseas, has never been easier.

Holding the traditional asset allocation of 60% in domestic equities and 40% in domestic bonds indefinitely increasingly appears archaic. Aside from the diversification benefits lost by failing to explore alternative asset classes, it can be a highly inefficient strategy since the volatility of equities dominates the risk in a 60/40 portfolio. An alternative would be for investors to allocate an equal amount of risk to stocks and bonds, to achieve 'risk parity', and show that this has delivered a superior risk-adjusted performance compared to the traditional 60/40 approach to asset allocation. Although, nominal returns have historically been quite low, proponents of this strategy argue that the drawback of constructing a portfolio comprised of risk parity weights can be overcome by employing leverage. Inker (2010), however, argues that the last three decades have been especially favourable to government bonds and that this has generated flattering results for risk parity portfolio construction techniques. Furthermore, critics have also pointed out that when applying risk parity rules investors are effectively taking no account of the future expected returns of an asset class.

There now exists a substantial literature that supports the idea that financial market momentum offers significant explanatory power with regard to future financial market returns. Typical momentum strategies involve ranking assets based on their past return and then buying the 'winners' and selling the 'losers'. Ilmanen (2011) argues that this is not an ideal approach to investing and that investors would be better served by ranking financial instruments or markets according to rankings based upon their past volatility.

Trend following has been widely used in futures markets, particularly commodities, for many decades. Trading signals can be generated by a variety of methods such as moving average crossovers and breakouts with the aim to determine the trend in the price's of either individual securities or broad market indices. Long positions are adopted when the trend is positive and short positions, or cash, are taken when the trend is negative. Because trend following is generally rules-based it can aid investors since losses are mechanically cut short and winners are left to run. This is frequently the reverse of investors' natural instincts. The return on cash is also an important factor, either as the collateral in futures trades or as the 'risk-off' asset for long-only methods. There are many advocates for the effectiveness of trend following.

A few studies have sought to combine strategies, for example using momentum and trend following in equity sector investing in the United States, or using momentum for trading between pairs of investments and then applying a quasi-trend following filter to ensure that the winners have exhibited positive returns. The risk-adjusted performance of these approaches has been a significant improvement on benchmark buy-and-hold portfolios.

The aim of this paper is to extend previous work in this area by combining and applying these strategies in a multi-asset class context. We find that trend following portfolios produce higher Sharpe ratios than a comparable, equally weighted buy and hold portfolios with much lower maximum drawdowns. This is the case both in multi-asset portfolios and within asset classes. Our results show that asset class weightings based on risk parity rules also produce much improved risk-adjusted returns in recent years compared to the same comparable buy and hold portfolios. However, further investigation does reveal that these results are largely due to the outperformance of bonds over other broad asset classes over our sample period. We find that a risk parity approach to investing adds little to performance within asset classes, in sharp contrast to our findings with regard to trend following rules which enhance portfolio performance still further when they are applied within asset class. Our results show that multi-asset class investing using momentum signals, does improve the risk-return characteristics of a multi asset class portfolio, compared to a buy-and hold equivalent, but not substantially. We also find that combining the momentum based rules, while simultaneously volatility adjusting the weights does not have a significant impact upon performance, but when we combine momentum based rules, whether the weights have been volatility-adjusted or not, with trend following rules we find a substantial improvement in performance, compared with applying just momentum-based rules. We also show how our findings can form part of a flexible asset allocation strategy, where trend following rules are used to rank 95 financial markets according to their volatility-weighted momentum. This flexible approach to asset allocation produces attractive and consistent risk-adjusted returns. Finally, we examine whether the impressive returns generated by some of these strategies could be explained by their exposure to known risk factors. We find that, although the alphas that we calculated were lower than unconditional mean returns, a significant proportion of the return could not be explained with reference to these risk factors.

Perhaps the most important implication of the results presented here relates to the degree to which a pure trend following strategy, or one overlayed on a momentum strategy with volatility-adjusted weightings, reduces drawdowns compared to buy and hold benchmark. We believe that such strategies would be ideal for risk averse investors, and perhaps particular for investors in the final years of saving for retirement, or in drawdown, where a drawdown could have a significant impact on their retirement income.

A working paper version of this research is available for download at the link below. It has previously been posted on SSRN.


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