Asset class picking

An asset class is a broad group of securities or investments that have similar financial characteristics. Choice of the right asset class mix is the greatest determinant of portfolio’s absolute performance. As most assets are strongly correlated to other members of its asset class, the majority of portfolio’s adjusted returns are likely to be driven by the asset class allocation rather than individual asset allocation. Asset class picking is the main concern of strategic asset allocation strategies.

Allocation in these strategies is driven by optimising return given risk based on market implied projections of the future. Strategic asset allocation avoids strong market views and is usually used in long term investment styles. A basic strategy (sometimes called asset class switching) consists of increasing allocation in equities during periods of economic growth and in bonds during downturns. Commodities are used as an inflation protection. Cash is used as a defensive asset for lowering total portfolio risk and increasing liquidity.

In the context of tactical strategies, asset class picking is an approach of using multiple asset classes for exploiting market inefficiencies. It is not surprising that momentum, value and carry have been found to be better performing if applied together across different asset classes rather than just within a single asset class. However, given strategy returns are not equally distributed across asset classes so it is better to find a market anomaly in one asset class and switch to other asset class once this opportunity is arbitraged away. Factor related asset class selection has been given attention in practitioner and academic research.

Momentum asset allocation strategies and trend following across asset classes has been particularly well documented (see Blitz and Vliet (2008)). Combined strategies –  momentum and value strategies applied to global asset allocation across twelve asset classes also deliver statistically and economically significant abnormal returns of 12% per annum over the 1986-2007 period (see Asness, Moskowitz and Pedersen (2012)). Wang and Kochard(2011) present several active strategies for combining value and momentum strategies in a tactical asset allocation framework.
They refine the basic yield approach to valuation by standardizing the value signal using the Z-score.

Such standardization not only enables us to directly compare valuation measures across asset classes, but also offers insight about each asset class’s absolute valuation by its own standard. Bhansali et al. (2015) report the results of an empirical study covering twenty major markets across four asset classes, and an extended sample period from 1960 to 2014. The results confirm overwhelmingly that having the trend and carry in your favour leads to significantly better returns. Cherkezov et al. (2017) find that style factors well established in the equity domain – such as value, momentum or quality – do extend to other asset classes as well. Even more so, multi-asset multi-factors significantly expand the investment opportunity set relative to a traditional multi-asset universe. Geczy and Samonov (2017) document that on average, since 1800, momentum effect appears significant in all asset classes, except in commodity spot
prices.

Cooper, Mitrache, Priestley (2017) conclude that global macroeconomic risk in the form of exposure to the global factors (rates and inflation, term and default spread, GDP and industrial production) plays an important role in summarizing the average returns of the value and momentum strategies as well as their combinations across many asset classes and markets. Furthermore, they find that asset classes within a country are integrated and asset markets across countries are integrated. This finding helps to explain returns on market anomalies across asset classes.

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The Encyclopedia of Quantitative Trading Strategies

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