Journal of Investment Strategies

Welcome to the summer 2013 issue of The Journal of Investment Strategies. In this issue you will find four research papers that cover diverse topics: from long-range market modeling to short-term market making.

In the first paper of the issue, "The enhanced risk premium factor model and expected returns", Javier Estrada introduces a novel version of the recently popularized risk premium factor model that attempts to improve it in several ways. First, it extends the risk premium factor model to explicitly forecast future values of the premium using the cyclically adjusted price-earnings ratio: this is important, as the original model implicitly assumes stationarity of the future risk premium factor. Second, it studies the forecasting ability of this enhanced risk premium factor model in both parametric and nonparametric settings and shows that in both cases the long-run forecasts of future returns on the S&P 500 are highly correlated with the actual future realized returns. Importantly, Estrada focuses not on the price returns but on the total returns, including dividend income, which is critical if the enhanced risk premium factor model is to be practically applied.

My take on this very interesting paper is that it provides a useful framework for building dynamic models that forecast long-run returns of the equity market. Specifically, I believe that in place of the cyclically adjusted price-earnings ratio and current interest rates, there could potentially be many other choices of plausible explanatory factors that would be useful in predicting the future value of the risk premium factor model. Hence, choosing any such set of variables and forecasting methodology, one can come up with many competing versions of the enhanced risk premium factor model, each of which might be better suited to some particular task - such as estimating excess returns, or downside risks - or possibly adjusted for various estimation horizons, trying to get a more nuanced picture of future returns. I am sure that readers will be able to imagine many such uses for their own objectives.

In our second paper, "An inflation-hedging strategy with commodities", Nicolas Fulli-Lemaire presents an economic study of inflation shocks and the channels through which they are related to commodities. An eye-opening discussion of the changing nature of exogenous-oil-shock-driven inflation is followed by detailed econometric modeling of the relationship between the headline and core inflation rates and commodities prices, resulting in a framework for efficient allocation of commodities as inflation hedges.

That commodities are supposed to be good hedges of inflation is often taken for granted by investors. This paper shows that the picture is more nuanced and that these nuances are very important: getting them right or wrong might mean reducing your portfolio's risk or it might mean increasing it. Given the importance of inflation in asset liability management and for making long-term investment decisions - especially taking into account the current state of the economy and under the current pro-inflation stance of most central banks - this paper could not have been more timely. I am sure that many readers will want to brush up on their econometrics so that they can read it and understand its implications fully.

In the issue's third paper, "Optimal limit order execution in a simple model for market microstructure dynamics", Yuri Burlakov, Michael Kamal and Michele Salvadore present a surprisingly simple yet powerful model of market microstructure dynamics and devise an optimal limit order execution strategy under such assumptions. The authors give us a welcome dose of the clear and intuitive logic that goes into market making. We get to see the trade-offs between risk and reward and appreciate the difference in vantage point from which the market maker views these trade-offs compared with a price-taking investor.

The model itself is elegant and solvable, and can thus be calibrated to observable variables with relative ease. The resulting optimal strategy turns out to be remarkably simple; so much so that it resembles the intuitive strategies actually employed by human market makers as a "rule of thumb". Experience tells us that such a coincidence is usually a sign that the model got some important parts of the nature of markets right. I am sure that everyone who is interested in automated market making - and more generally in algorithmic trading - will read this paper with great interest.

The paper by Jan Willem van den End, "Statistical evidence on the mean reversion of interest rates", takes an extremely long view of the markets: a 200-year-long view, to be precise. Given the length of the bond supercycle (or perhaps superbubble), which is itself measured in decades, I guess that one does indeed have to go back for a couple of hundred years to be able to judge whether this is a secular shift or whether it falls under the mean-reversion scenario with a very long time horizon.

The author is unafraid about taking on a long line of previous researchers who have not been able to conclusively find mean reversion in long-term interest rates. Of course, the rates are clearly bounded from below (by zero) and above (by economic forces, though that is a soft bound at best), but this alone does not imply stable mean reversion. The rates also exhibit strong persistence and can stay away from the "true mean" for a very long time. To clarify the problem and to resolve this paradox, van den End deploys a battery of econometric tests, from unit-root and cointegration analysis, to linear and regime-switching models. He concludes that sufficiently strong mean-reversion patterns are only observed in the outer ranges of the interest rate distribution, while in the normal regime of close-to-average rates they might actually behave more like a random walk. Similarly, he shows that the speed of mean reversion is also not constant.

I wish the paper found more clear-cut evidence of mean reversion - investors worldwide would then breathe a sigh of relief, knowing precisely when to start shorting bonds. Alas, life is not so easy. We know that rates will eventually go up - but guessing when, exactly, is one of the biggest challenges facing us in the coming years.

On behalf of the Editorial Board Iwould like to thank our readers for their continued support and keen interest in our journal. I look forward to sharing with you the growing list of excellent papers on a broad variety of topics related to modern investment strategies that we continue to receive from both academia and practitioners.