Best of Research Review 2017

So many research papers, so little time. How do you separate the wheat from the chaff? You might start with the following five economic and financial papers that appeared in The Capital Spectator’s Research Review column in 2017. In a sea of newly minted studies over the past 12 months, these titles stand out as worthy of a second read.

Time-Varying Risk Premiums and Economic Cycles
Thomas Raffinot (Millesime IS)
April 2017
Asset returns are not correlated with the business cycle but are primarily caused by the economic cycles. To validate this claim, economic cycles are first rigorously defined, namely the classical business cycle and the growth cycle, better known as the output gap. The description of different economic phases is refined by jointly considering both economic cycles. It improves the classical analysis of economic cycles by considering sometimes two distinct phases and sometimes four distinct phases. The theoretical influence of economic cycles on time-varying risk premiums is then explained based on two key economic concepts: nominal GDP and adaptive expectations. Simple dynamic investment strategies confirm the importance of economical cycles, especially the growth cycle, for euro and dollar-based investors. At last, this economic cyclical framework can improve strategic asset allocation choices.

Asset Allocation in a Low Yield Environment
John Huss (AQR Capital Mgt.), et al.
August 17, 2017
The year 2016 saw bond yields fall to unprecedented low levels in major developed markets, with nominal yields on 10-year German and Japanese government bonds even turning negative. While yields have risen off their lows in 2017, we are still in a very low rate environment. Does this demand exceptional action from investors – even those who usually maintain a strategic allocation to global bonds? We find that it does not, instead it highlights the importance of diversification across many return sources.

The Most Dangerous (and Ubiquitous) Shortcut in Financial Planning
John West and Amie Ko (Research Affiliates)
September 2017
Using historical returns to forecast the future is one of the most common shortcuts in financial planning. Investment advisors who use only past returns to forecast future returns may well be creating unrealistic expectations and poor investment outcomes for their clients. Our online Asset Allocation Interactive, which uses starting yields to forecast future long-term returns, gives advisors a rich toolkit with which to construct portfolios most likely to achieve their clients’ financial goals.

When (If Ever) Has it Paid to Wait for a Stock Market Correction?
Victor Haghani and James White (Elm Partners)
August 2017
Investors are periodically challenged with this question: with funds ready to invest, but faced with a market that is generally perceived to be expensive, is it better to wait for a market correction before investing? Many investors are certain that a correction must be around the corner, and thus little downside exists to holding excess cash. We explore the question of whether the historical record supports their near-certainty by examining the past 115 years of US stock market history. We conclude that while there may be valid reasons to hold excess cash based on specific forward-looking return estimates, the historical record does not suggest that, conditioned on a variety of entry criteria, waiting for a correction has positive expected return.

Can We Use Volatility to Diagnose Financial Bubbles? Lessons from 40 Historical Bubbles
Didier Sornette (ETH Zürich), et al.
April 19, 2017
We inspect the price volatility before, during, and after financial asset bubbles in order to uncover possible commonalities and check empirically whether volatility might be used as an indicator or an early warning signal of an unsustainable price increase and the associated crash. Some researchers and finance practitioners believe that historical and/or implied volatility increase before a crash, but we do not see this as a consistent behavior. We examine forty well-known bubbles and, using creative graphical representations to capture robustly the transient dynamics of the volatility, find that the dynamics of the volatility would not have been a useful predictor of the subsequent crashes. In approximately two-third of the studied bubbles, the crash follows a period of lower volatility, reminiscent of the idiom of a “lull before the storm”. This paradoxical behavior, from the lenses of traditional asset pricing models, further questions the general relationship between risk and return.

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