Editor’s Letter

The rise of cryptocurrencies as an asset class has led many to ask an old question. What makes an object an investment and, equally important, makes that object an institutional quality asset class? New emerging investment classes, such as cryptocurrencies, are often referred to as alternative alternatives in the asset management literature. Over the years, JAI has published many articles about these new asset classes, from art to whisky.

Generally, a long-lasting object expected to rise in value or generate income could be an investment. If this investment has common characteristics with other investments, it could form an asset class. One could consider sources of risk and return to measure if certain assets form an asset class. Alternative asset classes may be defined in opposition to traditional asset classes. When we decide publicly traded equities and bonds are traditional asset classes, everything else would be considered an alternative asset class. On the other hand, one could start with a set criterion that, once applied to an investment, would inform us whether the asset is traditional or alternative. For example, the Chartered Alternative Investment Analyst Association (CAIA) curriculum readings identify illiquidity as one of the characteristics of alternative assets.

There is no accepted definition of alternative investments. Often, they are highly illiquid investments, with small capitalizations and unclear sources of risk and returns. Further, they tend to have a very low correlation with traditional and alternative asset classes. For example, art and wine would fall into that category. Cryptocurrencies were initially part of this group, but because of increased liquidity and capitalization, some of them (e.g., bitcoin) have joined the institutional quality asset class. While some alternative alternatives may grow and become more important, eventually becoming an institutional quality asset class, others are bound to remain niche products. Most collectibles fall into this category.

The article by Fabian Y. R. P. Bocart, Christian Hafner, Yulia Kasperskaya, and Marti Sagarra, “Investing in Superheroes? Comic Art as a New Alternative Investment,” examines such a niche product. While comic art may never become an institutional quality asset class, it may have a place in high net-worth individual portfolios. Examining its return properties may provide insights into other collectibles. Drawing on a dataset of more than 106,000 comic art items sold at auction, the authors construct quarterly and semi-annual indices for American and European comic art. Between 2002 and 2017, annualized returns of US comic artworks outperformed most asset classes with a solid 11% annualized return, while European comic art achieved 25% yearly returns on average after 2009. Comic art delivered significant diversification benefits to an investment portfolio thanks to low correlations with other assets and the geographical diversification between European and American markets. These outcomes contrast with fine art in general, which delivered few diversification benefits when compared to equities and bonds between 2002 and 2017, and whose geographical markets are closely tied.

In “Questioning the Wisdom of the Crowds to Design Portfolio Diversification Strategies,” Vadim Zlotnikov, Mikhail Stukalo, Igor Halperin, Lisa Huang, and Cathy Pena attempt to provide an alternative to the traditional 60/40 portfolio of stocks and bonds, as bonds provide no hedge against equity risk in the current market conditions. Markets have recently experienced a regime change, impacting the negative correlation between stocks and bonds. As a result, multi-asset class investors searched for additional tools to mitigate risk. One novel tool involves creating a long-short portfolio of uncrowded assets. In particular, crowding in stocks held by asset managers significantly impacts stock performance. Crowded assets and strategies result in outperformance during trending markets but exhibit significant drawdowns and failures of diversification during spikes in volatility. Crowded stocks are expected to deliver negatively skewed market-adjusted returns and higher forward volatility once the market players give up on crowded trades. Conversely, uncrowded assets have the potential for positive skewness and long vol-like behavior. The authors compute a stock-level crowding measure based on active bets by mutual and hedge funds. They illustrate that a long-short equity portfolio that takes advantage of uncrowded trades combined with long equity and bond portfolios could provide an attractive risk-return profile.

Congwon Kim, Hyeonjong Jung, and Hyoung Goo-Kang develop a new approach to calculating the traditional hedge ratio used in futures markets in “A New Approach to Improving Hedging Performance in the OLS Model.” The basic approach is to regress returns on the asset, to be hedged against the return on the hedging instrument. The estimated beta tells us the size of the hedge position that one needs to hold. In this article, the authors focus on the relationship between the S&P 500 and VIX Indexes. They argue that the sensitivity of VIX futures to market movements changes over time with changes in market risk. Accordingly, in the case of using the OLS model to hedge S&P 500 exposure with VIX futures, hedge ratios are affected by changes in risk appetite, which in turn contributes to the overall hedging performance and the asymmetry of the performance distribution. The conventional OLS approach does not effectively reflect this phenomenon in the model. The authors explore a novel approach to improving hedging performance in the OLS model in this article. They introduce an interaction term between the VIX and VIX futures returns into the OLS model. They find that the hedge ratios derived by the new approach provide better hedging results than the univariate OLS model in terms of mean return and downside risk protection, and improve the asymmetry of the performance distribution.

“Bitcoin in a Multi-Asset Portfolio” by Stefan Hubrich examines the case of a multi-asset investor who is considering an allocation to digital assets. Using the case of bitcoin, the author argues that due to the short duration of available returns and the extreme volatility of the asset, historical returns are an unreliable basis for directly formulating forward return expectations. The author also shows that bitcoin’s return characteristics require an emphasis on portfolio construction considerations like rebalancing frequency, often peripheral in traditional asset allocation studies. The article demonstrates an allocation approach that addresses these concerns. The main idea is to extract required return thresholds for a small bitcoin investment (1% or 5%) that need to be underwritten by the investor rather than relying on explicit return expectations as the input. The results show that these return thresholds are surprisingly low, illustrating that the broader multi-asset portfolio perspective is critical when making investment decisions regarding high-volatility assets like bitcoin.

In “Office Real Estate as Hedge against Inflation and the Impact of Lease Contracts,” Ivo de Wit analyzes the hedging potential of real estate, especially lease contracts in various countries around the world, as inflation hedges. The dataset consists of direct real estate rent and capital value data for 59 cities in 25 countries between 1991 and 2020 to make international comparison over a long period possible. The results indicate that real estate is a good hedge against inflation, especially against unexpected inflation. Real estate inflation hedge capability is better for income than for changes in capital value, as rent contracts are adjusted for inflation. Countries with Graduated Rent and Revaluated Rent contracts have the most positive relationship with inflation. The analysis of the lease length confirms that real estate is a better hedge against unexpected inflation, but increasing the lease length does not seem to influence the hedging capability against unexpected inflation positively.

Levered exchange-traded products have been criticized for offering inferior long-term returns due to higher volatility and the belief that volatility diminished long-term expected returns. In “Levered and Inverse Exchange-Traded Products: Evidence from Simulations,” Donald Chambers and Stephen Horan challenge these beliefs. Following a simulation approach used in previous research, the authors analyze simulated returns of levered and inverse exchange-traded funds (ETFs) and conclude that their expected long-run values are not diminished by volatility. They identify natural counterparties to the rebalancing trades of levered exchange-traded funds (LETFs) and analyze the impact of autocorrelation on daily-rebalanced LETF returns, theoretically and empirically, for both LETFs and their counterparties. The results indicate that negative (positive) autocorrelation in daily returns will cause LETFs to perform relatively poorly (well) and their counterparties to perform relatively well (poorly). Accordingly, the extent to which levered and inverse ETFs have legitimate hedging applications and reasonable risk-adjusted returns (setting aside trading costs and fund expenses) depends on the extent to which the underlying returns are consistent with weak-form market efficiency.

In “The Disappeared Outperformance of Post-Reorg Equity,” Wei Jiang, Wei Wang, and Yan Yang use trading information from a comprehensive sample of relisted Chapter 11 firms in the past few decades to examine the performance of these firms once they emerge from bankruptcy. The authors find that an equal-weighted calendar-time portfolio generates 7.2% annualized excess risk-adjusted returns from 1992 to 2019. However, the outperformance concentrated in the 2000s, when institutional ownership of post-reorganization equity increased significantly. The positive post-emergence earnings announcement returns disappear in the most recent decade. The evidence suggests that the outperformance documented in earlier studies is most likely due to market expectation errors for future earnings. The initial undervaluation, corrected in the recent period by sophisticated institutional investors, has negatively impacted recent performance.

Hossein Kazemi

Editor-in-Chief

• © 2022 Pageant Media Ltd