Journal of Risk

Farid AitSahlia    
Warrington College of Business, University of Florida

This issue of The Journal of Risk addresses “dead angles” in risk models of equity portfolios, where investors lack data on detailed holdings and thus their risk exposures; the performance of Chinese hedge funds; the impact of Chinese climate policy uncertainty on market risk premiums; and the assessment of cryptocurrency risk.

In the issue’s first paper, “When betas meet the cross section: a hybrid risk model for equity portfolios”, Benoit Vaucher and Matteo Bagnara propose an implementation of the instrumented principal component analysis (IPCA) model in which traditional fundamental characteristics are replaced with regression-based exposures (betas) to risk factors. They show empirically that their hybrid approach benefits from the analytical depth of cross-sectional betas of the IPCA and the parsimony of times-series models, yielding high accuracy, granularity and numerical stability. The key advantage of the hybrid model is that its data requirements are very limited, while it exhibits excellent performance, both for analysis and optimization. This new implementation is particularly useful in the context of portfolios of funds, for which holdings and stock-level data is often unavailable for a large fraction of institutional and individual investors.

In “From expansion to recession: unraveling the performance of Chinese hedge funds through economic shifts”, the second paper in the issue, Xiangrui Zeng, Rui Guo, Zhigang Qiu and Hefei Wang use a combination of a Markov switching model and a stepwise regression to empirically evaluate the performance of Chinese hedge funds. China is a rapidly evolving financial market that presents unique challenges and opportunities distinct from more developed Western markets. The authors’ dynamic analysis shows that, in contrast to US funds, positive alpha is largely absent in momentum-driven strategies during economic expansions but is prevalent in neutral, event-driven and bond-driven strategies during recessions.

Our third paper, “Is climate policy uncertainty positively or negatively priced in the stock market, and why?” by Liang Wu, Binwei Xu and Meng Han, investigates Chinese climate policy uncertainty (CCPU) as a systematic risk factor within the intertemporal capital asset pricing model. The authors show that CCPU carries a significantly negative risk premium in the cross section of Chinese stock returns. They also show that assets with positive CCPU betas, predominantly in green sectors, serve as hedges against deteriorations in the investment opportunity set. They further show that a rising CCPU predicts lower aggregate market returns and higher volatility. Based on their results, Wu et al put forward several policy suggestions, including accelerating a clear and predictable carbon pricing system and providing a unified and stable measurement standard for investors to assess the risks of high-carbon assets and the opportunities of low-carbon assets.

Finally, in “Analyzing cryptocurrency risk with a stochastic volatility normal tempered stable process via hybrid optimization”, the issue’s fourth paper, Moshtagh Darvishi and Navideh Modarresi employ a subordinated Lévy process driven by a mean-reverting stochastic volatility model to study cryptocurrency risk. The resulting stochastic volatility normal-tempered stable process effectively captures stylized facts, such as heavy tails, asymmetry and volatility clustering. Darvishi and Modarresi also adopt a fast Fourier transform approach to numerically approximate the return density, together with Bayesian and particle swarm optimization, in order to compute tail risk measures, showing their effectiveness through standard backtesting evaluation. Completing their approach, portfolio optimization is performed by minimizing conditional value-at-risk across a selection of cryptocurrencies.