Journal of Risk

Farid AitSahlia

Warrington College of Business, University of Florida

This issue of The Journal of Risk contains papers that illustrate the application of mathematical optimization to currency carry trades under liquidity constraints and assess the impact of trade war on cryptocurrencies. Systemic risk amplification and the relevance of the Fundamental Review of the Trading Book (FRTB) to base currency reporting are also addressed.

In our first paper, “Optimal foreign exchange hedge tenor with liquidity risk”, Rongju Zhang, Mark Aarons and Gregoire Loeper propose a model to help determine the best tenor mix of foreign exchange forwards in order to optimize currency carry benefits while accounting for cashflow risk whenever these contracts mature. Under the assumption of mean-reversion of spot exchange rates, the authors show that the optimal tenor mix is very sensitive to the target cashflow at risk and the spot volatility.

In “Optimization of systemic risk: reallocation of assets based on bank networks”, the issue’s second paper, Hu Wang and Shou wei Li build a contagion model that combines two channels–solvency via interbank exposures and fire sales via overlapping portfolios – in such a way that balance sheets are optimized to reduce systemic risk. The authors find that decreasing interbank assets and increasing common asset holdings can reduce systemic risk, and that a high Herfindhal–Hirschman Index plays a critical role in risk amplification.

“A review of the foreign exchange base currency approach under the standardized approach of the Fundamental Review of the Trading Book and issues related to the pegged reporting currency”, the third paper in this issue, sees Ted Yu demonstrating the invariance of the foreign exchange delta risk charge of any reporting currency under a standardized FRTB approach. The author contrasts this with the variance resulting from using triangular relations between currency pairs.

In our fourth and final paper, “Forecasting Bitcoin returns: is there a role for the US–China trade war?”, Vasilios Plakandaras, Elie Bouri and Rangan Gupta conduct an empirical study that shows Bitcoin returns to be insulated from trade frictions. Theauthors’resultsarebasedontheout-of-sampleperformanceofpredictedBitcoin returns through a variety of models, including ordinary least squares, support vector regression and the least absolute shrinkage and selection operator (LASSO).