Abstract
This study explores optimal currency exposures in international equity portfolios through the lens of a modified mean–variance optimization framework. We decomposed the optimal currency portfolio into a “hedge portfolio” that uses a dynamic risk model to minimize equity volatility and an “alpha-seeking portfolio” based on the well-documented currency styles of value, momentum, fundamental momentum, and carry. This method is an integrated and economically intuitive approach to currency management that simultaneously provides lower risk and higher returns than either hedged or unhedged benchmarks. Crucially, the solution is practical, with realistic and implementable leverage, turnover, and tail-risk characteristics.
Highlights
Jacob Boudoukh is professor of finance at the Arison School of Business, Interdisciplinary Center Herzliya, and a consultant at AQR Capital Management, Greenwich, CT
We attempt to bridge the gap between theory and practice by presenting a “modified portfolio mean–variance optimization” (MPMVO) framework that is adapted to improve the practical relevance of a mean– variance approach
What is the optimal way to hedge the currency risk of international equity portfolios? We have shown that the optimal portfolio can be decomposed into a hedged equity component, a variance-minimizing currency-hedging portfolio, and an optimal allocation to a standalone maximum-Sharperatio currency portfolio
Summary
Note: Time series of return volatility and cumulative return performance of the hedged EQ, MINVAR, FXALPHA, and MPMVO portfolios. The investor would hold a small positive position in Swiss francs (3%), even though New Zealand dollars and Swiss francs are on the opposite sides of the carry trade Their strong negative unconditional correlation with each other (i.e., –0.41) makes them natural hedges for each other and, desirable to hold as a package. Notes: Robustness results for the Global equity portfolio using the MPMVO approach to optimize currency hedging with a perturbation to rebalancing frequency, common-sense portfolio constraints, and different sample periods. Estimates for the breakeven point range from 27 bps to 142 bps per dollar traded—much higher than most practitioners are likely to face in practice
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