Dynamic Global Currency Hedging

Christensen, Bent Jesper; Varneskov, Rasmus T.

doi:10.2139/ssrn.2717808

Cited by 5 publications

(5 citation statements)

References 96 publications

(104 reference statements)

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“…Such an ex ante approach necessarily can make use of only past or current data. In line with Christensen and Varneskov (2016), I find substantial time variation in the optimal currency hedging in G7 currencies for an international investor. Given the changing correlation properties of currencies, it is unsurprising that realistically feasible risk reductions are clearly lower than in sample.…”

supporting

confidence: 74%

“…Second, the covariance matrix and thus the currencies' (equity, bond, and commodity) market betas change through time. Evidence for changing risk characteristics in currencies abounds: Christensen and Varneskov (2016), for instance, find that the Japanese yen was positively correlated with world stock markets in the 1970s and 1980s but has since the 1990s been negatively correlated with stock markets. To react to this, a real-world investor has to find a suitable length of estimation period that trades off including enough data points to reliably estimate the past optimal FX coefficients while not including antiquated data that are no longer representative of current FX risk characteristics.…”

Section: Dynamic Real-world Hedgingmentioning

confidence: 99%

“…and 1970s with work by Grubel (1968), Levy and Sarnat (1970), and Solnik (1974), for example. However, as noted in Kroencke, Schindler, and Schrimpf (2014) and Christensen and Varneskov (2016), the inherent currency exposure in international investments and its diversification potential has often been neglected. Only with Perold and Schulman (1988), who find risk reductions for full relative to no hedging of international equity positions, has the diversification literature started to explicitly analyze the question of currency exposure.…”

mentioning

confidence: 99%

“…2 It seems a lot more intuitive to employ forward-looking risk factors for conditional risk management. Christensen and Varneskov (2016) make a first step in the right direction by making use of intraperiod dynamics in the 1 Based on a methodology developed by Anderson and Danthine (1981).…”

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confidence: 99%

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Conditional currency hedging

Bucher

2019

Financial Management

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I propose a simple and robust approach to hedge currency risk that can be directly applied by international investors in diverse asset classes. Compared to current mean-variance approaches, it is robust to overfitting and thus better anticipates risk-minimizing currency positions for global equity, bond, and commodity investors out of sample. Furthermore, correlations among currencies, equities, and commodities can be predicted by lagged implied foreign exchange volatility. This allows investors to dynamically adjust their hedges, resulting in significantly lower risk compared to other hedging alternatives while maintaining or even improving Sharpe ratio, particularly during crisis periods. K E Y W O R D S dynamic currency hedging, implied volatility, mean-variance analysis, overfitting 1 INTRODUCTION Since the demise of the postwar Bretton Woods system in the 1970s, currency fluctuations have been a major financial risk. International securities can provide better risk-reward trade-offs, but in a regime of floating foreign exchange (FX) rates, any investor dealing with a foreign currency is inherently exposed to adverse FX movements. It is therefore natural to ask whether and how one can optimally hedge this currency risk. I propose a simple and robust mean-variance approach to hedge FX risk for investors globally-dynamic conditional currency hedging (DCCH). This entails three contributions. First, I document that current mean-variance hedging approaches break down out of sample due to their in-sample bias and tendency to overfit. Second, I propose DCCH as an alternate hedging mechanism that is less prone to overfit and performs favorably both in and out of sample. Compared to the alternatives discussed in the literature to date, this approach leads to lower standard deviation and downside risk while maintaining or improving Sharpe ratio. Third, correlation patterns between major currency pairs and other assets, such as equities and commodities, can be strongly predicted by implied FX volatility (IVOL). Using this as conditional information for DCCH further reduces risk and improves the risk-return relationship of hedged returns. This paper contributes to three related streams of literature on international diversification, global risk factors, and systematic FX investment styles. The benefits of international diversification have long been established in the 1960s

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confidence: 74%

Section: Dynamic Real-world Hedgingmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Conditional currency hedging

Bucher

2019

Financial Management

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“…The general mean-variance problem, as applied to hedging, was solved by Anderson and Danthine (1981), with specific application for currencies appearing in, among others, Glen and Jorion (1993), Jorion (1994), Gagnon, Lypny, and McCurdy (1998), Ang and Bekaert (2002), , Campbell, Serfaty-de Medeiros, and Viceira (2010), , , Opie and Dark (2015), Christensen and Varneskov (2018), and Opie and Riddiough (2019). The practical relevance of fullblown mean-variance analysis is limited, however, because of both its opacity and its tendency to produce unintuitive portfolios as a result of overfitting of inputs that are inherently uncertain and ignoring investor preferences beyond mean and volatility.…”

Section: Currency Hedging: Theorymentioning

confidence: 99%

Optimal Currency Hedging for International Equity Portfolios

Boudoukh¹,

Richardson

Thapar³

et al. 2019

Financial Analysts Journal

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T he currency-hedging policies of international equity portfolios have been subject to much debate by academics and practitioners, yet a consensus has failed to emerge on an optimal approach. 1 Many investors choose simply to ignore the currency component of these portfolios-in an eVestment universe of 104 MSCI EAFE Index managers totaling $419 billion of assets, as of June 2018, only 18.3% pursued active currency management. 2 Perhaps this inaction stems from uncertainty about whether hedging can truly offset risk or from concerns that hedging programs that reduce risk may also create a drag on returns. Although academics and theorists have pointed to mean-variance optimization (MVO) as a potential framework for combining risk-andreturn considerations, its practical relevance has remained questionable because of its opacity and tendency to generate unrealistic portfolios with high leverage, turnover, and tail risk. We attempt to bridge the gap between theory and practice by presenting a "modified portfolio mean-variance optimization" (MPMVO) framework that is specifically adapted to improve the practical relevance of a meanvariance approach. The result of our work is a transparent and robust hedging solution, one that both lowers portfolio risk and raises realized returns, with manageable turnover, leverage, and tail properties. MPMVO decomposes the MVO portfolio into three distinct components: (1) a pure equity piece, taken as given, (2) a "hedging" portfolio designed to minimize equity volatility, and (3) a currency "alpha" portfolio that is focused on generating high standalone riskadjusted returns. The underlying theory determines the optimal mix 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.

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