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Volatility insurance and exchange rate predictability: The VRP currency strategy

Economists widely view exchange rate changes as unpredictable. This column explains a new currency trading strategy with economically valuable and statistically significant currency excess returns. The returns are generated primarily by spot exchange rate returns, rather than interest differentials. The strategy’s performance can be explained by speculator-hedger interactions in the currency market in the presence of time-varying capital constraints on speculators.

For decades, finance practitioners and academics alike have struggled to explain – or even understand – currency fluctuations using theoretically motivated predictors. This has led many experts to conclude that fluctuations in exchange rates are unpredictable.

The paradox is that some market participants seem to understand exchange rate movements well enough to make money. Buy-side asset managers, banks, hedge funds, and even individuals seem to find currency trading profitable. Indeed, a number of studies have documented high returns to currency investment strategies such as carry and momentum (e.g. Burnside et al. 2011, Lustig et al. 2011, Menkhoff et al. 2012 a,b).

These profitable currency strategies have two important properties.

  • First, it has been difficult to explain their success as compensation for some form of systematic risk.
  • Second, the primary driver of the historical performance of these strategies (most notably, carry) has been interest differentials rather than exchange rate appreciation or depreciation.
A new currency strategy

Our recent work discovers a new currency strategy with high average excess returns, excellent diversification benefits relative to the set of previously discovered currency strategies, and some unusual properties that provide clues as to the underlying drivers of exchange rate movements (Della Corte et al. 2013). The key to this new strategy is the significant predictive power of the currency volatility risk premium for currency excess returns.

A useful summary statistic of the importance of this new currency strategy (which we call VRP), is that over the 1996 to 2011 period, in a cross-section of up to 20 currencies, it has the highest weight (33%) in the global minimum variance portfolio of five well-known currency strategies, including carry and momentum (Figure 1).

Figure 1 Global minimum volatility portfolios

The high weight of VRP in the currency strategy portfolio is primarily a reflection of its very desirable correlation properties relative to the other widely studied currency strategies, as VRP does not have the highest returns among the strategies considered. This unusual low correlation partly arises from the excellent performance of VRP during crises, and primarily from the fact that the currency excess returns of VRP are almost completely obtained through predictable variation in exchange rates, rather than from interest rate differentials. The observed predictability of spot exchange rates associated with VRP is far stronger than that arising from carry (which is almost entirely driven by interest rate differentials) and currency momentum, as well as other currency trading strategies that we consider, as can be seen in Figure 2.

Figure 2 Currency strategies and payoffs

The volatility risk premium and VRP

The currency volatility risk premium is the difference between expected future realised volatility and a model-free measure of implied volatility derived from currency options. A growing literature studies the variance or the volatility risk premium in different asset classes. In general, this literature has shown that the volatility risk premium is on average negative – expected volatility is higher than historical realized volatility, and since volatility is persistent, expected volatility is also generally higher than future realized volatility.

  • A simple way to understand the volatility risk premium is that it represents compensation for providing insurance against fluctuations in the underlying currency. When it is high – realized volatility is higher than the option-implied volatility – insurance is relatively cheap, and vice versa.

Our strategy is to sort currencies into quintile portfolios at the end of each month, based on the level of the currency volatility risk premium; we track returns over the subsequent period. The VRP strategy goes long currencies with relatively cheap volatility insurance, i.e. the highest volatility risk premium quintile, and short currencies with relatively expensive volatility insurance, i.e. the lowest volatility risk premium quintile.

Why does the volatility risk premium forecast exchange rates?

We consider two potential explanations for the high returns generated by the VRP strategy.

  • The first is that these returns are simply compensation for systematic risk.

To test this explanation, we conduct a battery of asset pricing tests using risk factors proposed in the currency literature including dollar, carry, and global volatility, as suggested by Lustig et al. (2011) and Menkhoff et al. (2012). We find that these factors do not explain the returns to VRP; moreover, sets of risk factors, more commonly used in explaining equity returns and hedge fund returns, are similarly unsuccessful. We also explore the possibility that the currency volatility risk premium may capture dynamic variation in currencies’ betas on systematic risk factors, particularly volatility risk, and find little evidence that such a mechanism is able to explain our results.

  • Our preferred explanation relies on the presence of limits to arbitrage and its effects on the interaction between hedgers and speculators in the currency market.

There is a growing theoretical and empirical literature suggesting that such interactions are important in asset return determination (see, for example, Acharya et al. 2013). In the currency markets, this explanation comprises two components.

  • First, it requires time-variation in the amount of arbitrage capital available to natural providers of currency volatility insurance (‘speculators’), such as financial institutions or hedge funds.
  • The second ingredient is risk-averse natural ‘hedgers’ of currencies such as multinational firms, or financial institutions that inherit currency positions from their clients.

These hedgers are likely to be more comfortable holding (or entering into contracts denominated in) currencies with relatively inexpensive volatility insurance. Such institutions will also be more likely to avoid positions in currencies with relatively expensive volatility protection. The combination of these two ingredients would be sufficient to generate the patterns that we see in the data.

A simple example may be helpful. Assume that speculators face a shock to their available arbitrage capital. This limits their ability to provide cheap volatility insurance, especially in currencies in which they have large positions – for example, they may reduce their outstanding short put option positions in the currencies in which they trade. These limits on speculators' ability to satisfy demand for volatility insurance increase net demand in the options market for the specific currencies in which they are most active, increasing current option prices and making hedging more expensive. As in Gârleanu et al. (2009), this net demand imbalance would show up in a lower volatility risk premium for the currencies thus affected. Given the high cost of volatility insurance, natural hedgers may scale back the amount of spot currency they are willing to hold, or be more reluctant to get into new expensive hedges. This net demand will predictably depress spot currency rates, leading to relatively low returns on the spot currency position. When capital constraints loosen, we should see the opposite behaviour, i.e. a reversal in both the volatility risk premium and the spot currency position. In the cross-section of currencies, in an environment with limited arbitrage capital, time-variation in currency specialisation by speculators and/or time-variation in the contract denomination of natural hedgers would be sufficient to generate the patterns that we observe.

We find evidence in support of this explanation.

  • First, we find that currency volatility risk-premium sorted portfolio returns reverse over a holding period of a few months.
  • Second, at times when funding liquidity (as measured by the TED spread) is lower, and demand for volatility protection (as measured by VIX) is higher, we find that the spread in the cost of volatility insurance across currencies and the spread in spot exchange rate returns across portfolios both increase.
  • Third, when capital flows to currency and global macro hedge funds are high, signifying increased funding and thus lower hedge fund capital constraints, the returns to VRP are lower and vice versa.

Finally, we inspect the positioning of commercial and financial traders in the FX market using data provided by the CFTC in their Commitment of Traders reports. We find that commercial traders tend to sell currencies which are more expensive to insure, and buy currencies which are cheaper to insure; in contrast, financial traders appear to trade in a way that is exactly opposite to that of commercial traders (Figure 3). This pattern of trading behaviour corroborates our other evidence suggesting that VRP returns are driven by the interaction of natural hedgers and speculators in currency markets.

Figure 3 Futures net positions and volatility risk premium strategy


We discover a new currency strategy, VRP, with economically valuable and statistically significant currency excess returns. These returns are generated primarily by spot exchange rate returns, rather than interest differentials, which is a contributing factor to the very low correlation of VRP with pre-existing currency strategies, and the potential diversification gains from adding VRP to the strategies normally followed by currency managers. We find evidence that the performance of VRP can be explained by speculator-hedger interactions in the currency market in the presence of time-varying capital constraints on speculators.


Acharya, V, L A Lochstoer and T Ramadorai (2013), “Limits to Arbitrage and Hedging: Evidence from Commodity Markets,” Journal of Financial Economics 109, pp. 441-465.

Della Corte, P, T Ramadorai and L Sarno (2013), “Volatility Risk Premia and Exchange Rate Predictability”.

Burnside, C, M Eichenbaum, I Kleshchelski and S Rebelo (2011), “Do Peso Problems Explain the Returns to the Carry Trade?” Review of Financial Studies 24, 853-891.

Gârleanu, N B, L H Pedersen and A Poteshman (2009), “Demand-Based Option Pricing,” Review of Financial Studies 22, pp. 4259-4299.

Lustig, H, N Roussanov and A Verdelhan (2011), “Common Risk Factors in Currency Markets,” Review of Financial Studies 24, pp. 3731-3777.

Menkhoff, L, L Sarno, M Schmeling and A Schrimpf (2012a), “Carry Trades and Global FX Volatility,” Journal of Finance 67, pp. 681-718.

Menkhoff, L, L Sarno, M Schmeling and A Schrimpf (2012b), “Currency Momentum Strategies,” Journal of Financial Economics 106, pp. 620-684.

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