The Share of Systematic Variation in Bilateral Exchange Rates

Verdelhan, Adrien

doi:10.2139/ssrn.2121859

Cited by 36 publications

(83 citation statements)

References 34 publications

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“…4,5 F denotes a 3ˆ1 vector of currency-based risk factors, which comprises DOL, HML, and VOL, and the choice of the instrument z k t´1 follows Lustig et al (2011) andVerdelhan (2013). 6 This model is able to encompass the frameworks proposed in Ross (1976) and Menkhoff et al (2012) and has its theoretical foundation in no-arbitrage models for interest rates and exchange rates (Backus et al (2001) and Brennan and Xia (2006)) and the ICAPM (Campbell (1993(Campbell ( , 1996), respectively.…”

Section: Models Based On Risk Factorsmentioning

confidence: 99%

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Can currency-based risk factors help forecast exchange rates?

Ahmed

Liu

Valente

2016

International Journal of Forecasting

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The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract This paper examines time-series predictability of bilateral exchange rates from linear factor models that utilize unconditional and conditional expectations of three currency-based risk factors. Exploiting a comprehensive set of statistical criteria, we find that all versions of the linear factor models largely fail to outperform the benchmark of random walk with drift model in the out-of-sample forecasting of monthly exchange rate returns. This holds true for individual currencies and currency portfolios formed on forward discounts. We also show that the information embedded in the currency-based risk factors does not generate systematic economic value to investors. JEL Classification: F31, F37, G11, and G17.

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Section: Models Based On Risk Factorsmentioning

confidence: 99%

“…1 It has become a widely accepted view in international finance that individual exchange rates closely follow random walks (Engel and West (2005), Della Corte and Tiakas (2012), and Verdelhan (2013)). …”

Section: Introductionmentioning

confidence: 99%

Can currency-based risk factors help forecast exchange rates?

Ahmed

Liu

Valente

2016

International Journal of Forecasting

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“…First, working with currency portfolios limits the role of locally priced risk (Verdelhan (2012)), as idiosyncratic risks are averaged out when portfolios are constructed. Second, Lustig et al (2011) show that sensitivity to global risk explains the crosssectional dispersion of currency portfolio returns.…”

Section: The Underlying Mechanismmentioning

confidence: 99%

“…Asness, Moskowitz, and Pedersen (2013) show that value and momentum strategies for different asset classes, ranging from stock portfolios to commodity and currency markets, are closely related to each other. In this vein, Verdelhan (2012) finds that countries' systematic stock market risk is positively related to systematic bond and currency risk.…”

Section: Introductionmentioning

confidence: 99%

Foreign Currency Returns and Systematic Risks

Atanasov¹,

Nitschka²

2014

J. Financ. Quant. Anal.

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We apply an empirical approximation of the intertemporal capital asset pricing model (ICAPM) to show that cross-sectional dispersion in currency returns can be rationalized by differences in currency excess returns' sensitivities to the market return's cash-flow news component. This finding echoes recent explanations of the value and growth stock market anomaly. The distinction between cash-flow news and discount-rate news is key to jointly explain average stock and currency returns. Our analysis reveals the presence of a common source of systematic risk in stock and foreign currency returns that is reflected in the market return's cash-flow news component.

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“…6 See for example Lustig andVerdelhan (2007), Campbell, Serfaty-De Medeiros, andViceira (2010), Lustig et al (2011), Menkhoff et al (2012, David, Henriksen, andSimonovska (2016), andVerdelhan (2015).…”

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confidence: 99%

A Risk-based Theory of Exchange Rate Stabilization

Hassan¹,

Mertens²,

Zhang³

2016

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We propose a novel, risk-based transmission mechanism for the effects of currency manipulation: policies that systematically induce a country's currency to appreciate in bad times lower its risk premium in international markets and, as a result, lower the country's risk-free interest rate and increase domestic capital accumulation and wages. Currency manipulations by large countries also have external effects on foreign interest rates and capital accumulation. Applying this logic to policies that lower the variance of the bilateral exchange rate relative to some target country ("currency stabilization"), we find that a small economy stabilizing its exchange rate relative to a large economy increases domestic capital accumulation and wages. The size of this effect increases with the size of the target economy, offering a potential explanation why the vast majority of currency stabilizations in the data are to the U.S. dollar, the currency of the largest economy in the world. A large economy (such as China) stabilizing its exchange rate relative to a larger economy (such as the U.S.) diverts capital accumulation from the target country to itself, increasing domestic wages, while decreasing wages in the target country. Differences in real interest rates across developed economies are large and persistent; some countries have lower real interest rates than others for decades rather than years. These longlasting differences in interest rates correlate with differences in capital-output ratios across countries, and account for the majority of excess returns on the carry trade, a trading strategy where international investors borrow in low interest rate currencies, such as the Japanese yen, and lend in high interest rate currencies, such as the New Zealand dollar ( Lustig, Roussanov, and Verdelhan, 2011; Hassan and Mano, 2015; Hassan, Mertens, and Zhang, 2015).A growing literature studying these "unconditional" differences in currency returns argues that they may be attributable to heterogeneity in the stochastic properties of exchange rates:Currencies with low interest rates pay lower returns because they tend to appreciate in bad times and depreciate in good times, providing a hedge to international investors and making them a safer investment (Lustig and Verdelhan, 2007;Menkhoff et al., 2013). This literature has explored various potential drivers of heterogeneity of the stochastic properties of countries' exchange rates, ranging from differences in country size (Martin, 2012;Hassan, 2013) and financial development (Maggiori, 2013) to trade centrality (Richmond, 2015) and differential resilience to disaster risk (Farhi and Gabaix, 2015). 1 The common theme across these papers is that whatever makes countries different from each other results in differential sensitivities of their exchange rates to various shocks, such that some currencies tend to appreciate systematically in "bad" states of the world (when the price of traded goods is high). Currencies with this property then pay lower expected returns a...

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The Share of Systematic Variation in Bilateral Exchange Rates

Cited by 36 publications

References 34 publications

Can currency-based risk factors help forecast exchange rates?

Can currency-based risk factors help forecast exchange rates?

Foreign Currency Returns and Systematic Risks

A Risk-based Theory of Exchange Rate Stabilization

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