Diversification effect of standard and optimized carry trades

Standard carry trades, which consist of purchasing high- and selling low-yield currencies, provide an economic diversification effect. However, the diversification effect is not robust, and is not borne out by much statistical evidence. We introduce optimized carry trades, which incorporate risk components such as currency volatility or currency skewness in the selection process. These optimized carry trades provide a robust economic diversification effect observed by a larger Sharpe ratio, a reduced portfolio volatility, a smaller drawdown, or a reduced tail risk with respect to a benchmark portfolio. Moreover, a significant improvement of the mean-efficient frontier is observable, with the result that minimum-variance and tangency portfolio are enhanced. The empirical results reveal that optimized carry trades have a larger diversification effect than standard carry trades and their modifications.     

Information content of options trading volume for future volatility: Evidence from the Taiwan options market

This study follows the approach of Ni et al. [Ni, S.X., Pan, J., Poteshman, A.M., 2008. Volatility information trading in the option market. Journal of Finance 63, 1059–1091] – based upon the vega-weighted net demand for volatility – to determine whether volatility information exists within the Taiwan options market. Our empirical results show that foreign institutional investors possess the strongest and most direct volatility information, which is realized by the delta-neutral options/futures trades. In addition, a few individual investors (less than 1% of individuals’ trades) might be informed and realize their volatility information using the strangle strategy. Surprisingly, we find no evidence to support the predictive ability of the volatility demand from straddle trades, despite the widespread acknowledgement that such trades are sensitive to volatility.     

Crash-neutral currency carry trades

Currency carry trades exploiting violations of uncovered interest rate parity in G10 currencies deliver significant excess returns with annualized Sharpe ratios equal to or greater than those of equity market factors (1990–2012). Using data on out-of-the-money foreign exchange options, I compute returns to crash-hedged portfolios and demonstrate that the high returns to carry trades are not due to peso problems. A comparison of the returns to hedged and unhedged trades indicates crash risk premia account for at most one-third of the excess return to currency carry trades.     

A stochastic dominance analysis of yen carry trades

Yen carry trades have made headline news for over a decade. We examine the profitability of such trades for the period 2001–2009. Yen carry trades generated high mean returns and Sharpe ratios prior to the recent financial crisis. They continued to outperform major stock markets for the full sample period. Given the non-normality of carry trade returns, we apply non-parametric tests based on stochastic dominance (SD) to evaluate whether the high returns of yen carry trades are compatible with risk as reflected in returns on US and global stock market indices. We apply a general test for SD developed recently by Linton, Maasoumi and Whang (2005) to six currencies as well as portfolios of these currencies. For a large class of risk-averse investors, profits from yen carry trades cannot be attributed to risks.     

Does the choice of estimator matter when forecasting returns?

While the literature concerned with the predictability of stock returns is huge, surprisingly little is known when it comes to role of the choice of estimator of the predictive regression. Ideally, the choice of estimator should be rooted in the salient features of the data. In case of predictive regressions of returns there are at least three such features; (i) returns are heteroskedastic, (ii) predictors are persistent, and (iii) regression errors are correlated with predictor innovations. In this paper we examine if the accounting of these features in the estimation process has any bearing on our ability to forecast future returns. The results suggest that it does.     

Exchange rate volatility across financial crises

This paper studies the impact of global financial turmoil on the exchange rate policies in emerging countries. Spillovers from advanced financial markets to currencies in emerging countries are likely to be exacerbated during crisis periods. To test this hypothesis, we assess the exchange rate policies by currencies’ volatility and investigate their relationship to a global financial stress indicator, measured by the volatility on global markets. We introduce the possibility of nonlinearities by running smooth transition regressions over a sample of 21 emerging countries from January 1994 to September 2009. The results confirm that exchange rate volatility does increase more than proportionally with the global financial stress, for most countries in the sample. We also evidence regional contagion effects spreading from one emerging currency to other currencies in the neighboring area.     

Currency carry trade regimes: Beyond the Fama regression

We show that carry trade strategies resemble FX option strategies that sell out of the money puts on high interest rate currencies. Both strategies collect premiums to generate persistent excess returns that unwind sharply when volatility increases. We also show that the widely documented negative slope coefficient in regressions of exchange rate depreciation on forward currency premiums is an artifact of the volatility regime. In high volatility regimes, the so-called Fama regression produces a positive coefficient greater than unity. We finally document the existence of an intuitive co-movement between currency risk premiums and yield curve risk factors.     

International stock return predictability under model uncertainty

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predictive variables, whereas valuation ratios perform rather poorly. Yet, predictability of market excess returns weakens substantially, once model uncertainty is accounted for. We document notable differences in the degree of in-sample and out-of-sample predictability across different stock markets. Overall, these findings suggest that return predictability is neither a uniform, nor a universal feature across international capital markets.     

Countercyclical currency risk premia

We describe a novel currency investment strategy, the ‘dollar carry trade,’ which delivers large excess returns, uncorrelated with the returns on well-known carry trade strategies. Using a no-arbitrage model of exchange rates we show that these excess returns compensate U.S. investors for taking on aggregate risk by shorting the dollar in bad times, when the U.S. price of risk is high. The countercyclical variation in risk premia leads to strong return predictability: the average forward discount and U.S. industrial production growth rates forecast up to 25% of the dollar return variation at the one-year horizon. The estimated model implies that the variation in the exposure of U.S. investors to worldwide risk is the key driver of predictability.     

Carry trade strategies based on option-implied information: Evidence from a cross-section of funding currencies

We document carry trade returns based on the moments extracted from options on the underlying currencies. We establish three important results. First, a currency pair is predicted to have greater excess returns if option-implied returns are more volatile, are more left-skewed, and have fatter tails than the returns of other currency pairs. Second, strategies based on option-implied information improve on benchmark strategies based on realized market returns and macroeconomic data. Third, if the option-implied returns of a currency pair are more left-skewed than in the past, anti-carry trades rather than carry trades perform better.     

Long memory versus structural breaks in modeling and forecasting realized volatility

We explore the possibility of structural breaks in the daily realized volatility of the Deutschemark/Dollar, Yen/Dollar and Yen/Deutschemark spot exchange rates with observed long memory behavior. We find that structural breaks in the mean can partly explain the persistence of realized volatility. We propose a VAR-RV-Break model that provides superior predictive ability when the timing of future breaks is known. With unknown break dates and sizes, we find that a VAR-RV-I(d) long memory model provides a robust forecasting method even when the true financial volatility series are generated by structural breaks.     

Pricing exotic options with L-stable Padé schemes

In this paper we develop a strongly stable (L-stable) and highly accurate method for pricing exotic options. The method is based on Padé schemes and also utilizes partial fraction decomposition to address issues regarding accuracy and computational efficiency. Due to non-smooth payoffs, which cause discontinuities in the solution (or its derivatives), standard A-stable methods are prone to produce large and spurious oscillations in the numerical solutions which would mislead to estimating options accurately. The proposed method does not suffer these drawbacks while being easy to implement on concurrent processors. Numerical results are presented for digital options, butterfly spread and barrier options in one and two assets. In addition, the methods are tested on the Heston stochastic volatility model.     

Confidence building on Euro convergence: Evidence from currency options

We study the evolution of investor confidence in 1992-1998 over the chance of individual currencies to converge to the Euro, using data on currency option prices. Convergence risk, which may reflect uncertainty over policy commitment as well as exogenous fundamentals, induces a level of implied volatility in excess of actual volatility. This volatility wedge should gradually decrease as confidence grows over time as convergence policy is maintained, and the risk of a reversal is progressively resolved. Empirically, we indeed find a positive volatility wedge which declines over time only for currencies involved in the Euro convergence process. The wedge and other convergence risk measures are correlated with both exogenous fundamentals and proxies for policy commitment uncertainty. We also find that the wedge responds to policy shocks in an asymmetric fashion, suggesting that policy risk is resolved at different rates after negative and positive shocks. Finally, we estimate a regime-switching model of convergence uncertainty, using data on interest rates, currency rates, and currency option prices. The results confirm the time-varying and asymmetric nature of convergence risk, and indicate that investors demand a risk premium for convergence risk.     

Maxing out: Stocks as lotteries and the cross-section of expected returns

Motivated by existing evidence of a preference among investors for assets with lottery-like payoffs and that many investors are poorly diversified, we investigate the significance of extreme positive returns in the cross-sectional pricing of stocks. Portfolio-level analyses and firm-level cross-sectional regressions indicate a negative and significant relation between the maximum daily return over the past one month (MAX) and expected stock returns. Average raw and risk-adjusted return differences between stocks in the lowest and highest MAX deciles exceed 1% per month. These results are robust to controls for size, book-to-market, momentum, short-term reversals, liquidity, and skewness. Of particular interest, including MAX reverses the puzzling negative relation between returns and idiosyncratic volatility recently shown in 2 and 3.     

Intraday trading volume and international spillover effects

The objective of this paper is to explore whether lagged trading activity in one market contributes to the return and volatility process in other markets, using 5-min concurrent data from German and British equity market. Our results lend support to our initial premise that if international investors have access to the same information set as domestic traders, then after observing foreign trading activity, market makers adjust prices to reflect their expectation of the security value, conditional upon all available information, including prior trades. Our findings clearly indicate that intraday trading volume contains predictive power for cross-border return and volatility processes. Moreover, these volume effects are found to be asymmetric in the sense that the impact of positive volume changes upon foreign stock market volatility is greater than is the impact of negative changes.     

Volatility effects of institutional trading in foreign stocks

This paper examines the impact of institutional trades on volatility in international stocks across 43 countries. There is a temporary volatility spike during the trade execution period, merely reflecting the price impact costs faced by the institutions. Cross sectional regressions suggest that trade imbalances, enforcement of insider trading laws, stock prices, and an emerging market classification are positively associated with temporary volatility increases whereas the presence of market makers and better shareholders’ rights dampen such increases. In the long term, institutional trades do not destabilize markets as the levels of volatility after their trades are almost identical to their pre-decision levels.     

Accurate minimum capital risk requirements: A comparison of several approaches

In this paper we estimate, for several investment horizons, minimum capital risk requirements for short and long positions, using the unconditional distribution of three daily indexes futures returns and a set of short and long memory stochastic volatility and GARCH-type models. We consider the possibility that errors follow a t-Student distribution in order to capture the kurtosis of the returns’ series. The results suggest that accurate modelling of extreme observations obtained for long and short trading investment positions is possible with an autoregressive stochastic volatility model. Moreover, modelling futures returns with a long memory stochastic volatility model produces, in general, excessive volatility persistence, and consequently, leads to large minimum capital risk requirement estimates. Finally, the models’ predictive ability is assessed with the help of out-of-sample conditional tests.     

Regime switches in exchange rate volatility and uncovered interest parity

We use a regime-switching model to examine how exchange rate volatility is related to the failure of uncovered interest parity. Main findings are as follows. First, exchange rate returns are strongly influenced by regime switches in the relationship between the returns and interest rate differentials. Second, low-yielding currencies appreciate less frequently, but once it occurs, their movements are faster than when they depreciate. Third, depreciation of low-yielding currencies and low volatility are mutually dependent on each other. Finally, these three findings are more evident for shorter horizons. The second and third results are consistent with a market participants’ view: short-term carry trades in a low-volatility environment and their rapid unwinding substantially influence exchange rates. We consider the effects of funding liquidity to explain these results.     

Risk and return: Long-run relations,fractional cointegration,and return predictability

Univariate dependencies in market volatility, both objective and risk neutral, are best described by long-memory fractionally integrated processes. Meanwhile, the ex post difference, or the variance swap payoff reflecting the reward for bearing volatility risk, displays far less persistent dynamics. Using intraday data for the Standard & Poor's 500 and the volatility index (VIX), coupled with frequency domain methods, we separate the series into various components. We find that the coherence between volatility and the volatility-risk reward is the strongest at long-run frequencies. Our results are consistent with generalized long-run risk models and help explain why classical efforts of establishing a naïve return-volatility relation fail. We also estimate a fractionally cointegrated vector autoregression (CFVAR). The model-implied long-run equilibrium relation between the two variance variables results in nontrivial return predictability over interdaily and monthly horizons, supporting the idea that the cointegrating relation between the two variance measures proxies for the economic uncertainty rewarded by the market.     

Causality in quantiles and dynamic stock return–volume relations

This paper investigates the causal relations between stock return and volume based on quantile regressions. We first define Granger non-causality in all quantiles and propose testing non-causality by a sup-Wald test. Such a test is consistent against any deviation from non-causality in distribution, as opposed to the existing tests that check only non-causality in certain moment. This test is readily extended to test non-causality in different quantile ranges. In the empirical studies of three major stock market indices, we find that the causal effects of volume on return are usually heterogeneous across quantiles and those of return on volume are more stable. In particular, the quantile causal effects of volume on return exhibit a spectrum of (symmetric) V-shape relations so that the dispersion of return distribution increases with lagged volume. This is an alternative evidence that volume has a positive effect on return volatility. Moreover, the inclusion of the squares of lagged returns in the model may weaken the quantile causal effects of volume on return but does not affect the causality per se.