Are Option-Implied Forecasts of Exchange Rate Volatility Excessively Variable?

Market participants' forecasts of future exchange rate volatility can be recovered from option contracts on foreign currencies. Such implicit volatility forecasts for four currencies are used to test rational expectations jointly with the applicability of the standard Black-Scholes formula. First, we examine the null hypothesis that the market-anticipated one-month-ahead standard deviation is an unbiased estimator of the subsequent realized standard deviation. The parametric regression method rejects this hypothesis overwhelmingly: the implicit forecasts are themselves excessively variable. Simulations indicate that the rejection is not caused by non-normality of the error term. Second, we use a nonparametric method to test a weaker version of market rationality: the market can correctly forecast the direction of the change in exchange rate volatility. This time, the weaker version of rationality is confirmed- Third, we investigate how market forecasts are formed. We find some evidence that market participants put heavy weight on lagged volatility when forecasting future volatility. Finally, results from the Alternating Conditional Expectations algorithm provide further support for the central finding that when the market predicts a large deviation of volatility from its mean, it could do better by moderating its forecast.

Barriers to portfolio investments in emerging stock markets (Revised)

Portfolio Investment;Capital Movements;Capital Gains Tax

Advances in forecast evaluation

This paper surveys recent developments in the evaluation of point forecasts. Taking West's (2006) survey as a starting point, we briefly cover the state of the literature as of the time of West's writing. We then focus on recent developments, including advancements in the evaluation of forecasts at the population level (based on true, unknown model coefficients), the evaluation of forecasts in the finite sample (based on estimated model coefficients), and the evaluation of conditional versus unconditional forecasts. We present original results in a few subject areas: the optimization of power in determining the split of a sample into in-sample and out-of-sample portions; whether the accuracy of inference in evaluation of multi-step forecasts can be improved with judicious choice of HAC estimator (it can); and the extension of West's (1996) theory results for population-level, unconditional forecast evaluation to the case of conditional forecast evaluation.Forecasting

On some heteroskedasticity-robust estimators of variance-covariance matrix / 1993:105

Includes bibliographical references (p. 26

Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte-Carlo Evidence

Publicad

The use of semi-parametric methods in achieving robust inference

Doutoramento em MatemáticaThis thesis focuses on some topics in semi-parametric econometrics, particularly the use of semi-parametric methods of estimation to obtain robust inference. Chapter two proposes a study of the finite-sample performance of the heteroskedastic and autocorrelation consistent covariance matrix estimators (HAC). This performance is accessed through the bias of the first moment of HAC type estimators and the quality of the asymptotic normal approximation to the exact finite-sample distributions of HAC type Wald statistics of scalar linear hypothesis. In Chapter three, the use of the non-overlapping deleted-l jackknife is used to propose a new approach to estimate the covariance matrix of the least square estimator in a linear regression model. This estimator is robust to the presence of heteroskedastldty and autocorrelation in the errors. Chapter four deals with improved estimation of regression coefficients through an alternative and efficient method of estimation regression models under heteroskedasticity of tmknown form. Kernel and average derivative estimation are used to estimate the conditional variance of the response variable where this conditional variance is assumed to be in an index form. Chapter five is concerned with the estimation of duration models under unobserved heterogeneity. This is a typical problem in mlcroer.onometrics and is in general due to differences among individuals. It is suggested a method of estimation based on a roughness penalty approach

Parametric and semi-parametric modelling of vacation expenditures

Consumer Choice;Recreation