International Journal of Theoretical and Applied Finance

This paper proposes a theoretical model which is used to illustrate that transactions costs and a risk premium are not sufficient to explain the excess currency bid-ask spread. It illustrates that only in market structures that engender market power can foreign exchange dealers widen their currency bid-ask spread to exploit adverse economic forces and also exploit a relatively price inelastic demand for foreign exchange to charge higher-than-market-determined risk premiums thus charging an excess currency bid-ask spread.

We measure the performance of probabilistic models from a decision-theoretic perspective along the lines of Friedman and Sandow [6]. In particular, we adopt the point of view of an investor who evaluates models based on the test-sample averaged utility of the expected-utility-optimal strategies that the models suggest in the horse race setting. In this paper, we relax the assumptions of Friedman and Sandow [6]: we omit the notion of a "true" measure and we allow our investor to withhold or borrow cash, which widens the range of possible applications. We show that, in this setting, our relative model performance measure is odds-ratio independent if and only if the investor has a generalized logarithmic utility function, in which case it essentially reduces to the likelihood ratio. We also show that for horse races with nearly homogeneous returns, our relative performance measure is approximately equal to the likelihood ratio.

We propose a two-regime stochastic volatility extension of the LIBOR market model that preserves the positive features of the recently introduced (Joshi and Rebonato 2001) stochastic-volatility LIBOR market model (ease of calibration to caplets and swaptions, efficient pricing of complex derivatives, etc.) and overcomes most of its shortcomings. We show the improvements by analyzing empirically and theoretically the real and the model-produced change sin swaption implied volatility.

This paper uses a new restriction imposed by the no-arbitrage condition on interest rate processes to estimate the parameters of the short-term rates for US, France, UK and Germany. A general process that nests almost all previous one-factor models is estimated. The results show that the volatility structure of US short-term rate is similar to the processes suggested by Duffie and Kahn [9] or Chan et al. [4] depending on the proxy used for the short-term rate and the time period covered by the study. The volatility structures of the short-term rates in France and Germany do not have constant elasticity with respect to the short-term rate, while the elasticity of UK's short-term rate is constant and equal to 1.5.

We introduce a new Monte Carlo method for constructing the exercise boundary of an American option in a generalized Black–Scholes framework. Based on a known exercise boundary, it is shown how to price and hedge the American option by Monte Carlo simulation of suitable probabilistic representations in connection with the respective parabolic boundary value problem. The method presented is supported by numerical experiments.

S&P 500 index data sampled at one-minute intervals over the course of 11.5 years (January 1989–May 2000) is analyzed, and in particular the Hurst parameter over segments of stationarity (the time period over which the Hurst parameter is almost constant) is estimated. An asymptotically unbiased and efficient estimator using the log-scale spectrum is employed. The estimator is asymptotically Gaussian and the variance of the estimate that is obtained from a data segment of N points is of order . Wavelet analysis is tailor-made for the high frequency data set, since it has low computational complexity due to the pyramidal algorithm for computing the detail coefficients. This estimator is robust to additive non-stationarities, and here it is shown to exhibit some degree of robustness to multiplicative non-stationarities, such as seasonalities and volatility persistence, as well. This analysis suggests that the market became more efficient in the period 1997–2000.

We investigate the growth optimal strategy over a finite time horizon for a stock and bond portfolio in an analytically solvable multiplicative Markovian market model. We show that the optimal strategy consists in holding the amount of capital invested in stocks within an interval around an ideal optimal investment. The size of the holding interval is determined by the intensity of the transaction costs and the time horizon.