International Journal of Theoretical and Applied Finance

Asian and European financial markets impose daily price fluctuation limits on individual securities. In the US several futures exchanges are regulated by price fluctuation limits as well. The price limits in most exchanges are set daily, and they are usually based on a percentage change from the previous day's closing price. We show that the future cash flows of a security subject to price limit regulation resemble that of a distinctive contingent claim. Assuming that the security price follows a lognormal distribution, we use the risk-neutral valuation relation (RNVR) developed by [4] to derive the security valuation, in the presence of price fluctuation limits. The characteristics of the pricing formula are examined analytically and numerically.

We introduce the intensity-based defaultable Lévy Libor model, which generalizes the default-free Lévy Libor model introduced by Eberlein and Özkan in [The defaultable Lévy term structure: Ratings and restructuring, Mathematical Finance13(2) (2003) 277–300], and the intensity-based defaultable model presented by Bielecki and Rutkowski in [Credit Risk: Modeling, Valuation and Hedging, Springer Finance (Springer-Verlag, 2002)] by embedding it in the defaultable HJM framework introduced by Eberlein and Özkan in [The defaultable Lévy term structure: Ratings and restructuring, Mathematical Finance13(2) (2003) 277–300]. We also derive some additional results for defaultable HJM models such as the dynamics of credit spreads. We then go on and model the default-free Libor rates and credit spreads as the primal variable and derive the dynamics of the defaultable Libor rates under the defaultable forward measure. Finally, we derive an explicit formula for options on credit default swaps, using an idea introduced by Raible in [Lévy Processes in finance: Theory, numerics and empirical facts, PhD thesis, University of Freiburg i. Brsg. (2000)].

Geweke studied the measure of linear dependence and spectral feedback for grouped multivariate time series. This paper applies the measure of linear dependence and spectral feedback to examining the relationship between grouped variables of economy and stock market indices. Putting economic variables into one group and stock market variables into another, we examine the between-group relationship within the US, within Japan, and within the European Union. Using a self-developed computing program, the feedback spectra for grouped variables are calculated and displayed. Although risk might exist in that the significance levels for test may not be reliable because the feedback spectra are measured on possibly nonstationary variables in level, the patterns of the feedback spectra still provide information about the cyclical effect between the variable groups.

This paper is devoted to the application of the Independent Component Analysis (ICA) methodology to the problem of selecting portfolio strategies, so as to provide against extremal movements in financial markets. A specific ICA model for describing the extreme fluctuations of asset prices is introduced, stipulating that the distributions of the ICs are heavy tailed (i.e., with power law behavior at infinity). An inference method based on conditional maximum likelihood estimation is proposed for our model, which permits to determine practically optimal investment strategies with respect to extreme risk. Empirical studies based on this modeling are carried out to illustrate our approach.

We propose, in this paper, a new valuation method for contingent claims, which approximates to the exponential utility indifference valuation. In particular, we treat both ask and bid valuations. In the definition of the exponential utility indifference valuation, we require strong integrability for the underlying contingent claim. The new valuation in this paper succeeds in reducing it by using a kind of power functions instead of the exponential function. Furthermore, we shall investigate some basic properties and an asymptotic behavior of the new valuation.

The purpose of this paper is to introduce an approximation of the kernel-based log-optimal investment strategy that guarantees an almost optimal rate of growth of the capital under minimal assumptions on the behavior of the market. The new strategy uses much less knowledge on the distribution of the market process. It is analyzed both theoretically and empirically. The theoretical results show that the asymptotic rate of growth well approximates the optimal one that one could achieve with a full knowledge of the statistical properties of the underlying process generating the market, under the only assumption that the market is stationary and ergodic. The empirical results show that the proposed semi-log-optimal and the log-optimal strategies have essentially the same performance measured on past NYSE data.

In this paper we focus on the performance of volatility options as hedging instruments for hedging volatility risk. We investigate (a) the relative hedging performance of volatility and European options, (b) the relative hedging performance of volatility index and straddle options, and (c) the impact of model misspecification on hedging effectiveness. Our focus is on exotic options as the options to be hedged, because they are more sensitive to volatility risk and model risk and practically more relevant when the effectiveness of different hedging strategies is examined. Using a Monte Carlo simulation, we find that volatility options are especially useful for hedging options with a severe exotic feature and there is no significant difference between the performances of volatility index and straddle options. Furthermore, our results indicate that model misspecification has an important impact on the hedging performance.

We consider a model of the economy that splits investors into two groups. One group (the reference traders) trades an underlying asset according to the difference in realized returns between that asset and some evolving consensus estimate of those returns; the other group (hedgers) hedge options, namely straddles, on the underlying asset. We consider the cases when hedgers are long the straddle and when the hedgers are short the straddle. We numerically simulate the terminal distribution of the underlying asset price and find that hedgers that are long the straddle tend to push the underlying toward the strike, while hedgers that are short the straddle cause the underlying security to have a bimodal terminal probability distribution with a local minimum at the strike.

The innovative information-based framework for credit risk modeling, proposed recently by Brody, Hughston, and Macrina, is extended to a more general and practically important setup of random interest rates. We first introduce the market model, and we derive an explicit expression for defaultable bond price. Next, the dynamics of the information process and dynamics of defaultable bond are found for both deterministic and random interest rates. Finally, the valuation and hedging of derivative securities are briefly examined. In particular, the valuation formula for a European option on a defaultable bond is established.