Oliver J. Blaskowitz

Skewness and Kurtosis Trades

In this paper we investigate the profitability of ?skewness trades? and ?kurtosis trades? based on comparisons of implied state price densities versus historical densities. In particular, we examine the ability of SPD comparisons to detect structural breaks in the options market behaviour. While the implied state price density is estimated by means of the Barle and Cakici Implied Binomial Tree algorithm using a cross section of DAX option prices, the historical density is inferred by a combination of a non?parametric estimation from a historical time series of the DAX index and a forward Monte Carlo simulation.

Testing directional forecast value in the presence of serial correlation

Common approaches to test for the economic value of directional forecasts are based on the classical Chi-square test for independence, Fisher’s exact test or the Pesaran and Timmerman (1992) test for market timing. These tests are asymptotically valid for serially independent observations. Yet, in the presence of serial correlation they are markedly oversized as confirmed in a simulation study. We summarize serial correlation robust test procedures and propose a bootstrap approach. By means of a Monte Carlo study we illustrate the relative merits of the latter. Two empirical applications demonstrate the relevance to account for serial correlation in economic time series when testing for the value of directional forecasts.

A note on the model selection risk for ANOVA based adaptive forecasting of the EURIBOR swap term structure

The paper proposes a data driven adaptive model selection strategy. The selection crite- rion measures economic ex–ante forecasting content by means of trading implied cash flows. Empirical evidence suggests that the proposed strategy is neither exposed to selection bias nor to the risk of choosing excessively poor models from a parameterized class of candidate specifications.

Long Memory Effects Trading Strategy

Long range dependence is widespread in nature and has been extensively documented in economics and finance, as well as in hydrology, meteorology, and geophysics by authors such as Heyman, Tabatabai and Lakshman (1991), Hurst (1951), Jones and Briffa (1992), Leland, Taqqu, Willinger and Wilson (1993) and Peters (1994). It has a long history in economics and finance, and has remained a topic of active research in the study of financial time series, Beran (1994).

Trading on Deviations of Implied and Historical Densities

In recent years a number of methods have been developed to infer implied state price densities (SPD) from cross sectional option prices, Chapter 7 and 8. Instead of comparing this density to a historical density extracted from the observed time series of the underlying asset prices, i.e. a risk neutral density to an actual density, Ait-Sahalia, Wang and Yared (2000) propose to compare two risk neutral densities, one obtained from cross sectional S&P 500 option data and the other from the S&P 500 index time series. Furthermore, they propose trading strategies designed to exploit differences in skewness and kurtosis of both densities. The goal of this article is to apply the procedure to the german DAX index. While the option implied SPD is estimated by means of the Barle and Cakici, Barle and Cakici (1998), implied binomial tree version, the time series density is inferred from the time series of the DAX index by applying a method used by Ait-Sahalia, Wang and Yared (2000). Based on the comparison of both SPDs the performance of skewness and kurtosis trades is investigated.