Back to basics: historical option pricing revisited

We reconsider the problem of option pricing using historical probability distributions. We first discuss how the risk-minimisation scheme proposed recently is an adequate starting point under the realistic assumption that price increments are uncorrelated (but not necessarily independent) and of arbitrary probability density. We discuss in particular how, in the Gaussian limit, the Black-Scholes results are recovered, including the fact that the average return of the underlying stock disappears from the price (and the hedging strategy). We compare this theory to real option prices and find these reflect in a surprisingly accurate way the subtle statistical features of the underlying asset fluctuations.Comment: 14 pages, 2 .ps figures. Proceedings, to appear in Proc. Roy. So

Hedged Monte-Carlo: low variance derivative pricing with objective probabilities

We propose a new `hedged' Monte-Carlo (HMC) method to price financial derivatives, which allows to determine simultaneously the optimal hedge. The inclusion of the optimal hedging strategy allows one to reduce the financial risk associated with option trading, and for the very same reason reduces considerably the variance of our HMC scheme as compared to previous methods. The explicit accounting of the hedging cost naturally converts the objective probability into the `risk-neutral' one. This allows a consistent use of purely historical time series to price derivatives and obtain their residual risk. The method can be used to price a large class of exotic options, including those with path dependent and early exercise features.Comment: LaTeX, 10 pp, 3 eps figures (in text

Closure Theorem for Sequential-Design Processes

This chapter focuses on stochastic control and decision processes that occur in a variety of theoretical and applied contexts, such as statistical decision problems, stochastic dynamic programming problems, gambling processes, optimal stopping problems, stochastic adaptive control processes, and so on. It has long been recognized that these are all mathematically closely related. That being the case, all of these decision processes can be viewed as variations on a single theoretical formulation. The chapter presents some general conditions under which optimal policies are guaranteed to exist. The given theoretical formulation is flexible enough to include most variants of the types of processes. In statistical problems, the distribution of the observed variables depends on the true value of the parameter. The parameter space has no topological or other structure here; it is merely a set indexing the possible distributions. Hence, the formulation is not restricted to those problems known in the statistical literature as parametric problems. In nonstatistical contexts, the distribution does not depend on an unknown parameter. All such problems may be included in the formulation by the device of choosing the parameter space to consist of only one point, corresponding to the given distribution

Elements for a Theory of Financial Risks

Estimating and controlling large risks has become one of the main concern of financial institutions. This requires the development of adequate statistical models and theoretical tools (which go beyond the traditionnal theories based on Gaussian statistics), and their practical implementation. Here we describe three interrelated aspects of this program: we first give a brief survey of the peculiar statistical properties of the empirical price fluctuations. We then review how an option pricing theory consistent with these statistical features can be constructed, and compared with real market prices for options. We finally argue that a true `microscopic' theory of price fluctuations (rather than a statistical model) would be most valuable for risk assessment. A simple Langevin-like equation is proposed, as a possible step in this direction.Comment: 22 pages, to appear in `Order, Chance and Risk', Les Houches (March 1998), to be published by Springer/EDP Science

Growth Optimal Investment and Pricing of Derivatives

We introduce a criterion how to price derivatives in incomplete markets, based on the theory of growth optimal strategy in repeated multiplicative games. We present reasons why these growth-optimal strategies should be particularly relevant to the problem of pricing derivatives. We compare our result with other alternative pricing procedures in the literature, and discuss the limits of validity of the lognormal approximation. We also generalize the pricing method to a market with correlated stocks. The expected estimation error of the optimal investment fraction is derived in a closed form, and its validity is checked with a small-scale empirical test.Comment: 21 pages, 5 figure

Hedging by sequential regressions revisited

Almost 20 years ago Föllmer and Schweizer (1989) suggested a simple and influential scheme for the computation of hedging strategies in an incomplete market. Their approach of local risk minimization results in a sequence of one-period least squares regressions running recursively backwards in time. In the meantime there have been significant developments in the global risk minimization theory for semimartingale price processes. In this paper we revisit hedging by sequential regression in the context of global risk minimization, in the light of recent results obtained by Černý and Kallsen (2007). A number of illustrative numerical examples is given

Ein warhafftige Historien von Zweyen Mewssen (1543)

Die "Warhafftige Historien" (1543) des Protestanten Burkard Waldis reiht sich in das konfessionspolemische Schrifttum des 16. Jahrhunderts ein. Berichtet wird von dem angeblichen Skandal, dass zwei Mäuse durch katholische Geistliche verbrannt worden seien, weil sie die Hostien in einem Kirchentabernakel aufgefressen hätten. Diese online-Edition bietet eine kritische Textausgabe, eine ausführliche Einleitung sowie einen gründlichen Wort- und Sachkommentar