Option Pricing in Incomplete Markets


Book Description

This volume offers the reader practical methods to compute the option prices in the incomplete asset markets. The [GLP & MEMM] pricing models are clearly introduced, and the properties of these models are discussed in great detail. It is shown that the geometric L(r)vy process (GLP) is a typical example of the incomplete market, and that the MEMM (minimal entropy martingale measure) is an extremely powerful pricing measure. This volume also presents the calibration procedure of the [GLP \& MEMM] model that has been widely used in the application of practical problem




Closed-Form Solutions for Options in Incomplete Markets


Book Description

This paper reconsiders the predictions of the standard option pricing models in the context of incomplete markets. We relax the completeness assumption of the Black-Scholes (1973) model and as an immediate consequence we can no longer construct a replicating portfolio to price the option. Instead, we use the good-deal bounds technique to arrive at closed-form solutions for the option price. We determine an upper and a lower bound for this price and find that, contrary to Black-Scholes (1973) options theory, increasing the volatility of the underlying asset does not necessarily increase the option value. In fact, the lower bound prices are always a decreasing function of the volatility of the underlying asset, which cannot be explained by a Black-Scholes (1973) type of argument. In contrast, this is consistent with the presence of unhedgeable risk in the incomplete market. Furthermore, in an incomplete market where the underlying asset of an option is either infrequently traded or non-traded, early exercise of an American call option becomes possible at the lower bound, because the economic agent wants to lock in value before it disappears as a result of increased unhedgeable risk.




Option Pricing and Hedging Bounds in Incomplete Markets


Book Description

This paper has reviewed the literature on options pricing in incomplete markets. A tight upper and lower bounds can be derived based on the assumptions of mean and variance of the underlying asset price, not on its entire distribution. The differences between estimated upper or lower bounds and Black-Scholes price are quite small for deep in-the-money options, but can be very significant for deep out-of-the-money options. But at the same time, despite the wide pricing bounds, analysis of the implied hedging bounds suggests that the implications for asset allocation of incomplete markets are fairly limited.




On the Pricing of Options in Incomplete Markets


Book Description

In this paper we reconsider the pricing of options in incomplete continuous time markets. We first discuss option pricing with idiosyncratic stochastic volatility. This leads, of course, to an averaged Black-Scholes price formula. Our proof of this result uses a new formalization of idiosyncrasy which encapsulates other definitions in the literature. Our method of proof is subsequently generalized to other forms of incompleteness and systematic (i.e. non-idiosyncratic) information. Generally this leads to an option pricing formula which can be expressed as the average of a complete markets formula.







Options Pricing in Incomplete Markets: An Asymptotic Approach


Book Description

It is explored how incomplete markets can be studied with the help of asymptotics. A compound Poisson model for the stock price is assumed and an expansion for the price of a European option is obtained as the stock price process converges to a geometric Brownian motion. This formulation also permits one to confront statistical uncertainty in the volatility of the stock price, and we show how this uncertainty impacts on the value of the option.




Option-Pricing in Incomplete Markets


Book Description

Consider a non-spanned security C_T in an incomplete market. We study the risk/return trade-offs generated if this security is sold for an arbitrage-free price 'c0' and then hedged. We consider recursive one-period optimal self-financing hedging strategies, a simple but tractable criterion. For continuous trading, diffusion processes, the one-period minimum variance portfolio is optimal. Let C_0(0) be its price. Self-financing implies that the residual risk is equal to the sum of the one-period orthogonal hedging errors, sum Y_t(0) . To compensate the residual risk, a risk premium y_t ?t is associated with every Y_t. Now let C_0(y) be the price of the hedging portfolio, and sum (Y_t(y) + y_t ?t) is the total residual risk. Although not the same, the one-period hedging errors Y_t (0) and Y_t (y) are orthogonal to the trading assets, and are perfectly correlated. This implies that the spanned option payoff does not depend on y. Let c0=C_0(y). A main result follows. Any arbitrage-free price, c0, is just the price of a hedging portfolio (such as in a complete market), C_0(0), plus a premium, c0-C_0(0). That is, C_0(0) is the price of the option's payoff which can be spanned, and c0-C_0(0) is the premium associated with the option's payoff which cannot be spanned (and yields a contingent risk premium of sum y_t ?t at maturity). We study other applications of option-pricing theory as well.







Option Pricing in Discrete-Time Incomplete Market Models


Book Description

Various aspects of pricing of contingent claims in discrete time for incomplete market models are studied. Formulas for prices with proportional transaction costs are obtained. Some results concerning pricing with concave transaction costs are shown. Pricing by the expected utility of terminal wealth isalso considered.