Minimal Entropy Martingale Measure Research Articles

Martingale Schrödinger bridges and optimal semistatic portfolios

In a two-period financial market where a stock is traded dynamically and European options at maturity are traded statically, we study the so-called martingale Schrödinger bridge \(Q_{*}\), that is, the minimal-entropy martingale measure among all models calibrated to option prices. This minimisation is shown to be in duality with an exponential utility maximisation over semistatic portfolios. Under a technical condition on the physical measure \(P\), we show that an optimal portfolio exists and provides an explicit solution for \(Q_{*}\). This result overcomes the remarkable issue of non-closedness of semistatic strategies discovered by Acciaio et al. (Finance Stoch. 21:741–751, 2017). Specifically, we exhibit a dense subset of calibrated martingale measures with particular properties to show that the portfolio in question has a well-defined and integrable option position.

Deep Hedging: Learning Risk-Neutral Implied Volatility Dynamics

We present a numerically efficient approach for machine-learning a risk-neutral measure for paths of simulated spot and option prices up to a finite horizon under convex transaction costs and convex trading constraints. This approach can then be used to implement a stochastic implied volatility model in the following two steps: 1) Train a market simulator for option prices, for example as discussed in our recent work here; 2) Find a risk-neutral density, specifically in our approach the minimal entropy martingale measure. The resulting model can be used for risk-neutral pricing, or for Deep Hedging in the case of transaction costs or trading constraints. To motivate the proposed approach, we also show that market dynamics are free from in the absence of transaction costs if and only if they follow a risk-neutral measure. We additionally provide a more general characterization in the presence of convex transaction costs and trading constraints. These results can be seen as an analogue of the fundamental theorem of asset pricing for statistical arbitrage under trading frictions and are of independent interest.

On the minimal entropy martingale measure for Lévy processes

In the present paper, a new and simple approach is provided for proving rigorously that for general Lévy financial markets the minimal entropy martingale measure and the Esscher martingale measure coincide. The method consists in approximating the probability measure by a sequence of Lévy preserving probability measures with exponential moments of all order. As a by-product, it turns out that the problem of finding the minimal entropy martingale measure for the Lévy market is equivalent to the corresponding problem but for a certain one-step financial market. The existence of the Esscher martingale measure (and hence the minimal entropy martingale measure) will be characterized by using moment generating functions of the Lévy process.

Non-extensive minimal entropy martingale measures and semi-Markov regime switching interest rate modeling

A minimal entropy martingale measure problem is studied to investigate risk-neutral densities and interest rate modelling. Hunt & Devolder focused on the method of Shannon minimal entropy martingale measure to select the best measure among all the equivalent martingale measures and, proposed a generalization of the Ho & Lee model in the semi-Markov regime-switching framework [ 1 ]. We formulate and solve the optimization problem of Hunt & Devolder for deriving risk-neutral densities using a new non-extensive entropy measure [ 2 ]. We use the Lambert function and a new type of approach to obtain results without depending on stochastic calculus techniques.

Indifference pricing with counterparty risk

Abstract We present counterparty risk by a jump in the underlying price and a structural change of the price process after the default of the counterparty. The default time is modeled by a default-density approach. Then we study an exponential utility-indifference price of an European option whose underlying asset is exposed to this counterparty risk. Utility-indifference pricing method normally consists in solving two optimization problems. However, by using the minimal entropy martingale measure, we reduce to solving just one optimal control problem. In addition, to overcome the incompleteness obstacle generated by the possible jump and the change in structure of the price process, we employ the BSDE-decomposition approach in order to decompose the problem into a global-before-default optimal control problem and an after-default one. Each problem works in its own complete framework. We demonstrate the result by numerical simulation of an European option price under the impact of jump’s size, intensity of the default, absolute risk aversion and change in the underlying volatility.

Utility indifference pricing and hedging for structured contracts in energy markets

In this paper we study the pricing and hedging of structured products in energy markets, such as swing and virtual gas storage, using the exponential utility indifference pricing approach in a general incomplete multivariate market model driven by finitely many stochastic factors. The buyer of such contracts is allowed to trade in the forward market in order to hedge the risk of his position. We fully characterize the buyer’s utility indifference price of a given product in terms of continuous viscosity solutions of suitable nonlinear PDEs. This gives a way to identify reasonable candidates for the optimal exercise strategy for the structured product as well as for the corresponding hedging strategy. Moreover, in a model with two correlated assets, one traded and one nontraded, we obtain a representation of the price as the value function of an auxiliary simpler optimization problem under a risk neutral probability, that can be viewed as a perturbation of the minimal entropy martingale measure. Finally, numerical results are provided.

On skewed, leptokurtic returns and pentanomial lattice option valuation via minimal entropy martingale measure

This article develops, a lattice-based approach for pricing contingent claims when parameters governing the logs of the underlying asset dynamics are modelled by generalized hyperbolic distribution...

Semi-Markov regime switching interest rate models under minimal entropy martingale measure

Semi-Markov regime switching interest rate models under minimal entropy martingale measure

Pricing European options with stochastic volatility under the minimal entropy martingale measure

In this paper, a closed-form pricing formula in the form of an infinite series for European call options is derived for the Heston stochastic volatility model under a chosen martingale measure. Given that markets with the stochastic volatility are incomplete, there exists a number of equivalent martingale measures and consequently investors face a problem of making a choice of appropriate measure when they price options. The one we adopt here is the so-called minimal entropy martingale measure shown to be related to the expected utility maximization theory (Frittelli 2000 Math. Finance10(1), 39–52) and the financial rationality for choosing this measure will be further illustrated in this paper. A great advantage of our newly-derived pricing formula is that the convergence of the solution in series form can be proved theoretically; such a proof of the convergence is also complemented by some numerical examples to demonstrate the speed of convergence. To further show the validity of our formula, a comparison of prices calculated through the newly derived formula is made with those obtained directly from the Monte Carlo simulation as well as those from solving the PDE (partial differential equation) with the finite difference method.

The minimal entropy martingale measure in a market of traded financial and actuarial risks

In arbitrage-free but incomplete markets, the equivalent martingale measure Q for pricing traded assets is not uniquely determined. A possible approach when it comes to choosing a particular pricing measure is to consider the one that is ‘closest’ to the physical probability measure P, where closeness is measured in terms of relative entropy.In this paper, we determine the minimal entropy martingale measure in a market where securities are traded with payoffs depending on two types of risks, which we will call financial and actuarial risks, respectively. In case only purely financial and purely actuarial securities are traded, we prove that financial and actuarial risks are independent under the physical measure if and only if these risks are independent under the entropy measure. Moreover, in such a market the entropy measure of the combined financial–actuarial world is the product measure of the entropy measures of the financial and the actuarial subworlds, respectively.

On convergence of the utility indifference pricing in the model preserving the CGMY minimal entropy martingale measure

Motivated by financial instrument for pricing and hedging and also by the field of risk management, we consider measure changes for CGMY Levy processes which stay in the CGMY class. Within this two-parametric Esscher class of measure changes, we focus on the martingale measure with minimal relative entropy, called 'model preserving minimal entropy martingale measure' (MPMEMM). We link this measure to the utility-based indifference pricing. We precisely show that for bounded payoffs, the (exponential) utility indifference price goes to the option's price evaluated under the MPMEMM as the Arrow-Pratt measure of absolute risk aversion goes to zero. We also show that the class of Esscher martingale measures preserving the CGMY character is reduced to a single measure, described in full detail. Our results are new and contribute to the theory of option pricing under Levy models.

The Minimal Entropy Martingale Measure in a Market of Traded Financial and Actuarial Risks

In arbitrage-free but incomplete markets, the equivalent martingale measure Q for pricing traded assets is not uniquely determined. A possible approach when it comes to choosing a particular pricing measure is to consider the one that is 'closest' to the physical probability measure P, where closeness is measured in terms of relative entropy.In this paper, we determine the minimal entropy martingale measure in a market where securities are traded with payoffs depending on two types of risks, which we will call financial and actuarial risks, respectively. In case only purely financial and purely actuarial securities are traded, we prove that financial and actuarial risks are independent under the physical measure if and only if these risks are independent under the entropy measure. Moreover, in such a market the entropy measure of the combined financial-actuarial world is the product measure of the entropy measures of the financial and the actuarial subworlds, respectively.

On two-parametric Esscher transform for geometric CGMY Lévy processes

We present a new transformation measure depending on two parameters, called two-parametric Esscher transform, for CGMY processes. This transform defines a class of equivalent martingale measures for CGMY processes, preserving the CGMY character. We follow a decomposition approach by writing any CGMY process as sum of two independent CGMY ones. Next, following our approach, we focus on the relative entropy with respect to the initial probability and we provide optimal parameters, by minimising the relative entropy, which defines an equivalent martingale measure called ‘model preserving minimal entropy martingale measure’. This measure has the advantage of preserving the CGMY character of any CGMY process. As application, we finally show that Asian option’s price function, in a CGMY market model, is a solution of a time-dependent partial-integro differential equation.

A pricing defaultable claim model based on exponential utility indifference value process in an incomplete market

We study the dynamics of exponential utility indifference value process C t ( B , α ) for a defaultable claim in an incomplete market. Other than most of papers dealing with defautable claim, we do not assume the hypothesis of invariance of martingale that is H hypothesis. We firstly transform the default sensitive assets S to be a local martingale through progressively enlargement of filtration and changes of measure. Then, we introduce a specific backward stochastic differential equation (BSDE) and prove the existence and uniqueness of the solution. Finally, we prove the exponential utility indifference value process C t ( B , α ) is the solution to the BSDE based on the fact that C t ( B , α ) is a supermartingale for investment strategies and a martingale for optimal strategy under the minimal entropy martingale measure.

On the Minimal Entropy Martingale Measure and Multinomial Lattices with Cumulants

In this article, we describe with relevant examples based on empirical data how to use the minimal entropy martingale measure (MEMM) to price European and American Options in multinomial lattices which take into account cumulants information. For trinomial lattices, we show that minimal entropy prices are close to results obtained using the Black and Scholes option pricing formula. For pentanomial lattices, minimal entropy prices are close to results obtained under the mean-correcting martingale measure using the discrete Fourier transform. The MEMM is very easy to compute and is therefore a good candidate for option pricing in multinomial lattices.

A fuzzy approach to option pricing in a Levy process setting

Abstract In this paper the problem of European option valuation in a Levy process setting is analysed. In our model the underlying asset follows a geometric Levy process. The jump part of the log-price process, which is a linear combination of Poisson processes, describes upward and downward jumps in price. The proposed pricing method is based on stochastic analysis and the theory of fuzzy sets.We assume that some parameters of the financial instrument cannot be precisely described and therefore they are introduced to the model as fuzzy numbers. Application of fuzzy arithmetic enables us to consider various sources of uncertainty, not only the stochastic one. To obtain the European call option pricing formula we use the minimal entropy martingale measure and Levy characteristics.

Option pricing with discrete time jump processes

In this paper we propose new option pricing models based on class of models with jumps contained in the Lévy-type based models (NIG-Lévy, Schoutens, 2003, Merton-jump, Merton, 1976 and Duan based model, Duan et al., 2007). By combining these different classes of models with several volatility dynamics of the GARCH type, we aim at taking into account the dynamics of financial returns in a realistic way. The associated risk neutral dynamics of the time series models is obtained through two different specifications for the pricing kernel: we provide a characterization of the change in the probability measure using the Esscher transform and the Minimal Entropy Martingale Measure. We finally assess empirically the performance of this modelling approach, using a dataset of European options based on the S&P 500 and on the CAC 40 indices. Our results show that models involving jumps and a time varying volatility provide realistic pricing and hedging results for options with different kinds of time to maturities and moneyness. These results are supportive of the idea that a realistic time series model can provide realistic option prices making the approach developed here interesting to price options when option markets are illiquid or when such markets simply do not exist.

The Minimal Entropy Martingale Measure for Exponential Markov Chains

In this article we investigate the minimal entropy martingale measure for continuous-time Markov chains. The conditions for absence of arbitrage and existence of the minimal entropy martingale measure are discussed. Under this measure, expressions for the transition intensities are obtained. Differential equations for the arbitrage-free price are derived.

The Minimal Entropy Martingale Measure for Exponential Markov Chains

In this article we investigate the minimal entropy martingale measure for continuous-time Markov chains. The conditions for absence of arbitrage and existence of the minimal entropy martingale measure are discussed. Under this measure, expressions for the transition intensities are obtained. Differential equations for the arbitrage-free price are derived.

A note on convergence of option prices and their Greeks for Lévy models

We study the robustness of option prices to model variation after a change of measure where the measure depends on the model choice. We consider geometric Lévy models in which the infinite activity of the small jumps is approximated by a scaled Brownian motion. For the Esscher transform, the minimal entropy martingale measure, the minimal martingale measure and the mean variance martingale measure, we show that the option prices and their corresponding deltas converge as the scaling of the Brownian motion part tends to zero. We give some examples illustrating our results.