Rational expectations models: An approach using forward–backward stochastic differential equations

We show that a general class of continuous time rational expectations models can be reformulated as forward–backward stochastic differential equations (FBSDEs). Using this connection we obtain results on the conditions under which paths leading to, or keeping close to equilibrium exist, as well as their qualitative properties. We also provide a method for the construction of such paths through the connection of FBSDEs with quasilinear partial differential equations (PDEs). The theory is applied to specific macroeconomic models.     

Exchange rate bifurcation in a stochastic evolutionary finance model

This paper analyzes the stability and fluctuations of the exchange rate with a speculative bubble using the methods of evolutionary finance and stochastic differential equations. It constructs a hybrid stochastic system for the financial market involving a discrete time process and a continuous time process. The discrete process models the bubble and is meant to capture the behavior of less sophisticated investors who trade infrequently. The continuous time process is a stochastic differential equation for monetary policy together with a backward stochastic equation for the exchange rate. Monetary policy is affected by the bubble and in turn affects the exchange rate as well as speculation. The bubble and exchange rate exhibit a form of bifurcation. This means the bubble and exchange rate experience fluctuations as the propensity to chase trends or switch predictors changes.     

An existence theorem of intertemporal recursive utility in the presence of Lévy jumps

This paper presents an existence theorem for a class of backward stochastic integral equations. The main contribution is a generalization of Duffie and Epstein's [Duffie, D., Epstein, L., 1992. Stochastic differential utility, (Appendix C with Skiadas C.), Econometrica 60, 353–394.] existence theorem of intertemporal recursive utility to allow the information structure to be driven by a Lévy jump process. The existence theorem applies also for a more general class of utility functions, such as recursive utility with habit-formation, and can be used to prove the existence of an equilibrium asset price process as a unique solution to the stochastic Euler equation derived by Ma [Ma, C., 1993b. Valuation of Derivative Securities with Mixed Poisson–Brownian Information and Recursive Utility, McGill University, mimeo.].     

一族非李普希兹系数的随机微分方程

在非李普希兹条件下,对带跳随机微分方程数值方法的研究微乎其微。在非李普希兹系数下,对带跳随机微分方程数值方法进行了研究,并且得出近似解关于时间和开始点在Lp空间上一致收敛到解析解。     

Numerical solution of dynamic equilibrium models under Poisson uncertainty

We propose a simple and powerful numerical algorithm to compute the transition process in continuous-time dynamic equilibrium models with rare events. In this paper we transform the dynamic system of stochastic differential equations into a system of functional differential equations of the retarded type. We apply the Waveform Relaxation algorithm, i.e., we provide a guess of the policy function and solve the resulting system of (deterministic) ordinary differential equations by standard techniques. For parametric restrictions, analytical solutions to the stochastic growth model and a novel solution to Lucas' endogenous growth model under Poisson uncertainty are used to compute the exact numerical error. We show how (potential) catastrophic events such as rare natural disasters substantially affect the economic decisions of households.     

Consumption optimization for recursive utility in a jump-diffusion model

In this paper, we consider a market model with prices and consumption following a jump-diffusion dynamics. In this setting, we first characterize the optimal consumption plan for an investor with recursive stochastic differential utility on the basis of his/her own beliefs, then we solve the inverse problem to find what beliefs make a given consumption plan optimal. The problem is viewed in general for a class of homogeneous recursive utility, and later we choose a logarithmic model for the utility aggregator as an explicitly computable example. When beliefs, represented via Girsanov’s theorem, get incorporated into the model, the change of measure gives rise, up to a transformation, to a backward stochastic differential equation whose generator exhibits a quadratic behavior in the Brownian component and a locally Lipschitz one in the jump component, which is solvable on the basis of some recent results.     

Dynamic Modeling with Structural Equations and Stochastic Differential Equations: Applications with the German Socio-economic Panel

The paper discusses an application of linear dynamic models to multi-wave longitudinal data. Starting from three-wave and four-wave simplex models using standard structural equations, linear dynamic state space models with stochastic differential equations are presented. The main differences between longitudinal structural equations (static view) and stochastic differential equations (dynamic view) are emphasized. Substantively, the models prove the relation, stability and change of two concepts in a period of 10 years: National Identity and Intention to stay in Germany. Data from a sample of migrant workers in Germany included in the German Socio-economic Panel (GSOEP) are used for the analyses. Results and further developments of dynamic models are discussed in the final section.The authors thank Hermann Singer for his comments and discussions on applications of dynamic models.     

Utility indifference valuation for jump risky assets

We discuss utility maximization problems with exponential preferences in an incomplete market where the risky asset dynamics is described by a pure jump process driven by two independent Poisson processes. This includes results on portfolio optimization under an additional European claim. Value processes of the optimal investment problems, optimal hedging strategies and the indifference price are represented in terms of solutions to backward stochastic equations driven by the Poisson martingales. Via a duality result, the solution to the dual problems is derived. In particular, an explicit expression for the density of the minimal martingale measure is provided. The Markovian case is also discussed. This includes either asset dynamics dependent on a pure jump stochastic factor or claims written on a correlated non tradable asset.     

Option hedging theory under transaction costs

The problem of option hedging in the presence of proportional transaction costs can be formulated as a singular stochastic control problem. Hodges and Neuberger [1989. Optimal replication of contingent claims under transactions costs. Review of Futures Markets 8, 222–239] introduced an approach that is based on maximization of the expected utility of terminal wealth. We develop a new algorithm to solve the corresponding singular stochastic control problem and introduce a new approach to option hedging which is closer in spirit to the pathwise replication of Black and Scholes [1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637–654]. This new approach is based on minimization of a Black–Scholes-type measure of pathwise risk, defined in terms of a market delta, subject to an upper bound on the hedging cost. We provide an efficient backward induction algorithm for the problem of cost-constrained risk minimization, whose associated singular stochastic control problem is shown to be equivalent to an optimal stopping problem. This algorithm is then modified to solve the singular stochastic control problem associated with utility maximization, which cannot be reduced to an optimal stopping problem. We propose to choose an optimal parameter (risk-aversion coefficient or Lagrange multiplier) in either approach by minimizing the mean squared hedging error and demonstrate that with this “best” choice of the parameter, both approaches have similar performance. We also discuss the different notions of risk in both approaches and propose a volatility adjustment for the risk-minimization approach, which is analogous to that introduced by Zakamouline [2006. European option pricing and hedging with both fixed and proportional transaction costs. Journal of Economic Dynamics and Control 30, 1–25] for the utility maximization approach, thereby providing a unified treatment of both approaches.     

Superhedging under ratio constraint

We consider superhedging of contingent claims under ratio constraint. It has been widely recognized that the minimum cost of superhedging a contingent claim with certain portfolio constraints is equal to the price of a claim with appropriately modified payoff but without constraints. In terms of the backward stochastic differential equation (BSDE) and the variational inequality equation approach, we revisit this result and provide two counterexamples.     

Markovian lifts of positive semidefinite affine Volterra-type processes

We consider stochastic partial differential equations appearing as Markovian lifts of matrix-valued (affine) Volterra-type processes from the point of view of the generalized Feller property (see, e.g., Dörsek and Teichmann in A semigroup point of view on splitting schemes for stochastic (partial) differential equations, 2010. arXiv:1011.2651). We introduce in particular Volterra Wishart processes with fractional kernels and values in the cone of positive semidefinite matrices. They are constructed from matrix products of infinite dimensional Ornstein–Uhlenbeck processes whose state space is the set of matrix-valued measures. Parallel to that we also consider positive definite Volterra pure jump processes, giving rise to multivariate Hawkes-type processes. We apply these affine covariance processes for multivariate (rough) volatility modeling and introduce a (rough) multivariate Volterra Heston-type model.

     

Stochastic differential equation modeling the prevalence of rare chronic diseases with an application to systemic lupus erythematosus

In this article we describe a system of stochastic differential equations to model the age‐specific prevalence of rare chronic diseases from incidence and mortality rates. As an application, the age profile of the prevalence of systemic lupus erythematosus in England and Wales in1995 is calculated. The results are in good agreement with the observed epidemiological measures.     

Stochastic models of resonating markets

This paper describes a way to model a seasonally and irregularly peaking price dynamics, as that originated in commodity and energy markets, using a system of coupled nonlinear stochastic differential equations. The specific case of an electric power market is used to show which microeconomic features this approach is able to model. Critical point analysis is used in a simple way to show how the interaction between dynamic criticality and stochasticity can be used to develop further models, useful to explore more deeply other types of peaking price dynamics.     

Joint dynamic modeling and option pricing in incomplete derivative-security market

In this study, we evaluate the option prices on two assets under stochastic interest rates when the stochastic process that underlying asset prices follow is depending on a correlated bivariate Markov-modulated geometric Brownian motion model with jump risks. More specifically, we conduct the joint dynamic modeling by identifying two independent compound Poisson processes with the log-normal jump sizes to describe both individual jumps and systematic cojumps. Facilitating the cojumping behavior this way with the time-inhomogeneity of the volatility, option pricing expressions are readily obtainable since the Gerber–Siu’s approach is employed to determine a pricing kernel. The empirical results and numerical illustrations are provided to show the impact of cojumps and stochastic volatilities on option prices.     

Pricing vulnerable options with stochastic liquidity risk

In this paper, we consider vulnerable options with stochastic liquidity risk. We employ liquidity-adjusted pricing models to describe the underlying stock price and option issuer’s assets. In addition, the correlation between these assets is stochastic, depending on the market liquidity measures. In the proposed framework, we derive closed forms of vulnerable European options with stochastic liquidity risk and then use them to illustrate the effects of stochastic liquidity risk on vulnerable option prices. Numerical results show that the effects of liquidity risk on the prices of out-of-the-money options or the options with a short maturity are not negligible.     

Do interest rate options contain information about excess returns?

There is strong empirical evidence that long-term interest rates contain a time-varying risk premium. Options may contain valuable information about this risk premium because their prices are sensitive to the underlying interest rates. We use the joint time series of swap rates and interest rate option prices to estimate dynamic term structure models. The risk premiums that we estimate using option prices are better able to predict excess returns for long-term swaps over short-term swaps. Moreover, in contrast to the previous literature, the most successful models for predicting excess returns have risk factors with stochastic volatility. We also show that the stochastic volatility models we estimate using option prices match the failure of the expectations hypothesis.     

International Evidence on the Stability of the Optimizing IS Equation*

We provide international evidence on the issue of whether the optimizing IS equation is more stable than a backward‐looking alternative. This evidence consists of estimates of IS equations on quarterly data for the UK and Australia, both for the full sample of the last 40 years and for the period following major monetary policy shifts in 1979–80. Results suggest the parameters in the optimizing IS equations are more empirically stable than those of the backward‐looking alternative. The use of dynamic general equilibrium modelling in empirical work does deliver material benefits, in the form of equations more suitable for policy analysis.     

Model-free stochastic collocation for an arbitrage-free implied volatility: Part I

This paper explains how to calibrate a stochastic collocation polynomial against market option prices directly. The method is first applied to the interpolation of short-maturity equity option prices in a fully arbitrage-free manner and then to the joint calibration of the constant maturity swap convexity adjustments with the interest rate swaptions smile. To conclude, we explore some limitations of the stochastic collocation technique.

     

A simple approach to the parametric estimation of potentially nonstationary diffusions

A simple and robust approach is proposed for the parametric estimation of scalar homogeneous stochastic differential equations. We specify a parametric class of diffusions and estimate the parameters of interest by minimizing criteria based on the integrated squared difference between kernel estimates of the drift and diffusion functions and their parametric counterparts. The procedure does not require simulations or approximations to the true transition density and has the simplicity of standard nonlinear least-squares methods in discrete time. A complete asymptotic theory for the parametric estimates is developed. The limit theory relies on infill and long span asymptotics and is robust to deviations from stationarity, requiring only recurrence.     

PDE solutions of stochastic differential utility

This paper presents conditions for the existence and properties of stochastic differential utility as a solution of a partial differential equation. Stochastic differential utility is an extension of the classical additively-separable utility model that is designed as a platform for new financial asset pricing results. The extension is important, for example, when investors display preference for early or late resolution of uncertainty. The existence conditions admit Kreps-Porteus stochastic differential utility.