In a previous paper we introduced a new variance-reduction technique for regenerative simulations based on permuting regeneration cycles. In this paper we apply this idea to large classes of other estimators. In particular, we derive permuted versions of likelihood-ratio derivative estimators for steady-state performance measures, importance-sampling estima-tors of the mean cumulative reward un...

We develop strategies for integrated use of certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment. The building blocks for these integrated variance reduction strategies are the techniques of conditional expectation, correlation induction (including antithetic variates and Latin hypercube sampling), and control variates; and all p...

This paper proposes and estimates a more general parametric stochastic variance model of equity index returns than has been previously considered using data from both underlying and options markets. I conclude that the square root stochastic variance model of Heston (Rev. Financial Stud. 6 (1993) 327) is incapable of generating realistic returns behavior, and that the data are better represente...

High-performance oscillators, atomic clocks for instance, are important in modern industries, finance and scientific research. In this paper, the authors study the estimation and prediction of long-term stability based on convex optimization techniques and compressive sensing. To take frequency drift into account, its influence on Allan and modified Allan variances is formulated. Meanwhile, exp...

This paper provides a method for pricing options in the constant elasticity of variance (CEV) model environment using the Lie-algebraic technique when the model parameters are time-dependent. Analytical solutions for the option values incorporating time-dependent model parameters are obtained in various CEV processes with different elasticity factors. The numerical results indicate that option ...

We consider pricing of various types of exotic discrete variance swaps, like the gamma swaps and corridor swaps, under the 3/2-stochastic volatility models with jumps. The class of stochastic volatility models (SVM) that use a constant-elasticity-of-variance (CEV) process for the instantaneous variance exhibit nice analytical tractability when the CEV parameter takes just a few special values (...

A generalised minimum variance controller is developed for linear time-varying systems. The plants to be controlled are described using a controlled autoregressive moving average model and are exponentially stable. Both, the plant parameters and the noise variance are time-varying. The generalised minimum variance cost functional is the sum of a tracking error variance between a filtered plant ...

The purpose of this paper is to introduce a bivariate Lévy process constructed by subordination of a Brownian motion with independent components by a bivariate subordinator. A class of subordinated processes extensively studied in finance is the Variance Gamma one. They have been first introduced in literature by Madan and Seneta [5], [2], as models for stocks return. Let B̃ be a Brownian motion...

We analyse the all-pay auction with incomplete information and variance-averse bidders. We characterise the symmetric equilibrium for general distributions of valuations and any number of bidders. Variance aversion is a sufficient assumption to predict that high-valuation bidders increase their bids relative to the risk-neutral case while low types decrease their bid. Considering an asymmetric ...

In wireless communications, the relative strength of the direct and scattered components of the received signal, as expressed by the Ricean factor, provides an indication of link quality. Accordingly, efficient and accurate methods for estimating are of considerable interest. In this paper, we propose a general class of moment-based estimators which use the signal envelope. This class of estima...