Recent years have witnessed the rise of queue-scalping in congestion-prone service systems. A queue-scalper has no material interest in the primary service but proactively enters the queue in hopes of selling his spot later. This paper develops a queueing-game-theoretic model of queue-scalping...

We study a multi-period dynamic pricing problem with contextual information where the seller uses a misspecified demand model. The seller sequentially observes past demand, updates model parameters, and then chooses the price for the next period based on time-varying features. We show that model...

In this paper, we introduce our GDSGE framework and MATLAB toolbox for solving dynamic stochastic general equilibrium models with a novel global solution method. The framework encompasses many well-known incomplete markets models with highly nonlinear dynamics such as models on financial crises,...

The optimal growth of a wealth process toward a goal is studied under ambiguous markets with first- and second-order moment uncertainties relating to stock returns. Optimal strategies and value functions are solved explicitly. A verification theorem is proved to show that the results solve the...

In this research work we apply the Homotopy Perturbation Method (HPM) to solve the Three-dimensional mathematical model of Novel Coronavirus differential equation, which is applied to investigate the transmittal dynamics Novel Coronavirus infection in public. We have got the solution which has...

This article presents EVM (Expectation-Variance-Maximization) — an alternative algorithm to the EM algorithm that can reduce training times dramatically. The new approach belongs to the class of general Newton algorithms and is applicable in most situations where the EM algorithm is currently...

This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, the authors first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models....

In this paper, the authors empirically assess the extent to which early release inefficiency and definitional change affect prediction precision. In particular, they carry out a series of ex-ante prediction experiments in order to examine: the marginal predictive content of the revision process,...

The majority of work in mortality modeling involves factor-based approaches, with little use of information on the determinants and interpretable risk factors of mortality. At the same time, in the demographic community, there has been a lack of research attention towards the study of mortality...

Local volatility model is a relatively simple way to capture volatility skew/smile. In spite of its drawbacks, it remains popular among practitioners for derivative pricing and hedging. For long-dated options or interest rate/equity hybrid products, in order to take into account the effect of...