Recently, there has been a renewed interest in modeling economic time series by vector autoregressive moving-average models. However, this class of models has been unpopular in practice because of estimation problems and the complexity of the identification stage. These disadvantages could have led to the dominant use of vector autoregressive models in macroeconomic research. In this paper, sev...

The stochastic modeling and determination of reserves and risk capitals for variable annuity guarantee products are relatively new developments in the insurance industry. The current market practice is largely based on Monte Carlo simulations, which have great engineering flexibility but the demand for heavy computational power can be prohibitive in many cases. In this paper, we distinguish and...

This paper is aimed at investigating the effects of government intervention through unemployment benefits on macroeconomic dynamics in an agent-based decentralized matching framework. The major result is that the presence of such a public intervention in the economy stabilizes the aggregate demand and the financial conditions of the system at the cost of a modest increase of both the inflation ...

In this paper we argue that in realistically calibrated two period general equilibrium models with incomplete markets CAPM-pricing provides a good benchmark for equilibrium prices even when agents are not mean-variance optimizers and returns are not normally distributed. We numerically approximate equilibria for a variety of di erent speci cations for preferences, endowments and dividends and c...

Options are believed to contain unique information on the risk-neutral moment generating function (MGF) or the risk-neutral probability density function (PDF) of the underlying asset. This paper applies the wavelet method to approximate the implied risk-neutral MGF from option prices. Monte Carlo simulations are carried out to show how the risk-neutral MGF can be obtained using the wavelet meth...

This paper describes a simulation approach for modelling decisionmaking processes under incomplete and imperfect information in Agentbased Computational Economics (ACE). The main idea is to represent decision-making in a model-free framework that can be applied to a larger set of simulation problems, not just the domain modelled. The method translates some basic sociopsychological concepts from...

This paper presents a lattice algorithm for pricing both Europeanand American-style moving average barrier options (MABOs). We develop a finite-dimensional partial differential equation (PDE) model for discretely monitored MABOs and solve it numerically by using a forward shooting grid method. The modeling PDE for continuously monitored MABOs has infinite dimensions and cannot be solved directl...

The paper considers the conjecture that forecasts from preferred economic models or theories d-separate forecasts from less preferred models or theories from the actual realization of the variable for which a scientific explanation is sought. Dseparation provides a succinct notion to represent forecast dominance of one set of forecasts over another; it provides, as well, a criterion for model p...

In order to address the question whether Hayek might have been an Agent-based Computational Economist (ACE) avant-la-lettre, we consider an ACE model concerning the phenomenon of information contagion. Alongside increasing returns, network externalities, and information cascades, information contagion has been presented in the literature as an explanation for particular patterns of macrobehavio...

The Net Present Value maximizing model has a respectable ancestry and is considered by most scholars a theoretically sound decision model. In real-life applications, decision makers use the NPV rule, but apply a subjectively determined hurdle rate, as opposed to the “correct” opportunity cost of capital. According to a heuristics-and-biases-program approach, this implies that the hurdle-rate ru...