This paper provides a valuation algorithm based on Monte Carlo simulation for valuing a wide set of capital budgeting problems with many embedded real options dependent on many state variables. Along the lines of Gamba and Trigeorgis (2002b), we decompose a complex real option problem with many options into a set of simple options, properly taking into account deviations from value additivity d...

In this article, we show how to analyze analytically the equilibrium policies and prices in an economy with a stochastic investment opportunity set and incomplete financial markets, when agents have power utility over both intermediate consumption and terminal wealth, and face portfolio constraints. The exact local comparative statics and approximate but analytical expression for the portfolio ...

We build a multi-agent model of endogenous technical change in which heterogeneous investments in patented knowledge generate Pareto-Levy and lognormal distributed returns to investment in research from very weak distributional assumptions. Firms produce a homogenous good and a public stock of knowledge accumulates from the expired patents of privately produced knowledge. Increasing returns to ...

The attempt to match asset price characteristics such as the risk-free interest rate, equity premium and the Sharpe ratio with data for models with instantaneous consumption decisions and time separable preferences has not been very successful. Many recent versions of asset pricing models have, in order to match those financial characteristics better with the data, employed habit formation wher...

We develop an agent-based model in which heterogenous and boundedly rational agents interact by trading a risky asset at an endogenously set price. Agents are endowed with balance sheets comprising the risky asset as well as cash on the asset side and equity capital as well as debt on the liabilities side. The introduction of balance sheets and debt into an agent-based setup is relatively new t...

We propose a novel methodology for evaluating the accuracy of numerical solutions to dynamic economic models. Speci…cally, we construct a lower bound on the size of approximation errors. A small lower bound on errors is a necessary condition for accuracy: If a lower error bound is unacceptably large, then the actual approximation errors are even larger, and hence, we reject the hypothesis that ...

This paper provides a framework for discussing the empirical validation of simulation models of market phenomena, in particular of agent-based computational economics models. Such validation is difficult, perhaps because of their complexity; moreover, simulations can prove existence, but not in general necessity. The paper highlights the Energy Modeling Forum’s benchmarking studies as an exempl...

This paper studies the problem of how changes in the design of the genetic algorithm (GA) have an effect on the results obtained in real-life applications. In this study, focused on the application of a GA to the tuning of technical trading rules in the context of financial markets, our tentative thesis is that the GA is robust with respect to design changes. The optimization of technical tradi...

In this paper we show Case-based Decision Theory (Gilboa and Schmeidler, 1995) can explain the aggregate dynamics of cooperation in the repeated Prisoner’s Dilemma, as observed in the experiments performed by Camera and Casari (2009). Moreover, we find CBDT provides a better fit to the dynamics of cooperation than does the existing Probit model, which is the first time such a result has been fo...

We present an algorithm and software routines for computing nthorder Taylor series approximate solutions to dynamic, discrete-time rational expectations models around a nonstochastic steady state. The primary advantage of higher-order (as opposed to firstor secondorder) approximations is that they are valid not just locally, but often globally (i.e., over nonlocal, possibly very large compact s...