Discrete-time stochastic models of management of groundwater resources have been extensively used for understanding a variety of issues in groundwater management for agriculture. Most models used suffer from two drawbacks: relatively simplistic treatment of the cost of water extraction (remarked...

Discrete-time stochastic models of groundwater management have been extensively used for understanding a variety of issues in groundwater management for agriculture. Most models used suffer from two drawbacks: relatively simplistic treatment of extraction cost (remarked in many papers in the...

We study a continuous-time problem of optimal public good contribution under uncertainty for an economy with a finite number of agents. Each agent can allocate his wealth between private consumption and repeated but irreversible contributions to increase the stock of some public good. We study...

We present a model of firm investment under uncertainty and partial irreversibility in which uncertainty is represented by a jump diffusion. This allows to represent both the continuous Gaussian volatility and the discontinuous uncertainty related to information arrival, sudden changes and large...

To analyze the economic significance of pricing errors of stock index options, a system of linear inequalities is developed which completely characterizes all risk arbitrage opportunities which arise if a well-behaved pricing kernel does not exist. The Stochastic Arbitrage system can account for...

In this paper, I study the existence and uniqueness of recursive equilibria in economies with aggregate and idiosyncratic risk. Rather than relying on compactness to establish existence, I exploit the monotonicity property of the equilibrium model and rely on arguments from convex analysis. This...

We study the effect of ambiguity on timing decisions. An agent faces a stopping problem with an uncertain stopping payoff and a stochastic time limit. The agent is unsure about the correct model quantifying the uncertainty and seeks to maximize her payoff guarantee over a set of plausible...

Growth Optimal Portfolio (GOP) theory determines the path of bet sizes that maximize long-term wealth. How it is also known in practice GOP is too risky. We explain in this talk that the reason is in practice the investment horizon is finite and practitioners account for risk more explicitly. We...

Recent research in macroeconomics has sought to develop a tractable form of heterogeneity in attempting to model sluggishness of response of the economy consistent with data. Sims (2003) argued that limited information processing was a promising avenue for understanding pervasive stickiness....

Growth Optimal Portfolio (GOP) theory determines the path of bet sizes that maximize long-term wealth. This multi-horizon goal makes it more appealing among practitioners than myopic approaches, like Markowitz's mean-variance or risk parity. The GOP literature typically considers risk-neutral...