Online portfolio selection research has so far focused mainly on minimizing regret defined in terms of wealth growth. Practical financial decision making, however, is deeply concerned with both wealth and risk. We consider online learning of portfolios of stocks whose prices are governed by arbitrary (unknown) stationary and ergodic processes, where the goal is to maximize wealth while keeping ...

We study a growth model for a single resource-based economy, as an infinite-horizon optimal control problem. The resource is assumed to be governed by the standard model of logistic growth, and is related to the output of the economy through a Cobb-Douglass type production function with an exogenously driven knowledge stock. The problem involves unbounded controls and the non-concave Hamiltonia...

We present a novel argument demonstrating that when trade is characterized by uncertainty the comparative advantages doctrine is misleading and a positive level of diversification is growth enhancing. Applying a result developed in the mathematical biological literature, we show that, in Ricardian trade model in which capital available for investment depends on previous periods returns, incompl...

Discrete time infinite horizon growth optimal investment in stock markets with transactions costs is considered. The stock processes are modelled by homogeneous Markov processes. Assuming that the distribution of the market process is known, we show two recursive investment strategies such that, in the long run, the growth rate on trajectories (in "liminf" sense) is greater than or equal to the...

Many economic sectors, like housing or transportation, are exposed to climate and likely to suffer efficiency losses when climate changes. The global economy is far from being sheltered from climate, these sectors represent a significant fraction of the existing capital stock. Using an optimal growth model with perfect knowledge, we examine the balance between efficiency losses and investment i...

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We formulate the problem of influencing the growth of a network as a stochastic optimal control problem in which a structural cost function penalizes undesired topologies. We approximate this control problem with a restricted class of control problems that can be solved using probabilistic inference methods. To deal with the increasing problem dimensionality, we introduce an adaptive importance...

This paper analyzes the nature of economic dynamics in a one-sector optimal growth model in which the technology is generally nonconvex, nondifferentiable, and discontinuous. The model also allows for irreversible investment and unbounded growth. We develop various tools to overcome the technical difficulties posed by the generality of the model. We provide sufficient conditions for optimal pat...

As a consequence of optimal investment choices, a firm’s assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm’s systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: ~i! the time-series relation between the book-to-market ratio and asset returns; ~ii! the cross-se...

As expressions are developed which describe planetesimal collisions, it is instructive to find probability distributions for planetesimal parameters which maximize growth of the planetesimal system. Finding such optimal distributions provides clues as to the general efficiency of planet formation, and may help astronomers to determine whether young systems are likely to form planets. We conside...