Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves

作     者：Way, Rupert Lafond, François Lillo, Fabrizio Panchenko, Valentyn Doyne Farmer, J. 

作者机构：Institute for New Economic Thinking Oxford Martin School University of Oxford OxfordOX2 6ED United Kingdom Smith School of Enterprise and the Environment University of Oxford OxfordOX1 3QY United Kingdom Oxford Martin School Programme on Technological and Economic Change University of Oxford OX1 3BD United Kingdom Scuola Normale Superiore Piazza dei Cavalieri 7 Pisa56126 Italy CADS Center for Analysis Decisions and Society Human Technopole Milano20156 Italy School of Economics UNSW Business School SydneyNSW2052 Australia Mathematical Institute University of Oxford OxfordOX1 3LP United Kingdom Department of Computer Science University of Oxford OxfordOX1 3QD United Kingdom Santa-Fe Institute Santa FeNM87501 United States 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2017年

核心收录：

主　　题：Investments 

摘      要：We consider how to optimally allocate investments in a portfolio of competing technologies using the standard mean-variance framework of portfolio theory. We assume that technologies follow the empirically observed relationship known as Wright s law, also called a learning curve or experience curve, which postulates that costs drop as cumulative production increases. This introduces a positive feedback between cost and investment that complicates the portfolio problem, leading to multiple local optima, and causing a trade-off between concentrating investments in one project to spur rapid progress vs. diversifying over many projects to hedge against failure. We study the two-technology case and characterize the optimal diversification in terms of progress rates, variability, initial costs, initial experience, risk aversion, discount rate and total demand. The efficient frontier framework is used to visualize technology portfolios and show how feedback results in nonlinear distortions of the feasible set. For the two-period case, in which learning and uncertainty interact with discounting, we compare different scenarios and find that the discount rate plays a critical role. Copyright © 2017, The Authors. All rights reserved.