Climate Change and Environmental Risks
Multi-Period MV Approach to Risk & Return in Climate Change Policy
There is increasing public pressure on governments to commit to credible plans to reduce greenhouse gas emissions through carbon taxes, cap and trade or other regulatory systems. The responses of governments to climate change will have large impacts on the economy and on the profitability of key industries. Consequently, the financial sector has an interest in encouraging the adoption of the most cost effective policies in order to minimize any negative impacts on economic growth.
This research exploits recent advancements in stochastic optimization, namely in multi-period Mean Variance (M-V) portfolio allocation theory, to develop a robust method to determine an investment strategy (climate change mitigation) to achieve a targeted level of real GDP per capita at a future specified time, at minimum risk. By using a GDP target, this method avoids having to choose an arbitrary discount rate and reflects the desired to leave future generations a reasonable standard of living. An efficient frontier showing various possible target levels for real GDP per capital and their associated risk will be produced, providing a clear illustration of the risk-return trade-off for climate change policies.
|University:||University of Waterloo|
|Project Lead:||Peter Forsyth|
After graduating in 1979, Peter Forsyth was a Senior Simulation Scientist at the Computer Modelling Group (CMG) in Calgary, where he developed petroleum reservoir simulation software. After leaving CMG, Peter was the founding President of software start-up Dynamic Reservoir Systems (DRS), also in Calgary. DRS produced reservoir simulation software for PC's, using the then enormous amount of memory available (640K). DRS had three employees: a president and two vice-presidents. After selling out his shares in DRS (now owned by Duke) in 1987, Peter joined the University of Waterloo, where he is now a Professor in the Cheriton School of Computer Science. Peter's current research focuses on Computational Finance. He is a member of the Editorial Board of Applied Mathematical Finance and the Journal of Computational Finance. During the years 2008-2013, he was the Editor-in-chief of the Journal of Computational Finance.
Peter is currently a director of Aquanty, a software startup specializing in integrated modelling of three dimensional surface/subsurface water flows. Aquanty specializes in simulating the impact of industrial activity and climate change on water resources.