This thesis has applied the theory of real options to study forestry investment decision-making under stochastic timber prices. Suitable models have been developed for the stochastic timber prices, after addressing major issues in characterisation of the price process. First, the assumption of stochastic timber price process was based on detailed unit root tests, incorporating structural breaks in time-series analysis. The series was found to be stationary around shifting mean, justifying the assumption of mean reversion model. Due to shift in the mean, long-run mean to which the prices tended to revert could not be assumed constant. Accordingly, it was varied in discreet steps as per the breaks identified in the tests. The timber price series failed the normality test implying fat tails in the data. To account for these fat tails, ‘jumps’ were incorporated in the mean reversion model. The results showed that the option values for the jump model were higher than the mean reversion model and threshold levels for investment implied different optimal paths. Ignoring jumps could provide sub-optimal results leading to erroneous decisions. Second, the long-run mean to which prices reverted was assumed to shift continuously in a random manner. This was modeled through the incorporation of stochastic level and slope in the trend of the prices. Since the stochastic level and slope were not observable in reality, a Kalman-filter approach was used for the estimation of model parameters. The price forecasts from the model were used to estimate option values for the harvest investment decisions. Third, investment in a carbon sequestration project from managed forests was evaluated using real options, under timber price stochasticity. The option values and threshold levels for investment were estimated, under baseline and mitigation scenarios. Results indicated that carbon sequestration from managed forests might not be a viable investment alternative due to existing bottlenecks. Overall, the research stressed upon the need for market information and adaptive management, with a pro-active approach, for efficient investment decisions in forestry.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/16764 |
| Date | 19 January 2009 |
| Creators | Khajuria, Rajender |
| Contributors | Kant, Shashi |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
| Format | 796386 bytes, application/pdf |
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