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Abstract
The US South hosts the world’s largest forestry sector, characterized by a complex interplay between private corporate and noncorporate landowners and wood-consuming mills. Despite its importance, research gaps remain in areas like spatial price transmission, returns and risk assessment, and portfolio optimization. In Chapter 2, I used copula-based and smooth transition autoregressive models to explore spatial price transmission of sawtimber stumpage prices across 11 timber markets, including the state of Georgia and its neighbors. In Chapter 3, I used a strategic landscape planning model and a stochastic simulation process for assessing returns and risks on 15-year timberland investments. I complemented the literature by including current market trends, such as small-scale land selling for HBU, formal lease contracts, and call option contracts for solar developments. Finally, I applied modern portfolio theory to optimize timberland investment portfolios in the US South. In Chapter 4, I used returns and risks in a mean-variance model and estimated optimized portfolios across different risk budgets. Results from this study can help financial decision-making and enhance portfolio management strategies for investors and portfolio managers navigating timberland complexities and new market trends.