Up to this point, most research in the field of supply chain management has been focused on the optimal inventory and release policy in the presence of advance information. The purpose of this dissertation is to investigate the quantity and pricing decisions of both suppliers and manufacturers when advance contracts are available in addition to spot contracts. In order to quantify these decisions, I need a pricing model for products that have both private and market risks. This dissertation proposes a new way of deriving the correlation pricing formula to price assets that are indirectly linked to market assets. This pricing formula provides the theoretical foundation for the existence and uniqueness of risk-neutral probabilities and is shown to have a smaller variance than a regular time series model. Another contribution is a novel way to find the optimal mixture of advance and spot production from the supplier's point of view and the optimal order policy from the manufacturer's point of view. Other researchers have studied using price discounts as incentives to secure advance orders. This dissertation includes both discounts and price caps and proposes a model to capture the cost savings when the proportion of advance orders changes. The last contribution of this dissertation is two computational models that are risk-preference indifferent. Both Monte Carlo simulation in a risk-neutral setting and double lattices are applied to evaluate a price-capped multi-period advance contract.
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