Thesis (MSc (Mathematics))--Stellenbosch University, 2008. / In the Benchmark Approach to Finance, it has been shown that by taking the Growth Optimal Portfolio as numéraire, a candidate for a pricing derivatives formula under the real world probability can be given. This result allows us to price in an incomplete financial market model. The result comes from two different approaches. In the first approach we use the supermartingale property of portfolios in units of the benchmark portfolio which leads to the fact that an equivalent measure is not needed. In the second approach the numéraire property of the Growth Optimal Portfolio is used. The numéraire portfolio defines an equivalent martingale measure and by change of measure using the Radon-Nikodým derivative, a real world pricing formula is derived which is the same as the one given by the first approach stated above.

<p>In this dissertation, I investigated price dynamics in the hotel room-night market and attempted to explain pricing decisions from a market perspective. Since market dynamics of the hotel room-night market can be paralleled to those in the financial market, financial market models allowed for examination of various aspects of hotel room pricing decisions.</p><p>In the first study, advance-purchase discounts were estimated through application of an option pricing model considering property-specific attributes. Non-refundable advance-purchase discounts are a commonly used rate fence. One challenge to their implementation, however, is deciding upon the precise magnitude of the discount. Quan’s (2002) study on the price of room reservations is a good starting point, but it is a conceptual model that assumes away other property-specific factors. This study thus tested the idea that advance-purchase discounts are affected by various components, including the value of the right to cancel a reservation (e.g., cancelation option value) and the room- and property-specific factors in the hotel room-night market (e.g., uncertainty, reviews, and seasonality). The analysis supported this hypothesis and additionally revealed that advance-purchase discounts are smaller for rooms with high review ratings in a high-demand period. Interestingly, the divergence between advance-purchase discounts and cancelation option value components widened in a high-demand period, which implies a tendency by hotels to adjust their room rates rather than the amount of discount for customers who book their stay well in advance. Theoretically, this study thus contributes to finance literature by extending the application of the option pricing model to real options for non-financial assets. This study also contributes to the hospitality literature by demonstrating the effects of property-specific attributes on advance-purchase discount magnitude. The results also have implications to the hospitality industry by providing an analytical framework by which hoteliers can estimate property-specific advance-purchase discounts.</p><p>The second study concentrated on rate parity agreement’s effect on the hotel room-night market’s efficiency at reflecting product characteristics in room rates. This study examined the impact of rate parity agreement between hotels and online travel agencies by comparing hotel rates between Europe and the United States. This study found that room rates were less sensitive to property quality attributes under rate parity clauses. The reflection of property quality on room rates were less efficient when hotels have rate parity agreement with OTAs. Furthermore, the results supported the claim that rate parity exacerbates price increase in periods of high demand, which indicates possible collusion between suppliers (hotels) and distributors (OTAs). The findings provided theoretical implications by testing the market efficiency of the hotel room-night market and confirming the impact at the property level. This study also provided a perspective on pricing decision makers to understand how rate parity agreement influence their pricing decisions. Last, the findings provided support for recent policies in Europe that restrict rate parity agreements between hotels and OTAs.</p><p>The third study empirically examined hoteliers’ response to the demand by observing the price movement of two rates with different cancelation policies—free cancelation rates and non-refundable rates. By modifying Hasbrouck’s (1995) information share approach, this study examined the non-refundable rates’ contribution to the price discovery process. The perceived quality of accommodation by customers, one of the primary determinants of the price discovery process, was included in analysis. The results suggested that non-refundable rates were contribute more to the information variance than free cancelation rates did. The findings also suggested that consumers’ perceived quality and volatility influence non-refundable rates’ contribution to the price discovery process. The results also have practical implications for market participants, as they help to build an understanding of aggregated demand and its impact on pricing. Non-refundable rates are generally regarded as just one of many kinds of discounted rates, but the results of this study suggest that hoteliers should carefully consider the role that non-refundable rates play in their pricing strategy.<br></p>

Le but de cette thèse CIFRE est de construire un portefeuille de stratégies de trading algorithmique intraday. Au lieu de considérer les prix comme une fonction du temps et d'un aléa généralement modélisé par un mouvement brownien, notre approche consiste à identifier les principaux signaux auxquels sont sensibles les donneurs d'ordres dans leurs prises de décision puis alors de proposer un modèle de prix afin de construire des stratégies dynamiques d'allocation de portefeuille. Dans une seconde partie plus académique, nous présentons des travaux de pricing d'options européennes et asiatiques. / The aim of this CIFRE thesis is to build a portfolio of intraday algorithmic trading strategies. Instead of considering stock prices as a function of time and a brownian motion, our approach is to identify the main signals affecting market participants when they operate on the market so we can set up a prices model and then build dynamical strategies for portfolio allocation. In a second part, we introduce several works dealing with asian and european option pricing.