Chinese financial market: stock valuation from a data analysis perspective and option valuation using truncated binomial trees

This thesis comprises two parts. First, we try to answer the question in a data analysis perspective, which financial factor is more relevant to the market capitalisation movements. Second, due to price boundaries imposed by the market regulators, how could we price the financial options on such markets in a mathematically rigorous manner. In the first part of this thesis, after collecting large amount of real-world financial data for companies listed on the Chinese financial market, we carry out a data analysis and set up linear regressionmodels between market capitalisation and various financial data including PE ratio, total earning, etc. By calculating and comparing the coefficient of determination, those regressionmodels are ranked. We find that assets and earnings are highly correlated with market capitalisations. To extract information and reduce noise, principal component analysis technique is also used. Combining all results, a relationship between market capitalisation and other financial data is revealed. In the second part of this thesis, based on truncated binomial trees, several option valuation models are obtained. After introducing assumptions satisfying the specific price boundaries in the Chinese financial market, we derive an option valuation model from the Cox-Ross-Rubinstein model for European call options traded on the price-bounded financial market. A closed-form solution is obtained by assuming that security trading is continuous. Using the Chinese financial market data, empirical analysis result suggests that our modified model has more explanatory power than BS model in the Chinese financial market.