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1	Pricing risky bonds under discrete time models Kuo, Chia-Cheng 12 July 2005 (has links) Credit risk of derivative securities includes the risk of underlying company and the risk of seller's nonfulfilment of contracts. Take bonds for example, we regard Treasury bills as default-free bonds, and corporate bonds as risky bonds. When the liability of property of derivative securities underlying company is less than 1, we regard the company is of bankruptcy. And then the seller of derivative securities will break the contract. The essay extends two period risky bonds pricing valuation of Jarrow and Turnbull(1995) to multiperiod situation, and derive arbitrage-free condition. Furthermore, we derive formulae of risky bonds prices by assuming the logarithm of the odds ratio of an underlying company's bankruptcy probability satisfies an AR(1) or MA(1) processes. Empirical data of Rebar, Chinarebar, Ceon are studied, time series models are established for logarithm of odds ratios. In most cases, we find that the log odds ratios can be well fitted by AR(1) models. bond AR(1) model binomial tree model
2	Pricing American and European options under the binomial tree model and its Black-Scholes limit model Yang, Yuankai January 2017 (has links) We consider the N step binomial tree model of stocks. Call options and put options of European and American type are computed explicitly. With appropriate scaling in time and jumps, convergence of the stock prices and the option prices are obtained as N-> infinite. The obtained convergence is the Black-Scholes model and, for the particular case of European call option, the Black-Scholes formula is obtained. Furthermore, the Black-Scholes partial differential equation is obtained as a limit from the N step binomial tree model. Pricing of American put option under the Black-Scholes model is obtained as a limit from the N step binomial tree model. With this thesis, option pricing under the Black-Scholes model is achieved not by advanced stochastic analysis but by elementary, easily understandable probability computation. Results which in elementary books on finance are mentioned briefly are here derived in more details. Some important Java codes for N step binomial tree option prices are constructed by the author of the thesis. European option American option Binomial tree model Black-Scholes PDE Black-Scholes option pricing formula Mathematics Matematik
3	Applications of ROA to Value a Dotcom Start-up and a Professional Basketball player Karungi, Doreen, Huang, Wenqing January 2012 (has links) This paper attempts to evaluate a dotcom start-up company and a professional young basketball player using Real Option Analysis in the investors’ points of view. That is, we are standing in the financers’ shoes and valuing both cases if they are worth investing in. We believe that real option analysis is the most appropriate valuation method from our current knowledge compared to other traditional valuation methods notably like the Net Present Value (NPV), therefore we try to prove that using both qualitative and quantitative descriptions. The authors concentrate more on applying quantitative methods than giving detailed definitions of real options. Binomial Pricing Model and Monte Carlo simulation with the help of MS Excel and MATLAB were used in the evaluation. The paper consists of two case studies, each tackled differently but both summarized up all together. The paper concludes with a table exhibiting when real options are valuable and a belief that game theory is essential in ROA. / Matlab Codes and Simulation&Binary Tree Model(Excel) Real Options Project Uncertainty and flexibility Traditional DCF or NPV Methods Volatility Present Value of Underlying Assets Monte Carlo Simulation Binomial Tree Model Venture Business and Capitalist Internet Start-up Jeremy Lin.
4	Problèmes numériques en mathématiques financières et en stratégies de trading / Numerical problems in financial mathematics and trading strategies Baptiste, Julien 21 June 2018 (has links) 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. Pricing Modèles de marchés financiers Coûts de transaction Stratégies de trading Options européennes Apprentissage automatique Apprentissage supervisé Conditions de non-arbitrage Equations aux dérivées partielles Modèle Binomial Prix de sur-réplication Trading algorithmique Pricing Financial market models European options Algorithmic Trading Binomial tree model Diffusion partial differential equations Machine learning No-arbitrage condition Option pricing Super-hedging prices Supervised learning 519

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