Computational Finance
Learning Outcomes:
- Understanding the main functions of the financial system and the role of this module within it
- Learning about major financial instruments, including bonds and shares, and their pricing mechanisms
- Grasping the basics of derivative products and the concept of pricing by arbitrage
- Understanding the uses of options and basic option pricing facts using arbitrage principles
- Learning to price European and American options using binomial trees
- Understanding the principle of risk-neutral valuation for option pricing
- Learning to simulate stock price behavior and Wiener processes using random walks
- Manipulating stochastic differential equations using Ito's lemma
- Understanding the role of Brownian motion and Markov processes in financial modeling
- Deriving the Black-Scholes differential equation and formulas for European call and put options pricing
- Understanding various numerical methods for option pricing, including trees, Monte-Carlo, and PDEs
- Estimating stock volatility from market data
- Learning about hedging strategies and the calculation of Greek letters to quantify risk exposure
- Applying the Black-Scholes theory in practical hedging scenarios
- Understanding the concept of Value at Risk (VaR) and how it quantifies investment portfolio risk
- Calculating VaR using different methods and understanding the impact of diversification on VaR
- Discussing the applicability and limitations of financial models in the real-world context
- Exploring market efficiency hypotheses and current trends in finance
Skills for module:
Python
Probability
Statistics
Calculus
Mechanics
Problem Solving
Critical Thinking
Time Management
Computational Finance
CS3930
Learning Outcomes
- Understanding the main functions of the financial system and the role of this module within it
- Learning about major financial instruments, including bonds and shares, and their pricing mechanisms
- Grasping the basics of derivative products and the concept of pricing by arbitrage
- Understanding the uses of options and basic option pricing facts using arbitrage principles
- Learning to price European and American options using binomial trees
- Understanding the principle of risk-neutral valuation for option pricing
- Learning to simulate stock price behavior and Wiener processes using random walks
- Manipulating stochastic differential equations using Ito's lemma
- Understanding the role of Brownian motion and Markov processes in financial modeling
- Deriving the Black-Scholes differential equation and formulas for European call and put options pricing
- Understanding various numerical methods for option pricing, including trees, Monte-Carlo, and PDEs
- Estimating stock volatility from market data
- Learning about hedging strategies and the calculation of Greek letters to quantify risk exposure
- Applying the Black-Scholes theory in practical hedging scenarios
- Understanding the concept of Value at Risk (VaR) and how it quantifies investment portfolio risk
- Calculating VaR using different methods and understanding the impact of diversification on VaR
- Discussing the applicability and limitations of financial models in the real-world context
- Exploring market efficiency hypotheses and current trends in finance