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Financial Signal Processing

Quantitative finance is presented from a signal processing perspective. Probability measure and stochastic processes: filtrations, Radon-Nikodym derivative, martingales, Markov processes; discrete-time and continuous-time random walks, Wiener process, Ito calculus, stochastic differential equations, Black-Scholes; introduction to statistics. Modeling and analysis of financial concepts such as arbitrage, replicating portfolios, hedging, liquidity, derivatives, volatility, futures, options. Markovitz portfolio theory, capital asset pricing model, the greeks, portfolio optimization, sparse methods, trading strategies. Analysis of single and multiple correlated nonstationary time series, GARCH. Machine learning in finance. Course work includes programming projects in Python or MATLAB to analyze real financial data.

Prerequisite: ECE211 or permission of instructor

Credits: 3.00

Course Code: ECE 478

  • Founded by inventor, industrialist and philanthropist Peter Cooper in 1859, The Cooper Union for the Advancement of Science and Art offers education in art, architecture and engineering, as well as courses in the humanities and social sciences.

  • “My feelings, my desires, my hopes, embrace humanity throughout the world,” Peter Cooper proclaimed in a speech in 1853. He looked forward to a time when, “knowledge shall cover the earth as waters cover the great deep.”

  • From its beginnings, Cooper Union was a unique institution, dedicated to founder Peter Cooper's proposition that education is the key not only to personal prosperity but to civic virtue and harmony.

  • Peter Cooper wanted his graduates to acquire the technical mastery and entrepreneurial skills, enrich their intellects and spark their creativity, and develop a sense of social justice that would translate into action.