MAP542 Numerical processing of financial data
We will start with a short tutorial on Pandas with examples based on financial data.
The course will tackle the following topics:
· Sequential data in one dimension (main example: equity indices - SP500, Eurostoxx) : missing values, missing dates, interpolation. Estimation of volatilities, autocorrelations.
· Sequential data multi-dimensional : correlations, scarcity of data for high dimensional correlations estimation, inversion of covariance matrices.
· Order book data : volumes, information at bid and ask sides, slippage, market impact of a trade (data: order books on cryptocurrencies)
· Yield curves reconstruction/interpolation : from bonds, from futures (e.g. on cryptocurrency).
· Options data :
- option prices (on large equity index such as SP500), reconstruction of forward and discount factor from put-call parity.
- Black Scholes formula with some justification (without continuous time stochastic calculus), computation of implied volatilities (bisection method, Newton method).
- Static no-arbitrage conditions on option prices and implied volatilities, fitting of a parametric implied volatility smile (SVI, SSVI).
- Teaching coordinator: De Marco Stéfano