Projects related to financial modeling, primarily in Python
ARIMA: useful for time-series modeling and forecasting
ETS: exponential smoothing
GARCH: used to model volatility
CAPM: asset pricing model
ML basic: basic ML models including linear regression, logistic regression, k-nearest neighbors, gradient boosting
XGBoost: gradient boosting ML model useful for forecasting
options_pricing: Black-Scholes for European-style options, Binomial Tree Model for America-style (early exercise)
PINN: physics-informed neural network for options pricing when loss function residual is Black-Scholes PDE
TO-DO:
- ensure PINNs are using PDE as residual (2nd derivative) rather than explicit BS solution
- compare to real world data and ensure getting accurate predictions
- find novel solutions in non-constant volatility settings