Bayesian Machine Learning in Quantitative Finance : Theory and Practical Applications

1 Introduction To Bayesian Machine Learning In Quantitative Finance -- 2 Background To Bayesian Machine Learning In Quantitative Finance -- 3 On the Stochastic Alpha Beta Rho Model and Hamiltonian Monte Carlo Techniques -- 4 Learning Equity Volatility Surfaces using Sparse Gaussian Processes -- 5 Analyzing South African Equity Option Prices Using Normalizing Flows -- 6 Sparse and Distributed Gaussian Processes For Modeling Corporate Credit Ratings -- 7 Bayesian Detection Of Recovery On Charged-Off Loan Accounts -- 8 Bayesian Audit Outcome Model Selection Using Normalising Flows -- 9 Bayesian Detection Of Unauthorized Expenditure Using Langevin and Hamiltonian Monte Carlo -- 10 Bayesian Neural Network Inference Of Motor Insurance Claims -- 11 Shadow and Adaptive Hamiltonian Monte Carlo Methods For Calibrating The Nelson and Siegel Model -- 12 Static and Dynamic Nested Sampling For Yield Curve Model Selection -- 13 A Bayesian Investment Analyst On The Johannesburg Stock Exchange -- 14 Conclusions to Bayesian Machine Learning In Quantitative Finance.