Study resources for quantitative finance
A list of ressources for all topics related to quantitative finance.
This list accepts and encourages pull requests. See CONTRIBUTING
Electronic markets and limit order book. High frequency data. Statistical and structural models (Roll and its generalizations). Asymmetric information models (Glosten-Milgrom, Kyle). Information share. Inventory management models. Market making. Statistical limit order book models. Trading models: Market impact and order flow. Trading costs. Optimal execution. High Frequency Trading. High Frequency Econometrics: Realized volatility and covariance, Microstructure noise. Point processes in finance (Hawkes processes and ACD models).
Basic elements of graph theory. Random walks on graphs. Centrality measures. Scale free networks and small world graphs. Models of random graphs: Erdos Renyi graphs, Exponential random graphs, Stochastic block model, configuration model. Maximum entropy principle and networks. Networks from time series.
Mechanisms for systemic risk and models: Bank runs, leverage cycles, Interbank networks, Fire sales spillovers. Econometric approaches to systemic risk: CoVar, MES,SRISK, Granger causality networks. High frequency systemic risk: flash crashes, liquidity crises, systemic cojumps.
Polynomial curve fitting, foundations of statistical learning, no free lunch theorem, local volatility, interpolation of volatility surfaces, universal approximation, approximation by deep neural networks, empirical risk minimization, ridge regression, nonlinear regression, convex optimization, gradient descent, stochastic gradient descent, non-convex optimization, calibration of financial models, machine learning techniques for option pricing, deep model calibration.
BSDE approach to option pricing, deep solvers for BSDEs, Euler-Maruyama discretization of forward SDEs, existence and uniqueness of backward SDEs, linear BSDEs, applications in option pricing, comparison principles, Euler-Maruyama discretization of backward SDEs, classical solutions of semilinear PDEs, convergence rates of deep solvers for backward SDEs, scope and limitations.
Discrete time optimal stopping, Snell envelope, optimal stopping times, American put option, martingale duality, parametric approximation methods, regression based approximation methods, Longstaff-Schwartz algorithm, martingales from stopping rules, deep optimal stopping, low rank tensors, signatures and rough paths, optimal stopping with signatures.
Optimal liquidation problems, Markov decision processes, dynamic programming, Bellman equation, tabular methods, Q-learning, Monte Carlo methods, temporal difference methods, optimal liquidation revisited, optimal investment, deep Q-learning.