Numerical Methods and Optimization in Finance
Approximate Total Return of Bond
Pricing Plain-Vanilla Bonds
Zero-Bracketing
Theoretical Valuation of Euro Bund Future
Price a Plain-Vanilla Call with the Characteristic Function
Price of a European Call under the Heston Model
Price of a European Call under Merton's Jump--Diffusion Model
Full-rank Column Subset
Constant-Proportion Portfolio Insurance
Optimisation with Differential Evolution
Diversification Ratio
Drawdown
Computing Prices of European Calls with a Binomial Tree
Download Datasets from Kenneth French's Data Library
Optimisation with a Genetic Algorithm
Greedy Search
Grid Search
Local-Search Information
Stochastic Local Search
Simple Moving Average
Maximum-Sharpe-Ratio/Tangency Portfolio
Option Pricing via Monte-Carlo Simulation
Minimum Conditional-Value-at-Risk (CVaR) Portfolios
Compute Minimum Mean--Absolute-Deviation Portfolios
Minimum-Variance Portfolios
Computing Mean--Variance Efficient Portfolios
Internal NMOF functions
Numerical Methods and Optimization in Finance
Zero Rates for Nelson--Siegel--Svensson Model
Factor Loadings for Nelson--Siegel and Nelson--Siegel--Svensson
Pricing Plain-Vanilla (European and American) and Barrier Options (Eur...
Partial Moments
Particle Swarm Optimisation
Put-Call Parity
Prepare LaTeX Table with Quartile Plots
Create a Random Returns
Repair an Indefinite Correlation Matrix
Resample with Specified Rank Correlation
Restart an Optimisation Algorithm
Download Jay Ritter's IPO Data
Simulated-Annealing Information
Optimisation with Simulated Annealing
Download Robert Shiller's Data
Display Code Examples
Threshold-Accepting Information
Optimisation with Threshold Accepting
Classical Test Functions for Unconstrained Optimisation
Compute a Tracking Portfolio
Contract Value of Australian Government Bond Future
Integration of Gauss-type
Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Useful links