books

Numerical Methods and Optimization in Finance 2019 (2nd ed.), 2011 (1st ed.), with M. Gilli and D. Maringer [BibTeX] The book explains tools for computational finance with an emphasis on simulation and optimisation ... [more]
Financial Optimisation with R [pdf] [BibTeX] The nmof manual: how to do practical financial optimisation in r.
Portfolio Management with R (pmwr) [html] [pdf] [BibTeX] Pricing of financial instruments, computing profit-and-loss, reporting, backtesting and [more].

essays

(an incomplete list)

Backtesting 2018 [ssrn] [Code]
Optimization Heuristics: A Tutorial 2018 [ssrn] [Code]
Risk–Reward Optimisation for Long-Run Investors (Revisited) 2017, with M. Gilli [ssrn]
Accuracy and Precision in Finance 2015, with M. Gilli [pdf] [Data]
Optimisation Cultures 2014, with M. Gilli [ssrn] [BibTeX]
Heuristics for Portfolio Selection 2014, with M. Gilli [ssrn] [BibTeX]
Two pitfalls in comparing financial time-series 2013 [pdf] [BibTeX]
Style Analysis with Differential Evolution 2013 [pdf] [BibTeX]
Take-the-Best in Portfolio Selection 2013 [pdf] [BibTeX]
Heuristic Optimisation in Financial Modelling 2012, with M. Gilli [ssrn] [BibTeX] [Read-only version]
A note on 1/n and minimum-variance portfolios, and the fact that significance tests do harm (and no good) in financial decision-making 2012 [pdf]
Optimal enough? 2011, with M. Gilli [pdf] [ssrn] [BibTeX]
Heuristic Methods in Finance 2011, with D. Ardia [pdf] [BibTeX]
Risk–Reward Optimisation for Long-Run Investors: an Empirical Analysis 2011, with M. Gilli [ssrn] [BibTeX] [Read-only version]
Portfolio Optimization with ‘Threshold Accepting’: a Practical Guide 2010, with M. Gilli [BibTeX]
A Note on Volatility Pumping 2008 [pdf]

R code and packages. Many of the packages are also on [Sourcehut], [GitLab] and [GitHub].
Notes.
Slides and code for ‘A short course in practical financial optimisation'’; Rimini, May 2016.
Data and code for ‘Accuracy and precision in Finance’.
matlab code for ‘A Data-Driven Optimization Heuristic for Downside Risk Minimization’ (Journal of Risk 8/3, 2006, pp. 1–18) can be downloaded from the comisef homepage
matlab and r functions for ‘Implementing Binomial Trees’ are available from the comisef homepage.
matlab and r functions for ‘Calibrating Option Pricing Models with Heuristics’ are available from the comisef homepage.
r functions for ‘Calibrating the Nelson–Siegel–Svensson model’ are available from the comisef homepage.
r function for ‘A note on “good starting values” in numerical optimisation’ is available from the comisef homepage.