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Quantitative Finance Collector is a blog on Quantitative finance analysis, financial engineering methods in mathematical finance focusing on derivative pricing, quantitative trading and quantitative risk management. Random thoughts on financial markets and personal staff are posted at the sub personal blog.

Jun 15
I would like to take this opportunity to thank the author Thierry Roncalli for letting me know this great source.

QAM (Quantitative Asset Management) library:
QAM is the Gauss library which has been developped for the lecture notes on Quantitative Asset Management.

This library contains procedures:
for computing backtest (monthly rebalancing, currency hedging, strategy leveraging, fees managing, performance reporting, etc.).
for portfolio allocation (Black-Litterman, Markowitz, ERC, MDP, risk Bbdgeting, index sampling, 130/30, MSR, Sharpe style analysis, etc.).
for computing numerical algorithms (simplex set, Markov generator, quadrature rules, Fokker-Planck equation, etc.).
for derivatives pricing (dynamic delta hedging, Hedge fund replication, etc.).
for statistical methods (Artificial neural networks, copula, CSS, FLS, GMM, Huber, LAD, Logit, MARS, ML, NLS, PCA, Probit, Quantile regression, QP, Robust, Non-parametric Kernel regression, RBS, Tobit, factor models, etc.).
for time series analysis (arch, garch, vecm, spectral analysis, wavelets, etc.)
for strategy backtesting (covered call, bull-spread, carry trade, variance swaps, vix, long/short equity, absolute return strategy, trend-following strategy, etc.);
for stock screening (gini optimization, scoring methods, boosting, baging method, etc.)
for risk management (stop loss strategy, take profit strategy, concentration, etc.)

Please download the manual, library and lecture notes (in French only, unfortunately) at the author's webpage.
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