Advanced Algorithmic Trading（原书加代码）

[{"title":"（ 48 个子文件 12.76MB ） Advanced Algorithmic Trading（原书加代码）","children":[{"title":"aat-ebook-full-source-code-20170711","children":[{"title":"chapter-time-series-analysis-hidden-markov-models","children":[{"title":"hmm.R <span style='color:#111;'> 2.87KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-bayesian-statistics-linear-regression","children":[{"title":"bayes-linear-reg-sim.py <span style='color:#111;'> 2.88KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-bayesian-statistics-stochastic-volatility-model","children":[{"title":"student_t_plot.py <span style='color:#111;'> 495B </span>","children":null,"spread":false},{"title":"pymc3_bayes_stochastic_vol.py <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false},{"title":"exponential_plot.py <span style='color:#111;'> 484B </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-bayesian-statistics-markov-chain-monte-carlo","children":[{"title":"bayes-binomial-mcmc.py <span style='color:#111;'> 1.64KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-time-series-analysis-arima-garch-models","children":[{"title":"arima_models.R <span style='color:#111;'> 2.09KB </span>","children":null,"spread":false},{"title":"garch_models.R <span style='color:#111;'> 1.51KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-time-series-analysis-arma-models","children":[{"title":"ma_models.R <span style='color:#111;'> 2.48KB </span>","children":null,"spread":false},{"title":"arma_models.R <span style='color:#111;'> 2.37KB </span>","children":null,"spread":false},{"title":"ar_models.R <span style='color:#111;'> 2.17KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-trading-strategies-introductory-portfolio-strategies","children":[{"title":"equities_bonds_60_40_etf_portfolio_backtest.py <span style='color:#111;'> 540B </span>","children":null,"spread":false},{"title":"strategic_weight_etf_portfolio_backtest.py <span style='color:#111;'> 718B </span>","children":null,"spread":false},{"title":"monthly_rebalance_run.py <span style='color:#111;'> 3.11KB </span>","children":null,"spread":false},{"title":"equal_weight_etf_portfolio_backtest.py <span style='color:#111;'> 718B </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-bayesian-statistics-binomial-proportion","children":[{"title":"beta_plot.py <span style='color:#111;'> 604B </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-trading-strategies-regime-detection-hmm-qstrader","children":[{"title":"regime_hmm_train.py <span style='color:#111;'> 2.68KB </span>","children":null,"spread":false},{"title":"regime_hmm_risk_manager.py <span style='color:#111;'> 3.18KB </span>","children":null,"spread":false},{"title":"regime_hmm_strategy.py <span style='color:#111;'> 2.42KB </span>","children":null,"spread":false},{"title":"regime_hmm_backtest.py <span style='color:#111;'> 3.01KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-trading-strategies-arima-garch","children":[{"title":"forecasts.py <span style='color:#111;'> 703B </span>","children":null,"spread":false},{"title":"forecasts_new.csv <span style='color:#111;'> 209.11KB </span>","children":null,"spread":false},{"title":"arima_garch.R <span style='color:#111;'> 3.16KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-machine-learning-natural-language-processing","children":[{"title":"reuters-svm.py <span style='color:#111;'> 6.57KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-machine-learning-cross-validation","children":[{"title":"cross_validation.py <span style='color:#111;'> 8.16KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-machine-learning-linear-regression","children":[{"title":"lin_reg_sklearn.py <span style='color:#111;'> 1.77KB </span>","children":null,"spread":false},{"title":"lin_reg_distribution_plot.py <span style='color:#111;'> 1.31KB </span>","children":null,"spread":false}],"spread":true},{"title":"chapter-time-series-analysis-serial-correlation","children":[{"title":"serial_cor.R <span style='color:#111;'> 571B </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-time-series-analysis-state-space-models-kalman-filter","children":[{"title":"kalman_filter_dynamic_hedge_ratio.py <span style='color:#111;'> 2.97KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-trading-strategies-cointegration-strategies","children":[{"title":"coint_bollinger_backtest.py <span style='color:#111;'> 1.72KB </span>","children":null,"spread":false},{"title":"coint_cadf.R <span style='color:#111;'> 983B </span>","children":null,"spread":false},{"title":"coint_bollinger_strategy.py <span style='color:#111;'> 5.58KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-time-series-analysis-cointegration","children":[{"title":"sim.R <span style='color:#111;'> 839B </span>","children":null,"spread":false},{"title":"johansen.R <span style='color:#111;'> 1.22KB </span>","children":null,"spread":false},{"title":"cadf.R <span style='color:#111;'> 3.17KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-trading-strategies-kalman-filter-pairs-trading","children":[{"title":"kalman_qstrader_strategy.py <span style='color:#111;'> 5.78KB </span>","children":null,"spread":false},{"title":"kalman_qstrader_backtest.py <span style='color:#111;'> 1.45KB </span>","children":null,"spread":false}],"spread":false},{"title":"aat-ebook-20170711.pdf <span style='color:#111;'> 13.98MB </span>","children":null,"spread":false},{"title":"chapter-machine-learning-clustering-methods","children":[{"title":"simulated_data.py <span style='color:#111;'> 1.46KB </span>","children":null,"spread":false},{"title":"ohlc_clustering.py <span style='color:#111;'> 5.84KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-trading-strategies-sentdex-sentiment-qstrader","children":[{"title":"sentdex_sentiment_backtest.py <span style='color:#111;'> 2.25KB </span>","children":null,"spread":false},{"title":"sentdex_sentiment_strategy.py <span style='color:#111;'> 1.83KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-time-series-analysis-random-walks-white-noise","children":[{"title":"random_walk_white_noise.R <span style='color:#111;'> 931B </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-trading-strategies-intraday-ml","children":[{"title":"intraday_ml_backtest.py <span style='color:#111;'> 2.66KB </span>","children":null,"spread":false},{"title":"intraday_ml_strategy.py <span style='color:#111;'> 2.73KB </span>","children":null,"spread":false},{"title":"intraday_ml_model_fit.py <span style='color:#111;'> 5.51KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-machine-learning-decision-trees","children":[{"title":"ensemble_prediction.py <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false}],"spread":false},{"title":"chapter-bayesian-statistics-intro-to-bayesian-methods","children":[{"title":"beta_binomial.py <span style='color:#111;'> 1.79KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}]