Hands-On AI Trading with Python, Quantconnect, and AWS - Pik, Jiri
- Format: Relié
- 416.0 pages Voir le descriptif
Vous en avez un à vendre ?
Vendez-le-vôtreExpédition rapide et soignée depuis l`Angleterre - Délai de livraison: entre 10 et 20 jours ouvrés.
Nos autres offres
-
62,32 €
Produit Neuf
Ou 15,58 € /mois
- Livraison à 0,01 €
Nouvel article expédié dans le 24H à partir des Etats Unis Livraison au bout de 20 à 30 jours ouvrables.
-
61,39 €
Produit Neuf
Ou 15,35 € /mois
- Livraison : 3,99 €
- Livré entre le 26 et le 28 juillet
-
111,99 €
Produit Neuf
Ou 28,00 € /mois
- Livraison : 25,00 €
- Livré entre le 6 et le 11 août
Apres acceptation de la commande, le delai moyen d'expedition depuis le Japon est de 48 heures. Le delai moyen de livraison est de 3 a 4 semaines. En cas de circonstances exceptionnelles, les delais peuvent s'etendre jusqu'à 2 mois.
- Payez directement sur Rakuten (CB, PayPal, 4xCB...)
- Récupérez le produit directement chez le vendeur
- Rakuten vous rembourse en cas de problème
Gratuit et sans engagement
Félicitations !
Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !
TROUVER UN MAGASIN
Retour
Avis sur Hands - On Ai Trading With Python, Quantconnect, And Aws Format Relié - Livre
0 avis sur Hands - On Ai Trading With Python, Quantconnect, And Aws Format Relié - Livre
Donnez votre avis et cumulez 5
Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.
Présentation Hands - On Ai Trading With Python, Quantconnect, And Aws Format Relié
- LivreAuteur(s) : Pik, Jiri - Chan, Ernest P - Broad, Jared - Sun, Philip - Singh, VivekEditeur : WileyLangue : AnglaisParution : 01/01/2025Format : Moyen, de 350g à 1kgNombre de pages : 416.0 ...
Résumé : Biographies xiii? Preface: QuantConnect xv? Introduction xxiii? Part I Foundations of Capital Markets and Quantitative Trading 1? Chapter 1 Foundations of Capital Markets 3? Market Mechanics 3? Market Participants 4? Trading Is the Play 4? The Stage and Basic Rules of Trading-The Limit Order Book 4? Actors-Liquidity Trader, Market Maker, and Informed Trader 5? Liquidity Trader 5? Market Maker 5? Informed Trader 6? AI Actors Wanted! 7? Data and Data Feeds 7? Custom and Alternative Data 9? Brokerages and Transaction Costs 10? Transaction Costs 11? Security Identifiers 13? Assets and Derivatives 15? US Equities 15? US Equity Options 19? Index Options 21? US Futures 21? Cryptocurrency 23? Chapter 2 Foundations of Quantitative Trading 25? Research Process 25? Research 25? Backtesting 26? Parameter Optimization 26? Paper and Live Trading 26? Testing and Debugging Tools 26? Debuggers 27? Logging 27? Charting 27? Object Store 28? Coding Process 28? Time and Look-ahead Bias 29? Look-ahead Bias 29? Market Hours and Scheduling 30? Strategy Styles 30? Trading Signals 31? Allocating Capital 31? Regimes and Portfolios of Strategies 32? Parameter Sensitivity Testing and Optimization 33? 1. Remove 33? 2. Replace 34? 3. Reduce 34? Parameter Sensitivity Testing 34? Margin Modeling 35? Equities 35? Equity Options 36? Futures 37? Diversification and Asset Selection 37? Fundamental Asset Selection 38? ETF Constituents Asset Selection 39? Dollar-Volume Asset Selection 40? Universe Settings 40? Indicators and Other Data Transformations 41? Automatic Indicators 41? Manual Indicators 41? Indicator Warm Up 42? Storing Objects 42? Indicator Events 42? Sourcing Ideas 42? Hypothesis-driven Testing 43? Data Driven Investing 44? Quantpedia 44? QuantConnect Research and Strategy Explorer 45? Part II Foundations of Ai and Ml in Algorithmic Trading 47? Step-by-step Guide for AI-based Algorithmic Trading 48? Chapter 3 Step 1: Problem Definition 49? Chapter 4 Step 2: Dataset Preparation 53 ?? Data Collection 53? Exploratory Data Analysis 53? Data Preprocessing 54? Handling Missing Data 55? Handling Outliers 58? Feature Engineering 61? Normalization and Standardization of Features 62? Transforming Time Series Features to Stationary 64? Identification of Cointegrated Time Series with Engle-Granger Test 70? Feature Selection 76? Correlation Analysis 76? Feature Importance Analysis 77? Auto-identification of Features 78? Dimensionality Reduction/Principal Component Analysis 80? Splitting of Dataset into Training, Testing, and Possibly Validation Sets 83? How to Split Your Data 83? Chapter 5 Step 3: Model Choice, Training, and Application 87? Regression 88? Linear Regression 89? Polynomial Regression 91? LASSO Regression 93? Ridge Regression 96? Markov Switching Dynamic Regression 99? Decision Tree Regression 103? Support Vector Machines Regression with Wavelet Forecasting 105? Classification 110? Multiclass Random Forest Model 110? Logistic Regression 114? Hidden Markov Models 117? Gaussian Naive Bayes 119? Conv...
Biographie: Biographies xiii Preface: QuantConnect xv Introduction xxiii Part I Foundations of Capital Markets and Quantitative Trading 1 Chapter 1 Foundations of Capital Markets 3 Market Mechanics 3 Market Participants 4 Trading Is the Play 4 The Stage and Basic Rules of Trading-The Limit Order Book 4 Actors-Liquidity Trader, Market Maker, and Informed Trader 5 Liquidity Trader 5 Market Maker 5 Informed Trader 6 AI Actors Wanted! 7 Data and Data Feeds 7 Custom and Alternative Data 9 Brokerages and Transaction Costs 10 Transaction Costs 11 Security Identifiers 13 Assets and Derivatives 15 US Equities 15 US Equity Options 19 Index Options 21 US Futures 21 Cryptocurrency 23 Chapter 2 Foundations of Quantitative Trading 25 Research Process 25 Research 25 Backtesting 26 Parameter Optimization 26 Paper and Live Trading 26 Testing and Debugging Tools 26 Debuggers 27 Logging 27 Charting 27 Object Store 28 Coding Process 28 Time and Look-ahead Bias 29 Look-ahead Bias 29 Market Hours and Scheduling 30 Strategy Styles 30 Trading Signals 31 Allocating Capital 31 Regimes and Portfolios of Strategies 32 Parameter Sensitivity Testing and Optimization 33 1. Remove 33 2. Replace 34 3. Reduce 34 Parameter Sensitivity Testing 34 Margin Modeling 35 Equities 35 Equity Options 36 Futures 37 Diversification and Asset Selection 37 Fundamental Asset Selection 38 ETF Constituents Asset Selection 39 Dollar-Volume Asset Selection 40 Universe Settings 40 Indicators and Other Data Transformations 41 Automatic Indicators 41 Manual Indicators 41 Indicator Warm Up 42 Storing Objects 42 Indicator Events 42 Sourcing Ideas 42 Hypothesis-driven Testing 43 Data Driven Investing 44 Quantpedia 44 QuantConnect Research and Strategy Explorer 45 Part II Foundations of AI and ML in Algorithmic Trading 47 Step-by-step Guide for AI-based Algorithmic Trading 48 Chapter 3 Step 1: Problem Definition 49 Chapter 4 Step 2: Dataset Preparation 53 Data Collection 53 Exploratory Data Analysis 53 Data Preprocessing 54 Handling Missing Data 55 Handling Outliers 58 Feature Engineering 61 Normalization and Standardization of Features 62 Transforming Time Series Features to Stationary 64 Identification of Cointegrated Time Series with Engle-Granger Test 70 Feature Selection 76 Correlation Analysis 76 Feature Importance Analysis 77 Auto-identification of Features 78 Dimensionality Reduction/Principal Component Analysis 80 Splitting of Dataset into Training, Testing, and Possibly Validation Sets 83 How to Split Your Data 83 Chapter 5 Step 3: Model Choice, Training, and Application 87 Regression 88 Linear Regression 89 Polynomial Regression 91 LASSO Regression 93 Ridge Regression 96 Markov Switching Dynamic Regression 99 Decision Tree Regression 103 Support Vector Machines Regression with Wavelet Forecasting 105 Classification 110 Multiclass Random Forest Model 110 Logistic Regression 114 Hidden Markov Models 117 Gaussian Naive Bayes 119 Convolutional Neural Networks 122 Ranking 127 LGBRanker Ranking 127...
Détails de conformité du produit
Personne responsable dans l'UE