Python for Algorithmic Trading Cookbook: Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing, Limited
2024
|
| Ausgabe: | 1st ed |
| Schlagworte: | |
| Online-Zugang: | DE-2070s |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (404 Seiten) |
| ISBN: | 9781835087763 |
Internformat
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| 100 | 1 | |a Strimpel, Jason |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Python for Algorithmic Trading Cookbook |b Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| 250 | |a 1st ed | ||
| 264 | 1 | |a Birmingham |b Packt Publishing, Limited |c 2024 | |
| 264 | 4 | |c ©2024 | |
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| 505 | 8 | |a Cover -- Title Page -- Copyright & -- Credits -- Contributors -- Table of Contents -- Preface -- Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries -- Technical requirements -- Working with stock market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historic futures data with the OpenBB Platform -- Getting ready... -- How to do it... -- There's more... -- See also -- Navigating options market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Harnessing factor data using pandas_datareader -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 2: Analyze and Transform Financial Market Data with pandas -- Diving into pandas index types -- How to do it... -- How it works... -- There's more... -- See also -- Building pandas Series and DataFrames -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Manipulating and transforming DataFrames -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining and selecting data from DataFrames -- How to do it... -- How it works... -- There's more... -- See also -- Calculating asset returns using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Measuring the volatility of a return series -- How to do it... -- How it works... -- There's more... -- See also -- Generating a cumulative return series -- Getting ready... -- How to do it... -- How it works... -- See also -- Resampling data for different time frames -- How to do it... -- How it works... -- There's more... -- See also -- Addressing missing data issues -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Applying custom functions to analyze time series data | |
| 505 | 8 | |a Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash -- Quickly visualizing data using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Animating the evolution of the yield curve with Matplotlib -- How to do it... -- How it works... -- There's more... -- See also -- Plotting options implied volatility surfaces with Matplotlib -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Visualizing statistical relationships with Seaborn -- How to do it... -- How it works... -- There's more... -- See also -- Creating an interactive PCA analytics dashboard with Plotly Dash -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 4: Store Financial Market Data on Your Computer -- Storing data on disk in CSV format -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data on disk with SQLite -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in a PostgreSQL database server -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in ultra-fast HDF5 format -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Chapter 5: Build Alpha Factors for Stock Portfolios -- Identifying latent return drivers using principal component analysis -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Finding and hedging portfolio beta using linear regression -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing portfolio sensitivities to the Fama-French factors -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also | |
| 505 | 8 | |a Assessing market inefficiency based on volatility -- How to do it... -- How it works... -- There's more... -- See also -- Preparing a factor ranking model using Zipline Pipelines -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 6: Vector-Based Backtesting with VectorBT -- Building technical strategies with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Conducting walk-forward optimization with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Optimizing the SuperTrend strategy with VectorBT Pro -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded -- Technical Requirements -- For Windows, Unix/Linux, and Mac Intel users -- For Mac M1/M2 users -- Backtesting a momentum factor strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Exploring a mean reversion strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded -- Preparing backtest results -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating the information coefficient -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining factor return performance -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating factor turnover -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio -- Preparing Zipline backtest results for Pyfolio Reloaded -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also | |
| 505 | 8 | |a Generating strategy performance and return analytics -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Building a drawdown and rolling risk analysis -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing strategy holdings, leverage, exposure, and sector allocations -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Breaking Down Strategy Performance to Trade Level -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 10: Set Up the Interactive Brokers Python API -- Building an algorithmic trading app -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating a Contract object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating an Order object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historical market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Getting a market data snapshot -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Streaming live market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Storing live tick data in a local SQL database -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 11: Manage Orders, Positions, and Portfolios with the IB API -- Executing orders with the IB API -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Managing orders once they're placed -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Getting details about your portfolio -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also | |
| 505 | 8 | |a Inspecting positions and position details -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Computing portfolio profit and loss -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 12: Deploy Strategies to a Live Environment -- Calculating real-time key performance and risk indicators -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Sending orders based on portfolio targets -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying a monthly factor portfolio strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an options combo strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an intraday multi-asset mean reversion strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 13: Advanced Recipes for Market Data and Strategy Management -- Streaming real-time options data with ThetaData -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Using the ArcticDB DataFrame database for tick storage -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Triggering real-time risk limit alerts -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Storing trade execution details in a SQL database -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Index -- Other Books You May Enjoy | |
| 650 | 4 | |a Python (Computer program language) | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Strimpel, Jason |t Python for Algorithmic Trading Cookbook |d Birmingham : Packt Publishing, Limited,c2024 |z 9781835084700 |
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Datensatz im Suchindex
| _version_ | 1823676361245458432 |
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| adam_text | |
| any_adam_object | |
| author | Strimpel, Jason |
| author_facet | Strimpel, Jason |
| author_role | aut |
| author_sort | Strimpel, Jason |
| author_variant | j s js |
| building | Verbundindex |
| bvnumber | BV050102436 |
| collection | ZDB-30-PQE |
| contents | Cover -- Title Page -- Copyright & -- Credits -- Contributors -- Table of Contents -- Preface -- Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries -- Technical requirements -- Working with stock market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historic futures data with the OpenBB Platform -- Getting ready... -- How to do it... -- There's more... -- See also -- Navigating options market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Harnessing factor data using pandas_datareader -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 2: Analyze and Transform Financial Market Data with pandas -- Diving into pandas index types -- How to do it... -- How it works... -- There's more... -- See also -- Building pandas Series and DataFrames -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Manipulating and transforming DataFrames -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining and selecting data from DataFrames -- How to do it... -- How it works... -- There's more... -- See also -- Calculating asset returns using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Measuring the volatility of a return series -- How to do it... -- How it works... -- There's more... -- See also -- Generating a cumulative return series -- Getting ready... -- How to do it... -- How it works... -- See also -- Resampling data for different time frames -- How to do it... -- How it works... -- There's more... -- See also -- Addressing missing data issues -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Applying custom functions to analyze time series data Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash -- Quickly visualizing data using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Animating the evolution of the yield curve with Matplotlib -- How to do it... -- How it works... -- There's more... -- See also -- Plotting options implied volatility surfaces with Matplotlib -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Visualizing statistical relationships with Seaborn -- How to do it... -- How it works... -- There's more... -- See also -- Creating an interactive PCA analytics dashboard with Plotly Dash -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 4: Store Financial Market Data on Your Computer -- Storing data on disk in CSV format -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data on disk with SQLite -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in a PostgreSQL database server -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in ultra-fast HDF5 format -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Chapter 5: Build Alpha Factors for Stock Portfolios -- Identifying latent return drivers using principal component analysis -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Finding and hedging portfolio beta using linear regression -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing portfolio sensitivities to the Fama-French factors -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also Assessing market inefficiency based on volatility -- How to do it... -- How it works... -- There's more... -- See also -- Preparing a factor ranking model using Zipline Pipelines -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 6: Vector-Based Backtesting with VectorBT -- Building technical strategies with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Conducting walk-forward optimization with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Optimizing the SuperTrend strategy with VectorBT Pro -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded -- Technical Requirements -- For Windows, Unix/Linux, and Mac Intel users -- For Mac M1/M2 users -- Backtesting a momentum factor strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Exploring a mean reversion strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded -- Preparing backtest results -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating the information coefficient -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining factor return performance -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating factor turnover -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio -- Preparing Zipline backtest results for Pyfolio Reloaded -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also Generating strategy performance and return analytics -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Building a drawdown and rolling risk analysis -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing strategy holdings, leverage, exposure, and sector allocations -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Breaking Down Strategy Performance to Trade Level -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 10: Set Up the Interactive Brokers Python API -- Building an algorithmic trading app -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating a Contract object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating an Order object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historical market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Getting a market data snapshot -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Streaming live market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Storing live tick data in a local SQL database -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 11: Manage Orders, Positions, and Portfolios with the IB API -- Executing orders with the IB API -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Managing orders once they're placed -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Getting details about your portfolio -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also Inspecting positions and position details -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Computing portfolio profit and loss -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 12: Deploy Strategies to a Live Environment -- Calculating real-time key performance and risk indicators -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Sending orders based on portfolio targets -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying a monthly factor portfolio strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an options combo strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an intraday multi-asset mean reversion strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 13: Advanced Recipes for Market Data and Strategy Management -- Streaming real-time options data with ThetaData -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Using the ArcticDB DataFrame database for tick storage -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Triggering real-time risk limit alerts -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Storing trade execution details in a SQL database -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Index -- Other Books You May Enjoy |
| ctrlnum | (ZDB-30-PQE)EBC31532174 (ZDB-30-PAD)EBC31532174 (ZDB-89-EBL)EBL31532174 (OCoLC)1446795233 (DE-599)BVBBV050102436 |
| dewey-full | 332.6450285 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.6450285 |
| dewey-search | 332.6450285 |
| dewey-sort | 3332.6450285 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| edition | 1st ed |
| format | Electronic eBook |
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disk with SQLite -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in a PostgreSQL database server -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in ultra-fast HDF5 format -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Chapter 5: Build Alpha Factors for Stock Portfolios -- Identifying latent return drivers using principal component analysis -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Finding and hedging portfolio beta using linear regression -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing portfolio sensitivities to the Fama-French factors -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Assessing market inefficiency based on volatility -- How to do it... -- How it works... -- There's more... -- See also -- Preparing a factor ranking model using Zipline Pipelines -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 6: Vector-Based Backtesting with VectorBT -- Building technical strategies with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Conducting walk-forward optimization with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Optimizing the SuperTrend strategy with VectorBT Pro -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded -- Technical Requirements -- For Windows, Unix/Linux, and Mac Intel users -- For Mac M1/M2 users -- Backtesting a momentum factor strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Exploring a mean reversion strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded -- Preparing backtest results -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating the information coefficient -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining factor return performance -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating factor turnover -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio -- Preparing Zipline backtest results for Pyfolio Reloaded -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Generating strategy performance and return analytics -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Building a drawdown and rolling risk analysis -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing strategy holdings, leverage, exposure, and sector allocations -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Breaking Down Strategy Performance to Trade Level -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 10: Set Up the Interactive Brokers Python API -- Building an algorithmic trading app -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating a Contract object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating an Order object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historical market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Getting a market data snapshot -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Streaming live market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Storing live tick data in a local SQL database -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 11: Manage Orders, Positions, and Portfolios with the IB API -- Executing orders with the IB API -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Managing orders once they're placed -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Getting details about your portfolio -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Inspecting positions and position details -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Computing portfolio profit and loss -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 12: Deploy Strategies to a Live Environment -- Calculating real-time key performance and risk indicators -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Sending orders based on portfolio targets -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying a monthly factor portfolio strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an options combo strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an intraday multi-asset mean reversion strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 13: Advanced Recipes for Market Data and Strategy Management -- Streaming real-time options data with ThetaData -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Using the ArcticDB DataFrame database for tick storage -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Triggering real-time risk limit alerts -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Storing trade execution details in a SQL database -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Index -- Other Books You May Enjoy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield 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| id | DE-604.BV050102436 |
| illustrated | Not Illustrated |
| indexdate | 2025-02-10T13:15:07Z |
| institution | BVB |
| isbn | 9781835087763 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035439598 |
| oclc_num | 1446795233 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (404 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | Packt Publishing, Limited |
| record_format | marc |
| spelling | Strimpel, Jason Verfasser aut Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python 1st ed Birmingham Packt Publishing, Limited 2024 ©2024 1 Online-Ressource (404 Seiten) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Cover -- Title Page -- Copyright & -- Credits -- Contributors -- Table of Contents -- Preface -- Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries -- Technical requirements -- Working with stock market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historic futures data with the OpenBB Platform -- Getting ready... -- How to do it... -- There's more... -- See also -- Navigating options market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Harnessing factor data using pandas_datareader -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 2: Analyze and Transform Financial Market Data with pandas -- Diving into pandas index types -- How to do it... -- How it works... -- There's more... -- See also -- Building pandas Series and DataFrames -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Manipulating and transforming DataFrames -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining and selecting data from DataFrames -- How to do it... -- How it works... -- There's more... -- See also -- Calculating asset returns using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Measuring the volatility of a return series -- How to do it... -- How it works... -- There's more... -- See also -- Generating a cumulative return series -- Getting ready... -- How to do it... -- How it works... -- See also -- Resampling data for different time frames -- How to do it... -- How it works... -- There's more... -- See also -- Addressing missing data issues -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Applying custom functions to analyze time series data Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash -- Quickly visualizing data using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Animating the evolution of the yield curve with Matplotlib -- How to do it... -- How it works... -- There's more... -- See also -- Plotting options implied volatility surfaces with Matplotlib -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Visualizing statistical relationships with Seaborn -- How to do it... -- How it works... -- There's more... -- See also -- Creating an interactive PCA analytics dashboard with Plotly Dash -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 4: Store Financial Market Data on Your Computer -- Storing data on disk in CSV format -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data on disk with SQLite -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in a PostgreSQL database server -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in ultra-fast HDF5 format -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Chapter 5: Build Alpha Factors for Stock Portfolios -- Identifying latent return drivers using principal component analysis -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Finding and hedging portfolio beta using linear regression -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing portfolio sensitivities to the Fama-French factors -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also Assessing market inefficiency based on volatility -- How to do it... -- How it works... -- There's more... -- See also -- Preparing a factor ranking model using Zipline Pipelines -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 6: Vector-Based Backtesting with VectorBT -- Building technical strategies with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Conducting walk-forward optimization with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Optimizing the SuperTrend strategy with VectorBT Pro -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded -- Technical Requirements -- For Windows, Unix/Linux, and Mac Intel users -- For Mac M1/M2 users -- Backtesting a momentum factor strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Exploring a mean reversion strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded -- Preparing backtest results -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating the information coefficient -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining factor return performance -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating factor turnover -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio -- Preparing Zipline backtest results for Pyfolio Reloaded -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also Generating strategy performance and return analytics -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Building a drawdown and rolling risk analysis -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing strategy holdings, leverage, exposure, and sector allocations -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Breaking Down Strategy Performance to Trade Level -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 10: Set Up the Interactive Brokers Python API -- Building an algorithmic trading app -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating a Contract object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating an Order object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historical market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Getting a market data snapshot -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Streaming live market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Storing live tick data in a local SQL database -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 11: Manage Orders, Positions, and Portfolios with the IB API -- Executing orders with the IB API -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Managing orders once they're placed -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Getting details about your portfolio -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also Inspecting positions and position details -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Computing portfolio profit and loss -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 12: Deploy Strategies to a Live Environment -- Calculating real-time key performance and risk indicators -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Sending orders based on portfolio targets -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying a monthly factor portfolio strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an options combo strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an intraday multi-asset mean reversion strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 13: Advanced Recipes for Market Data and Strategy Management -- Streaming real-time options data with ThetaData -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Using the ArcticDB DataFrame database for tick storage -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Triggering real-time risk limit alerts -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Storing trade execution details in a SQL database -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Index -- Other Books You May Enjoy Python (Computer program language) Erscheint auch als Druck-Ausgabe Strimpel, Jason Python for Algorithmic Trading Cookbook Birmingham : Packt Publishing, Limited,c2024 9781835084700 |
| spellingShingle | Strimpel, Jason Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python Cover -- Title Page -- Copyright & -- Credits -- Contributors -- Table of Contents -- Preface -- Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries -- Technical requirements -- Working with stock market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historic futures data with the OpenBB Platform -- Getting ready... -- How to do it... -- There's more... -- See also -- Navigating options market data with the OpenBB Platform -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Harnessing factor data using pandas_datareader -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 2: Analyze and Transform Financial Market Data with pandas -- Diving into pandas index types -- How to do it... -- How it works... -- There's more... -- See also -- Building pandas Series and DataFrames -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Manipulating and transforming DataFrames -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining and selecting data from DataFrames -- How to do it... -- How it works... -- There's more... -- See also -- Calculating asset returns using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Measuring the volatility of a return series -- How to do it... -- How it works... -- There's more... -- See also -- Generating a cumulative return series -- Getting ready... -- How to do it... -- How it works... -- See also -- Resampling data for different time frames -- How to do it... -- How it works... -- There's more... -- See also -- Addressing missing data issues -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Applying custom functions to analyze time series data Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash -- Quickly visualizing data using pandas -- How to do it... -- How it works... -- There's more... -- See also -- Animating the evolution of the yield curve with Matplotlib -- How to do it... -- How it works... -- There's more... -- See also -- Plotting options implied volatility surfaces with Matplotlib -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Visualizing statistical relationships with Seaborn -- How to do it... -- How it works... -- There's more... -- See also -- Creating an interactive PCA analytics dashboard with Plotly Dash -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 4: Store Financial Market Data on Your Computer -- Storing data on disk in CSV format -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data on disk with SQLite -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in a PostgreSQL database server -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Storing data in ultra-fast HDF5 format -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also... -- Chapter 5: Build Alpha Factors for Stock Portfolios -- Identifying latent return drivers using principal component analysis -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Finding and hedging portfolio beta using linear regression -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing portfolio sensitivities to the Fama-French factors -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also Assessing market inefficiency based on volatility -- How to do it... -- How it works... -- There's more... -- See also -- Preparing a factor ranking model using Zipline Pipelines -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 6: Vector-Based Backtesting with VectorBT -- Building technical strategies with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Conducting walk-forward optimization with VectorBT -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Optimizing the SuperTrend strategy with VectorBT Pro -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded -- Technical Requirements -- For Windows, Unix/Linux, and Mac Intel users -- For Mac M1/M2 users -- Backtesting a momentum factor strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Exploring a mean reversion strategy with Zipline Reloaded -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded -- Preparing backtest results -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating the information coefficient -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Examining factor return performance -- How to do it... -- How it works... -- There's more... -- See also -- Evaluating factor turnover -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio -- Preparing Zipline backtest results for Pyfolio Reloaded -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also Generating strategy performance and return analytics -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Building a drawdown and rolling risk analysis -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Analyzing strategy holdings, leverage, exposure, and sector allocations -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Breaking Down Strategy Performance to Trade Level -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 10: Set Up the Interactive Brokers Python API -- Building an algorithmic trading app -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating a Contract object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Creating an Order object with the IB API -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Fetching historical market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Getting a market data snapshot -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Streaming live market data -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Storing live tick data in a local SQL database -- Getting ready... -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 11: Manage Orders, Positions, and Portfolios with the IB API -- Executing orders with the IB API -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Managing orders once they're placed -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Getting details about your portfolio -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also Inspecting positions and position details -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Computing portfolio profit and loss -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 12: Deploy Strategies to a Live Environment -- Calculating real-time key performance and risk indicators -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Sending orders based on portfolio targets -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying a monthly factor portfolio strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an options combo strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Deploying an intraday multi-asset mean reversion strategy -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 13: Advanced Recipes for Market Data and Strategy Management -- Streaming real-time options data with ThetaData -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Using the ArcticDB DataFrame database for tick storage -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Triggering real-time risk limit alerts -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Storing trade execution details in a SQL database -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Index -- Other Books You May Enjoy Python (Computer program language) |
| title | Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| title_auth | Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| title_exact_search | Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| title_full | Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| title_fullStr | Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| title_full_unstemmed | Python for Algorithmic Trading Cookbook Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| title_short | Python for Algorithmic Trading Cookbook |
| title_sort | python for algorithmic trading cookbook recipes for designing building and deploying algorithmic trading strategies with python |
| title_sub | Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python |
| topic | Python (Computer program language) |
| topic_facet | Python (Computer program language) |
| work_keys_str_mv | AT strimpeljason pythonforalgorithmictradingcookbookrecipesfordesigningbuildinganddeployingalgorithmictradingstrategieswithpython |