Applied quantitative finance: using Python for financial analysis
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cham, Switzerland
Palgrave Macmillan
[2021]
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| Series: | Palgrave pivot
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xxvi, 240 Seiten Illustrationen 21 cm |
| ISBN: | 9783030291402 3030291405 |
Staff View
MARC
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Record in the Search Index
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| adam_text | r Contents Why Python? Installing Python in the Computer Using Jupyter Notebooks with Python Understanding Jupyter Notebooks Using Google Colab References Learning to Use Python: The Basic Aspects Understanding Numbers in Python Understanding Numbers in Python Using Data Structures in Python What Is a Listi How to Create a Listi Indexing and Cutting a List Appending Lists Arranging Lists From List to Matrices From List to Dictionaries Modifying a Dictionary Other Interesting Functions of a Dictionary The DataFrame Boolean, Loops and Other Features If, Else and Elif in Python 1 4 6 7 14 17 19 20 21 25 25 25 27 32 32 33 33 35 35 36 42 44 xi
xii CONTENTS Loops For Loop While Loop List Comprehension References 46 46 52 55 57 Using FRED® API for Economic Indicators and Data (Example) Installing the FRELfl API Using the FRElfl API to Retrieve Data First Step Second Step Third Step The Gross Domestic Product The Gross Domestic Product Price Deflator Understanding the Process into the Basics Comparing GDP 59 59 60 60 60 60 63 65 66 67 Using Stock Market Data in Python API Sources Моџ Important Librariesfor Uńng Data in Python in the Present Book Other Important Libraries Not Used in This Book Suggestion ofLibrariesfor Other Applications Using Python with Yahoo Finance API Using Python with Quandi API Usingf.fiг ( ) for Retreiving Information Using Python with Excel Conclusion Regarding Using Data in Python 71 71 72 74 74 75 77 79 81 83 Statistical Methods Using Python for Analyzing Stocks The Central Limit Theorem Creating a Histogram Creating a Histogram with Line Plots Histograms Using ffit () Histogram (Percent Change) with Two Variables Histogram (Logarithmic Return) with Two Variables Interquartile Range and Boxplots Вохрlot with Two Variables Kernel Density Plot and Volatility 85 85 88 94 96 96 98 99 102 104
CONTENTS ХІІІ Kernel Density Plot (Percent Change) with Two Variables Covariance and Correlation Scatterţlots and Heatmaps Works Cited 108 109 113 117 Elements for Technical Analysis Using Python 119 The Linear Plot with One Stock Price (Max Min Values and the Range) When to Use Linear Plots in Finance The Linear Plot with Two or More Stock Price Linear Plot with Volume Volume of Trade Comparison of Securities with Volume Plots and Closing Prices Candlestick Charts Candlestick Charts and Volume Customizing Candlestick Charts and Volume with **Kwargs OHLC Charts with Volume Line Charts with Volume Moving Average with Matplotlib Moving Average with Mplfinance The Exponential Moving Average (EMA) The Moving Average Convergence Divergence (MACD) with Baseline The Moving Average Convergence Divergence (MACD) with Signal Line Bollinger Bands® Backtesting Strategies for Trading Parabolic SAK Fast and Slow Stochastic Oscillators References Valuation and Risk Models with Stocks Creating a Portfolio Calculating Statistical Measures on a Portfolio The Capital Asset Pricing Model The Beta The Beta and the CAPM Sharpe Ratio Traynor Ratio 119 123 123 126 128 129 133 136 138 138 140 142 147 149 153 157 160 162 162 165 169 171 171 174 176 176 182 188 194
XIV CONTENTS Jensen ’s Measure Information Ratio References Value at Risk 197 201 209 Historical VaR (95) Historical VaR(99) VaR for the ‘Ňext 10 Days Historical Drawdown Wrapping Up the Book—Understanding Performance Portfolio Performance usingffn() Fund Performance using ffii() Works Cited 211 211 213 214 218 222 222 226 234 Works Cited 235 Index 239
|
| adam_txt |
r Contents Why Python? Installing Python in the Computer Using Jupyter Notebooks with Python Understanding Jupyter Notebooks Using Google Colab References Learning to Use Python: The Basic Aspects Understanding Numbers in Python Understanding Numbers in Python Using Data Structures in Python What Is a Listi How to Create a Listi Indexing and Cutting a List Appending Lists Arranging Lists From List to Matrices From List to Dictionaries Modifying a Dictionary Other Interesting Functions of a Dictionary The DataFrame Boolean, Loops and Other Features If, Else and Elif in Python 1 4 6 7 14 17 19 20 21 25 25 25 27 32 32 33 33 35 35 36 42 44 xi
xii CONTENTS Loops For Loop While Loop List Comprehension References 46 46 52 55 57 Using FRED® API for Economic Indicators and Data (Example) Installing the FRELfl API Using the FRElfl API to Retrieve Data First Step Second Step Third Step The Gross Domestic Product The Gross Domestic Product Price Deflator Understanding the Process into the Basics Comparing GDP 59 59 60 60 60 60 63 65 66 67 Using Stock Market Data in Python API Sources Моџ Important Librariesfor Uńng Data in Python in the Present Book Other Important Libraries Not Used in This Book Suggestion ofLibrariesfor Other Applications Using Python with Yahoo Finance API Using Python with Quandi API Usingf.fiг ( ) for Retreiving Information Using Python with Excel Conclusion Regarding Using Data in Python 71 71 72 74 74 75 77 79 81 83 Statistical Methods Using Python for Analyzing Stocks The Central Limit Theorem Creating a Histogram Creating a Histogram with Line Plots Histograms Using ffit () Histogram (Percent Change) with Two Variables Histogram (Logarithmic Return) with Two Variables Interquartile Range and Boxplots Вохрlot with Two Variables Kernel Density Plot and Volatility 85 85 88 94 96 96 98 99 102 104
CONTENTS ХІІІ Kernel Density Plot (Percent Change) with Two Variables Covariance and Correlation Scatterţlots and Heatmaps Works Cited" 108 109 113 117 Elements for Technical Analysis Using Python 119 The Linear Plot with One Stock Price (Max Min Values and the Range) When to Use Linear Plots in Finance The Linear Plot with Two or More Stock Price Linear Plot with Volume Volume of Trade Comparison of Securities with Volume Plots and Closing Prices Candlestick Charts Candlestick Charts and Volume Customizing Candlestick Charts and Volume with **Kwargs OHLC Charts with Volume Line Charts with Volume Moving Average with Matplotlib Moving Average with Mplfinance The Exponential Moving Average (EMA) The Moving Average Convergence Divergence (MACD) with Baseline The Moving Average Convergence Divergence (MACD) with Signal Line Bollinger Bands® Backtesting Strategies for Trading Parabolic SAK Fast and Slow Stochastic Oscillators References Valuation and Risk Models with Stocks Creating a Portfolio Calculating Statistical Measures on a Portfolio The Capital Asset Pricing Model The Beta The Beta and the CAPM Sharpe Ratio Traynor Ratio 119 123 123 126 128 129 133 136 138 138 140 142 147 149 153 157 160 162 162 165 169 171 171 174 176 176 182 188 194
XIV CONTENTS Jensen ’s Measure Information Ratio References Value at Risk 197 201 209 Historical VaR (95) Historical VaR(99) VaR for the ‘Ňext 10 Days Historical Drawdown Wrapping Up the Book—Understanding Performance Portfolio Performance usingffn() Fund Performance using ffii() Works Cited 211 211 213 214 218 222 222 226 234 Works Cited 235 Index 239 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Garita, Mauricio |
| author_facet | Garita, Mauricio |
| author_role | aut |
| author_sort | Garita, Mauricio |
| author_variant | m g mg |
| building | Verbundindex |
| bvnumber | BV047499802 |
| classification_rvk | QP 890 |
| ctrlnum | (OCoLC)1286881806 (DE-599)KXP1761747797 |
| dewey-full | 332.02855133 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.02855133 |
| dewey-search | 332.02855133 |
| dewey-sort | 3332.02855133 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Book |
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| illustrated | Illustrated |
| index_date | 2024-07-03T18:18:29Z |
| indexdate | 2024-07-10T09:13:48Z |
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| isbn | 9783030291402 3030291405 |
| language | English |
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| physical | xxvi, 240 Seiten Illustrationen 21 cm |
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| spelling | Garita, Mauricio Verfasser aut Applied quantitative finance using Python for financial analysis Mauricio Garita Cham, Switzerland Palgrave Macmillan [2021] xxvi, 240 Seiten Illustrationen 21 cm txt rdacontent n rdamedia nc rdacarrier Palgrave pivot Finanzmathematik (DE-588)4017195-4 gnd rswk-swf Finanzanalyse (DE-588)4133000-6 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Finance / Data processing Python (Computer program language) Finance ; Data processing Finanzmathematik (DE-588)4017195-4 s Finanzanalyse (DE-588)4133000-6 s Python Programmiersprache (DE-588)4434275-5 s DE-604 Erscheint auch als Online-Ausgabe 10.1007/978-3-030-29141-9 978-3-030-29141-9 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032900875&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Garita, Mauricio Applied quantitative finance using Python for financial analysis Finanzmathematik (DE-588)4017195-4 gnd Finanzanalyse (DE-588)4133000-6 gnd Python Programmiersprache (DE-588)4434275-5 gnd |
| subject_GND | (DE-588)4017195-4 (DE-588)4133000-6 (DE-588)4434275-5 |
| title | Applied quantitative finance using Python for financial analysis |
| title_auth | Applied quantitative finance using Python for financial analysis |
| title_exact_search | Applied quantitative finance using Python for financial analysis |
| title_exact_search_txtP | Applied quantitative finance using Python for financial analysis |
| title_full | Applied quantitative finance using Python for financial analysis Mauricio Garita |
| title_fullStr | Applied quantitative finance using Python for financial analysis Mauricio Garita |
| title_full_unstemmed | Applied quantitative finance using Python for financial analysis Mauricio Garita |
| title_short | Applied quantitative finance |
| title_sort | applied quantitative finance using python for financial analysis |
| title_sub | using Python for financial analysis |
| topic | Finanzmathematik (DE-588)4017195-4 gnd Finanzanalyse (DE-588)4133000-6 gnd Python Programmiersprache (DE-588)4434275-5 gnd |
| topic_facet | Finanzmathematik Finanzanalyse Python Programmiersprache |
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