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381Publicado 2017Tabla de Contenidos: “…Machine generated contents note: Preface 1 I Introduction to Volatility and Variance 3 1 Derivatives, Volatility and Variance 5 1.1 Option Pricing and Hedging 5 1.2 Notions of Volatility and Variance 7 1.3 Listed Volatility and Variance Derivatives 8 1.3.1 The US History 8 1.3.2 The European History 10 1.3.3 Volatility of Volatility Indexes 11 1.3.4 Products Covered in this Book 12 1.4 Volatility and Variance Trading 12 1.4.1 Volatility Trading 13 1.4.2 Variance Trading 14 1.5 Python as Our Tool of Choice 15 1.6 Quick Guide Through Rest of the Book 15 2 Introduction to Python 19 2.1 Python Basics 19 2.1.1 Data Types 19 2.1.2 Data Structures 21 2.1.3 Control Structures 23 2.1.4 Special Python Idioms 24 2.2 NumPy 27 2.3 matplotlib 32 2.4 pandas 36 2.4.1 pandas Data Frame class 36 2.4.2 Input-Output Operations 40 2.4.3 Financial Analytics Examples 43 2.5 Conclusions 48 3 Model-Free Replication of Variance 49 3.1 Introduction 49 3.2 Spanning with Options 49 3.3 Log Contracts 50 3.4 Static Replication of Realized Variance and Variance Swaps 51 3.5 Constant Dollar Gamma Derivatives and Portfolios 51 3.6 Practical Replication of Realized Variance 52 3.7 VSTOXX as Volatility Index 57 3.8 Conclusions 59 II Listed Volatility Derivatives 61 4 Data Analysis and Strategies 63 4.1 Introduction 63 4.2 Retrieving Base Data 63 4.2.1 EURO STOXX 50 Data 63 4.2.2 VSTOXX Data 65 4.2.3 Combining the Data Sets 67 4.2.4 Saving the Data 68 4.3 Basic Data Analysis 69 4.4 Correlation Analysis 72 4.5 Constant Proportion Investment Strategies 77 4.6 Conclusions 82 5 VSTOXX Index 83 5.1 Introduction 83 5.2 Collecting Option Data 84 5.3 Calculating the Sub-Indexes 91 5.3.1 The Algorithm 91 5.4 Calculating the VSTOXX Index 98 5.5 Conclusions 101 5.6 Python Scripts 103 5.6.1 index_collect_option_data.py 103 5.6.2 index_subindex_calculation.py 107 5.6.3 index_vstoxx_calculation.py 110 6 Valuing Volatility Derivatives 113 6.1 Introduction 113 6.2 The Valuation Framework 113 6.3 The Futures Pricing Formula 114 6.4 The Option Pricing Formula 115 6.5 Monte Carlo Simulation 118 6.6 Automated Monte Carlo Tests 123 6.6.1 The Automated Testing 123 6.6.2 The Storage Functions 126 6.6.3 The Results 128 6.7 Model Calibration 133 6.7.1 The Option Quotes 133 6.7.2 The Calibration Procedure 134 6.7.3 The Calibration Results 138 6.8 Conclusions 141 6.9 Python Scripts 141 6.9.1 srd_functions.py 141 6.9.2 srd_simulation_analysis.py 145 6.9.3 srd_simulation_results.py 148 6.9.4 srd_model_calibration.py 151 7 Advanced Modeling of the VSTOXX Index 155 7.1 Introduction 155 7.2 Market Quotes for Call Options 155 7.3 The SRJD Model 158 7.4 Term Structure Calibration 159 7.4.1 Futures Term Structure 159 7.4.2 Shifted Volatility Process 163 7.5 Option Valuation by Monte Carlo Simulation 164 7.5.1 Monte Carlo Valuation 165 7.5.2 Technical Implementation 165 7.6 Model Calibration 169 7.6.1 The Python Code 169 7.6.2 Short Maturity 171 7.6.3 Two Maturities 173 7.6.4 Four Maturities 175 7.6.5 All Maturities 176 7.7 Conclusions 181 7.8 Python Scripts 181 7.8.1 srjd_fwd_calibration.py 181 7.8.2 srjd_simulation.py 183 7.8.3 srjd_model_calibration.py 185 8 Terms of the VSTOXX and its Derivatives 191 8.1 The EURO STOXX 50 Index 191 8.2 The VSTOXX Index 192 8.3 VSTOXX Futures Contracts 192 8.4 VSTOXX Options Contracts 193 8.5 Conclusions 195 III Listed Variance Derivatives 197 9 Realized Variance and Variance Swaps 199 9.1 Introdution 199 9.2 Realized Variance 199 9.3 Variance Swaps 204 9.3.1 Definition of a Variance Swap 204 9.3.2 Numerical Example 205 9.3.3 Mark-to-Market 208 9.3.4 Vega Sensitivity 209 9.3.5 Variance Swap on the EURO STOXX 50 211 9.4 Variance vs. …”
Libro electrónico -
382por Mullen, Tony, 1971-Tabla de Contenidos: “…Animating and Rendering the AnimaticChapter 4: Modeling; Organic Modeling Techniques; Cloth and Clothing; Inorganic Modeling; Chapter 5: Rigging Characters; Using Armatures, Modifiers, and Deformation; Mastering Complex PyDrivers; Controlling Textures with PyDrivers; Chapter 6: Animating a Character Scene; Preparing to Animate; Implementing the Stages of Character Animation; Creating Facial Animation; Adding Cloth and Hair; Chapter 7: Descent into the Maelstrom; Setting the Scene; Using Textures, Modifiers, and Simulation; Touching Up the Shot with Node-Based Compositing…”
Publicado 2010
Libro electrónico -
383Publicado 2021“…Developers who want to create web applications with Python and plan to implement TDD methodology with PyTest will find this book useful. Basic knowledge of Python programming is required…”
Libro electrónico -
384Publicado 2022“…You will start with the basics of Python, Pandas, Scikit-learn, NumPy, Keras, Prophet, statsmod, SciPy, and more. You will learn statistics and probability for data science in detail. …”
Video -
385Publicado 2018“…Einführung in alle Sprachgrundlagen: Klassen, Objekte, Vererbung, Dictionaries Benutzungsoberflächen und Multimediaanwendungen mit PyQt, Datenbanken, XML und Internet-Programmierung Wissenschaftliches Rechnen mit NumPy, parallele Verarbeitung großer Datenmengen, Datenvisualisierung mit Matplotlib Übungen mit Musterlösungen zu jedem Kapitel Die Skriptsprache Python ist mit ihrer einfachen Syntax hervorragend für Einsteiger geeignet, um modernes Programmieren zu lernen. …”
Libro electrónico -
386Publicado 2019“…Das umfassende Praxisbuch Einführung in alle Sprachgrundlagen: Klassen, Objekte, Vererbung, Dictionaries Benutzungsoberflächen und Multimediaanwendungen mit PyQt, Datenbanken, XML und Internet-Programmierung Wissenschaftliches Rechnen mit NumPy, parallele Verarbeitung großer Datenmengen, Datenvisualisierung mit Matplotlib Übungen mit Musterlösungen zu jedem Kapitel Die Skriptsprache Python ist mit ihrer einfachen Syntax hervorragend für Einsteiger geeignet, um modernes Programmieren zu lernen. …”
Libro electrónico -
387Publicado 2021“…A practical guide simplifying discrete math for curious minds and demonstrating its application in solving problems related to software development, computer algorithms, and data scienceKey FeaturesApply the math of countable objects to practical problems in computer scienceExplore modern Python libraries such as scikit-learn, NumPy, and SciPy for performing mathematicsLearn complex statistical and mathematical concepts with the help of hands-on examples and expert guidanceBook DescriptionDiscrete mathematics deals with studying countable, distinct elements, and its principles are widely used in building algorithms for computer science and data science. …”
Libro electrónico -
388Publicado 2021Tabla de Contenidos: “…-- Chapter 3: OWL Ontologies -- Chapter 4: Accessing Ontologies in Python -- Chapter 5: Creating and Modifying Ontologies in Python -- Chapter 6: Constructs, Restrictions, Class Properties -- Chapter 7: Automatic Reasoning -- Chapter 8: Annotations, Multilingual Texts and Full Text Search -- Chapter 9: Using Medical Terminologies with PyMedTermino and UMLS -- Chapter 10: Mixing Python and OWL -- Chapter 11: Working with RDF Triples and Worlds…”
Libro electrónico -
389por Seitz, JustinTabla de Contenidos: “…5: Immunity Debugger -- The Best of Both Worlds5.1 Installing Immunity Debugger; 5.2 Immunity Debugger 101; 5.2.1 PyCommands; 5.2.2 PyHooks; 5.3 Exploit Development; 5.3.1 Finding Exploit-Friendly Instructions; 5.3.2 Bad-Character Filtering; 5.3.3 Bypassing DEP on Windows; 5.4 Defeating Anti-Debugging Routines in Malware; 5.4.1 IsDebuggerPresent; 5.4.2 Defeating Process Iteration; 6: Hooking; 6.1 Soft Hooking with PyDbg; 6.2 Hard Hooking with Immunity Debugger; 7: DLL and Code Injection; 7.1 Remote Thread Creation; 7.1.1 DLL Injection; 7.1.2 Code Injection; 7.2 Getting Evil; 7.2.1 File Hiding…”
Publicado 2009
Libro electrónico -
390Publicado 2018Tabla de Contenidos: “…. -- Chapter 7: Improving Python Performance with PyPy -- Introduction -- What is PyPy? -- Getting ready -- How to do it... -- There's more... -- What is RPython? …”
Libro electrónico -
391Publicado 2018Tabla de Contenidos: “…-- Plotting with glyphs -- Creating line plots -- Creating bar plots -- Creating patch plots -- Creating scatter plots -- Customizing glyphs -- Summary -- Chapter 3: Plotting with different Data Structures -- Technical requirements -- Creating plots using NumPy arrays -- Creating line plots using NumPy arrays -- Creating scatter plots using NumPy arrays -- Creating plots using pandas DataFrames -- Creating a time series plot using a pandas DataFrame -- Creating scatter plots using a pandas DataFrame -- Creating plots with ColumnDataSource -- Creating a time series plot using the ColumnDataSource -- Creating a scatter plot using the ColumnDataSource -- Summary -- Chapter 4: Using Layouts for Effective Presentation -- Technical requirements -- Creating multiple plots along the same row -- Creating multiple plots in the same column -- Creating multiple plots in a row and column -- Creating multiple plots using a tabbed layout -- Creating a robust grid layout -- Linking multiple plots together -- Summary -- Chapter 5: Using Annotations, Widgets, and Visual Attributes for Visual Enhancement -- Technical requirements -- Creating annotations to convey supplemental information -- Adding titles to plots -- Adding legends to plots -- Adding color maps to plots -- Creating widgets to add interactivity to plots…”
Libro electrónico -
392Publicado 2017Tabla de Contenidos: “…Analyzing big data -- Introduction to data analysis with Scala and Spark -- Recommending music and the audioscrobbler data set -- Predicting forest cover with decision trees -- Anomaly detection in network traffic with K-means clustering -- Understanding Wikipedia with latent semantic analysis -- Analyzing co-occurrence networks with GraphX -- Geospatial and temporal data analysis on the New York City taxi trip data -- Estimating financial risk through Monte Carlo simulation -- Analyzing genomics data and the BDG project -- Analyzing neuroimaging data with PySpark and Thunder…”
Libro electrónico -
393Publicado 2023Tabla de Contenidos: “…Table of Contents Introduction to Data Ingestion Principals of Data Access – Accessing your Data Data Discovery – Understanding Our Data Before Ingesting It Reading CSV and JSON Files and Solving Problems Ingesting Data from Structured and Unstructured Databases Using PySpark with Defined and Non-Defined Schemas Ingesting Analytical Data Designing Monitored Data Workflows Putting Everything Together with Airflow Logging and Monitoring Your Data Ingest in Airflow Automating Your Data Ingestion Pipelines Using Data Observability for Debugging, Error Handling, and Preventing Downtime…”
Libro electrónico -
394Publicado 2015Tabla de Contenidos: “…Analyzing big data -- Introduction to data analysis with Scala and Spark -- Recommending music and the audioscrobbler data set -- Predicting forest cover with decision trees -- Anomaly detection in network traffic with K-means clustering -- Understanding Wikipedia with latent semantic analysis -- Analyzing co-occurrence networks with GraphX -- Geospatial and temporal data analysis on the New York City taxi trip data -- Estimating financial risk through Monte Carlo simulation -- Analyzing genomics data and the BDG project -- Analyzing neuroimaging data with PySpark and Thunder…”
Libro electrónico -
395Publicado 2016Tabla de Contenidos: “…Creating a background and foreground index in the shellCreating and understanding sparse indexes; Expiring documents after a fixed interval using the TTL index; Expiring documents at a given time using the TTL index; Chapter 3: Programming Language Drivers; Introduction; Executing query and insert operations with PyMongo; Executing update and delete operations using PyMongo; Implementing aggregation in Mongo using PyMongo; Executing MapReduce in Mongo using PyMongo; Executing query and insert operations using a Java client; Executing update and delete operations using a Java client…”
Libro electrónico -
396Publicado 2015Tabla de Contenidos: “…Basic collision detection gameSummary; Chapter 6: PyPlatformer; An introduction to game design; Level design; Platformer skills; Component-based game engines; Introducing Pymunk; Building a game framework; Adding physics; Renderable components; The Camera component; The InputManager module; The Game class; Developing PyPlatformer; Creating the platforms; Adding pickups; Shooting!…”
Libro electrónico -
397Publicado 2018“…En esta investigación presentamos el estado del arte sobre los conceptos de Gobierno de TI, y su aporte de valor a las PyMEs ; así mismo se hace una revisión de la importancia de las PyMEs en Chile y como la implementación de un marco de referencia para el gobierno y gestión de las TI incrementaría el aportede valor a la empresa…”
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Tesis -
398Publicado 1996Tabla de Contenidos: “…. -- Bibliografia Algunes remarques sobre les nocions d'exolinguisme i de bilinguisme / Bernard Py. -- P. 47-59. -- Bibliografia Una proposta des de l'area de llengua estrangera : les causes comunes poden unir / M. …”
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Artículo -
399Publicado 2016“…What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. …”
Libro electrónico -
400Publicado 2016“…An example-rich, comprehensive guide for all of your Python computational needs About This Book Your ultimate resource for getting up and running with Python numerical computations Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules A hands-on guide to implementing mathematics with Python, with complete coverage of all the key concepts Who This Book Is For This book is for anyone who wants to perform numerical and mathematical computations in Python. …”
Libro electrónico