Haskell Financial Data Modeling and Predictive Analytics PDF
Preview Haskell Financial Data Modeling and Predictive Analytics
Haskell Financial Data Modeling and Predictive Analytics Table of Contents Haskell Financial Data Modeling and Predictive Analytics Credits About the Author About the Reviewers www.PacktPub.com Support files, eBooks, discount offers and more Why Subscribe? Free Access for Packt account holders Preface What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support Downloading the example code Errata Piracy Questions 1. Getting Started with the Haskell Platform The Haskell platform Quick tour of Haskell Laziness Functions as first-class citizens Datatypes Type classes Pattern matching Monads The IO monad Summary 2. Getting your Hands Dirty The domain model The Attoparsec library Parsing plain text files Parsing files in applicative style Outlier detection Essential mathematical packages Grubb's test for outliers Template Haskell, quasiquotes, type families, and GADTs Persistent ORM framework Declaring entities Inserting and updating data Fetching data Summary 3. Measuring Tick Intervals Point process Counting process Durations Experimental durations Maximum likelihood estimation Generic MLE implementation Poisson process calibration MLE estimation Akaike information criterion Haskell implementation Renewal process calibration MLE estimation Cox process calibration MLE estimation Model selection The secant root-finding algorithm The QuickCheck test framework QuickCheck test data modifiers Summary 4. Going Autoregressive The ARMA model definition The Kalman filter Matrix manipulation libraries in Haskell HMatrix basics The Kalman filter in Haskell The state-space model for ARMA ARMA in Haskell ACD model extension Experimental conditional durations The Autocorrelation function Stream fusion The Autocorrelation plot QML estimation State-space model for ACD Summary 5. Volatility Historic volatility estimators Volatility estimator framework Alternative volatility estimators The Parkinson's number The Garman-Klass estimator The Rogers-Satchel estimator The Yang-Zhang estimator Choosing a volatility estimator The variation ratio method Forecasting volatility The GARCH (1,1) model Maximum likelihood estimation of parameters Implementation details Parallel computations Code benchmarking Haskell Run-Time System The divide-and-conquer approach GARCH code in parallel Evaluation strategy Summary 6. Advanced Cabal Common usage Packaging with Cabal Cabal in sandbox Summary A. References Index Haskell Financial Data Modeling and Predictive Analytics Haskell Financial Data Modeling and Predictive Analytics Copyright © 2013 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. First published: October 2013 Production Reference: 1221013 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.. ISBN 978-1-78216-943-7 www.packtpub.com Cover Image by Duraid Fatouhi (<[email protected]>) Credits Author Pavel Ryzhov Reviewers Gregory Collins Ivan Perez Acquisition Editor Sam Birch Commissioning Editor Harsha Bharwani Technical Editors Krishnaveni Haridas Chandni Maishery Project Coordinator Joel Goveya Proofreader Clyde Jenkns Indexer Tejal Soni Graphics Ronak Dhruv Production Coordinator Nilesh R. Mohite Cover Work Nilesh R. Mohite
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