Haskell Financial Data Modeling and Predictive Analytics

Content: Cover
 Copyright
 Credits
 About the Author
 About the Reviewers
 www.PacktPub.com
 Table of Contents
 Preface
 Chapter 1: Getting Started with 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
 Chapter 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 GADTsPersistent ORM framework
 Declaring entities
 Inserting and updating data
 Fetching data
 Summary
 Chapter 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 modifiersSummary
 Chapter 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
 Autocorrelation plot
 QML estimation
 State space model for ACD
 Summary
 Chapter 5: Volatility
 Historic volatility estimators
 Volatility estimator framework
 Alternative volatility estimators
 The Parkinson\'s number. The Garman-Klass estimatorThe 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
 Chapter 6: Advanced Cabal
 Common usage
 Packaging with Cabal
 Cabal in sandbox
 Summary
 Appendix: References
 Index.