Haskell Financial Data Modeling and Predictive Analytics

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Haskell Financial Data Modeling and Predictive Analytics by Pavel Ryzhov
2013 | ISBN: 1782169431 | English | 112 pages | PDF | 3 MB


Get an in-depth analysis of financial time series from the perspective of a functional programmer

Overview

Understand the foundations of financial stochastic processes
Build robust models quickly and efficiently
Tackle the complexity of parallel programming

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Haskell Financial Data Modeling and Predictive Analytics by Pavel Ryzhov2013 | ISBN: 1782169431 | English | 112 pages | PDF | 3 MB

Get an in-depth analysis of financial time series from the perspective of a functional programmer
Overview
Understand the foundations of financial stochastic processesBuild robust models quickly and efficientlyTackle the complexity of parallel programming
In Detail
Haskell is one of the three most influential functional programming languages available today along with Lisp and Standard ML. When used for financial analysis, you can achieve a much-improved level of prediction and clear problem descriptions.
Haskell Financial Data Modeling and Predictive Analytics is a hands-on guide that employs a mix of theory and practice. Starting with the basics of Haskell, this book walks you through the mathematics involved and how this is implemented in Haskell.
The book starts with an introduction to the Haskell platform and the Glasgow Haskell Compiler (GHC). You will then learn about the basics of high frequency financial data mathematics as well as how to implement these mathematical algorithms in Haskell.

With Haskell Financial Data Modeling and Predictive Analytics, you will learn everything you need to know about financial data modeling and predictive analytics using functional programming in Haskell.
What you will learn from this book
Learn how to build a FIX protocol parserCalibrate counting processes on real dataEstimate model parameters using the Maximum Likelihood Estimation methodUse Akaike criterion to choose the best-fit modelLearn how to perform property-based testing on a generated set of input dataCalibrate ACD models with the Kalman filterUnderstand parallel programming in HaskellLearn more about volatility predictionApproach
This book is a hands-on guide that teaches readers how to use Haskell's tools and libraries to analyze data from real-world sources in an easy-to-understand manner.
Who this book is written for
This book is great for developers who are new to financial data modeling using Haskell. A basic knowledge of functional programming is not required but will be useful. An interest in high frequency finance is essential.

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Tags: Predictive, Analytics, Modeling, Financial, Haskell
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