eBooks-it.org Logo
eBooks-IT.org Inner Image

Haskell Financial Data Modeling and Predictive Analytics

Haskell Financial Data Modeling and Predictive Analytics Image

Book Details:

Publisher:Packt Publishing
Series: Packt
Author:Pavel Ryzhov
Edition:1
ISBN-10:1782169431
ISBN-13:9781782169437
Pages:112
Published:Oct 25 2013
Posted:Nov 19 2014
Language:English
Book format:PDF
Book size:3.27 MB

Book Description:

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 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. You will also learn about the most popular Haskell libraries and frameworks like Attoparsec, QuickCheck, and HMatrix. You will also become familiar with database access using Yesods Persistence library, allowing you to keep your data organized. The book then moves on to discuss the mathematics of counting processes and autoregressive conditional duration models, which are quite common modeling tools for high frequency tick data. At the end of the book, you will also learn about the volatility prediction technique. 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 parser Calibrate counting processes on real data Estimate model parameters using the Maximum Likelihood Estimation method Use Akaike criterion to choose the best-fit model Learn how to perform property-based testing on a generated set of input data Calibrate ACD models with the Kalman filter Understand parallel programming in Haskell Learn more about volatility prediction Approach 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.

Download Link:

Related Books:

Commercial Data Mining

Processing, Analysis and Modeling for Predictive Analytics Projects
Commercial Data Mining Image
Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cros...

Data Mining and Business Analytics with R

Data Mining and Business Analytics with R Image
Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topic...

Cassandra Data Modeling and Analysis

Cassandra Data Modeling and Analysis Image
Design, build, and analyze your data intricately using Cassandra About This BookBuild professional data models in Cassandra using CQL and appropriate indexesGrasp the Model-By-Query techniques through working examplesStep-by-step tutorial of a stock market technical analysis applicationWho This Book Is ForIf you are interested in Cassandra and want to develop real-world analysis applications, then this book is perfect for you. It would be helpful to have prior knowledge of NoSQL database. In Detail Starting with a quick introduction to Cassandra, this book flows through various aspects such as fundamental data modeling approaches, selection of data types, designing a data model, choosing suitable keys and indexes through to a real-world application, ...



2007 - 2021 © eBooks-IT.org