By Pavel Ryzhov
ISBN-10: 1782169431
ISBN-13: 9781782169437
Get an in-depth research of monetary time sequence from the viewpoint of a useful programmer
Overview
- Understand the rules of monetary stochastic processes
- Build strong types fast and efficiently
- Tackle the complexity of parallel programming
In Detail
Haskell is without doubt one of the 3 such a lot influential practical programming languages to be had this day in addition to Lisp and conventional ML. while used for monetary research, you could in achieving a much-improved point of prediction and transparent challenge descriptions.
Haskell monetary info Modeling and Predictive Analytics is a hands-on advisor that employs a mixture of idea and perform. beginning with the fundamentals of Haskell, this e-book walks you thru the maths concerned and the way this can be applied in Haskell.
The e-book begins with an creation to the Haskell platform and the Glasgow Haskell Compiler (GHC). you are going to then know about the fundamentals of excessive frequency monetary facts arithmetic in addition to how one can enforce those mathematical algorithms in Haskell.
You also will find out about the most well-liked Haskell libraries and frameworks like Attoparsec, QuickCheck, and HMatrix. additionally, you will familiarize yourself with database entry utilizing Yesod’s patience library, permitting you to maintain your facts prepared. The booklet then strikes directly to speak about the math of counting strategies and autoregressive conditional period versions, that are very common modeling instruments for top frequency tick information. on the finish of the booklet, additionally, you will find out about the volatility prediction technique.
With Haskell monetary information Modeling and Predictive Analytics, you are going to examine every thing you must learn about monetary information modeling and predictive analytics utilizing practical programming in Haskell.
What you are going to examine from this book
- Learn how you can construct a repair protocol parser
- Calibrate counting strategies on actual data
- Estimate version parameters utilizing the utmost probability Estimation method
- Use Akaike criterion to decide on the best-fit model
- Learn the best way to practice property-based trying out on a generated set of enter data
- Calibrate ACD types with the Kalman filter
- Understand parallel programming in Haskell
- Learn extra approximately volatility prediction
Approach
This booklet is a hands-on consultant that teaches readers easy methods to use Haskell's instruments and libraries to research info from real-world resources in an easy-to-understand manner.
Who this ebook is written for
This publication is excellent for builders who're new to monetary information modeling utilizing Haskell. A uncomplicated wisdom of practical programming isn't required yet might be necessary. An curiosity in excessive frequency finance is essential.
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Extra resources for Haskell Financial Data Modeling and Predictive Analytics
Sample text
Hs You can use putStr/putStrLn to output a string to the standard output and getLine to read a line from the standard input. Summary In this chapter, we learned a bit of Haskell history, made a quick overview of language basics, and figured out how to install the Haskell platform. In the next chapter, we will continue getting into more advanced Haskell features, such as template Haskell and quasiquotes, along with building a tick database from CSV sources. Chapter 2. Getting your Hands Dirty Market microstructure studies usually means messing a lot of data.
As I had to use a legacy database table, appropriate mappings should be provided to Persistent for getting the right column names. Moreover, it is usually better to move entity definitions into a separate module. hs. In the legacy table description the sql option allows us to define a native SQL table and/or column to be use in generated SQL statements. There should be no whitespace between the equality sign and definitions; otherwise, quasiquoter will ignore the options and EntityDefs would be wrong.
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Haskell Financial Data Modeling and Predictive Analytics by Pavel Ryzhov
by Jason
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