e-book Haskell Financial Data Modeling and Predictive Analytics

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[Book] Haskell Financial Data Modeling and Predictive Analytics : haskell

Business Management. Enterprise Resource Planning. Operations Management. Real Time Communication. UI Development. Video Editing. Get an in-depth analysis of financial time series from the perspective of a functional programmer. Skip to the end of the images gallery.

Skip to the beginning of the images gallery. Read Now Look inside. More Information Learn 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 About Haskell is one of the three most influential functional programming languages available today along with Lisp and Standard ML.

Table of contents. The Haskell platform Quick tour of Haskell Summary. Point process Counting process Durations Poisson process calibration Renewal process calibration Cox process calibration Model selection The secant root-finding algorithm Summary. Historic volatility estimators Volatility estimator framework Alternative volatility estimators Forecasting volatility Summary. Common usage Packaging with Cabal Cabal in sandbox Summary. Add to Cart. What do I get with a Packt subscription?

Exclusive monthly discount - no contract Unlimited access to entire Packt library of over eBooks and Videos new titles added every month on new and emerging tech. What do I get with a Video? Download this Video course in MP4 format DRM FREE - read and interact with your content when you want, where you want, and how you want Immediately access your video course for viewing or download through your Packt account.

What do I get with an eBook? Add To Cart. Start a FREE day trial. Related Products. 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. Understand the foundations of financial stochastic processes Build robust models quickly and efficiently Tackle the complexity of parallel programming.

The Haskell platform. Quick tour of Haskell. The domain model. The Attoparsec library. Parsing plain text files.

Parsing files in applicative style. Outlier detection. Persistent ORM framework. Point process.


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Counting process. Poisson process calibration. Renewal process calibration. Cox process calibration. Model selection. The secant root-finding algorithm. The ARMA model definition. No description, website, or topics provided. Branch: master New pull request. Find File. Download ZIP. Sign in Sign up. Launching GitHub Desktop Go back. Launching Xcode Launching Visual Studio Latest commit May 11, You signed in with another tab or window.

Reload to refresh your session. You signed out in another tab or window. May 11, Developing Web Apps with Haskell and Yesod, 2nd.