https://www.haskell.org/
    https://www.haskell.org/documentation
https://en.wikipedia.org/wiki/Haskell_(programming_language)
very good: http://learnyouahaskell.com/syntax-in-functions

books:
    terse:
    https://www.amazon.com/Haskell-Financial-Modeling-Predictive-Analytics/dp/1782169431        
        Haskell Financial Data Modeling and Predictive Analytics Paperback – October 25, 2013
            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

    https://www.amazon.com/Haskell-Analysis-Cookbook-Nishant-Shukla/dp/1783286334/ref=pd_sim_14_2?_encoding=UTF8&pd_rd_i=1783286334&pd_rd_r=8BRP36CESAK7B08ADZS4&pd_rd_w=sStWy&pd_rd_wg=UdmKs&psc=1&refRID=8BRP36CESAK7B08ADZS4
        no? algo proofs/docs


    finance-programming-platforms in general:
        http://falconair.github.io/2015/01/30/composingcontracts.html
        
        Simulating a financial exchange in Scala
            processing orders ... 
                http://falconair.github.io/2015/01/05/financial-exchange.html

    Packages:

        Data Visualization
            https://github.com/netogallo/Visualizer
                Just words?
                    Features
                    To archive the vision established above, the following features are required:
                        Visualization mechanism for numbers, vectors and matrices. Each with it's own type-class.
                        Plotting mechanism for time series.
                        The parameters of the plot have to be controllable with the UI. 
                        The user can choose to hide several dimensions, zoom in, zoom out and navigate through each axis within the plot via scrolling.
                        Mechanism to add additional calculations to display alongside visualizations or plots (ie. mean square error, spectral radius, eigen-values, etc.)
                        Automatic creation of configuration. Possibly by crating a hidden directory whenever the library is launched, 
                        this way every time the project is opened from the same path, all the plots are plotted like last time.
                        Support to link several dependent values and objects in order to create groups self updating plots.

        Haskell 2 JavaScript/Web:
            https://hackage.haskell.org/package/QuickPlot


        A statistics visualization library built on top of Chart inspired by Seaborn. Amby
            https://hackage.haskell.org/package/amby