Why switch from Excel to Julia for your predictive analysis?

  • Monte-Carlo simulation in Julia is 1500x faster than Excel
  • The ability to integrate data APIs to streamline data preperation in your workflows.
  • DataFrames.jl blows the doors off Pandas
  • Julia is the next frontier for economic analysis
  • Julia is so impressive for numerical computing that we built an entire open source project called MCHammer.jl dedicated to building models quickly and easily

 

 

Why use MCHammer.jl,

  • Its the only Monte-Carlo package with Rank Order Correlation methods
  • MCHammer streamlines your model development with simple excel-like formulas
  • Can be used to take an Excel model and put into your production systems (ERP, CRM...)
  • Applies a similar approach to modelling as Oracle Crystal Ball and Palisade @RISK, so the learning curve is short.
  • Did we mention it's fast?

MCHammer.jl Project Overview

The MC in MCHammer.jl stands for Monte-Carlo. This tool is inspired by seminal tools such as Oracle Crystal Ball and Palisade @RISK for their ability to quickly build and analyze Monte-Carlo simulation models using excel functions and automations. MCHammer.jl replicates their logic, functions and elemental tools in Julia, thus significantly reducing the time, complexity and effort to perform advanced modeling and simulation. Some key tools include

  • Rank Correlation
  • Risk Events
  • Simulated Time-Series using GBM
  • Simulation Charts in one function (Trend, Histogram, Density, Sensitivity)

If you have questions or want to get actively involved in developping MCHammer.jl, please reach out to [email protected]

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