Blog Archives

Introducing RITCH: Parsing ITCH Files in R (Finance & Market Microstructure)

November 30, 2017
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Introducing RITCH: Parsing ITCH Files in R (Finance & Market Microstructure)

Recently I was faced with a file compressed in NASDAQ’s ITCH-protocol, as I wasn’t able to find an R-package that parses and loads the file to R for me, I spent (probably) way to much time to write one, so here it is. But you might wonder, what exactly is ITCH and why should I

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The Importance of Out-of-Sample Tests and Lags in Forecasts and Trading Algorithms

October 14, 2016
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The Importance of Out-of-Sample Tests and Lags in Forecasts and Trading Algorithms

I recently had the opportunity to listen to some great minds in the area of high-frequency data and trading. While I won’t go into the details about what has been said, I wanted to illustrate the importance of proper out-of-sample testing and proper variable lags in potential trade algorithms or arbitrage models that has been

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A Gentle Introduction to Finance using R: Efficient Frontier and CAPM – Part 1

May 24, 2016
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A Gentle Introduction to Finance using R: Efficient Frontier and CAPM – Part 1

The following entry explains a basic principle of finance, the so-called efficient frontier and thus serves as a gentle introduction into one area of finance: “portfolio theory” using R. A second part will then concentrate on the Capital-Asset-Pricing-Method (CAPM) and its assumptions, implications and drawbacks. Note: All code that is needed for the simulations, data

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Speeding “Bayesian Power Analysis t-test” up with Snowfall

January 15, 2016
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Speeding “Bayesian Power Analysis t-test” up with Snowfall

This is a direct (though minor) answer to Daniel’s blogpost Power Analysis for default Bayesian t-tests, which I found very interesting, as I have been trying to get my head around Bayesian statistics for quite a while now. However, one thing that bugs me, is the time needed for the simulation. On my machine it

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Simulating backtests of stock returns using Monte-Carlo and snowfall in parallel

September 23, 2015
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Simulating backtests of stock returns using Monte-Carlo and snowfall in parallel

You could say that the following post is an answer/comment/addition to Quintuitive, though I would consider it as a small introduction to parallel computing with snowfall using the thoughts of Quintuitive as an example. A quick recap: Say you create a model that is able to forecast 60% of market directions (that is, in 6

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Getting that X with the Glog function and Lambert’s W

July 16, 2015
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Getting that X with the Glog function and Lambert’s W

Facing a simple, yet frustrating formula like this and the task to solve it for x left me googling around for hours until I found salvation in Wolfram Alpha, Wikipedia, and a nice blog post with R-syntax to solve a similar equation. Using the results from Wolfram Alpha I was able to find the solution with the ‘gsl’

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Getting started with PostgreSQL in R

May 18, 2015
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Getting started with PostgreSQL in R

When dealing with large datasets that potentially exceed the memory of your machine it is nice to have another possibility such as your own server with an SQL/PostgreSQL database on it, where you can query the data in smaller digestible chunks. For example, recently I was facing a financial dataset of 5 GB. Although 5

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Agent Based Modelling with data.table OR how to model urban migration with R

May 12, 2015
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Agent Based Modelling with data.table OR how to model urban migration with R

Introduction Recently I found a good introduction to the Shelling-Segregation Model and to Agent Based Modelling (ABM) for Python (Binpress Article by Adil). The model follows an ABM approach to simulate how urban segregation can be explained. I will concentrate on the R-code, if you want to know more about the Shelling-Segregation Model (which brought

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Using rvest and dplyr to look at aviation incidents

April 30, 2015
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Using rvest and dplyr to look at aviation incidents

For a project I recently faced the issue of getting a database of all aviation incidents. As I really wanted to try Hadley’s new rvest-package, I thought I will give it a try and share the code with you. The data of aviation incidents starting in 1919 from the Aviation Safety Network can be found

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