This is a post that has been a long time in the making. Following on from the excellent Stanford Machine Learning Course I have made examples of the main algorithms covered in R.We have Linear RegressionFollowed by Neural NetworksAnd Support ...

I recently posted an introduction to the Kaggle Algorithmic Trading Challenge, which I competed in.I said that I would post about my experiences, and this is hopefully the first of a series. We were given tick data from the London Stock Exchange(specifically, the FTSE 100) over random time intervals during parts of 37 days. Each data row...

Quantitative Finance, Technical Trading & Analysis. Fotis Papailias, Dimitrios Thomakos Fotis Quantitative Finance & Technical Trading R-Code Yahoo Finance Data LoadingHere is an R script that downloads Yahoo Finance Data without the need of additional packages/libraries. In the .zip file is the code with an example on how to use it. Download the code here: You can also...

R is used extensively in the financial industry; many of my recent clients have been working in or developing products for the financial sector. Some common applications are to use R to analyze market data and evaluate quantitative trading strategies. ...

R is used extensively in the financial industry; many of my recent clients have been working in or developing products for the financial sector. Some common applications are to use R to analyze market data and evaluate quantitative trading strategies. Custom solutions are almost always the best way to do this, but the quantstrat package The post Installing...

Stumbling blocks on the trek from theory to practical optimization in fund management. Problem 1: portfolio optimization is too hard If you are using a spreadsheet, then this is indeed a problem. Spreadsheets are dangerous when given a complex task. Portfolio optimization qualifies as complex in this context (complex in data requirements). If you are … Continue reading...

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