DataRTime series modelling
A Simple Trick for Dealing with Overlapping Data
Last week, we looked at simple data analysis techniques to test for persistence. But we only looked at a feature
A Simple Trick for Dealing with Overlapping Data
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Quant tradingRThink like a traderTools of the tradeData Analysis and Edge Extraction for Traders
Towards the end of last year, we ran a couple of free Zoom webinars on: Here are the recordings: Basics
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RTools of the trade
More Intuitive Joins in dplyr 1.1.0 – how to do an asof join on trades and quotes data
dplyr 1.1.0 was a significant release that makes several common data operations more syntactically intuitive. The most significant changes relate
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Quant tradingRWorking with Tidy Financial Data in tidyr
Holding data in a tidy format works wonders for one’s productivity. Here we will explore the tidyr package, which is
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RTools of the tradePerformant R Programming: Chunking a Problem into Smaller Pieces
When data is too big to fit into memory, one approach is to break it into smaller pieces, operate on
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Quant tradingRTools of the tradeHow to Fill Gaps in Large Stock Data Universes Using tidyr and dplyr
When you’re working with large universes of stock data you’ll come across a lot of challenges: Stocks pay dividends and
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RTools of the tradeHandling a Large Universe of Stock Price Data in R: Profiling with profvis
Recently, we wrote about calculating mean rolling pairwise correlations between the constituent stocks of an ETF. The tidyverse tools dplyr
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RTools of the tradeHow to Wrangle JSON Data in R with jsonlite, purr and dplyr
Working with modern APIs you will often have to wrangle with data in JSON format. This article presents some tools
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RTools of the tradeHow to Calculate Rolling Pairwise Correlations in the Tidyverse
How might we calculate rolling correlations between constituents of an ETF, given a dataframe of prices? For problems like this,
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R
Financial Data Manipulation in dplyr for Quant Traders
In this post, we’re going to show how a quant trader can manipulate stock price data using the dplyr R
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FactorsOptionsQuant tradingRHow To Get Historical S&P 500 Constituents Data For Free
In this post, we are going to construct snapshots of historic S&P 500 index constituents, from freely available data on
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OptionsQuant tradingRHow to Hedge a Portfolio with Put Options
There are 2 good reasons to buy put options: because you think they are cheap because you want downside protection.
