Publications by R programming
How to Design Quant Trading Strategies Using R?
This blog covers in brief the concept of strategy back-testing using R. Before dwelling into the trading jargons using R let us spend some time understanding what R is. R is an open source. There are more than 4000 add on packages,18000 plus members of LinkedIn’s group and close to 80 R Meetup groups currently in existence. It is a perfect tool...
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An example of a trading strategy coded in R
Back-testing of a trading strategy can be implemented in four stages. Getting the historical data Formulate the trading strategy and specify the rules Execute the strategy on the historical data Evaluate performance metrics In this post, we will back-test our trading strategy in R. The quantmod package has made it really easy to pull historical...
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A Guide on R quantmod Package: How to Get Started?
“The quantmod package for R is designed to assist the quantitative trader in the development, testing, and deployment of statistically based trading models.” It is a rapid prototyping environment where enthusiasts can explore various technical indicators with minimum effort. It offers charting facilities that is not available elsewhere in...
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Quantitative Trading Strategy Using R: A Step by Step Guide
In this post we will discuss about building a trading strategy using R. Before dwelling into the trading jargons using R let us spend some time understanding what R is. R is an open source. There are more than 4000 add on packages,18000 plus members of LinkedIn’s group and close to 80 R Meetup groups currently in existence. It is a perfect tool...
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Common R Programming Errors Faced by Beginners
There are two ways to write error-free programs; only the third one works. – Alan Perlis Error messages can be intimidating for novice coders, and sometimes even for the experienced ones. Trying to decipher the error can be a time-consuming task. In this issue we look at some of the common errors that you can encounter while working in R. ‘co...
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Shorting at High: Algo Trading Strategy in R
By Milind Paradkar Milind began his career in Gridstone Research, building earnings models and writing earnings notes for NYSE listed companies, covering Technology and REITs sectors. Milind has also worked at CRISIL and Deutsche Bank, where he was involved in modeling of Structured Finance deals covering Asset Backed Securities (ABS), and Collat...
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How to Check Data Quality using R
By Milind Paradkar Do You Use Clean Data? Always go for clean data! Why is it that experienced traders/authors stress this point in their trading articles/books so often? As a novice trader, you might be using the freely available data from sources like Google or Yahoo finance. Do such sources provide accurate, quality data? We decided to do a qu...
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[WEBINAR] Trading in Live Markets using R
Trading using R on Interactive Brokers The session would be covering the following aspects: Installing R-studio IDE Reference sheet for the IBroker Package – https://cran.r-project.org/web/packages/IBrokers/IBrokers.pdf TWS configuration Viewing account information details in R Downloading historical data in R Printing real-time data on R con...
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Forecasting Stock Returns using ARIMA model
By Milind Paradkar “Prediction is very difficult, especially about the future”. Many of you must have come across this famous quote by Neils Bohr, a Danish physicist. Prediction is the theme of this blog post. In this post, we will cover the popular ARIMA forecasting model to predict returns on a stock and demonstrate a step-by-step proces...
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R Weekly Bulletin Vol – I
We are starting with R weekly bulletins which will contain some interesting ways and methods to write codes in R and solve bugging problems. We will also cover R functions and shortcut keys for beginners. We understand that there can be more than one way of writing a code in R, and the solutions listed in the bulletins may not be the sole referen...
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