There are tons of resources to help you learn the different aspects of R, and as a beginner this can be overwhelming. It’s also a dynamic language and rapidly changing, so it’s important to keep up with the latest tools and technologies. That’s why R-bloggers and DataCamp have worked together to bring you a learning path for R. Each section...
I was surprised to see there weren’t more of these types of calculators in the R community. Inflation and adjusted payments seem like they would be more common. I was able to find a way to gather Consumer Price Index data using the quantmod package but quantmod leaves you to your own devices in converting
This post is in response to Michael Harris' Price Action Lab post, where he uses some simple R code to evaluate the asymmetry of returns from the day's close to the following day's open. I'd like to respond to his 3 notes, which I've included below.The R backtest assumes fractional shares. This means that equity is fully...
Markets are very smart in absorbing and reflecting information. If you think otherwise, try making money by trading. If you are new to it, make sure you don’t bet the house. In other words, markets are efficient. At least most of the time. So then why people trade? The general believe is that there are
Life has been busy and has kept me away from blogging, and from trading, mostly. Still, I can’t stay away from monitoring the markets, and, with the recent rally, I started asking myself – has the situation changed since the 200 day SMA signaled an exit. What do you think – make up your mind
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...
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
In the previous post, I went through a simple exercise which, to me, clearly demonsrtates that 60% out of sample guess rate (on daily basis) for S&P 500 will generate ridiculous returns. From the feedback I got, it seemed that my example was somewhat unconvincing. Let’s dig a bit further then. Let’s add Sharpe ratio