In finance and investing the term portfolio refers to the collection of assets one owns. Compared to just holding a single asset at a time a portfolio has a number of potential benefits. A universe of asset holdings within the … Continue reading →

The article below is an updated version of an article I wrote for R-Bloggers in August 2010. As a first post I thought it was a good idea to introduce one of the best tool out there for quantitative trading: R R is a free software environment for statistical computing and graphics. It compiles and

In this tutorial I am going to share my R&D and trading experience using the well-known from statistics Autoregressive Moving Average Model (ARMA). There is a lot written about these models, however, I strongly recommend Introductory Time Series with R, which I find is a perfect combination between light theoretical background and practical implementations in

I've been working on different projects lately and my time for this blog, unfortunately, has been close to zero. But that's going to change. Don't expect new post every day, but there should be a new post at least in every two weeks. Anyway, let's get back to the point of this post. One of the readers contacted

Quantitative Finance, Technical Trading & Analysis. Fotis Papailias, Dimitrios Thomakos Fotis Quantitative Finance & Technical Trading Ichimoku Clouds R Code Trading Download the full program here Here you can find an R Code for Ichimoku Clouds analysis and trading. Have fun! # The function for computing the Ichimoku cloud ichimoku <- function(data,pars) { # REMEMBER THAT THE DATA...

I recently participated in the Kaggle Algorithmic Trading Competition under the username VikP. For those who do not know what Kaggle is, it is a web site where individuals and corporations can host data analysis competitions. This particular competit...

Quantum Financier wrote an interesting article Regime Switching System Using Volatility Forecast. The article presents an elegant algorithm to switch between mean-reversion and trend-following strategies based on the market volatility. Two model are examined: one using the historical volatility and another using the Garch(1,1) Volatility Forecast. The mean-reversion strategy is modeled with RSI(2): Long when

(This article was first published on Eran Raviv » R, and kindly contributed to R-bloggers) A few words for those of you who are not familiar with the “pairs trading” concept. First you should understand that the movement of every stock is dominated not by the companies performance but by the general market movement. This is the origin of...

Frank Hassler at Engineering Returns blog wrote an excellent article Rotational Trading: how to reduce trades and improve returns. The article presents four methods to reduce trades: Trade less frequently. I.e. weekly instead of daily rebalancing. Different criteria for enter / exit a trade. Smooth the rank over the last couple of bars. Combination of

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