OSTIRION

Stock markets shocks are notoriously difficult to predict. In general, periods of high volatility can lead to both large market gains and...

It is time to put our randomly generated Deep Neural Networks (DNNs) to the test. These neural networks, left to chance due to our...

Designing the architecture of a deep neural network is difficult. There are multiple decisions to be made regarding the network...

In this post, we will quickly check the information really contained in the video files produced by digital recording systems and obtain...

In some cases, it is necessary to conduct a rapid survey of the data obtained from source data without devoting too much development...

To finish exploring the possible uses for geographic source data for the obtention of intelligence (covered in this post and this post),...

Map generation from geographic data.

Data is the new oil. Data is the new gold. The mithril of Moria. These phrases are used to emphasize the value of data in the current...

Our attempt at using the correlation index as a trading signal did not generate very good results. After optimizing for historical...

In our last analysis, we found that the correlation index for the top traded stocks in the SPY index could potentially contain...

We have seen that there are times when those companies at the top of the SPY index in terms of capitalization move in lockstep and times...

SPY correlation index for the recent past. Can stock movements be predicted by the returns correlation of the most capitalized companies?

Cryptocurrencies are new assets compared to traditional means of exchange and stores of value. The ratio of the prices of the two most...

Today we revisit our very first post on the application of visual pattern recognition methods to stock market price predictions. This...

This is an interlude to our usual topics. This post will be one level inside quantitative model development, one level below using a...

Cumulative sum filtering is a signal sampling method presented in Marcos Lopez de Prado. 2018. Advances in Financial Machine Learning...

Now we have a tool that will flexibly obtain labels for our hypothetical trading positions, all of them inside a certain space of future...

We will continue adapting the methods presented in Marcos Lopez de Prado. 2018. Advances in Financial Machine Learning (1st. ed.). Wiley...

This post extends the code for our interpretation of the fractional differentiation calculation methods presented in Marcos Lopez de...

If there is momentum, take advantage of it. Our previous posts on fractional differentiation have surged in visits in the past weeks, so...