Predicting stock prices using recurrent neural networks (LSTM)


Impressions about Quantopian

Usually I don’t write about services I use, but one came into my way that I like – Quantopian. For a while I am interested in financial side of computer science, quantitative analysis, machine learning applications to predicting a stock market, etc. However, I was not really able to get grasp of these fields. I certainly could get some data from either Yahoo Finance and I even had access to Bloomberg terminal to play a bit with at the University library. I made some models, published a paper or ArXiv , made a tool that make these models available and published it on GitHub and I am talking with people at MUTIS Finance society to make a Quant


FinAnalizer – Tool for financial analysis of stocks

For a while I was playing with financial data and financial data mining. I have already written about it in a separate post. Now, I decided to try to make my research so far accessible a bit more, so people can use it. Basically, what I previously did is that I used a bunch of technical financial parameters, such as price, P/E ratio, Price to Sales, Price to Book and many other ratios to try to create a model that will be able to predict a stock price movement over the long term (1 year period). It seems that it is working for about 75% of times using machine learning, namely Random Forests algorithm. For more details you can


How to predict future movement of stock prices using machine learning

For a while, I have been interested in finance and especially in algorithmic trading. I had this question over my head for some time “Can the long term investment be helped by machine learning?”. The answer seems to be yes based on many models we currently have for company evaluation, especially when it comes to evaluating intrinsic value of the company and comparing it to the market price. Benjamin Graham set a set of criteria, which are pretty much numerical and require analyst to look at couple of financial ratios. Graham criteria are hard to apply in today’s market because they are too harsh. But the question is, can we learn new criteria by using historical data?

0 – Money saving app

In sunday we have finaly released in Prelovac Media, money saving app for Android tablets and iPads. It is minimalistic financial application that will help you track your family finances. Simple in design, easy to use, secure, and most importantly free.


– Beautiful graphics

– Easy-accessible and readable user interface

– Choose from a number of predefined income and expense categories with beautiful icons

– Ability to add all your family members and assign their photos

– Daily-level statistics for your balance, income and expense

– Expense and income statistics breakdown by category or by family member

– Privacy and safety: