## MLLib – Prediction of Stock Prices from Financial KPIs

Financial KPIs can be used to drive investment decisions. So it was my goal to create a comprehensive set of KPIs across different dimensions. In this document we will use EDGAR to calculate KPIs to measure the following dimensions of a reporting company – Profitability – Liquidity – Efficiency – Read more…

## Smile: Predicting the Direction of Stock Market Prices using a Random Forrest Classifier

In this demo we show how to forecast if the NASDAQ-100 is moving up or down. We do this with the help of a Random Forrest Classifier from the Smile Machine Learning Framework. I tried to replicate the result from a research paper authored by Luckyson Khaidem, Snehanshu Saha, Sudeepa Read more…

## OpenNLP: Predicting Stock Movements from the News

In my last blog I demonstrated how to build a model that can predict if a stock is going up or down based on the news headlines using Spark MLLib. In this demo I will do the same – but with the help of OpenNLP. The solution consists of the following Read more…

## Predicting the Direction of Stock Market Prices using a Random Forest Classifier

In this demo I will show how to predict if the closing price of Apple, General Electric and Samsung Electronics is moving up or down. We do this with the help of a Random Forest Classifier. I tried to replicate the result from a research paper authored by Luckyson Khaidem, Snehanshu Read more…

## Investor – Stock Forecasting with LSTM

In this blog we show how to forecast the closing price of AAPL using a LSTM RRN network. We use the open, closing, high and low rates and the volume of the current day as input in order to predict the subsequent closing price. This demo has been implemented in Read more…

## Will you get rich by investing in Funds ?

In recent years most banks are pushing their customers to invest in Funds with the argument that this is more profitable than any other option. As always it is valid to question this statement. As a compelling argument an index chart is presented which shows indeed that the stock market Read more…

## Investor – Validating DL4J LSTM Stock Forecasting (using the HarmonicStockOscillator)

A Long short-term memory (LSTM) network is a special type of a recurrent neural network (RNN). It remembers values over arbitrary time intervals which makes it suited to be used for forecasting of time series. I was struggling with the DL4J implementation of the LSTM to be used to forecast stock data and I Read more…

## Investor – HarmonicStockOscillator¶

I thought it might be cool to have a stock price generator which is generating a steady sinus output, so that it can be used for the testing of trading strategies. A sinus generator function generally needs the following input amplitude omega phase This is oscillating between -amplitude and +amplitude Read more…

## Investor and Machine Learning (MLlib and DL4J)

In this Blog we demonstrate how Investor can be used together with DL4j and Spark’s MLlib. In general the idea is to use the stock history data in order to predict an increase or decrease of the stock value with the help of Machine Learning. We will demonstrate how we can Read more…

## Investor and BeakerX 1.2.0

BeakerX is available with Version 1.2.0 now: So it is time to convert my static resources with the dynamic tables and charts which are made available with the help of Widgets. Heres is the link to my gist which shows the use of these Widgets in Scala with the Investor Read more…