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…
Financial KPIs can be used to drive investment decisions. So it was my goal to create a comprehensive set of KPIs across different dimensions that are based on the information which can be determined from EDGAR: Profitibility Liquidity Efficiency Innovation Growth Leadereship Surprises In this document we demonstrate the approach Read more…
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…
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…
In this blog we will demonstrate how we can predict if a stock is going up or down based on the news headlines. The solution consists of the following components: Spark MLLib (Machine Learning) My News-Digest (which I have described in my last blogs) Investor (we determine the stock prices Read more…
I am planning to use the DL4J Doc2Vec implementation for a sentiment analysis. However, I don’t want to start with an empty network but the staring point should be a pre-trained network: The initial trining should be done with the Sentiment140 dataset which can be found at https://www.kaggle.com/kazanova/sentiment140. It contains Read more…
The basic goal of a ‘sentiment analysis’ is to classify a given text into positive, negative or neutral. SentiWordNet is a lexical resource for opinion mining. It assigns sentiments to each synset of WordNet which makes it possible to “calculate” an overall sentiment for a text. A SentiWordNet implementation can Read more…
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…
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…
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…