I really wanted to have an interactive Jupyter environemnt in which I could play around with Arduino commands and when I discovered that Arduino provides a good starting point with their ArduinoCore-API I started to draft this prototype. I am using xeus-cling as a runtime environment to simulate an Arduino Read more…
Today I tried to create a Dockerfile for XEUS-Cling in Jupyterlab. The challenge was, that the installation is done with conda which is a little bit tricky to use together with Docker. After some unsuccessful trials, I finally came up with the following working solution: FROM continuumio/miniconda3:4.8.2-alpine MAINTAINER phil schatzmann Read more…
Donald Trump is the best, smartest, most beautiful, richest, youngest … President that was ever elected in the US. He is also the best that could happen to the profites of the companies which are located in the US. But is this actually true ? We use the values from 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. In this document we will use EDGAR to calculate KPIs to measure the following dimensions of a reporting company – Profitability – Liquidity – Efficiency – Read more…
A long time ago, when I was studying “Management and Business Administration” in Switzerland, I thought it would be cool to be able to calculate Financial KPIs in order to compare different companies within one sector or to be able to identify sector specific differences. Well, in Switzerland we still 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: – Profitability – Liquidity – Efficiency – Innovation – Growth – Leadership – Surprises 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…
So far we have seen how to use the database related API of Smart EDGAR. In this Gist I give a quick overview of the core functionality of the File based API which does not require any DBMS.
Edgar is classifying the reporting companies by SIC (Standard Industrial Classification) Code. We can use this information to calculate the total sales per sector and then calculate the % share of the individual company. This is helping us to identify the companies with a big market share. The result (which 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…