Identity Management and Authentication for Java Webservices and Javascript GUIs

I am currently working on a new project which uses Vue.js on the frontend and JAX-RS Webservices implemented in Java in the backend. Both, the frontend and the backend will be deployed with Docker. The solution will need to manage customers, users and provide authentication to protect the web application and web services. It does not make any sense to build my own solution for this so I decided to base my architecture on some Read more…

By pschatzmann, ago

Docker and Treafik – A Comprehensive Tutorial

In Docker you expose functionality by specifying a port mapping and then you can address the application on the physical host with the mapped port. I am using Docker quite some time now and this was getting a little bit too tedious because each mapped port needs to be unique and then you need to remember the port numbers to be able to start your application. So I wanted to simpler way by using speaking Read more…

By pschatzmann, ago

NFS in Docker-Compose

My main Docker deployments are on a single linux server. I have a central ‘data’ directory where I keep my common data. The application specific data or settings are stored in /srv/. But for testing or demos I am usually using local Docker installations on my McBook or McBook Air under OS/X. I am using NFS to access the shared central data. In this Blog I give a quick overview of the setup: Install the Read more…

By pschatzmann, ago

Using the ‘Smart EDGAR’ Library to Access EDGAR Filings

The initial concept of Smart EDGAR was to provide the tools to download the data from the EDGAR website and – store the information as local files – store the information in a SQL database – provide reporting functionality from this data We have extended the functionality a little bit so that the Smart EDGAR Library can be used without having any data available locally. So we also provide – an API which retrieves the Read more…

By pschatzmann, ago

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 – Innovation – Growth – Leadereship – Surprises It is the expectation that the stock price of companies with better KPIs will grow faster than their Read more…

By pschatzmann, ago

Smart EDGAR: Definition of a Comprehensive Set of Financial KPIs

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 don’t have any requirement to file the Financial Reports electronically and unfortunately this will not change anytime soon. Fortunately there are countries which are more Read more…

By pschatzmann, ago

Smart EDGAR: Calculation of Surprises

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 In this document we demonstrate the approach on how to calculate the Surprises

By pschatzmann, ago

Smart EDGAR: Calculation of Growth Parameters

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 on how to calculate the Growth Parameters

By pschatzmann, ago

Calculating the Market Share of US Companies with the Help of EDGAR

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 uses Spark) can be found in the following Gist. Alternatively here is a version which purely relies on Scala and Smart EDGAR

By pschatzmann, ago