Because Investor has been implemented in Java and is available as jars from a Maven repository we can easily use the framework in all languages which are based on the the JVM. Here is a quick demo using Jupyter Lab (using Beakerx) with: – Scala – Java – Groovy – Kotlin – Clojure Here is a screen shot of Jupyter Lab: Scala Scala combines object-oriented and functional programming in one concise, high-level language. Scala’s static Read more…
So far we have looked at the trading simulation functionality which was using the historic stock data to evaluate strategies on a single stock or a portfolio of stocks. In this document we want to demonstrate how to do trading with actual data. We still use the PaperTrader to demonstrate the basic logic Setup We add the necessary jars and import all relevant packages: %classpath config resolver maven-public https://software.pschatzmann.ch/repository/maven-public/ %%classpath add mvn ch.pschatzmann:investor:0.9-SNAPSHOT ch.pschatzmann:jupyter-jdk-extensions:0.0.1-SNAPSHOT Added Read more…
In this document we demonstrate how to use the Edgar Database for the selection of the stocks into a portfilio with the help of the Investor library. This functionality is using the Edgar Webservice which is based on the data which is available on https://www.sec.gov/edgar.shtml. Setup We add the necessary jars and import the related packages. %classpath config resolver maven-public http://software.pschatzmann.ch/repository/maven-public/ %classpath add mvn ch.pschatzmann:investor:0.9-SNAPSHOT %classpath add mvn ch.pschatzmann:jupyter-jdk-extensions:0.0.1-SNAPSHOT // our stock evaluation framwork import Read more…
Our Mobile Phone Companies here in Switzerland are providing fast unlimited Internet access at competitive prices. So I was considering to switch from my Cable Network to a pure Mobile access. Salt up to 300 Mbit/s: 35 CHF / Month Sunrise up to 10 Mbit/s: 19 CHF / Month Sunrise up to: 300 Mbit/s: 49 CHF / Month Swisscom up to 5 Mbit/s: 60 CHF / Month Swisscom up to 30 Mbit/s: 70 CHF / Read more…
Forecasting The longer you look back, the farther you can look forward. (Winston Churchill) Forecastig of the development of stocks is quite a challangning task with uncertain outcome. We currently support the following approaches: – Forecast based on History – Arima Setup %classpath config resolver maven-public http://pschatzmann.ch:8081/repository/maven-public/ %classpath add mvn ch.pschatzmann:investor:0.9-SNAPSHOT %classpath add mvn ch.pschatzmann:jupyter-jdk-extensions:0.0.1-SNAPSHOT Added new repo: maven-public Added jars: [websocket-common-9.2.20.v20161216.jar, commons-cli-1.3.1.jar, htmlunit-2.24.jar, qdox-1.5.jar, investor-0.9-SNAPSHOT.jar, httpclient-4.5.3.jar, hamcrest-core-1.1.jar, slf4j-api-1.7.25.jar, commons-codec-1.10.jar, jetty-io-9.2.20.v20161216.jar, timeseries-forecast-1.1.1.jar, commons-lang3-3.5.jar, jackson-databind-2.9.4.jar, commons-io-2.5.jar, Read more…
Selection of Stocks into a Portfilio In the current document we show how you can pick the best stock and strategy combinations out of a big collecion from a universe. Setup Import Libraries %classpath config resolver maven-public http://software.pschatzmann.ch/repository/maven-public/ %classpath add mvn ch.pschatzmann:investor:0.9-SNAPSHOT %classpath add mvn ch.pschatzmann:jupyter-jdk-extensions:0.0.1-SNAPSHOT Imports // our stock evaluation framwork import ch.pschatzmann.dates._; import ch.pschatzmann.stocks._; import ch.pschatzmann.stocks.data.universe._; import ch.pschatzmann.stocks.input._; import ch.pschatzmann.stocks.accounting._; import ch.pschatzmann.stocks.accounting.kpi._; import ch.pschatzmann.stocks.execution._; import ch.pschatzmann.stocks.execution.fees._; import ch.pschatzmann.stocks.execution.price._; import ch.pschatzmann.stocks.parameters._; import ch.pschatzmann.stocks.strategy._; import Read more…
Processing a Portfolio of Stocks This project provides an easy to use functionality to implement and evaluate automatic stock trading strategies. It is implemented in java and therefore can be used in any environment which builds on the JVM. It provides the following functionality: – Simple access to stock data – Declarative formulation of trading strategies – Evaluation of trading strategies – Optimization of trading strategies – Support of portfolio of multiple stocks / trading Read more…
Parameter Optimization This project provides an easy to use functionality to implement and evaluate automatic stock trading strategies. It is implemented in java and therefore can be used in any environment which builds on the JVM. It provides the following functionality: – Simple access to stock data – Declarative formulation of trading strategies – Evaluation of trading strategies – Optimization of trading strategies – Support of portfolio of multiple stocks / trading strategies In this Read more…
Impact Analysis Now that we have the tool we can do some investigations: What is the impact of changing the data source ? Does it make a difference if we take avarage rates instead of end of day rates ? Setup the Environmant But first we need to setup the JupyterLab environment %classpath config resolver maven-public http://pschatzmann.ch:8081/repository/maven-public/ %classpath add mvn ch.pschatzmann:investor:0.9-SNAPSHOT %classpath add mvn ch.pschatzmann:jupyter-jdk-extensions:0.0.1-SNAPSHOT Added new repo: maven-public Added jars: [htmlunit-2.24.jar, jackson-annotations-2.9.4.jar, commons-codec-1.10.jar, ta4j-core-0.10.jar, Read more…
Introduction Last year I was busy to build my own project which provides an easy to use functionality to implement and evaluate automatic stock trading strategies. It is implemented in java and therefore can be used in any environment which builds on the JVM. It provides the following functionality: – Simple access to stock data – Declarative formulation of trading strategies – Evaluation of trading strategies – Optimization of trading strategies – Support of portfolio Read more…