Investor – Impact Analysis…

Published by pschatzmann on

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, websocket-api-9.2.20.v20161216.jar, jcl-over-slf4j-1.7.25.jar, commons-cli-1.3.1.jar, commons-attributes-api-2.2.jar, httpmime-4.5.2.jar, httpcore-4.4.6.jar, htmlunit-core-js-2.23.jar, sevenzipjbinding-9.20-2.00beta.jar, ant-1.5.jar, YahooFinanceAPI-3.12.3.jar, jfreechart-1.5.0.jar, jetty-util-9.2.20.v20161216.jar, slf4j-log4j12-1.7.25.jar, cssparser-0.9.21.jar, neko-htmlunit-2.24.jar, commons-io-2.5.jar, xml-apis-1.4.01.jar, serializer-2.7.2.jar, qdox-1.5.jar, jetty-io-9.2.20.v20161216.jar, commons-lang3-3.5.jar, timeseries-forecast-1.1.1.jar, httpclient-4.5.3.jar, jackson-databind-2.9.4.jar, sojo-1.0.5.jar, commons-jcs-core-2.0.jar, investor-0.9-SNAPSHOT.jar, junit-4.10.jar, jackson-core-2.9.4.jar, websocket-client-9.2.20.v20161216.jar, xercesImpl-2.11.0.jar, hamcrest-core-1.1.jar, combinatoradix-0.8.2.jar, sevenzipjbinding-all-platforms-9.20-2.00beta.jar, sac-1.3.jar, websocket-common-9.2.20.v20161216.jar, slf4j-api-1.7.25.jar, xalan-2.7.2.jar, log4j-1.2.17.jar]




Added jars: [jcs-1.3.jar, commons-logging-1.1.jar, servlet-api-2.3.jar, logkit-1.0.1.jar, jupyter-jdk-extensions-0.0.1-SNAPSHOT.jar, avalon-framework-4.1.3.jar, in-memory-stardb-0.0.1-SNAPSHOT.jar, concurrent-1.3.4.jar, common-0.0.1-SNAPSHOT.jar]

// 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 ch.pschatzmann.stocks.strategy.optimization._;
import ch.pschatzmann.stocks.strategy.allocation._;
import ch.pschatzmann.stocks.strategy.selection._;
import ch.pschatzmann.stocks.integration._;
import ch.pschatzmann.stocks.integration.ChartData.FieldName._;
import ch.pschatzmann.stocks.strategy.OptimizedStrategy.Schedule._;

/// jupyter custom displayer
import ch.pschatzmann.display.Displayers

// java
import java.util.stream.Collectors;
import java.util._;
import java.lang._;
import java.util.function.Consumer;



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 ch.pschatzmann.stocks.strategy.optimization._
import ch.pschatzmann.stocks.strategy.allocation._
import ch.pschatzmann.stocks.strategy.selection._
import ch.pschatzmann.stocks.integration._
import ch.pschatzmann.stocks.integration.ChartData.FieldName._
import ch.pschatzmann.stocks.strategy.OptimizedStrategy.Schedule._
import ch.pschatzmann.d...

Displayers.setup()


true

Impact of Data Source

First we want to investigate the impact of the data source on the result of a trading strategy. We use Apple with the RSI2 Strategy and check the result for different data readers.

MarketArchiveHttpReader

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0));
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader());
var strategy = new RSI2Strategy(stockdata);
var trader = new PaperTrader(account);
var state = new Fitness(trader).getFitness(strategy, account.getDateRange());

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn);


Return: 56741.0

Quandl WIKI

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0));
var stockdataQ = new StockData(new StockID("AAPL", "NASDAQ"), new QuandlWIKIReader());
var strategy = new RSI2Strategy(stockdataQ);
var trader = new PaperTrader(account);
var state = new Fitness(trader).getFitness(strategy, account.getDateRange());

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn);

Return: 36996.0

Yahoo

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0));
var stockdataYahoo = new StockData(new StockID("AAPL", "NASDAQ"), new YahooReader());
var strategy = new RSI2Strategy(stockdataYahoo);
var trader = new PaperTrader(account);
var state = new Fitness(trader).getFitness(strategy, account.getDateRange());

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn);

Return: 5585.0

AlphaVantageReader

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0));
var stockdataYahoo = new StockData(new StockID("AAPL", "NASDAQ"), new AlphaVantageReader());
var strategy = new RSI2Strategy(stockdataYahoo);
var trader = new PaperTrader(account);
var state = new Fitness(trader).getFitness(strategy, account.getDateRange());

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn);

Return: 49922.0

We can compare the three data sources on a chart

IEXReader

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0));
var stockdataYahoo = new StockData(new StockID("AAPL", "NASDAQ"), new IEXReader());
var strategy = new RSI2Strategy(stockdataYahoo);
var trader = new PaperTrader(account);
var state = new Fitness(trader).getFitness(strategy, account.getDateRange());

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn);

Return: 0.0


new TimeSeriesChart().add(stockdata).add(stockdataQ).add(stockdataYahoo)

Impact of Selection of Rate

Closing Prices

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new ClosePrice())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 56741.0

Open Prices

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new OpenPrice())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 46682.0

Avarege (between High and Low) Prices

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new AvaragePrice())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 1060.0

Impact of Delays

Same Day

We assume that we can do the deal at the close price for the same day. This suffers from look ahead bias because during the day the close price is not know

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new ClosePrice())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 56741.0

Open Price of Next Day

We get the buy/sell signar based on the closing price and perform the trade the next day at the open price

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new OpenPrice())
trader.setDelay(new OneDayDelay())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 54389.0

Close Price of Next Day

We get the buy/sell signar based on the closing price and perform the trade the next day at the close price

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new ClosePrice())
trader.setDelay(new OneDayDelay())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 56004.0

Avarage Price of Next Day

We get the buy/sell signar based on the closing price and perform the trade the next day at the close price

var account = new Account("Simulation","USD", 100000.00, Context.date("2015-01-01"), new PerTradeFees(10.0))
var stockdata = new StockData(new StockID("AAPL", "NASDAQ"), new MarketArchiveHttpReader())
var strategy = new RSI2Strategy(stockdata)
var trader = new PaperTrader(account)
trader.setPrice(new AvaragePrice())
trader.setDelay(new OneDayDelay())
var state = new Fitness(trader).getFitness(strategy, account.getDateRange())

// print one parameter
"Return: " + state.result().getValue(KPI.AbsoluteReturn)

Return: 4439.0

see also:

  1. Deeplearning4j – Iris Classification Example
  2. Deeplearning4j – Recurrent Neural Networks (RNN)
  3. Multiple Wordpess Instances in Docker with NGINX & https
  4. Docker + WordPress = Danger
  5. Docker and Treafik – A Comprehensive Tutorial
  6. How to Blink in Arduino – Alternative Designs
  7. Microcontrollers and MIDI – Using the Bluetooth Serial Interface
  8. Implementing Arduino tone() for the Rasperry Pico
  9. Setting up WordPress on a Raspberry Pi with Docker Compose
  10. The Cheapest Camera for Octoprint
Categories: Quantitative Trading

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