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PythonMatlab
  

Get Started With Quantiacs

Python 3.7

The Quantiacs Toolbox helps you with the development and the backtesting of your trading algorithms. The following 3 steps will get you started with the Quantiacs Toolbox: 

  • Install the Quantiacs Toolbox
  • Run a sample trading algorithm
  • Making your first changes
 
You need to be logged-in to submit a system.
Sign Up Now


 

1. Install the Quantiacs Toolbox

Download and install Python 3.7. For an easy installation process, we recommend Anaconda since it will reliably install all the necessary dependencies. To download Anaconda, please follow the instructions on the installation page for Windows, MacOS and Linux.

The easiest way to install the Quantiacs toolbox is to use Anaconda and create a virtual environment for Quantiacs as follows:

First, create the environment:
conda create --name quantiacsbox
Then, activate it using:
conda activate quantiacsbox
 Finally install the Quantiacs toolbox:
conda install -c quantiacspkg quantiacstoolbox

Anaconda will take care of installing the required dependencies.

You can also download the toolbox from github and install it using setuptools, or install it using pip.

2. Run a sample trading algorithm

With the toolbox installed, you can now backtest your trading algorithms. We put several examples on github as a starting point.  To evaluate sample algorithms type in the command line:

	python path/to/trading_system.py
This runs the evaluation of the sample system on the defined data set. Once the system is evaluated it opens a GUI with important performance indicators like the equity curve, the long vs short exposure, marketwise performance and the Sharpe Ratio.

The Sharpe Ratio is one of several important performance numbers. It compares the realized performance against the risk (or volatility) taken to achieve that performance. Investors usually prefer systems with high performance and low risk. Here you can find more about important aspects of a trading algorithm and its performance.


3.    Make your first changes

Finally, we change the sample system, rerun it and submit a test to the Quantiacs marketplace. Open the downloaded sample strategy with your preferred editor. A sample trend-following trading system uses a Simple Moving Average (SMA) as an indicator to predict trends. The basic idea of an SMA is to smooth out fluctuating data points to lower the noise and detect signals. Here is an illustration of what these SMAs might look like.


Within 'myTradingSystem' the algorithm evaluates two SMAs over two different time periods: longerPeriod = 200 days, shorterPeriod = 40 days. You can define how much the data is smoothened by setting the number of days over which we average the data. The higher the number, the more days you average, the smoother the SMA.

	longerPeriod=200
	shorterPeriod=40
Change the numbers of longerPeriod and/or shorterPeriod, save the changes and rerun the strategy. You will see how this changes the equity curve and the Sharpe Ratio.

To submit your tweaked strategy to the Quantiacs marketplace simply click the button ‘Submit Trading System’ at the bottom of the GUI. This redirects you to the website.

You can also simply login and upload the system from your private user area using the upload form.

Congratulations! You just successfully submitted your first trading algorithm to Quantiacs.

  

Get Started With Quantiacs

Matlab

The Quantiacs Toolbox helps you with the development and the backtesting of your trading algorithms. The following 3 steps will get you started with the Quantiacs Toolbox: 

  • Install the Quantiacs Toolbox
  • Run a sample trading algorithm
  • Making your first changes
You need to be logged-in to submit a system.
Sign Up Now


1.    Install the Quantiacs Toolbox

To get the Matlab Toolbox, download it from here or from github. Add the opened zip-file to your Matlab search path. This will make the toolbox functions available from the command window.

2.    Run a sample trading algorithm

With the toolbox in your matlab search path, you can now backtest your trading algorithms. We put simple sample algorithm examples on github as a starting point. To evaluate the trend-following sample algorithm place the file in your Matlab search path (the current folder is recommended). Then type in the command line:

	runts(‘trading_system_name’)
This runs the evaluation of the sample system on the defined market list. Once the system is evaluated it opens a GUI with important performance indicators like the equity curve, the long vs short exposure, marketwise performance, and Sharpe Ratio.

The Sharpe Ratio is one of several important performance numbers. It compares the realized performance against the risk (or volatility) taken to achieve that performance. Investors usually prefer systems with high performance and low risk. Here you can find more about important aspects of a trading algorithm and its performance.

3.    Make your first changes

Finally, we change the sample trend-following system, rerun it and submit it to Quantiacs. The sample trading system uses a Simple Moving Average (SMA) as an indicator to predict trends. The basic idea of an SMA is to smooth out fluctuating data points to lower the noise and detect signals. Here is an illustration of what these SMAs might look like.


Within, 'myTradingSystem', the algorithm evaluates two SMAs over two different time periods: longerPeriod = 200 days, shorterPeriod = 40 days. You can define how much the data is smoothened by setting the number of days over which we average the data. The higher the number, the more days you average, the smoother the SMA.

	longerPeriod=200
	shorterPeriod=40
Change the numbers of longerPeriod and/or shorterPeriod, save the changes and rerun the strategy. You will see how this changes the Sharpe Ratio.

To submit your tweaked strategy to the Quantiacs marketplace simply click the button ‘Submit Trading System’ in the upper right of the GUI. This redirects you to the website. 
 
You can also upload the system once you are in your user area using the upload form.

Congratulations! You just successfully submitted your first trading algorithm to Quantiacs.

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