Read more about OpenQuant platform
You start developing a trading strategy with an idea that you
test on historical data by applying quantitative analysis. You need
a tool like Matlab to do the job but will spend up to 80% of your
time developing the historical data interface to give your analytics
access to market data. You will test new strategies on end-of-day
data first but will still require real-time data for testing afterwards.
You will make the decision of whether to rebalance your portfolio
at the end of the day based on closing prices but you will still
need to track stop loss and position closing orders throughout the
day to minimize risk. You will also need to collect and store historical
tick data and process it.
If testing of your system is profitable on historical data you
will need to paper-trade it. This requires integration of a real-time
feed and usually a new datafeed interface. Backtesting is done by
processing ticks from disk while the real-time datafeed requires
an event-driven approach. You will probably need to change your
analysis and decision-making code to support the event-driven nature
of real-time data. You will also need to ask your traders to simulate
buy/sell orders in the current market using their trading expertise.
If paper trading works then you will need to integrate trade execution
into the system or develop a production version in C++ or other programming language. You will
also need to link your newly minted system to your back office,
risk management, reporting and other processes.
OpenQuant frees you from all of the unneeded hassle. We include
in our framework all of the blocks required for building a trading
system. Our macro and script editor is designed for fast prototyping.
It's not just a text editor with a .NET compiler attached. No, we
include a whole user front-end! When you run the macro editor you
are instantly plugged into our market data warehouse, data feeds,
execution, etc. You can jump up in the middle of the night and test
your strategy without spending any time on unnecessary groundwork.
This is what we call fast prototyping.
You can work with a simulated data feed and virtual trade execution.
You can play back historical tick data to simulate a real-time market
data feed. You can quickly prove that your strategy works on true
real-time market data. Just plug in a ESignal or IB datafeed adapter
instead of the included simulated data provider into your code.
Simulate stop, limit, stop limit and other types of orders with
our simulated execution interface and quickly switch over to Interactive
Brokers. You can collect executed orders into a portfolio and compile
performance statistics of your trading strategy.
The ability to switch from simulated to real-time market trading
by replacing two lines in your code gives you a few key advantages
1. Time savings. All standard blocks are included and you don't
need to reinvent the wheel. Quickly put just the required blocks
of your trading system together.
2. Fast prototyping. Everything needed for analysis is included
in OpenQuant. No need to be concerned with anything but designing
and testing of new trading strategies. You expect from your quants
new ideas that will bring in more money. You do not expect from
them new tools to process market data.
3. OpenQuant smashes the barrier between analysis and trading.
Execution is seamlessly integrated into the system. No need to integrate
disparate systems such as Matlab, Excel, Flex Trade or broker API.
4. Finally, we will always implement your trading ideas for you
and let you concentrate on trading. We are the implementation wizards!
You can focus on making money while we concentrate on coding.
Read more about OpenQuant platform