The Strategy Studio is the command and control center of the Marketcetera Automated Trading Platform, built around the workflow of a quantitative trader. The process or creating, testing and deploying strategies is at the heart of algorithmic trading, and we have designed our Strategy Studio to create maximum flexibility for our clients.
Research - All quantitative trading processes begin with an initial period of research. This research process encompasses finding a strategy, seeing whether the strategy fits into a portfolio of other strategies you may be running, obtaining any data necessary to test the strategy and trying to optimise the strategy for higher returns and/or lower risk.
The Strategy Studio is designed to simply and efficiently present any data-type you require for this ideation process, including historical data, reference data, newsfeeds, end of day data and of course any number of real time feeds. As an open and flexible tool Marketcetera integrates with whatever market data tools our clients prefer, such as Quandl, YAHOO Finance, Dukascopy, QuantGo, as well as proprietary historical data sets that you may have assembled. Marketcetera incorporates this data into the Strategy Studio via our Market Data Nexus so it is visible in our customizable UI and available to your strategies.
A single Nexus instance can deliver in excess of 50,000 messages per second (the equivalent of top of book and latest execution for everything traded on NASQAQ) AND Nexus is almost perfectly n-scalable. Marketcetera can either make available all of your data in its entirety or we can pre-process your data via our bundled instance of the ESPER Complex Event Processing Engine.
Prototype - The Strategy Studio has been designed for maximum flexibility. Many of our clients have been working with tools like MATLAB, R, TA-Lib, Python and Excel for years. These products have become familiar, trusted productivity tools and their deep, rich libraries for nearly any mathematical operation imaginable are tremendous assets for our quantitative clients. Marketcetera integrates with all of these tools to reduce time to market and help our clients move more quickly between the prototype and production stages.
Backtest - Perhaps the most subtle area of quantitative trading is backtesting. In simple terms, backtesting is carried out by exposing your particular strategy algorithm to a stream of historical financial data, which leads to a set of trading signals. Each trade (defined as a 'round-trip' of two signals) will have an associated profit or loss and the accumulation of this profit/loss over the duration of your strategy backtest results in your total P&L.
In reality backtesting is a far more complex process. In order to provide evidence that the strategy is profitable when applied to both historical and out-of-sample data, traders are required to navigate several biases such as look-ahead bias, survivorship bias and optimisation bias. Traders also have to ensure they have the right period of clean historical data, factor in realistic transaction costs, etc.
Our philosophy is to provide our clients with technology options and the means to control their technology stack. For clients that have purchased dedicated backtesting products or have already built their own tools, we offer open APIs to integrate with their existing tools. For clients that want to build out their own proprietary backtesting system, we offer them affordable open source tools and expertise to accelerate their time to market. The Marketcetera Automated Trading Platform is not a dedicated backtesting solution, but we offer our clients the following capabilities. Clients can incorporate any kind of historical data into our platform via our Data Nexus. Clients can use our IDE to script their strategy in either Java, Ruby or Python, or they can use their own strategy IDE. Clients can run this data through their strategy at their desired replay speed, execute trades in our exchange simulator and track P&L by strategy. To simulate more complex scenarios, traders can load up one side of the order book with trades designed to test their strategy against specific market conditions. Traders can also connect multiple instances of the MATP to the exchange simulator to test their strategy against alternative trading algorithms.
Test - The Strategy Studio provides traders a controlled environment to transition from backtesting to paper trading. Strategy Studio incorporates that concept of "Trade Suggestions" so our clients can run their strategies against live market data, generate trade suggestions and track the P&L performance without ever sending an order to their broker. Clients can also use Strategy Studio to paper trade multiple strategies in parallel to benchmark their strategies.
Deploy - Order routing is one of the real strengths of the Marketcetera platform. The Strategy Studio was designed to provide clients the ability to take advantage of server-side processing power. The Strategy Studio connects to the Marketcetera DARE order routing server for execution. DARE deploys strategy execution agents remotely, so if a client has co-located their servers at a datacenter proximate to their liquidity venue, these remote agents will fully leverage the processing power of their servers to maximize performance.
Dare is architected to guarantee high levels of availability and fail-over. Every client has their individual standards for these issues, there is no "one size fits all" approach. Marketcetera is designed with a series of configurable options to achieve the unique requirements of each individual client.
The Strategy Studio also enables clients to write custom algorithms to optimize their order execution. The DARE order routing engine maintains the state of each trade, which Strategy Studio uses to inform strategies written to optimize execution. DARE determines whether any message needs to be modified (based on Message Modifier APIs) and then forwards them to the broker for execution. If any persistent state is changed it is saved by the state management. When the broker sends back ack or any other message such as fills, DARE forward’s it back to client (strategy) and also saves it using the state management component. Modules can register for callback notifications for this type of messages.
Monitor - Perhaps no other component of the trading stack is as "personal" as the user interface. The trading UI is a virtual extension of the trader's workflow which imposes unique customization challenges for clients with multiple traders. We have designed our UI to provide our clients with maximum flexibility - including the option to not use our UI at all.
Clients have the option to use the Marketcetera UI or we can integrate with their custom UI. The Marketcetera UI is an Eclipse Rich Client Platform (RCP) application that offers tremendous flexibility. The architecture includes a library of "widgets" that can be moved, re-sized or eliminated including a shares pricing watch, intraday and history charts with technical analysis indicators, level II/market depth view, news watching, and P&L.
Separate "perspectives" are available for each of the supported asset classes, each with the appropriate order ticket for manual trading. Clients have the option to select multiple instances of a particular widget, modify those widgets or create their own widgets.