Why Algorithmic Trading is the Next Big Thing for Programmers

Like most other industries, Wall Street is being disrupted by the explosion in information processing technologies. Long established players in the hedge fund industry are finding themselves in uncharted territory and revamping their approach by hiring computer scientists and mathematicians. This approach looks to leverage the skills of these practitioners by setting up algorithmic trading systems as a way to automate trading activities in hopes of gaining an advantage over competing funds.

What Is Algorithmic Trading?

The term “algorithmic trading” is a bit intimidating on the surface, but the definition itself is not overly complex. In simplest terms, algorithmic trading is the process of using computers to place and execute trades automatically within a given market at the direction of a pre-programmed software application. The key characteristic of any automated, method-based trading system is that the computer designated to conduct trading operations acts autonomously within the marketplace, independent of any real-time human intervention.

Algo, or “black box,” trading requires several inputs in order to be a viable approach for active market participation. The following components must be present and readily available:

  • A comprehensive trading methodology or system: By definition, an “algorithm” is a set of steps used in a problem solving process. Accordingly, a trading methodology that is defined by concrete parameters governing trade selection and execution must be present.
  • Computer hardware: Computing power capable of supporting numerous software applications while simultaneously streaming live market data is required.
  • Software-based trading Platform: Trading software is the trader’s gateway to the marketplace. In the case of algo trading, the software is programmed according to the tenets of the adopted trading system, and interacts with the market on behalf of the trader. Examples of trading platforms are Trading Station, MetaTrader4 and NinjaTrader.
  • Market connectivity: A high-speed internet connection to the desired marketplace or exchange is necessary to conduct trading operations.

From Programming/Coding To Trading

In the forex marketplace, FXCM is a global leader in providing technology and supporting infrastructure to currency traders. Many programmers break into algorithmic trading with FXCM through QuantConnect, an in-browser IDE.[1] This open-source, desktop-cloud hybrid platform is designed to give programmers the flexibility they need to test and execute their strategies. QuantConnect opens access to years of forex data and coding options to give programmers maximum control in their algorithms, which is then tied to FXCM’s premier execution.

Much of the functionality needed to create a custom algo trading approach is also present in the software platforms available at FXCM. Trading Station, MetaTrader 4 and NinjaTrader each provides the trader advanced features and functionality that can aid in system development and implementation.

The Trading Station, MetaTrader 4 and NinjaTrader platforms feature:

  • Fully automated trading
  • Customized algorithmic system development
  • Advanced system backtesting
  • System optimization

In addition to the professional-level functionality afforded to traders by the supported trading platforms, FXCM provides the trader with access to specialists in the areas of market research, data analysis, trading education, and software development. Advanced programming services are available through FXCM along with proprietary and customizable trading applications.

FXCM also offers software solutions built specifically to aid in the field of algorithmic trading. FXCM’s API suite (FIX, Java, ForexConnect) helps to minimize latency and give users free access to FXCM’s full price history. Marketscope Indicore SDK is a software suite that gives the trader various backtesting and debugging options when vetting a promising new strategy. Precision in algo system development is a necessity, and Marketscope Indicore SDK aids in accurately turning trading ideas into live-market trading systems.


Ultimately, each market participant is left to decide if its implementation is a suitable path towards profitability. If so, vast resources are at the trader’s disposal to create a potentially successful algorithm-based trading approach.

PS. Want to learn more? Read my interviews with a DIY quant and his CTO.

PPS. Can’t wait to get started? Jump right in with my Ultimate Algorithmic Traders Guide.

Forex trading on margin carries a risk of losses in excess of your deposited funds. The products may not be suitable for all investors. Please ensure that you fully understand the risks involved. Algorithmic trading does not take into consideration your individual personal circumstances and trading objectives. Therefore it should not be considered as a personal recommendation or investment advice. There is no guarantee that the systems, trading techniques, trading methods, and/or indicators will result in profits or not result in losses. 

[1] FXCM is an independent legal entity and is not affiliated with QuantConnect. FXCM does not endorse any product or service of the third-party offering services. Nothing associated with this promotion shall be considered a solicitation to buy or an offer to sell any product or service to any person in any jurisdiction where such offer, solicitation, purchase or sale would be unlawful under the laws or regulations of such jurisdiction.

Be sure to read the next Financial article: Why APIs Help Programmers Become Ideal Traders