Algorithms account for nearly 73 percent of all U.S. equity trading. But are YOUR trades part of that statistic? Chances are no. Institutional traders, investment banks, and hedge funds are still the dominant users of algo. While the last few years have seen multiple attempts at bringing automated trading applications to retail investors, the high entry barriers have kept this technology still under the monopoly of financial power players.
What are these barriers? Algo-trading typically requires you to be well-versed in programming knowledge, such as Python, JAVA, C++, etc., to create your own trading bot. Then there is the challenge of gathering institutional data (most of them locked behind paywalls) to test the validity of your algorithm. You also need to learn several data science concepts to find correlations between data sets and test and optimize your algorithms with the extensive amounts of data you have just paid for. And then, you need to find platforms that allow you to backtest your algo and assess its viability using paper trading. Finally, you need to overcome the challenge of connecting the algo to your broker with an open API.
Each of these barriers cull the group of retail investors genuinely interested in implementing algo-trading in their portfolio. Most people resort to trading with gut feelings, while institutions continue to hold a competitive advantage by having algorithms at their disposal.
Algo-trading is no longer just a hedge fund’s super-power. Breaking Equity democratizes algo-trading, eliminating the elusiveness of this powerful application and making it accessible to all. Using the intuitive interface, you can create algos without being a programming whiz, conduct robust backtests using 20-year historical data, find opportunities using multiple filters, paper trade using real-time data, and then automatically integrate your algo to your current broker (we support most US brokers, including Robinhood) — all in one platform.