Algorithmic trading is machines trading automatically without human intervention, where the trading decisions are derived from the sophisticated mathematical models running in the backend. In developed markets of the USA, the UK, and Europe, algorithmic trading is quite popular amongst the retail players. The market share of algorithmic trading is about 70% of total trades including a high percentage of retail trading.
In emerging markets of Asia, Africa and South America, the retail participation in Algorithmic Trading has been growing as the markets have been changing. However, the chunk of the Algo share is still taken up by the big hedge funds and banks here. Nonetheless, the number of exchanges that allow Algorithmic Trading for retail players and the types of automated software available for retail traders has been multiplying worldwide.
Should retail traders get into Algorithmic Trading?
Multiply your profitable trades
The main reason is if you are trading a strategy which is profitable for you, you need to be able to increase the number profitable trades to earn more. In trading, the losses and wins happen together. You come out profitable only when your wins compensate your losses enough so as to account for your efforts and costs. Algorithmic trading is a way to do the same.
Discipline your trading decisions
Another reason is traditionally retail traders have been trading on gut feeling based on the ‘feel’ of the market. There is nothing wrong with that especially if you are a seasoned player with lot of market insights to be put to use. However, the gut feeling often turns to be wrong, mostly when there is greed and fear involved. When the markets are falling many amateur traders sell quickly as they fear further crash. Algorithmic trading follows pre-decided entry-exit rules which prevent such emotional trading and hence avoidable losses.
Increase your market reach
One of the main reasons why Quantitative trading has been gaining popularity is because it allows traders to build strategies quantitatively and use modelling techniques to be able to manage risks. This further enables them to trade in instruments such as options and derivatives which are otherwise too volatile for retail players.
How can retail traders start Algorithmic Trading?
The process and requirements for Algo trading is same for retail and institutional traders. The main difference is in the capacity of investment and expected returns for a retail trader. The steps involved in executing your own Algorithmic trading strategy are as shown in the diagram below:
These steps are explained in details below:
- Ideation or Strategy Hypothesis: Come up with a strategy idea which you believe would be profitable
- Strategy writing & Backtesting: To test that idea, write that strategy using any tool such as Excel, R, Python and backtest using historical prices
- Coding on the platform: Assuming that your strategy was indeed profitable on historical data, which happens only 1% of the time, you need to deploy this strategy on the execution platform. Sometimes the backtesting platform is the same as the execution platform. We will get in to that in a while.
- Live market trading: Before trading in live markets, you need to test your strategy on a simulator which simulates market like conditions. Here you do an event-driven testing which means, you test your strategy as per the events in the market such as buy/sell offers. You can change your parameters or tweak your strategies based on the order fills your strategy gets and final profits it make in the simulated environment. After final changes, you take your strategy live.
To connect to with the exchange for live trading, most retail traders use the services of brokers such as Interactive Brokers, TradeStation which also have their own backtesting platforms and simulators. There are other locally present brokers who have their propriety software with which retail traders can connect.
Software for Algorithmic Trading
Retail traders often use their personal computer and internet connection to connect to the brokers interface. Though it works well for low frequency strategy there are some drawbacks such as power failure or internet connection loss situations. A good strategy must have risk managements in place to take decision under such situations, when the system is no longer connected. Also, the trader must have alternate arrangements ready for quickly getting connected again.
To reduce latency, quant funds usually opt for co-location facilities available at the exchanges, to reduce the geographical distance between the exchange and trading server. However, for retail traders this is usually prohibitively expensive. Hence, it is recommended that retail traders go for strategies which do not require high speed connectivity or execution.
All your queries related hardware and networking of automated systems are answered in this post.
Software for Backtesting Strategies
Typically, a retail trader will use a backesting platform such as MetaTrader, Quantopian, QuantConnect, TradeStation, Algo-Trader, Marketcetera which are a few popular and globally used options. MetaTrader is very popular among brokers and hence very popular among retail users. It is primarily used to trade in Forex, offers its API in ML4 which is quite similar to C++ and offers in-built indicators as well. There are many backtesting platforms, among which are Quantopian and Marketcetera that can connect to Interactive Brokers for live trading. Quantopian is one of the first online trading platforms which allow different contributors to share strategy and work together online.
If you’re a retail trader or a tech professional looking to start your own automated trading desk, start learning algo trading today! Begin with basic concepts like backtesting strategies, automated trading architecture, market microstructure, strategy backtesting system and order management system. You can also enrol in EPAT which is one of the most extensive algorithmic trading courses available in the industry.