Application of digital technology in financial services has seen to be increased over the years. Adaptation of Artificial Intelligence and Machine Learning to use data driven by digital channels and provide better service to improve customer experience is also observed. Financial service firms such as insurance companies, asset management firms and the banking sector are focusing more on digitalization to enhance customer interface.
One such use of technology in financial services is Algorithmic Trading which allows users to opt for high frequency trading. Algorithmic Trading is an AI powered trading system that analyzes huge amounts of data faster than humans. Moreover, innovations in cloud service and cloud computing are beneficial for algorithmic trading and its adaptation will be great for the growth of the algorithmic trading market.
What Is Algorithmic Trading?
Algorithmic trading is also known as automated trading, black-box trading or simply algo trading is a method of executing trades using automated programs using a predefined set of instructions for accounting variables such as time, price and volume. This process follows the algorithm (instructions) for placing a trade to generate profits at high speed and frequency that is impossible for humans.
It combines programming technology with the financial market to provide trading execution at precise moments. The mathematical model used for the instruction set of algo trading makes the market more systematic by ruling out the impact of human emotions on trading activities. Execution of this algorithm is also based on trading volume i.e volume-weighted average price or the passage time i.e. time-weighted average price.
In this process, a computer program will automatically monitor the stock price and the moving average indicators. It will place the buy or sell orders when the defined conditions are met. Using algo trading, a trader no longer needs to monitor live prices and graphs or put in the orders manually. This trading system automatically identifies the correct trading opportunity and opts for it.
Algorithmic trading can be used in different forms of trading and investment activities which includes mid-to-long term investors, short term traders or systematic traders. There are certain strategies followed in this method and some of the common algorithmic trading strategies are trend-following strategies, index fund rebalancing and arbitrage opportunities.
Technical Requirements for Algorithmic Trading
Algorithmic trading allows traders to build their own algorithm and use it to generate buy or sell signals. Although it has some technical requirements which need to be carried through in order to get proper results. To transfer the identified trading strategy into an integrated computerized trading system one need to have computer programming knowledge or hire skilled programmers or one can use pre made trading softwares.
In addition to that, network connectivity, access to trading platforms and market data feeds to monitor opportunities and place trades is vital. It also requires infrastructure to backtest the trading system before its utilization in the real market. The backtesting needs historical data available to study complexity of implemented instruction in the algorithm.
Benefits of Algorithmic Trading
Algorithmic trading method provides many benefits to the customer or trader as well as to the financial service providers. Some of its benefits are discussed below.
- Trader order placement is executed instantly and at best possible prices.
- It reduces risk of manual errors while placing trades and also reduces transaction cost.
- Algo trading simultaneously checks multiple market conditions and helps to avoid any significant price fluctuation.
- Traders can backtest different trading strategies using historical and real time data to check if it is viable to use in current market conditions.
Algorithmic trading is based on quantitative analysis and it brings software technology and the finance sector together to provide high frequency trading. Increasing knowledge and accessibility of share trading individuals have shown interest to invest in the market.
Also, progressive attitude towards full time trading is something financial service providers look forward to and focus on incorporating better technology interface. This will benefit the global algorithmic trading industry in the coming year.