Algorithmic trading, also known as automated trading, black-box trading, or algo-trading, involves placing a deal using a computer programme that adheres to a predetermined set of guidelines (an algorithm). Theoretically, the deal can produce profits at a pace and frequency that are beyond the capabilities of a human trader.
The specified sets of instructions might be based on a mathematical model, time, pricing, quantity, or any other factor. In addition to providing the trader with prospects for profit, algo trading increases market liquidity and makes trading more organised by minimising the influence of human emotions.
- Computer programming and financial markets are combined in algorithmic trading to carry out deals at exact moments.
- Algorithmic trading aims to remove emotions from transactions, provides the best possible execution of a deal, instantly puts orders, and could result in cheaper trading commissions.
- Trend-following tactics, arbitrage possibilities, and index fund rebalancing are examples of popular trading methods.
- Additionally, algorithmic trading is carried out in accordance with trading volume (volume-weighted average price) or time (time-weighted average price).
- You need computer access, network access, financial market expertise, and coding skills in order to begin algorithmic trading.
Using Algorithms in Trading
- When a stock's 50-day moving average surpasses its 200-day moving average, buy 50 shares of the company. (A moving average is a calculation that takes the average of previous data points to smooth out daily price volatility and identify patterns.)
- When the stock's 50-day moving average drops below the 200-day moving average, sell any shares you still have.
A computer software will automatically monitor the stock price (as well as the moving average indicators) and place the buy and sell orders when the predetermined criteria are satisfied using these two straightforward instructions. The trader is no longer need to manually enter orders or keep an eye on live pricing and graphs. This is automatically accomplished by the algorithmic trading system, which accurately recognises the trade opportunity.
Benefits of Algorithmic Trading
- The most competitive pricing are used to complete trades.
- Placing trade orders is quick and precise (there is a high chance of execution at the desired levels).
- To prevent material price movements, trades are executed immediately and at the proper moment.
- lower transactional expenses.
- automated tests running simultaneously on various market situations. less possibility of human mistake when placing transactions.
- To determine whether algorithmic trading is a feasible trading method, accessible historical and real-time data may be used for backtesting.
- decreased the likelihood that human traders would make errors based on emotional and psychological reasons.
High-frequency trading (HFT), which tries to profit by placing a lot of orders quickly across a variety of markets and different decision factors based on preprogrammed instructions, makes up the majority of algo trading today.
Algorithmic Trading Strategies
Any algorithmic trading strategy has to have a profitable opportunity that can increase revenues or decrease costs that has been found. The following are typical trading methods employed in automated trading:
Strategies for Following Trends
The most popular algorithmic trading techniques rely on price level changes, moving average trends, channel breakouts, and other relevant technical indicators. Since these techniques don't need making any predictions or price projections, they are the simplest and easiest to apply using algorithmic trading. Without delving into the complexities of predictive analysis, trades are started based on the occurrence of favourable patterns, which are simple and basic to apply using algorithms. A well-liked trend-following tactic is to use the 50- and 200-day moving averages.
Opportunities for Arbitrage
The price difference can be used as risk-free profit or arbitrage by purchasing a dual-listed stock at a cheaper price in one market and simultaneously selling it at a higher price in another market. Since there are occasionally price differences between stocks and futures products, the same procedure can be repeated. Profitable possibilities are made possible by implementing an algorithm to find these price differentials and placing the orders effectively.
Rebalancing of Index Funds
In order to bring their holdings into line with their respective benchmark indexes, index funds have set times for rebalancing. This generates lucrative trading opportunities for algorithmic traders, who profit from anticipated transactions that, depending on the number of stocks in the index fund, give returns of 20 to 80 basis points right before index fund rebalancing. For prompt execution and the best pricing, such transactions are started using algorithmic trading algorithms.