Algorithmic Trading

Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. Let us simplify it, Algorithmic trading is basically a computer making calculated and informed trade decisions for you. This system is extremely useful as it eliminates the possibility of human error such as making a decision based on less information, a decision based on emotion, or having issues with making the best possible decision.

Benefits of Algorithmic Trading:

  • Best Pricing: Trades are always well calculated and is only done for the best possible price.
  • Accurate and Instant:  The trade order is always placed at the correct instant of time.
  • Correct Timing: Trades are timed correctly to avoid high prices.
  • Low Cost: Trading is done in such a way that the transaction cost is reduced.
  • Checking: Simultaneous automated checks on multiple market conditions.
  • Back-testing: Algo-trading can be backtested which helps to identify the trading strategy used.
  • Avoiding Human Error: Reduces the possibility of human error that can be made by traders based on emotional and psychological factors.

Where is Algorithmic Trading used?

Algorithmic trading is being widely used in today’s world because of its various benefits. Some areas where it is being used widely are:

Mid-long term investors purchase stocks in large quantities but do not want to influence stock prices with discrete, large-volume investments.eg: pension funds, mutual funds, insurance companies.

Short-term traders and sell-side participants benefit from automated trade execution; in addition, algorithmic-trading aids in creating sufficient liquidity for sellers in the market.eg: market makers, speculators, and arbitrageurs.

Systematic traders use programs or codes with their trading rules and strategy and allow the computer to trade on its own. eg: trend followers, pairs traders, hedge funds, etc.

Trading Strategies:

Common trading strategies used in algorithmic trading to ensure profits and reduce costs are as follows:

  • Trend-following Strategies: There are trends like moving averages, channel breakout, price level movement, etc which can be used in algorithmic trading, using these trends directly and not involving predictive analysis is a very easy way to do algorithmic trading. Trades are initiated based on the occurrence of desirable trends, which are easy to implement through algorithms without getting into the complexity of predictive analysis. 
  • Arbitrage Opportunities: Arbitrage or risk-free profit is the process of buying a dual-listed stock at a lower price in one market and selling it in another for the differential price. The possibility of the price differential existing is less so an algorithm is made to scan the market for such differential and when found, efficient orders are made that ensure profit.
  • Mathematical Model-based Strategies: Using Proven mathematical models, like the delta-neutral trading strategy, allows trading to be safe and profitable.
  • Trading Range: It is a strategy is based on the concept that the price of asset returns to the average or mean price after a certain amount of time. Identifying and defining a price range and implementing an algorithm that trades when the defined price range is identified.
  • Volume-weighted Average Price: The strategy is to break up large orders and release dynamically determined smaller chunks to the market using stock-specific historical volume profiles. 
  • Time-weighted Average Price: The strategy is to break up large orders and release dynamically determined smaller chunks to the market using evenly divided time slots between a start and end time. 

Demerits of Algorithmic Trading:

  • Dependence on Technology: This means that if there is an error like a virus or loss of internet connectivity there could be many problems.
  • Loss of Human Control: Algo-Trading is completely automatic which means that even if a human finds a better trade it cannot be implemented.
  • Need for Constant Monitoring: Ideally, the point of algorithmic trading is so that humans don’t need to spend time on it. However, in reality, constant human monitoring for errors is essential.
  • Need to understand programming: For one to use algorithmic trading understanding of the program is important which makes it less available for everyone.
  • Not all strategies can be automated: Not all trading strategies can be programmed and automated.
  • Inability to understand irrational markets: It is not possible for programs to understand irrational markets. 

Ideally, algorithmic trading can achieve the profit and speed that most human traders cannot. For that reason, it is a bedrock of the modern financial world. However, this method has its downsides, so choosing algorithmic trading should be situational and should be after weighing both the pros and cons.

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