Strategies That Govern Algorithmic Trading

Capital Markets CIO Outlook | Tuesday, January 22, 2019

Algorithmic trading is a set of rules and instructions, which are used on a stock exchange to automate the execution of orders without any human intervention. The rules are based on timing, price, quantity, and any other mathematical model, which helps a user to place a trade to generate profits at a high frequency and speed. Written below are a few algorithmic trading strategy and modeling ideas:

Momentum-based strategies:  Momentum-based strategies are methods of following trends to place a trade. Algo traders use this strategy to gain profit from an existing trend by taking advantage of the market swings. This strategy works as it does not make decisions based on behavioral or emotional biases. The traders need to detect the price momentum by following trends that have been going up for several days in a row. There are two types of Momentum Trading strategies:

•  Earnings momentum strategies: This strategy profits from the under-reaction, to information related, to short-term earnings.

•  Price momentum strategies: It benefits from the market’s slow response to a broader set of information.

However proper risk management techniques and monitoring are required to safeguard against any losses.

Arbitrage algorithmic trading strategies: Arbitrage algorithmic trading strategies are event-driven strategies that are triggered by the pricing inefficiencies before an acquisition, bankruptcy, mergers, spin-offs, and so on. Hedge funds and proprietary traders generally use this strategy.

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Statistical arbitrage algorithmic trading strategies: Traders using statistical arbitrage seek to profit from mispricing of assets based on the expected value of the assets. Misquoting in prices can be very beneficial for an algorithmic trading strategy. These opportunities exist for a very short duration, and algorithmic trading strategies can track such changes using automated machines. Another way to explain this strategy is to spread the risk among thousands of trades in a concise holding time and expecting to gain profit from the law of large numbers. It is based on a mean reversal hypothesis.

Market Making Algorithmic Trading Strategies: A market maker is an organization or an individual that quotes a buy and sell price of a commodity in order to make a profit on the bid-offer spread, or turn. They can enhance the demand-supply of securities. Market making gives liquidity to security which is not generally traded on a stock exchange.

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