7 Proven Algorithmic Trading Techniques Used by Institutional Investors

Published July 5, 2019


Are you a retail investor who thinks algorithmic trading is impractical due to its cost as well as trading volume? It’s time to mimic institutional investors, hedge funds as well as significant banks. They routinely use various computer-driven algorithmic strategies in volatile markets which succumb to trade influence as well as market makers. These techniques enable them to cut costs of trades as well as improve their revenues. Here are some of the methods used

  1. Arbitrage

When institutional-based investors seek to take advantage of occasional tiny market price discrepancies, which arise in security’s market price trading on two different exchanges, they incorporate this strategy.

For arbitrage to take place, three conditions are met

  • Similar assets shouldn’t trade at a comparable price on all markets
  • Two assets with identical cash flows shouldn’t buy or sell as the same prices
  • An asset whose future charge is known shouldn’t trade today using the future price

Arbitrage is only possible with finance products as well as securities trades electronically. Transactions need to occur parallel to each other to reduce chances of market risks or opportunities of a single market changing before either transaction completes

  1. Index fund re-balancing

This technique focuses on mutual funds such as an individual’s retirement accounts as well as pension funds. They are adjusted regularly to show a new fee of funds’ underlying assets.

Re-balancing creates a chance for trading people using algorithms to capitalise the foreseen buys as well as sell depending on stocks’ numbers in an index fund. Buying as well as selling is carried out by computerised systems to enable the best prices, low-cost as well as timely results.

  1. Mean reversion

This strategy entails using mathematical formulae in stock investing. Experts compute stock’s highest and lowest prices to get an average. Investors use this, to determine the trading range for shares and calculate the average price by the use of an analytical strategy.

In a situation where the current market’s price is lagging, average price and stock are referred to as attractive in the hope that its price will rise.

When the price of the current market is beyond the low estimate, stocks are said to become undesirable, and investors predict the price will fall, this will force them to revert to the original mean price. Standard deviation is majorly used as a trading indicator. This technique is commonly used in algorithm trades.

  1. Market timing

Another common technique is market timing. Institutional investors use this method, and it involves three tests. They are as follows

  • Back-test – this is the first step in market timing. It usually consists of simulating a hypothetical trade using a piece of in-sample information. Optimisation then follows in acquiring the most optimal result.
  • Forward-test – here, algorithms run through the mere days to make sure its performance is within back-tested expectations.
  • Live-test – here a developer had to make a comparison between the live trades and the back-tests not forgetting the forward test models.
  1. Scalping

This is a different technique from others. It depends on a difference in bid and a given security price. The main objective in using this technique is to make an impact in the markets where traders or investors formulated a spread on a bid.

Serious capital is required for this technique to provide the anticipated results. Its complex thus requires experts to handle it. If you are a novice when it comes to investing, stay clear of this strategy until you learn the ropes of trade techniques fruitfully.

  1. Trend following

It’s one of the most popular techniques used on trading based on algorithms. The strategy is to identify specified patterns that are used to carry out buying and selling. In a situation where a trading stock breaks resistance and you carry out an order to purchase. It’s time to stay alert because once the strength breaks free, you may short sell the security in question.

  1. Momentum

Institutional investors’ are keen on markets’ trends as well as markets’ sentiments. They aim at finding patterns which portray a continuity in specific trends towards a particular direction. They then focus on it to see how it goes. A good example is where one may buy a tiny position of a specified stock and add to it when shifting in prices are in your favour.

Using trading based on algorithms technique, you hardly have to keep a close eye on them. You sit back and watch the trading portfolio order the systems any time you want it to execute a specified order.

Benefits of using these strategies are because of its ability to zero out emotions in the trading process. Institutional investors are very keen on their money, and they need something that provides high-quality judgement. Automating procedures curbs overtrades as some trades buy and sell at the slightest opportunity a trade window opens. These techniques minimise situations of human-based errors. It’s a desirable option for investing as it responds in a fraction of a minute to marketing conditions. Its time as a retail investor to think of this strategy next time you want to invest!

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