Let’s take a quick look at some of the Top Algo Trading Strategies expert traders follow.
Momentum and Trend based Strategy:

These algo trading strategies are the simplest and most widely used. They simply follow
the trends and the momentum in the market and the trades are executed accordingly.
The technical indicators like moving averages and price level movements are studied
and buy or sell orders will be generated automatically when a set of conditions are
fulfilled based on these technical indicators.
The momentum and trend based strategy also considers the historical and current price data to
analyse if the trend is likely to continue or not and makes decisions accordingly. There are no
complex predictions to be made; just straight and easy trend following. If the desired event
occurs, trade is executed, if not then not.
A simple example can be to set the algorithm in such a way that the system is instructed to buy
the shares of a company when the 30-days moving average goes above the 180-days moving
average and sell the shares when the 30-days moving average goes below the 180-days moving
average. This strategy is a simple interpretation of the technical indicators.
Arbitrage Strategy

Arbitrage opportunities exist when there is a price difference in the securities on different stock
exchanges. Arbitrage strategy is one of the algo trading strategies that make use of these
arbitrage opportunities by using the computers to identify the opportunity as quickly as
possible and making use of it.
If a stock is listed at a lower price on one exchange and at a higher price on the other, the
algorithm immediately identifies the price differential and executes a trade to buy on the low-
priced exchange and sell on the high-priced exchange.
This is where the speed and accuracy of algo trading, compared to human trading, plays a
significant role. Although the price difference between the exchanges is not too much, so the
volumes of such trades need to be kept high to gain considerable amounts of profit. This
strategy is mostly applicable in terms of forex trading.
As an example of the strategy, Infosys is listed on both NSE and NYSE.
The algorithm will receive feeds from both the exchanges about the price of the company’s
stock and with the help of the forex rates, the price in one currency will be converted into the
other. If the algorithm finds a large enough price differential in both the listings due to the
currency rates, it will automatically place a buy order on lower-priced exchange and sell order
on higher priced one. Once the order gets executed, the trader gets arbitrage profits.
Mean Reversion Strategy

Mean reversion strategy is one of the algo trading strategies that is based on the basic
premise that the prices of a security may go high or low, but they do come back to an
average or mean value at some point in time. It is also known as the counter-trend or
reversal strategy.
This strategy finds out the upper and lower price limit of a stock and the algorithm
works to execute orders when the price goes beyond the normal range. The algorithms
calculate an average price based on the historical data of the security and execute a
trade expecting that the prices will come back to the average price. This means that if
the prices are very high, they will come down and if they are very low, they will go up.
So, this algo trading strategy is useful when the prices are at the extremes and the
traders can benefit from the unexpected swings. However, this strategy may also end up
backfiring when the prices actually do not end up reversing as fast as expected and by
that time the moving average matches up with the price, leading to a reduced reward to
risk ratio.
As an example of the strategy, when the 30-days ‘moving average’ of a security is lower
than the 90-days moving average, it is assumed that the price is too low and is expected
to return to the 90-days moving average price. This gives a signal to the algorithm to buy
the security.
Statistical Arbitrage Strategy

Statistical arbitrage is one of the short-term algo trading strategies.
It is based on the trading opportunities that arise due to the price inefficiencies and
misquoting of the price of the securities. This occurs in securities that are related to
each other or are similar in nature. Now it is quite evident that inefficiencies and
misquoting do not stay for a very long time.
They get corrected in a short duration and therefore algo trading becomes an efficient
way to catch them and make profits. In this case, the algorithms consist of complex
mathematical models that detect the price inefficiencies as soon as possible and
execute the trade before the prices get corrected.
A human trader may not be able to track such changes, even if he is extremely
dedicated, aware and up to date, but the algorithm, due to the predefined instructions,
tracks them as soon as they occur. As an example of the strategy, the two companies
Bajaj Auto and Hero MotoCorp are somehow related to each other in terms of security
pricing. If the price of Bajaj goes down, the price of Hero will also go down but it will
soon come up as the price went down due to market inefficiencies.
Based on statistical arbitrage strategy, the algorithm will immediately detect the fall in
Hero’s stock price and buy it and then sell it later when the price gets corrected, thereby
making a profit.
Weighted Average Price Strategy:

This is also one of the most efficient algo trading strategies. It can either be based on
volume weighted average price or time-weighted average price. In this strategy, the
orders are large but they are not released at one go. The orders are released in small
parts using either historical volume profiles of the stock or certain pore defined time
slots between a start and end time.
The objective of this strategy is to execute the order as close as possible to the volume
weighted average price or the time-weighted average price, to reduce the impact on the
market. The computers and algorithm play a successful role in releasing the orders in
small parts, which may not be humanly possible with as much efficiency and accuracy.
Thus, we can observe that there are multiple strategies that can be chosen from while
doing algo trading. The algorithms are designed in ways that are compatible with the
strategy chosen by the trader and the orders are executed accordingly.
So, although it is the algorithm that is placing the orders, it is actually the trader who
designed the algorithms and the strategies at I Cap Financial Services who defines how
the trading will occur. The traders can choose which strategy to follow at what time
depending upon the market conditions and other factors.