The use of quantitative trading strategies are becoming more and more prevalent these days.
These strategies comprises methods which are both simple as well as complicated, in order to find the optimal investment strategies.
These strategies only take volume and price into consideration to compute the trade trends.
The main logic lying underneath the quantitative trading strategies is that if a stock is rising, no matter for whatever reason then it should be able to be tracked or traded, using a particular mathematical formula.
The two major categories of these strategies are momentum trading and mean reversion.
Momentum trading first analyzes the historical data, in order to find a trend or a pattern and then compare it with the current prices.
This analysis looks for trends that are growing in value at increasing rates.
Every single piece of data will either contradict or support the trend.
The mean reversion analysis establishes a statistical relationship between current prices to the statistical trend.
Reversion price basically means that the current price will return to its earlier advanced stage or to its historical mean.
Some of the most common tools used in quantitative analysis are statistical probability, moving averages and oscillators.
The accuracy of the methods used may vary in different cases or situations.
These strategies use variety of mathematical and statistical tools to filter the data, in order to separate the trending periods from the non trending ones and then to capture the trend as far as possible.
The advancement in information and technology has allowed people to add data real time and thus, you can easily add updated information in order to have better accuracy in finding the trend.
Arbitrage has also started becoming a popular quantitative strategy.
However, it requires much computer knowledge and advanced algorithm, which makes people reluctant to use it.