A brief guide to quantitative trading

A brief guide to quantitative trading

There are many strategies traders and investors use to make money. These strategies are designed to maximize the Return on Investment (ROI) of the traders. For instance, a number of traders use technical analysis while others use fundamental principles to trade. Other traders combine the two strategies. In this article, I will introduce the quantitative technique which is used by a number of traders. From the onset, this strategy is a bit complicated especially to new traders. It is also a bit complicated to traders with no experience on programming languages such as MATLAB and Python. For traders with this background, creating a quantitative technique can help them achieve success within a very short period of time. In quant trading, a trader needs to follow four key strategies: formulating a strategy, strategy back testing, execution, and risk management.

Formulation or identification of strategy

In this stage, the goal is to find a good strategy that suits you, exploiting the edge and then deciding on the trading frequency. This is the stage where research is very important because it encompasses the strategy, seeing whether the strategy will fit into your portfolio, getting the required data to test the strategy, and optimizing the strategy. This is simply because it will help you maximize returns and minimize the amount of risk involved in trading. As a retail trader, you need to examine your capital requirements and how the allocation will affect your strategy.

In finding the strategy, research is very important. Luckily, there are many online resource sites that can help you in research. A good source is Seeking Alpha which presents research from thousands of traders, investors and researchers. Another good place to find this information is the investor market place which is provided by interactive brokers.

Two key areas of strategies will fall into mean-revision and trend-following strategies. The former strategy attempts to use the long-term mean of prices of assets. A good example is the spread between two correlated assets and standard deviations among the assets. The later looks at a trend with the aim of buying at the bottom and selling on the top. Another key strategy you can take advantage of is on the frequency. This should be done with the timing of your strategy in mind. Low frequency strategies should be done for traders who wish to hold positions for long periods while high frequency trades should be good for traders aiming to trade for short periods.

Strategy backtesting

No strategy should be applied in trading without backtesting. In backtesting, the goal is to establish whether a strategy applies to historical data. First, you need to find historical data which is available from many vendors. As a trader with a small account, Yahoo finance can help you. Alternatively, the best vendors are Bloomberg and Reuters. The historical data that you use should factor in 3 main issues: accuracy, survivor bias, and corporate actions. After finding the data, backtesting should be done using a good and credible software such as MATLAB, Excel and trade station. Backtesting will help you asses the applicability of the strategy.

Execution system

An execution system is the platform which will execute trades based on the strategy that you have developed. The system can be automatic, semi-automatic, or manual. When creating the execution system, it is important to consider the interface of your broker, the transaction costs, and the divergence performance. By making these considerations, you will be at a good place to have a good and credible system that has been backdated efficiently.

Risk Management

Risk management is a very important aspect for you to consider in quantitative trading. This is because the strategy is not always perfect. In fact, in the past, many quantitative hedge funds have been closed because of the massive losses. Therefore, it is important to have a good risk management strategy. One strategy this happens is through the Optimal Capital Allocation which is a branch of portfolio theory. It basically states that funds must be allocated in assets which gives it the maximum returns.

The second strategy you must always have in mind deals with psychology. Trading psychology is very important because losses can lead to serious psychological issues. Many people have committed suicide while others have gotten into suicide for failure to maintain losses.

As seen in the above chapters, quantitative trading is a very complicated area but one that is very interesting. Many brokerages provide investors with platforms for algorithmic trading. These platforms help the traders build up their strategies and implement them. If you have the time, quantitative trading can be very rewarding. In addition, quant is not always perfect. Therefore, having a good psychological edge can help you minimize losses.