Quantitative Trading: Strategies of Quantitative Stock Analysis
- Quant trading uses algorithms and models for stock analysis.
- It is unhindered by emotions, unlike qualitative analysis.
- It comprises ratio analysis and project earnings.
Provide a short introductory paragraph here.
What Is Quantitative Trading?
Quantitative trading is defined as the trading of stocks based on their quantitative analysis. It emerged in the computer era, where computational algorithms and mathematical models have been used to study the financial status of the company’s stock in the market. Quants (Quantitative trading analysts) perform a valuation of the stock by checking numbers, whereas qualitative trading analysts use the traditional way, which involves researching the product, visiting companies, and meeting management teams. Quants have a scientific background, and hence they apply statistics to the analysis of stocks while trading.
Trading is always associated with emotion, either the emotion of greed or the emotion of fear, but quantitative trading is unhindered by emotions associated with financial decisions. The quantitative analysis comprises ratio analysis and project earnings. Ratio analysis is a method that involves the calculation of a certain basic ratio to check a company’s performance over time, and these ratios are determined in five different ways; liquidity ratios, profitability ratios, solvency ratios, market multiplies, and activity or efficiency ratios. In the project earnings, the dividend paid by the firm is determined as it is precisely proportional to the company’s future earnings.
Steps and Strategies of Quantitative Trading
There are four basic steps in quantitative trading; strategy identification, backtesting, execution, and risk management. Strategy identification is explored in great detail. The model must be extensively backtested after strategy selection and should be used in the real-time market to execute trades. In the end, if there is any risk involved, then risk management techniques should be employed.
Strategies of quantitative trading include momentum investing, trend following, mean reversion, statistical arbitrage, algorithm pattern recognition, and sentiment analysis.
- Momentum Investing: In this, the stock’s momentum is checked, and many indicators such as RSI (Relative strength index), etc. are used to measure the momentum.
- Trend Following: It is sometimes interchangeable with momentum investing.
- Mean Reversion: The model is programmed to detect markets with a long-term average.
- Statistical Arbitrage: It follows the same logic as mean reversion.
- Algorithm Pattern Recognition: It uses algorithms and does require powerful HFT (High-frequency trading) systems.
- Sentiment Analysis: It is not concerned with market data and usually analyzes text using natural language processing.
Advantages and Disadvantages of Quantitative Trading
The advantages of quant trading are that it eliminates human errors, backtesting, fewer resources, faster transactions, and data analysis.
The disadvantages are loss of control, extensive skills, continuous adjustments, technical errors, and curve fitting.
Conclusion
Quantitative trading is based on algorithms and models, which makes it much better than traditional qualitative analysis of stocks. It is unhindered by emotions, which avoids financial losses. Strategies for using the most appropriate model before implementing the analysis are the most important step in this type of stock analysis. It comes with both benefits and risks that should be taken care of by investors.
