In this article, we will discuss
- What is Quantitative Analysis?
- What Is Quantitative Trading and How Does It Work?
- What Are the Metrics Used in Quantitative Analysis?
- What are the Pros and Cons of Using Quantitative Analysis?
- How to Implement Quantitative Analysis While Trading?
After the introduction of digital trading platforms, there is practically no limit to the number of trades which individuals can indulge in within a day. However, with the increase in trading activity also comes high chances of human errors, which can lead to losses. Thus, traders need specific techniques which can help them execute high-volume trades and increase their chances of generating substantial returns.
One of them is quantitative analysis. Keep reading this blog to learn more!
What is Quantitative Analysis?
Quantitative analysis is a trading technique that leverages mathematical and statistical data to estimate the value of financial assets. It helps traders understand the current reality of the market and how it can affect the returns from a particular asset.
This strategy also takes into consideration affecting factors like interest rates, GDP, etc. It helps investors, as well as financial analysts, draw a comparison between past and present events in order to estimate future outcomes.
Now that you have a clear idea of quantitative analysis, let's move on to its application in trading.
What Is Quantitative Trading and How Does It Work?
As the name suggests, quantitative trading is an investment strategy which utilises quantitative analysis. It uses mathematical computations, number crunching and other statistical methods to help traders identify trading opportunities.
For this purpose, traders usually take the help of specialised software in order to conduct current and historical data analysis of their target assets. These algorithms usually have pre-set rules for providing buying and selling signals and help traders make informed decisions.
They usually scan the market for data after specific intervals and also take into account the prevailing market factors. This enables such software to perform statistical analysis of the given data and help investors get an idea of the possible future outcomes.
What Are the Metrics Used in Quantitative Analysis?
Now, there are various metrics used by investors when they conduct quantitative analysis. Some of the most popular ones are as follows:
- Revenue Growth
Revenue is one of the most important indicators of a business’s financial standing. Thus, while checking a company's financial statements, investors need to analyse its revenue growth or decline over a particular time period.
To calculate the revenue growth of a company, apply the formula given below:
Revenue growth = (Revenue for this period - revenue for last period) ÷ revenue for last period x 100%
Experts say that annual revenue growth of 10%, which has been sustained by an organisation for a considerable time period, is a very good sign.
- P/E Ratio
A company’s profit-to-earnings (P/E) ratio is the amount of money which investors are willing to pay for buying a stock to its earnings. For instance, if the P/E ratio of Reliance is 25.62, it means investors are willing to pay ₹25.62/share for the earnings each share provides.
You can use the formula given below to find the P/E ratio of your target asset:
P/E ratio = Current share price/earnings per share
Now, high P/E ratios usually represent a company’s high growth potential and vice versa. However, it is not a hard and fast rule. But, experts always recommend comparing an organisation’s P/E ratio with that of its peers in the same sector.
In case it has a higher P/E ratio than the industry average, it may indicate that the stock is overvalued. Alternatively, a low P/E ratio may indicate the stock to be undervalued.
- Gross Profit Margin
The gross profit margin of a company represents its gross profit percentage to its sales. Essentially, it is the amount of profit that remains after deducting the cost of goods sold (COGS). You can find it out by using this formula:
Gross profit margin = (Net Sales - COGS) / net sales
Now, a high gross profit margin in a company is considered a sign of good performance. It entails that the organisation makes justified use of its COGS and can adequately cover its financing, operating and other expenses. A high gross profit margin also shows a company’s cost efficiency.
Thus, it helps investors analyse a company’s overall financial health along with peer-to-peer comparisons.
- Peer-To-Peer Comparison
To draw a comparison between companies in the same sector, peer-to-peer comparison is a very effective metric. It allows investors to compare organisations of the same size and assess their fair value.
Generally, investors use metrics like earnings before interest taxes , EBITDA, P/E ratio, price-to-sales (P/S) ratio, etc., to conduct peer-to-peer analysis. It helps them make an estimation of the growth potential of each company and make an informed decision. This metric also comes in handy while conducting portfolio management.
What are the Pros and Cons of Using Quantitative Analysis?
Just like any other trading strategy, quantitative analysis also has its set of pros and cons. They are listed below:
Here are the advantages of using quantitative analysis:
- This trading strategy uses specific data models or algorithms. Thus, it significantly minimises the chances of human error.
- Quantitative research mechanisms can enable individuals to execute trades at a lightning pace. For instance, they can assess more than 100 strategies and place their trade orders within a matter of seconds.
- It also allows back testing, which enables investors to test current data with historical data.
- Quantitative data analysis techniques allow individuals to scan through immense volumes of share market data, saving a lot of time.
Mentioned below are the disadvantages of quantitative analysis:
- Executing quantitative analysis strategies requires a high level of skill.
- There are always chances of technical errors due to potential bugs present in the algorithm’s code.
- Due to this strategy’s reliance on historical data, it is prone to curve fitting. Thus, in situations when there is randomness in the market, the data model can generate irrational outcomes.
- Also, the algorithms are automatic; there is no way to adjust the data model during times of high market volatility. Under such circumstances, it can either shut down or generate unreliable results.
- Given the market's dynamic nature, most quantitative strategies can become obsolete within a span of years, requiring investors to change them completely.
How to Implement Quantitative Analysis While Trading?
Here are the steps you can follow to apply quantitative analysis in your trading strategy:
Step 1 – Decide which strategy you wish to implement. It may include momentum investing, sentiment analysis, mean reversion, etc.
Step 2 – Design your data model. In this regard, there are several tools available in the market which will help you generate your own model.
Step 3 – Run the diversification criteria and test it out on sample data in order to ensure its accuracy.
Step 4 – Include the algorithm in your current strategy and use it while conducting trades.
Now that you know the power of quantitative analysis, you can use this strategy to choose the most profitable assets. However, using this tactic involves high trade volumes, which can lead to significant brokerage charges. In this regard, the New-Gen Samco app can be an ideal choice.
Brokerage charges on this platform are flat ₹20 per executed order, helping you bank more profits per trade. Furthermore, its unique engine assesses all your past trades and provides personalised trading suggestions so that you can make informed decisions.
Download the Samco app today and take your trading game to the next level!
1. What is the difference between quantitative and qualitative analysis?
Ans. Quantitative analysis is an investment technique that aims to find the profitability of an asset based on various financial metrics like P/E ratio, Gross Profit margin, etc. Alternatively, qualitative analysis aims to assess the profit-making potential of a company depending upon its qualitative aspects like product and service quality, management, etc.
2. What are the different quantitative analysis strategies?
Ans. Some of the commonly used quantitative analysis strategies are algorithmic pattern recognition, momentum investing, sentiment analysis, trend following, mean reversion and statistical arbitrage.
3. What are the different tools used in quantitative analysis?
Ans. Investors use a wide array of tools when it comes to quantitative analysis. Some of them are mathematical analysis software, graphs, hypothesis testing and linear regressions.
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