1. What is Quantitative analysis?

Quantitative analysis is a process of gathering and evaluating mathematical and statistical data such as revenues, expenditure and profits of a company to understand the performance of the company. Previously managers used to make mostly decisions based on their experience or on the spot but now as we have evolved with new technology and gadgets with the help of computers managers can analyze huge data and then take decisions accordingly which benefit the company the most. Quantitative analysts identify various trading patterns, then build models to assess those patterns, and use the information extracted from them to make future predictions about the price and direction of different stocks and commodities. 

 

2. Difference between quantitative and qualitative analysis?

In quantitative analysis managers use data sets or numbers for decision making and completely rely on current collected data or historic data. So these are objective and deductive in nature. Usually with the help of quantitative analysis it leads to better decision making, this is because no non-data is involved in this no misinformation or ambiguity or emotions just pure numbers. Whereas managers use qualitative analysis to assess a company’s performance when numbers are very less or difficult to find. The analysis doesn’t include numbers and so it is subjective and inductive. The various ways to collect this analysis are Customer feedback, in depth interviews, Group discussions, searching and analysis of close competitors.

Both are best in their own ways but to get best results mostly companies do both types of analysis to get maximum accuracy in taking future decisions and for growth of the company.

 

3. Quantitative analysis techniques

There are various tools with the help of which quantitative analysis can be done. Few of them are:

1. Data Mining

It is a mixture of computer programming skills and statistical methods. With the help of data mining one gets a huge increase in the quantity and size of available data sets. Data mining techniques are used to evaluate huge sets of data, with the aim of finding patterns or any kind of correlation between them which could possibly help the company in future.

 

2. Regression Analysis

It is a very common and widely used technique nowadays which is used by various people apart from managers of companies like the statisticians and economists. In this analysis statistical equations are made to predict or estimate the impact of one variable on another. For instance, regression analysis can be used to determine how much profits a company can earn in the near future by analyzing the historic data.  Or what could be the sales in coming years, basically we check the correlation of two factors one dependent and other independent and we can have various independent variables as well and then we check how due to change in independent variables dependent variable change, also we get to know whether there is positive or negative correlation to help predict future using same method.

3. Linear Programming

Many companies usually encounter a shortage of resources such as factory space, production machinery, and labor. In these situations, company managers must find ways to allocate resources effectively. Linear programming is another quantitative analysis method that determines how to achieve goals in such an optimal solution. It is also used to determine how a company can make optimal profits and reduce its operating costs, keeping other things constant.