Qualitative analysis is a process of analyzing stocks, that utilizes subjective judgment dependent on non-quantifiable data, for example, the executives aptitude, industry cycles, quality of innovative work and worker relations.
Qualitative analysis stands out from quantitative analysis, which centers around numbers found in reports, for example, balance sheets.
The two methods, nonetheless, will frequently be utilized together to look at an organization's operations and assess its potential as an opportunity for investment.
The difference between qualitative and quantitative methodologies is like the contrast between human and artificial intelligence.
Quantitative analysis utilizes definite information sources, for example, profit margins, debt ratios, earnings multiples, etc.
These can be connected to an electronic model to yield a precise outcome, for example, the reasonable estimation of a stock or an estimated figure for earnings growth.
Obviously, for now, a human needs to compose the program that does the math, and that includes a reasonable level of subjective judgment.
When they are customized, however, PCs can perform quantitative analysis in portions of a second, while it may take even the most talented and profoundly prepared people minutes or hours.
Qualitative analysis, then again, works with intangible, inexact concerns that belong to the social and experiential domain instead of the mathematical one.
This methodology relies upon the sort of intelligence that machines, as of now lack, since things like positive relationship with a brand, management reliability, customer loyalty, competitive advantage and cultural movements are troublesome, seemingly impossible, to capture with numerical inputs.