Quantitative analysis is the use of mathematical models to analyze data points, with the intent of understanding a condition. This type of analysis is used to predict future outcomes, and is a key concept in financial modeling, as well as in other areas.
For example, large data sets can be examined to estimate the following on future dates:
- The prices of commodities
- The risk of hurricanes hitting a coastline
- The prices of equity instruments
- Changes in interest rates
- The severity of earthquake damage in certain areas
To improve the outcome of quantitative analysis, it may be necessary to install a feedback loop, where the models underlying predicted results are constantly adjusted to make the predictions of the model more closely align with "real world" results.
There is a tendency to rely completely upon the models underlying quantitative analysis. However, some individuals prefer to adjust the resulting predictions based on their own opinions or the experience of experts. This "qualitative analysis" can provide significantly enhanced results if there is a deep pool of experience that can be applied to a mathematical model, and which has never been numerically incorporated into the model.
In the business world, quantitative analysis is commonly used to model different financial outcomes, which can then be incorporated into the corporate budget model. It can also be used to forecast customer demand, the reactions of competitors in the marketplace, and the likely prices of options and warrants.