We present a methodology to perform Financial Analysis with as much information as available. The problem we solve is the assessment of investment projects; we are to determine whether or not an investment project is profitable. We perform that task at the qualitative, semi-quantitative, and quantitative levels, depending on how much information there is at hand.
The main advantage of the method presented here is that it can deal with very little information about quantities, still yielding some results. The least piece of information the system can work with is a set of Order of Magnitude Relations (omrs) among the model variables. If those omrs are sufficient to disambiguate the results of our model, we can tell whether an investment project is worthwhile or not. If all we have is a few omrs it may or may not determine the outcome of our investment project analysis. Later on, we provide the system with additional information (perhaps imprecise), and the results will be refined. The more precise the provided information is, the more accurate the results will be. If at the end, all provided variables are precise, the results are the same as performed via traditional analysis.
Keywords: order of magnitude reasoning, approximate reasoning, qualitative reasoning, interval computation, financial analysis.