Integrated valuation model

Abstract

As mergers and acquisitions have become flavor of the industry and company market capitalizations oscillating very dynamically, knowing an accurate price of a company has become paramount both for the investment bankers and the academia. From discounted cash flows, earning-based valuations and industry benchmarking various models have been proposed but all are closely linked with critical assumptions and guess work and cannot be uniformly applied across diverse industries, geographies and dynamic economic and financial environment. There are multiple versions of valuation models available in the market selling from tens to hundreds of dollars. These models, while sufficient in most of the situations, do not take context into account. That leads to a disparity in valuations because there are several aspects outside of earnings that affect the final value. We have identified the following correctable flaws that we aim to improve upon. We think the focus of many valuation models is too narrow, and limits their use. Also, sometimes the industry and macroeconomic contexts are missed in the analysis. The database, usually, is not structured around learning, but rather a static set of values which need manual updating. Resultantly, no uniform standard is followed by hundreds of analysts and stock traders. Also these models are one-off jobs, once valued they don t take the output into account for further calibration of the process by incorporating the feedback of the output into the input! We have attempted to incorporate features that address the above issues, in both the input and output part of the valuation. In the input section, we have linked up with sites like IMF and BSE to render real time macroeconomic and script data. This customizes the values for each economy, and for sectors and industries within the economy. Thus after entering some details about a company or a script, the model is able to make several useful assumptions based on the context. Also, through the model we aim to optimally use the data available online, and obviate the need to manually update the database and make the comparable companies data available for user to provide inputs in an informed and intelligent manner. In the form for output, we have incorporated the data from various methods of valuation, both separately and as an average. This allows a user to see the impact of various forces as they affect the valuation of the company they are interested in, and allows a single number valuation based on all parameters combined. Additionally, it has been ensured that the model follows certain user guidelines in terms of look and feel, error checks and help menus so as the overall experience of using the model is encouraging and pleasant. What adds to its vigor in time is the retention of previous values, and the ability to draw upon the previous valuations. This allows the possibility of learning. The real time updating allows the model to remain robust even in the face of changes in the environment, with no input needed from a user other than regular use. To be sure, there are areas where more work is needed. Some areas where we think the model needs further refinement are in the realm of user interface by adding graphical charts, stringent error checks, augmenting the industry sectors and countries, additional approaches of valuations leading to an improved experience and precise results. The objective is to position this model as a full-fledged producton internet to popularize the model among the business managers, investment bankers and academia and in turn getting some valuable and real-life feedback. However, as it stands, the model in its current shape is indeed an integrated valuation model that incorporates the effects of various parameters, and is therefore flexible enough to be used anywhere, anytime. The model offers a novel approach to valuation modeling and a chance to refine it further dynamically to incorporate many more features. The same feeling has been echoed by number of our batch mates who were the trial user base for this model.