On the oscillatory behavior of long distance traffic and telecom investments - an application for short term prediction

Until recently, the behavior of the telecommunications industry had shown a steady growth, as measured by a great variety of indicators: network and infrastructure deployments, equipment manufacturing, network usage, numbers of subscribers and users, stock prices, etc. This behavior suffered a recent upturn, accompanied by clear contraction symptoms, which fortunately are already evolving into a new growth period. The oscillatory nature of this industry can be explained using different theories, but the most adequate one is based on the accelerated growth in capacity deployment, partially originated by new entrants competing for new market shares, and over- optimistically projecting their required capacities. As a result, large network portions have remained "dark" and/or underutilized. This recent down cycle (already showing signs of recovery) will probably not be completely reversed, until a larger portion of the installed capacity is used, a fact which very likely will happen when there is a significant growth on the demand side. In this paper we analyze the oscillatory behavior of several telecom indicators, using Fourier theory and logistic growth models, which can be used to construct near term future industry scenarios. In this paper we analyze the oscillatory behavior of network usage (as measured by long distance traffic minutes originating and terminating in the United States, over a period of 27 years) and of worldwide investments in the telecom sector. The objective is to model the general growth trend of these indicators, as well as their oscillations with respect to