The paper presents an approach to forecast competitors’ market share in the banking industry. Multivariate linear time series analysis was applied to a state space model with stochastic components. Three time series were interrelated as two exogenous variables and one endogenous variable. The interrelation was restricted to stochastic trends. Two dummy variables were added to the model to smoothen the exogenous variables. In the example, market shares development analysis was presented, two competitors correlate positively; that is, they have a nearly parallel development. Both competitors, however, correlate negatively with a third competitor; that is, the third competitor has an antagonistic relation to each of them. This type of analysis allows accurate and reliable forecasts which are important for competitor monitoring. Moreover, the forecasts can be used as an expected case in the market scenario. The paper is an important contribution to the exploration of the quantitative dynamics of competition systems that are generated by the business activities of competitors.

A time series usually consists of two regular components and one irregular component. The regular component is the trend, and in the present case, the season. The irregular component represents the random and serves as noise or shock or innovation. Trend is the backbone of development, which is described by a time series, because it indicates the direction—upward, downward or sideward (Enders, 2004). The season, however, represents regularity depending on the course of time, whose data accomplishes the trend data to a vibrating process (Franses, 1998). Additionally, the irregular component shapes the process with the result that the time series oscillates more or less. The study explores in more detail the role of trend in time series with respect to market shares.

Methodology

In the context of analyzing a competitive situation, the development of market shares is an important aspect because it brings to light the market dynamics that are driven by the ruling power structure. Both the study of the development of different market shares and the statistical analysis of the quantitative relations between the changing market shares provide information on competitors’ interaction. In this regard, it is of great importance to know whether the different developments show trends. If they show, it is crucial to find out what type of trend is present. Typically, market shares do not often show any deterministic trends, such as linear, quadratic and cubic, but rather very often show stochastic trends which have a stochastic component that is additively linked (multiplicatively linked terms, which are characteristic of non-linear trends, are omitted from this discussion for reasons of space) with the intercept of the trend.

Marketing Management Journal, Forecasting Competitor, Market Share, Multivariate Linear Time Series, Quarterly Market Shares, Loans Granted, German Tourist and Restaurant Industry.