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The traditional view of the investment analyst is of someone who forecasts the performance of stocks using personal skills and any relevant information that he is able to acquire. A successful analyst should be able consistently to pick share portfolios that significantly out‐perform arbitrarily selected portfolios of similar risk. Modern Portfolio Theory (MPT), by providing a consistent basis on which assets could be classified according to risk, made possible a rigorous examination of the potential for generating excess returns through such ‘active’ portfolio management. The consensus amongst finance academics is that the evidence overwhelmingly supports the proposition that one cannot generate excess returns using purely public information, e.g. money supply forecasts or published accounting data, though few would seriously question the commercial value of monopolistic access to non‐public information.

There are two distinct types of forecasting model in which past experience is used as an indicator of the future, and these may be termed “causal” models and “non‐causal” models. (An extensive discussion of these model types appears in Robinson and Wood and Fildes.) Non‐causal (naive) models simply extrapolate past history on the forecast variable and disregard those forces which caused the particular pattern for the time series. The object is to select the type of curve which provides the closest fit to a given historical series, and complex statistical procedures exist for carrying out this exercise. The great problem with forecasting by extrapolation is that it presupposes that the factors which were the main cause of growth in the past will continue to be the main cause in the future, which may be incorrect, and if this is the case the use of this technique will result in poor forecasts. If one considers sales of foreign holidays as an example, one realises that there may be significant changes in the variables affecting these sales, such as income changes, fare changes, and changes in exchange rates. In order to forecast sales of foreign holidays reasonably accurately it is therefore necessary to construct a causal model in which sales are explicitly related to the determining forces.

Roles of leadership in coping with uncertainty are explored in this paper. Through an in‐depth, empirically (CEOs of top, ASEAN publicly listed corporations) grounded discussion, the authors argued for the presence of a deep cultural divide between Eastern and Western leaders on coping with uncertainty. In the process, the authors devise a two dimensional, organic versus forecastability model of strategy behavior for polarizing East‐West leadership styles. Aspects of the Sun Tzu’s Art of War and 5,000 years old, I Ching are discussed with respect to foreknowledge and foresight respectively.