Dilek Önkal

Evaluating probabilistic forecasts of stock prices in a developing stock market

Recent literature on the accuracy of forecasting in financial markets reveals contradictory results. These discrepancies can be attributed to the differences in forecasting environments as well as the differences in forecaster expertise that are employed by the researchers. Since the use of point and interval predictions by themselves do not aid in explaining the various aspects of forecaster performance, probabilistic forecasting provides a better alternative that can be used to gain insight into forecasting accuracy in such settings. This study aims to test the effects of forecaster expertise and forecasting environment on forecasting accuracy. Accordingly, various aspects of forecasting performance are studied in a developing stock-market framework.

Do forecasts expressed as prediction intervals improve production planning decisions

A number of studies have shown that providing point forecasts to decision makers can lead to improved production planning decisions. However, point forecasts do not convey information about the level of uncertainty that is associated with forecasts. In theory, the provision of prediction intervals, in addition to point forecasts, should therefore lead to further enhancements in decision quality. To test whether this is the case in practice, participants in an experiment were asked to decide on the production levels that were needed to meet the following weeks demand for a series of products. Either underproduction cost twice as much per unit as overproduction or vice versa. The participants were supplied with either a point forecast, a 50% prediction interval, or a 95% prediction interval for the following weeks demand. The prediction intervals did not improve the quality of the decisions and also reduced the propensity of the decision makers to respond appropriately to the asymmetry in the loss function. A simple heuristic is suggested to allow people to make more effective use of prediction intervals. It is found that applying this heuristic to 85% prediction intervals would lead to nearly optimal decisions.

Values and Risk Perceptions: A Cross-Cultural Examination

This article examines the relationship between values and risk perceptions regarding terror attacks. The participants in the study are university students from Turkey (n = 536) and Israel (n = 298). Schwartz value theory (1992, 1994) is applied to conceptualize and measure values. Cognitive (perceived likelihood and perceived severity) and emotional (fear, helplessness, anger, distress, insecurity, hopelessness, sadness, and anxiety) responses about the potential of (i) being personally exposed to a terror attack, and (ii) a terror attack that may occur in ones country are assessed to measure risk perceptions. Comparison of the two groups suggests that the Turkish participants are significantly more emotional about terror risks than the Israeli respondents. Both groups perceive the risk of a terror attack that may occur in their country more likely than the risk of being personally exposed to a terror attack. No significant differences are found in emotional representations and perceived severity ratings regarding these risks. Results provide support for the existence of a link between values and risk perceptions of terror attacks. In both countries, self-direction values are negatively related to emotional representations, whereas security values are positively correlated with emotions; hedonism and stimulation values are negatively related to perceived likelihood. Current findings are discussed in relation to previous results, theoretical approaches (the social amplification of risk framework and cultural theory of risk), and practical implications (increasing community support for a course of action, training programs for risk communicators).

Evaluating strategic directional probability predictions of exchange rates

The current paper aims to examine strategic predictions (with forecast horizons greater than six months) via the empirical probability (EP) technique. This technique was proposed initially to examine short-term tactical predictions (with forecast horizons less than three months), as set out in Pollock et al. (2005). The proposed procedure is based on the hypothesis that changes in logarithms of daily exchange rates follow a normal distribution over short horizons (of 10 to 30 days), but longer term forecast evaluation requires consideration of cumulative parameters consistent with changing means and standard deviations arising from primary and secondary trends. It is shown that ex-post EPs can be obtained for any predictive horizon above 30 days (e.g., 180 days) by using a combination of shorter (e.g., 20-day) Student t distributions. The procedure is illustrated using daily Euro/USD series from 4 January 1999 to 29 January 2008 to evaluate a set of Euro/USD directional probability predictions.

When providing optimistic and pessimistic scenarios can be detrimental to judgmental demand forecasts and production decisions

This paper examines the accuracy of judgmental forecasts of product demand and the quality of subsequent production level decisions under two different conditions: (i) the availability of only time series information on past demand; (ii) the availability of time series information together with scenarios that outline possible prospects for the product in the forthcoming period. An experiment indicated that production level decisions made by participants had a greater deviation from optimality when they also received optimistic and pessimistic scenarios. This resulted from less accurate point forecasts made by these participants. Further analysis suggested that participants focussed on the scenario that was congruent with the position of the latest observation relative to the series mean and discounted the opposing scenario. This led to greater weight being attached to this observation, thereby exacerbating the tendency of judgmental forecasters to see systematic changes in random movements in time series.

Forecasting in health-service provision

Good decisions and policy depend on a reasonable degree of foresight; this in turn relies on a forecasting process that is well-integrated with the strategic management of an organization. There is, however, very little research into the forecast process within organizations generally, or health-services in particular. N.......Noting this gap, a framework for health-services forecasting research is proposed. Further, results from a study conducted within this framework are conveyed. This study reports a questionnaire on a group of administrators in Turkish health- service sector involving 39 chiefs of staff, 38 hospital directors, 37 head nurses, 12 managers from in-patient medical institutions, 55 administrators from the Ministry of Health, and 56 administrators from provincial health directorates. Data collected were analyzed using descriptive statistics and nominal logistic regressions. The results revealed that as forecast providers, the most importance is given to the credibility of technique and ease in using available data in selecting a forecasting technique. As forecast users, the highest importance is given to forecast provider’s credibility and expected predictive accuracy. Interval predictions were perceived to be the most useful prediction format, while point forecasts are considered the least useful. These assessments persist, irrespective of their experience, position, and background.