D81 - Criteria for Decision-Making under Risk and UncertaintyReturn

The purpose of this article is to present an industrial application of the Reference Class Forecasting Method (RCFM) developed by Kahneman and Tversky for planning and decision-making under uncertainty. Project plans are usually prepared on the basis of detailed calculations and arrangements according to selected project management methodology. Undertakings that are planned in this manner often fail and do not achieve their goals. However, the American Planning Association recommends using the RCFM as an additional method. The article presents four groups of projects implemented by a chemical industry company over four years. A few of the projects were accomplished according to the plan in terms of triple constraint i.e. time, cost, and scope. The cost aspect was taken into account in the paper. During the study, the planned and implemented costs of 222 projects were analysed. On the basis of the distribution of cost overruns, according to RCFM, new patterns of planned costs were prepared. The Reference Class Forecasting Method, which was effective for large homogeneous projects turned out to be completely useless for various projects implemented by the chemical company.

In the globalised world of the past decade, the characteristic movement of the real economy in Europe has been in the lower amplitudes of the economic cycle and has been complicated by the low effectiveness of fiscal and monetary policy tools and instability on the financial markets, which, in relation to the real economy, display features of autonomy and virtuality. The exchange rates of the euro, rouble and Czech crown display exceptional volatility, while the yields from financial instruments are at a historic minimum. These phenomena are the result of the stagnation of the European economy, a high level of indebtedness and an inability to effectively solve escalating political problems, such as military conflicts, terrorism, mass migration, economic sanctions, etc.

The article presents a short overview of heuristics and biases in managerial decision-making under risk and the consequences of such non-standard preferences for financial health of organisations. It is argued that, particularly in the case of inefficient ownership control or poor corporate governance, such bounded rationality manifestations can have a significant impact on a firm's performance. We also argue that in such cases risk preferences of individual managers can be more idiosyncratic. We illustrate that using the concepts of limited attention, reference-dependence decision-making and especially overconfidence (over-optimism). The relevance of such concepts is shown on a number of real data studies analysing investment policies of firms, their leverages, financing strategies and decisions on mergers and acquisitions. We also include recommendations targeted at minimising negative outcomes of bounded rationality at the managerial level in respect of financial health of firms. The final parts concern limits of the current empirical literature.

The income of agricultural enterprises has always been influenced by both weather and price volatility. Nevertheless, the risk environment of various farms seems not to be the same. Similarly, risk factors are not independent of each other. The aim of the paper is to assess the spatial and commodity particularities determining the risk environment of agricultural enterprises in the Czech Republic. Within the main objective, the efficiency of crop insurance depending on farm size is also considered. Using calculation of statistical indicators of variability in the panel data, as well as Monte Carlo simulation, differences in farm risk exposure and efficiency of crop insurance between small and large farms were found. It was found that the risk of crop price volatility is generally of a more systemic nature and it is more difficult to diversify than the risk of crop yield volatility. The hypothesis that smaller crop acreage increases the risk of farm crop yield fluctuation was not statistically confirmed within a set of medium and large agricultural enterprises. In the sample of typical farms with specialized crop field types of farming, it was revealed that agricultural insurance is more effective for small farms than for large agricultural enterprises. Based on the main findings, we make some recommendations for the business sector and policy makers.

Our rapidly changing world has been challenging insurers to keep the pace. Given the qualitative changes in risk trends, the insurance industry has encountered a problem of insurability limits and shifting boundaries of the private insurance sector. The possibilities of covering enormous uncertainties, particular risks and new or modified risks are discussed in this paper. The basic problem of how the nature of risks has evolved over time and obstacles to insuring against certain risks are explained in this paper, and some innovative ways to overcome the mentioned obstacles are listed. One of the most recently discussed issues is the impact of catastrophic losses and man-made disasters since their frequency and extent have been continuously growing recently. In order to handle the rapid changes in our world and to maintain its stable position, the insurance industry has found some ways to heighten the limits of insurability, i.e., adjustments of terms and conditions, careful risk selection and pricing, reinsurance, innovations, public private partnerships, or multi-source financing of incurred losses have been used recently. However, given the more stringent regulatory requirements which are going to be implemented by 2013, capital requirements may increase and thus the capacity of the insurance industry might be reduced and the industry might have to find other solutions for heightening its capacity.

The paper is concerned with an implementation of behavioral aspects of a heterogeneous agents model (HAM) with the worst out algorithm (WOA). The WOA replaces periodically the trading strategies that have the lowest performance level of all strategies presented on the market by the new ones. The model includes a possibility to change the mood of the investors on the market. This modification allows for changing phases of optimism and pessimism. This feature enables generation of more realistic financial time series. It is shown how a mood change on the financial market influence a persistence of financial time series.