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The paper proposes a ranking of WIG20 portfolio components based on the concept of the significance of components. We set an effective portfolio, composed of all of the components of a WIG20 portfolio, on a Markowitz curve. By the significance of components we understand a loss as an effect of a component being omitted. A loss itself can be measured by a variety of methods. In this paper the authors present a means of measuring the significance of components using the investor utility function, with the aid of which the optimum portfolio with maximal utility has been determined on the Markowitz curve. Next, each of the components is eliminated from the portfolio successively. The maximal utility of the optimal portfolio obtained from this elimination is then determined on the Markowitz curve. The suitable difference is the loss of utility for every tested component and this loss has been interpreted as the significance of the component. The ranking established in this paper has been compared to one obtained using the Sharpe coefficient.
The article shows that the Markowitz curve can be interpreted as an envelope of hyperbolas (parabolas). Describing a set of investment opportunities as a family of curves dependent on established parameters serves as an introduction to solving this issue.
The paper presents the problem of assessment of risk in financial models. This is important from practical point of view since inappropriate use of models in financial markets may cause large losses. The paper describes the sources of model risk and the methods of measuring and handling this risk. Two types of measures are proposed: distribution based measures and sensitivity measures. The remaining part of the paper contains two examples. The first one concerns risk of optimal two-stock selection related to estimation of the correlation coefficient, the second one concerns the risk of option pricing related to estimation of the volatility parameter.
The paper assesses the importance of industry effects present in stock returns, and compares them to country effects. We follow the assumption that strong industry effects might be present as a result of increasing power of globalization and economic integration, which lower the country-level differences. We find this development to be a contradiction to the theories of previous decades that suggested a dominance of country over the industry effects. As the economies change, we expect the country effect to become less dominant, or even fall behind the industry effects. These ideas are used in an application of portfolio management, in which we compare the risk and return characteristics of portfolios created using different strategies. By forming diversified and concentrated portfolios with industrial and country emphasis we show that industry diversification provides the greatest risk reduction.
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