The following article is dedicated to the construction of an investment portfolio consisting of 3 investments from the Polish capital market found in the WIG20 index and from investment in gold. The purpose of the study was to determine the optimal length of the estimation window for building a portfolio with minimal risk and maximum efficiency. The length of the estimation window was also assessed in terms of the rate of return and the maximum cumulative loss. Data from 2017 was used to build the portfolio, and the weightings determined for the portfolio based on these data were evaluated using data from 2018 (from January to October). Based on the research, it was found that the optimal length of the estimation window ranges from 144 to 160 daily observations from the past. However, depending on the investment objective (risk minimization or maximization of efficiency) and the characteristics describing the portfolio, other lengths of the estimation window may also be appropriate.
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Artykuł poświęcono konstrukcji portfela inwestycyjnego składającego się z trzech inwestycji z polskiego rynku kapitałowego (inwestycji wchodzących w skład indeksu WIG20) oraz z inwestycji w złoto. Celem poniższego opracowania jest wyznaczenie optymalnej długości okna estymacji dla budowy portfela o minimalnym ryzyku oraz maksymalnej efektywności. Długość okna estymacji została także oceniona pod względem stopy zwrotu oraz maksymalnej skumulowanej straty. Do budowy portfela wykorzystano dane z roku 2017, a wyznaczone w oparciu o te dane wagi dla portfela poddano ocenie dla danych z roku 2018 (od stycznia do października). Na podstawie badań stwierdzono, że długość optymalnego okna estymacji zawiera się w przedziale od 144 do 160 dziennych obserwacji z przeszłości. W zależności od przyjętego celu inwestycyjnego (minimalizacja ryzyka lub maksymalizacja efektywności) oraz charakterystyki opisującej portfel można mówić o szerszych wartościach powyższego przedziału okna estymacji.
The article describes the main determinants influencing success of investment in diamonds. The purpose of the article is to examine how the caratage, clarity, cut, color, shape and the certification institution influence the price of a diamond. For this purpose, five econometric models were built (for specific weights of diamonds and one for all of the collected data). For the realization of this research goal characteristics of more than 265,000 diamonds were used. The paper identifies the differences between the variants of studied traits and the price of diamonds. The analysis found that the heavier stone the greater differences in price because of the variants of studied traits. The average difference in the valuation of diamonds due to the single-difference in the color of the stone is over 11% for all examined observations. In the case of the clarity this average difference in price between neighboring steps of the clarity of the stone is almost 8%, and for the quality of cutting is less than 5%. In addition, it has been shown that the most expensive stones are certified by GIA certification firm, AGS and HRD, and for the ten analyzed shapes most expensive form is round. For the shape characteristics an inverse relationship was noted than for other characters used, ie. the lighter stone is, the greater difference in the price of round diamonds than for other shapes. Round shape is the most popular for the jewellery application, especially in engagement rings and because this round shape is more expensive than other shapes.
The article describes the concept of the hedge, diversifier and safe haven investments. The main goal of this study is to examine whether there are links between the rates of return achieved on the Warsaw Stock Exchange (WSE) and rates of return on investments in gold. The author tested following hypothesis: the return on investment in gold acts as a hedge investment in the long term in relation to investments in the WSE main index, and at a time when investment in the WSE main index recorded a negative rate of return, investment in gold is a safe haven investment. To verify the hypothesis the author uses correlation coefficients and his own measure. The main conclusion from the research is that investing in gold acts as a safe haven investment for the investor which invests on the WSE.
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