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EN
Aim/purpose–In this paper, a market volatility-robust portfolio composition frame-work under the modified Markowitz’s approach with the use of sampling methods is developed in order to improve the allocation efficiency for a portfolio of financial in-struments formulation procedure at an increased market volatility.Design/methodology/approach–In order to overcome the risk of not receiving an optimal solution to the portfolio optimization (suboptimal outcomes of attribution of weights in allocation procedures) the developed model, first, implements the rationale that financial markets largely feature two states, i.e., quiescent (non-crisis; low market volatility) periods that are occasionally interspersed with stress (crisis; high market volatility) periods and, second, relies on many input samples of rates of return, either from an empirical distribution or a theoretical distribution (mitigating estimation risk). All computational results are reported for publicly available historical daily data sets on selected Polish blue-chip securities. Findings–Not only did the presented method produce more diversified allocation, but also successfully minimized the unfavorable effects of increased market volatility by providing less risky portfolios in comparison to Newton’s method, typically used for optimization under portfolio theory. Research implications/limitations–The research emphasized that in order to get a more diversified investment portfolio it is crucial to outdo the limitations of a single sample approach (utilized in Markowitz’s model) which may on some occasions be statistically biased. Thus it was proved that sampling methods allow to obtain a less concentrated and volatile allocation which contributes the investment decision-making. However, the current research focused solely on publicly available input data of particular securities. In this manner, an additional analysis can be prepared for other jurisdictions and asset classes. There can also be considered a use of other than variance risk measures.Originality/value/contribution–The suggested framework contributes to existing methods a wide array of quantitative data analysis and simulation tools for composing an unique approach that directly addresses the task of minimizing the adverse implications of increased market volatility that, in consequence, pertains to knowledgeable attributing of investment portfolio proportions of either individual or institutional investors. The prepared method is also proved to hold demanded computational quality and, importantly, the capacity for further development.
XX
Transformacja systemu podatkowego w Polsce trwa od 1992 r. Podatki stanowią nadal główne źródło wpływów budżetowych, jednak punkt ciężkości został przesunięty z płatności obciążających dochód na obciążenia konsumpcji (VAT, akcyza). Wpływy z podatków pośrednich zapewniają obecnie ponad 60%, a z podatków dochodowych 25% dochodów budżetu państwa. Tym samym rola VAT i akcyzy w dochodach budżetowych w ciągu 10 lat wzrosła trzykrotnie, a podatków dochodowych zmniejszyła się o połowę. Udział podatków pośrednich w PKB kształtował się na poziomie 11,0—13,0%, a podatków dochodowych zmniejszył się o połowę. Analiza polskiego systemu podatkowego, wykorzystująca test Paersona, wykazała, że na decyzje inwestycyjne przedsiębiorstw nieznacznie większy wpływ miała zmiana opodatkowania dochodów niż opodatkowanie wydatków. Można więc powiedzieć, że zmiany systemu podatkowego w kierunku zmniejszenia udziału opodatkowania dochodów zarówno we wpływach budżetowych, jak i w PKB były właściwe. (abstrakt oryginalny)
EN
The transformation of the tax system has been continued since 1992 in Poland. Taxes still represent the main source of budget revenue; however, the fiscal charge was moved from income tax payments to tax consumption (VAT, excise tax). The indirect tax revenue provides government 's budget with 60% revenue and income taxes with 25%, respectively. In the process, during the last 10 years, the importance of VAT and excise tax in government's revenue has increased 3 times and the importance of the income taxes decreased by a half. The share of indirect taxes in GDP was going for around 11,0-13,0%, and the share of the income taxes was reduced by half. The analysis of Polish tax system, using the Pearson 's test, showed that changes in the taxation of income had slightly greater impact on the enterprises investment decisions than the taxation of expenditures. Therefore, it can be said, that the changes in tax system directed to reduce the share of income tax in budget revenue, as well as in GDP, were reasonable. (original abstract)
EN
The effects of investment decisions are different. Many studies show that the average investor earns significantly below their expectations, and often even below the market average. The blame for this could be the irrational investors behaviors. The cause of these behaviors are among the others behavioral inclinations. The paper presents methods which show the effects of irrational behavior of investors, as well as methods that allow the verification of behavioral inclinations.
EN
Both the prospect theory as well as the cumulative prospect theory are aimed at explaining the way the decision-maker see and evaluate risky decisions. They allow for the explanation of some inconsistency between observed decision-makers behaviours and axioms of the expected utility theory. For years financial aspects of cumulative prospect theory are the subject of many research studies. The purpose of the paper is to review some issues connected with the cumulative prospect theory and its application to financial market. Presented papers concern issues related to the value functions, concept of loss aversion and the construction of portfolio selection models with some simplifying assumptions. In our paper we also present observed in real life, but often mysterious, behaviours of investors, who evaluate investment choices relative to some reference point, feel loss aversion and revalue objective probabilities.
EN
The application of neural network system for multi-dimensional stock market data analysis is presented in the paper. Developed system predicts stock price movements based on daily quotation data like: volume, minimum and maximum session price, opening and closing price. Several studies were carried out, to compare systems investment decisions, with decisions that were made on the basis of some commonly used methods of stock market analysis. These methods are: MACD, Bootstrap, Markowitz Portfolio. For valuation purpose, the real stock market data of the four largest Polish companies were used. All companies are quoted on the Warsaw Stock Exchange and belong to the WIG 20 index. For the benchmarking, only stock data from the year 2009 were used. In order to enrich the benchmarking tests, three investment scenarios were added. First known as the skeptical assume that only incorrect investment decisions were made. Second known as the optimistic assume that only correct investment decisions were made. Last one known as passive assume that no investment decision were made - it is so called "buy and hold" conception. The benchmarking results confirmed, that the neural network system is able to make investment decisions, that significantly increase the profitability of the investment portfolio. Neural network system provide investment suggestions, that can be considered as an alternative to other commonly used methods of stock market analysis. However statistical tests proved a high correlation between quality of systems investment decisions and market trend and lack of correlation to the "optimistic" scenario. Neural network systems may help in investment process, but cannot be considered as fully reliable way of investment process automation.
XX
Celem artykułu jest zbadanie możliwości samofinansowania działalności inwestycyjnej w przedsiębiorstwach o liczbie pracujących powyżej 9 osób według wybranych sekcji PKD. Na podstawie danych statystycznych GUS zbadano wielkość wypracowanej nadwyżki finansowej i jej rozdysponowanie oraz poziom samofinansowania przyrostu aktywów obrotowych i aktywów ogółem w badanych przedsiębiorstwach. W artykule poziom samofinansowania przyrostu aktywów obliczono jako relację poziomu nadwyżki finansowej do przyrostu aktywów. Nadwyżkę finansową obliczono natomiast jako sumę wyniku finansowego netto i amortyzacji. Badaniami objęto lata 2002-2007.
EN
The article presents assets the self-financing possibilities survey of companies where work more than 9 people. An amount of the generated finance surplus and an increase level in the current assets self-financing as well as assets in total in examined companies were surveyed on the basis of statistical data. The author made an attempt to answer a question what is the ability of self-financing assets increase in analysed companies. The surveys cover the years 2002-2007. Statistical data concerned the examined companies have been presented by selected sections of the Polish Classification of Activities.(original abstract)
PL
Określenie struktury zależności jest kluczową kwestią w zarządzaniu instrumentami finansowymi. Niewłaściwa interpretacja siły powiązań rynków może prowadzić do błędnych decyzji inwestycyjnych. Zastosowanie modeli przełącznikowych pozwala modelować dynamikę badanych procesów. Połączenie teorii kopul i modeli przełącznikowych daje w efekcie elastyczne narzędzie, które może być wykorzystane do modelowania zmieniającej się w czasie struktury zależności. Charakterystyki, które możemy określić po oszacowaniu parametrów (takie jak średnie czasy powrotu do poszczególnych stanów i czasy trwania w stanach) są istotnymi informacjami, które mogą być wykorzystane przez inwestorów. Jako przykład zastosowania przestawionej metodologii przedstawiono wyniki dotyczące wzajemnych związków DAX oraz WIG20. Wyniki potwierdzają ścisły związek równoczesnych okresów bessy na obu rynkach. (fragment tekstu)
EN
The aim of this paper is to investigate of DAX and WIG20 dependency based on weekly returns. In order to capture asymmetry of dependence structure, Archimedean copulas were used. The dynamics of this relationship were obtained by applying two-state switching model. The copula based regime switching model allows us to model time varying dependence structure in a flexible way. Empirical results confirm dynamic lower tail dependence.(original abstract)
PL
Problemem każdego inwestora jest podjęcie decyzji, w które z dostępnych na rynku giełdowym spółek powinien zainwestować, aby osiągnąć maksymalny zysk przy minimalnym ryzyku. Kolejny problem to ile różnych spółek powinno znaleźć się w jego portfelu inwestycyjnym. W klasycznych modelach konstrukcji optymalnych portfeli inwestycyjnych zazwyczaj spółki wybierane są na podstawie danych dotyczących notowań giełdowych. Jednak na stopę zwrotu danej spółki wpływają różne czynniki, które w czasie trwania inwestycji ulegają zmianom. W artykule zostanie omówiona dynamiczna metoda konstrukcji optymalnego portfela inwestycyjnego, w której spółki zostają wyselekcjonowane przez zastosowanie podejścia min-max dla wybranych wskaźników charakteryzujących spółkę. Metoda wyboru portfeli inwestycyjnych zostanie zastosowana do wybranych danych pochodzących z Giełdy Papierów Wartościowych w Warszawie.
EN
Every investor must make decision which of stocks he should choose to portfolio to received maximum return and minimum risk in the future. The next problem is how many stocks should find out in his investment portfolio. In classical approach to construction the optimal investment portfolio, stocks usually are selected on the base of the data concerning exchange quotations. However, many different factors affect on the rate of return of given index. All these factors are changing during the investment period. So it is important to make changes in portfolio during the investment. In this paper the dynamic method to construction the optimal investment portfolio will be presented. In presented approach, stocks will be selected by application the min-max rule to selected indicators characterizing given index. The model of selection of investment portfolio will be applied to data from the Warsaw Stock Exchange.
EN
This paper applies to investment decisions on housing markets based on forecasts housing prices constructed on the basis of expert opinion using the Weibull distribution. The first part shows the different ways to generate or increase revenue from property. The second part addresses the issue of using different types of price forecasts on the housing market that are useful in making investment decisions. The third section deals with the aim of the study i.e. indicates the possibility of using the model of subjective probability Weibull distribution built on the judgment of experts to construct house price forecasts and to assess the chances of profitability of investment.
XX
W artykule przedstawiono analizę uwarunkowań podejmowania inwestycji deweloperskich w głównych miastach Polski. Do tego celu wykorzystano elementy analizy taksonomicznej. Wzięto pod uwagę zmienne diagnostyczne reprezentujące merytorycznie dwa aspekty: uwarunkowania społeczno-ekonomiczne potencjalnych obszarów geograficznych (miast) inwestycji deweloperskiej oraz uwarunkowania rynku mieszkań. Dokonując wyboru konkretnych zmiennych kierowano się nie tylko adekwatnością merytoryczną, lecz także łatwą dostępnością danych oraz ich kompletnością i wiarygodnością. W analizie wykorzystano dane GUS.
EN
For many decades Poland has been struggling with housing deficit. In present economic circumstances this problem should be gradually solved by market behaviours, i.e. natural forming demand and supply. The deficit elimination depends, i.a. on developer enterprises, working in market circumstances, as well as on private construction. The Author proposes utilisation of taxonomic methods to research circumstances of taking decisions by developers on different local markets in 18 cities. (original abstract)
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