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Wyszukujesz frazę "Statistical simulation methods" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Sampling methods for investment portfolio formulation procedure at increased market volatility
Autorzy:
Dzicher, Mateusz
Powiązania:
https://bibliotekanauki.pl/articles/2027253.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Investment decisions
Optimization techniques
Portfolio selection
Statistical simulation methods
Opis:
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 instruments 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.
Źródło:
Journal of Economics and Management; 2021, 43; 70-89
1732-1948
Pojawia się w:
Journal of Economics and Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of two-stage endo-atmospheric separation using statistical methods
Autorzy:
Samani, M.
Pourtakdoust, S. H.
Powiązania:
https://bibliotekanauki.pl/articles/280453.pdf
Data publikacji:
2014
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
separation
safe distance
uncertainty
statistical methods
Monte Carlo simulation
Opis:
In this paper, selection and analysis of an atmospheric two stage separation system is di- scussed. The main purpose of this system is to test a supersonic parachute projectile, where a stage separation occurs after the burn out. Subsequently, the parachute is ejected from the payload after a minimum elapsed time. The separation times, for the supersonic parachute ejection, as well as the time needed for a safe clearing distance between the two stages are two critical issues in the separation process. In this respect, the knowledge of the relative position between the two stages is necessary to assure a safe distance and in order to ad- just the required system parameters. In addition, as the nature of the parameters involved in the separation process is not deterministic, it would be useful to utilize the concept of random variables in the dynamic modeling of the separation process. In this paper, the mo- deling and simulation of the separation process is initially performed and partially verified. Subsequently, an approximate statistical method is utilized to acquire some probabilistic in- formation about the relative distances at the two critical times. According to the simulation results, the relative distance between the two stages falls in a safe region. Finally, Monte Carlo simulation is also performed for comparison and verification of the statistical results that indicated a small and acceptable deviation between the two approaches. Thus, it can be concluded that the simpler approximate statistical approach is also valid for uncertainty analysis and can provide valuable knowledge needed in the preliminary design phase of the separation system.
Źródło:
Journal of Theoretical and Applied Mechanics; 2014, 52, 4; 1115-1124
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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