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Pariteta tveganja v portfeljih vrednostnih papirjev : delo diplomskega seminarja
ID Škerlep, Matej (Author), ID Bernik, Janez (Mentor) More about this mentor... This link opens in a new window, ID Valentinčič, Aljoša (Comentor)

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Abstract
V želji vlagateljev po čim boljši naložbeni strategiji obstaja veliko različnih metod sestave optimalnega portfelja. Med manj znanimi so strategije, ki se primarno osredotočajo na razporeditev tveganja med finančnimi instrumenti. Mednje spada tudi pariteta tveganja, pri kateri želimo, da so relativni doprinosi k volatilnosti celotnega portfelja enaki za vse vrednostne papirje. V delu diplomskega seminarja je matematično formuliran pogoj za pariteto tveganja in njegova variacija z metodo najmanjših kvadratov. V nadaljevanju s pomočjo algoritmov implementiranih v programskem jeziku R analiziramo učinkovitost metode na delnicah indeksa S&P 500 ter rezultate primerjamo z Markowitzevim in enakomerno uteženim portfeljem. Podrobneje se osredotočimo tudi na padec finančnih trgov spomladi leta 2020 zaradi pandemije koronavirusa.

Language:Slovenian
Keywords:optimalen portfelj, pariteta tveganja, minimizacija variance, metoda najmanjših kvadratov, alokacija kapitala, S&P 500, FAANG
Work type:Final seminar paper
Typology:2.11 - Undergraduate Thesis
Organization:FMF - Faculty of Mathematics and Physics
Year:2021
PID:20.500.12556/RUL-128975 This link opens in a new window
UDC:519.8
COBISS.SI-ID:73965827 This link opens in a new window
Publication date in RUL:20.08.2021
Views:1279
Downloads:104
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Secondary language

Language:English
Title:Risk parity approach to portfolio construction
Abstract:
There exist many different asset management strategies which aim to find an optimal portfolio. Less known are strategies that primarily focus on risk allocation among financial instruments. One of these is the risk parity approach, where we seek to find a portfolio in which the relative risk contributions of all assets are equal. We derive the condition for risk parity and look at its modification using the method of least squares. Afterwards, we present algorithms implemented in the programming language R and analyse the efficiency of the risk parity approach on stocks included in the S&P 500 index. Further, the results are compared to the Markowitz model and equally-weighted portfolio. Part of the analyses is focused on the market crash in the spring of 2020 due to the Covid pandemic.

Keywords:optimal portfolio, risk parity, minimum variance, least squares, capital allocation, S&P 500, FAANG

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