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Title:Analiza indikatorjev dna na borznem trgu
Authors:ID Plečko, Samuel (Author)
ID Strašek, Sebastjan (Mentor) More about this mentor... New window
Files:.pdf MAG_Plecko_Samuel_2022.pdf (2,52 MB)
MD5: 28E818B1CCC094328FAC363916522597
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:EPF - Faculty of Business and Economics
Abstract:Namen magistrske naloge je predstaviti pomembne indikatorje borznega dna v času medvedjih trendov in preučiti njihovo napovedno moč na primeru indeksa S&P 500 v času dot-com balona, velike recesije in krize zaradi koronavirusa. Osredotočamo se na indikatorje razpoloženja, indikatorje tehnične analize in makroekonomska indikatorja ter indeks volatilnosti in multiplikator čistega dobička. Ugotavljamo, da je edini indikator, ki je pravilno napovedal vsa tri borzna dna, indikator razpoloženja individualnih investitorjev, vendar le z enim izmed treh uporabljenih kriterijev. Uspešna napovedovalca pa sta bila tudi indeks volatilnosti VIX in multiplikator čistega dobička. Ocenili smo tudi tri probit modele za napovedovanje borznega trenda, vendar je njihova natančnost pri določanju borznega dna v primerjavi z uporabo izbranih indikatorjev slabša. Na podlagi zbranih rezultatov ugotavljamo, da je mogoče na podlagi treh omenjenih indikatorjev zanesljivo napovedati borzno dno.
Keywords:S&P 500, borzni trend, indikatorji razpoloženja, indikatorji tehnične analize, makroekonomski indikatorji
Place of publishing:[Maribor
Publisher:S. Plečko
Year of publishing:2022
PID:20.500.12556/DKUM-82827 New window
UDC:330.4:336.76
COBISS.SI-ID:127056899 New window
Publication date in DKUM:25.10.2022
Views:980
Downloads:134
Metadata:XML DC-XML DC-RDF
Categories:EPF
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:05.09.2022

Secondary language

Language:English
Title:Analysis of bottom market indicators
Abstract:The purpose of this master's thesis is to present important indicators of the stock market bottom during bearish trends and to examine their predicted strength on the example of the S&P 500 index during the dot-com bubble, the great recession and, the covid crisis. We focus on sentiment indicators, technical analysis indicators, and macroeconomic indicators, as well as volatility index and price-to-earnings ratio. We find that the only indicator that correctly predicted all three stock market bottoms is the sentiment indicator of individual investors, but with only one of the three criteria used. The VIX volatility index and the price-to-earnings ratio were also successful predictors. We also evaluated three probit models for predicting the stock market trend, but their accuracy in determining the stock market bottom is worse than to the use of the selected indicators. Based on the results, we determine whether it is possible to reliably predict the bottom of the stock market based on the three mentioned indicators.
Keywords:S&P 500, stock market trend, sentiment indicators, technical analysis indicators, macroeconomic indicators


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