Temat: Portfolio analysis - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Wielowymiarowa analiza atrakcyjności inwestycyjnej spółek sektora spożywczego notowanych na Giełdzie Papierów Wartościowych w Warszawie
Multivariate investment attractiveness analysis of food sector companies of Warsaw Stock Exchange
Autorzy:: Kijek, Arkadiusz
Powiązania:: https://bibliotekanauki.pl/articles/425056.pdf
Data publikacji:: 2014
Wydawca:: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:: investment attractiveness index
linear ordering
portfolio analysis
optimization
Opis:: The article presents the results of study of investment attractiveness of food sector companies listed at the Warsaw Stock Exchange. The multivariate statistical methods are applied to evaluate the financial standing of companies. The author constructs the investment attractiveness index that is used to order companies by their economic and financial standing. Based on the values of investment attractiveness index the structure of optimal portfolios are determined according to Markowitz portfolio theory. The results of survey indicate directions of investment portfolio diversification.
Źródło:: Econometrics. Ekonometria. Advances in Applied Data Analytics; 2014, 4(46); 175-188
1507-3866
Pojawia się w:: Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Forecast of prices and volatility on the day ahead market
Autorzy:: Ganczarek-Gamrot, Alicja
Powiązania:: https://bibliotekanauki.pl/articles/425278.pdf
Data publikacji:: 2013
Wydawca:: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:: principal component analysis (PCA)
SARIMA model
DCC model
Value-at- -Risk
portfolio
Opis:: The subject of this paper is the forecast of prices and volatility on the Day Ahead Market (DAM). The analysis was made for two portfolios of four contracts from 30.03.2009 to 28.10.2011 for two fixings on DAM. Four out of 24 contracts noted on DAM were chosen by PCA. Prices were forecast by the SARIMA models incorporating autocorrelation and seasonality. Value-at-Risk calculated through the DCC model was used to forecast volatility. These models describe well the prices and volatility on the DAM and may be used for forecasting purposes. Prices on fixing 2 are characterized by higher volatility than prices on fixing 1.
Źródło:: Econometrics. Ekonometria. Advances in Applied Data Analytics; 2013, 1(39); 111-120
1507-3866
Pojawia się w:: Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:: Biblioteka Nauki

Artykuł

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