MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE
E-Jurnal Matematika, 2016 When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks.
I GEDE ERY NISCAHYANA +2 more
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Conditional Variance Forecasts for Long-Term Stock Returns [PDF]
Risks, 2019 In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate ...
Enno Mammen +3 more
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Conditional Variance Estimator for Sufficient Dimension Reduction [PDF]
Bernoulli, 2021 23 pages, 3 ...
Lukas Fertl, Efstathia Bura
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Common Persistence in Conditional Variances [PDF]
Econometrica, 1993 Summary: Since the introduction of the autoregressive conditional heteroskedastic (ARCH) model by the second author [ibid. 50, 987-1007 (1982; Zbl 0491.62099)], numerous applications of this modeling strategy have already appeared. A common finding in many of these studies with high frequency financial or monetary data concerns the presence of an ...
Tim Bollerslev, Robert F. Engle
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Variance clustering improved dynamic conditional correlation MGARCH estimators [PDF]
Computational Statistics & Data Analysis, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gian Piero Aielli, Massimiliano Caporin
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Modelling and forecasting of growth rate of new COVID-19 cases in top nine affected countries: Considering conditional variance and asymmetric effect. [PDF]
Chaos Solitons Fractals, 2021 Ekinci A.
europepmc +3 more sources
Mean–variance relationship and uncertainty [PDF]
Seonmul yeongu, 2022 This study investigates the impact of uncertainty on the mean-variance relationship. We find that the stock market's expected excess return is positively related to the market's conditional variances and implied variance during low uncertainty periods ...
Jun Sik Kim
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Modeling Realized Variance with Realized Quarticity
Stats, 2022 This paper proposes a model for realized variance that exploits information in realized quarticity. The realized variance and quarticity measures are both highly persistent and highly correlated with each other.
Hiroyuki Kawakatsu
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The Use of GARCH Autoregressive Models in Estimating and Forecasting the Crude Oil Volatility [PDF]
European Journal of Interdisciplinary Studies, 2022 Today, oil is one of the most popular commodities traded globally, due to its indispensable character and multiple properties offered to mankind. Increased attention is paid to the analysis of volatile and fluctuating trends in the overall price of this ...
Radu-Cristian MUȘETESCU +2 more
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Modeling the exchange rate of the euro against the dollar using the ARCH/GARCH models [PDF]
Bankarstvo, 2016 The analysis of time series with conditional heteroskedasticity (changeable time variability, conditional variance instability, the phenomenon called volatility) is the main task of ARCH and GARCH models.
Kovačević Radovan
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