Results 61 to 70 of about 2,588 (267)

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source

VOLATILITY ANALYSIS AND INFLATION PREDICTION IN PANGKALPINANG USING ARCH GARCH MODEL

Barekeng
One of the concerns of both developed and developing countries, as well as in a region, is the amount of inflation that occurs. Inflation is a serious problem.
Desy Yuliana Dalimunthe, Elyas Kustiawan, Khadijah -, Niken Halim, Helen Suhendra   +4 more
doaj   +1 more source

Modeling the interaction across international conventional and Islamic stock indices

Cogent Economics & Finance, 2021
Islamic financial instruments have been experiencing rapid growth in the last 50 years. Despite the unique motivation in formulating them, namely based on Syariah law, their movement might link to those of the conventional ones.
Abdul Hakim, Awan Setya Dewanta, Sahabudin Sidiq, Riska Dwi Astuti   +3 more
doaj   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source

Price Volatility Spillover in Agricultural Markets: An Examination of U.S. Catfish Markets

Journal of Agricultural and Resource Economics, 2003
Price volatility spillovers in the U.S. catfish supply chain are analyzed based on monthly price data from 1980 through 2000 for catfish feed, its ingredients, and farm- and wholesale-level catfish.
Cumhur Buguk, Darren Hudson, Terrill R. Hanson   +2 more
doaj   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

Mixed normal conditional heteroskedasticity [PDF]

, 2002
Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components ...
Paolella, Marc, Haas, Markus, Mittnik, Stefan   +2 more
openaire   +3 more sources

Identifying Drivers of Deviations From Rational Expectations: Using a New Irrational Index for Inflation Forecasts

Journal of Forecasting, EarlyView.
ABSTRACT Most studies on inflation forecasts have studied behavioral biases, informational frictions, or external shocks in isolation, without considering how these factors jointly drive deviations from rational expectations. We therefore adopt an integrated framework that simultaneously estimates the behavioral, informational, and external ...
Belen Chocobar, Peter Claeys
wiley   +1 more source

Analysis of Istanbul Stock Market Returns Volatility with ARCH and GARCH Models

İstanbul İktisat Dergisi
In today’s world where globalization is intensely experienced, differences in risk perception, developments in capital markets, and the negativities faced in the markets due to uncertainty are very important when researching the structures of the stock ...
İpek M. Yurttagüler
doaj   +1 more source