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KAJIAN MODEL HIDDEN MARKOV UNTUK MENDUGA VOLATILITAS INDEKS HARGA SAHAM
Prima: Jurnal Pendidikan Matematika, 2019 Abstrak Volatility is a measure of uncertainty. Volatility can either be measured by using the standard deviation or variance between returns. The problem is volatility is unobservable, and estimating volatility is not a trivial task.
Abdul Baist
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Forecasting Foreign Exchange Volatility Using Deep Learning Autoencoder-LSTM Techniques
Complexity, 2021 Since the breakdown of the Bretton Woods system in the early 1970s, the foreign exchange (FX) market has become an important focus of both academic and practical research.
Gunho Jung, Sun-Yong Choi
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Sustainable Development and Engineering Economics, 2023 Measurement and forecasting of volatility and income correlation are achieved by non-parametric methods using high-frequency price data. Due to accurate calculations of conditional volatility and correlation forecasting, it is possible to correctly ...
John Guyomey, Andrey Zaitsev
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Measuring and Forecasting Volatility in Chinese Stock Market Using HAR-CJ-M Model
Abstract and Applied Analysis, 2013 Basing on the Heterogeneous Autoregressive with Continuous volatility and Jumps model (HAR-CJ), converting the realized Volatility (RV) into the adjusted realized volatility (ARV), and making use of the influence of momentum effect on the volatility, a ...
Chuangxia Huang +3 more
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Modeling and Forecasting the Volatility of Eastern European Emerging Markets
East Asian Economic Review, 2009 This study has attempted to seek a volatility forecasting model that can reflect sufficiently the long memory characteristic in the volatility of four Eastern European emerging stock markets, naThis study has attempted to seek a volatility forecasting ...
Sang Hoon Kang , Seong-Min Yoon
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Frontiers in Environmental Science, 2022 There is increasing evidence that European Union allowance (EUA) futures return distributions exhibit features of time-varying higher moments (skewness and kurtosis), which plays an important role in modeling and forecasting EUA futures volatility ...
Xinyu Wu, Xueting Mei, Zhongming Ding
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Historical Perspectives in Volatility Forecasting Methods with Machine Learning
RisksVolatility forecasting for financial institutions plays a pivotal role across a wide range of domains, such as risk management, option pricing, and market making.
Zhiang Qiu +3 more
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Hybrid Forecasting Models Based on the Neural Networks for the Volatility of Bitcoin
Applied Sciences, 2020 In this paper, we study the volatility forecasts in the Bitcoin market, which has become popular in the global market in recent years. Since the volatility forecasts help trading decisions of traders who want a profit, the volatility forecasting is an ...
Monghwan Seo, Geonwoo Kim
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Evaluating Volatility and Correlation Forecasts [PDF]
, 2009 This chapter considers the problems of evaluation and comparison of volatility forecasts, both univariate (variance) and multivariate (covariance matrix and/or correlation). We pay explicit attention to the fact that the object of interest in these applications is unobservable, even ex post, and so the evaluation and comparison of volatility forecasts ...
Andrew J. Patton, Kevin Sheppard
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Adding dummy variables: A simple approach for improved volatility forecasting in electricity market
Journal of Management Science and Engineering, 2023 This study used dummy variables to measure the influence of day-of-the-week effects and structural breaks on volatility. Considering day-of-the-week effects, structural breaks, or both, we propose three classes of HAR models to forecast electricity ...
Xu Gong, Boqiang Lin
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