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Time series analysis and forecasting = selected contributions from ITISE 2023 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Time series analysis and forecasting/ edited by Olga Valenzuela ... [et al.].
其他題名:	selected contributions from ITISE 2023 /
其他題名:	ITISE 2023
其他作者:	Valenzuela, Olga.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xii, 329 p. :ill. (some col.), digital ;24 cm.
內容註:	- Part I Advanced Econometric Methods -- Banking sector development and economic growth in developing countries. Does the change in the shadow economy matter? A Nonlinear Panel ARDL -- Improving the prediction of Norwegian household consumption by adjusting for temporary fluctuations in dividend income -- Inflation expectations change during the pre-war and war period. A comparison of Ukraine and neighboring economies -- Analysis of diversification in investment portfolios Return and Risk for different time horizons -- Economic Diversity and the Dutch Disease in Angola -- Part II Artificial Intelligence and Time Series -- Increasing the Performance and Plausibility of Machine Learning via Data Analysis Techniques -- Combining Forecasts of Time Series with Complex Seasonality using LSTM-based Meta-Learning -- Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-distributed Errors -- Forecasting of the F10.7 solar radio index: A Multivariate Deep Learning Approach -- Part III Financial Forecasting and Risk Analysis -- Risk-adjusted Returns of Croatian Largest Manufacturers and Their Determinants -- Usage of portfolio replication in non-life insurance -- Encoding Stock Returns Relationships via Latent Embeddings for Enhanced Portfolio Optimization -- A Measure of Bivariate Long Memories in Financial Time Series with Applications to Granger Causality Networks -- Volatility-inspired σ-LSTM cell -- Part IV Theoretical Aspects of Time Series -- Bayesian Analysis of Systemic Risks Distributions -- Empirical function-based time series analysis for high-dimensional ground motion data: A focus on nonstationary and nonlinear phenomena -- Extended Research on Categorical Data Encoding Techniques for Recursive Multi-Step Prediction of Vessel Trajectory -- Part V Time Series Analysis Applications -- Predicting Safety- Critical Events in Traffic Flow Based on Time-Series -- Two-Factor and ARIMA-LS-SVR Models for Forecasting of EUA Futures Prices -- Interest Rate Sensitivity of the largest European Pharmaceutical Companies. An Extension of The Fama and French Five-Factor Model.
Contained By:	Springer Nature eBook
標題:	Time-series analysis - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-69750-0
ISBN:	9783031697500

Time series analysis and forecasting = selected contributions from ITISE 2023 /
Time series analysis and forecastingselected contributions from ITISE 2023 /[electronic resource] :ITISE 2023edited by Olga Valenzuela ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xii, 329 p. :ill. (some col.), digital ;24 cm. - Contributions to statistics,2628-8966. - Contributions to statistics..

- Part I Advanced Econometric Methods -- Banking sector development and economic growth in developing countries. Does the change in the shadow economy matter? A Nonlinear Panel ARDL -- Improving the prediction of Norwegian household consumption by adjusting for temporary fluctuations in dividend income -- Inflation expectations change during the pre-war and war period. A comparison of Ukraine and neighboring economies -- Analysis of diversification in investment portfolios Return and Risk for different time horizons -- Economic Diversity and the Dutch Disease in Angola -- Part II Artificial Intelligence and Time Series -- Increasing the Performance and Plausibility of Machine Learning via Data Analysis Techniques -- Combining Forecasts of Time Series with Complex Seasonality using LSTM-based Meta-Learning -- Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-distributed Errors -- Forecasting of the F10.7 solar radio index: A Multivariate Deep Learning Approach -- Part III Financial Forecasting and Risk Analysis -- Risk-adjusted Returns of Croatian Largest Manufacturers and Their Determinants -- Usage of portfolio replication in non-life insurance -- Encoding Stock Returns Relationships via Latent Embeddings for Enhanced Portfolio Optimization -- A Measure of Bivariate Long Memories in Financial Time Series with Applications to Granger Causality Networks -- Volatility-inspired σ-LSTM cell -- Part IV Theoretical Aspects of Time Series -- Bayesian Analysis of Systemic Risks Distributions -- Empirical function-based time series analysis for high-dimensional ground motion data: A focus on nonstationary and nonlinear phenomena -- Extended Research on Categorical Data Encoding Techniques for Recursive Multi-Step Prediction of Vessel Trajectory -- Part V Time Series Analysis Applications -- Predicting Safety- Critical Events in Traffic Flow Based on Time-Series -- Two-Factor and ARIMA-LS-SVR Models for Forecasting of EUA Futures Prices -- Interest Rate Sensitivity of the largest European Pharmaceutical Companies. An Extension of The Fama and French Five-Factor Model.

This volume on the latest developments in the theory and applications of time series analysis and forecasting comprises a selection of refereed papers presented at the 9th International Conference on Time Series and Forecasting, ITISE 2023, held in Gran Canaria, Spain, July 12-14, 2023. It is divided into several parts that address modern theoretical aspects of time series analysis, advanced econometric methods, time series and machine learning, financial forecasting and risk analysis, and applications to various disciplines, including econometrics and energy research. The broad range of topics and applications presented, including matters of particular relevance for sustainable development, gives readers a modern perspective on the subject. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.

ISBN: 9783031697500

Standard No.: 10.1007/978-3-031-69750-0doiSubjects--Topical Terms:

678578
Time-series analysis
--Congresses.

LC Class. No.: QA280

Dewey Class. No.: 519.55

Time series analysis and forecasting = selected contributions from ITISE 2023 /
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