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Hui-Kuang Tiffany Yu

Personal Details

First Name:Hui-Kuang
Middle Name:Tiffany
Last Name:Yu
Suffix:
RePEc Short-ID:pyu117
[This author has chosen not to make the email address public]

Affiliation

Department of Public Finance
College of Business
Feng Chia University

Taichung, Taiwan
http://www.pf.fcu.edu.tw/
RePEc:edi:dpfcutw (more details at EDIRC)

Research output

as
Jump to: Articles

Articles

  1. Wang, David Han-Min & Yu, Tiffany Hui-Kuang & Hu, Heng-Chang, 2012. "On the asymmetric relationship between the size of the underground economy and the change in effective tax rate in Taiwan," Economics Letters, Elsevier, vol. 117(1), pages 340-343.
  2. Yu, Tiffany Hui-Kuang, 2011. "Heterogeneous effects of different factors on global ICT adoption," Journal of Business Research, Elsevier, vol. 64(11), pages 1169-1173.
  3. Tiffany Hui-Kuang Yu & Kun-Huang Huarng & Rapon Rianto, 2009. "Neural network-based fuzzy auto-regressive models of different orders to forecast Taiwan stock index," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 1(3), pages 347-358.
  4. Tiffany Hui-Kuang Yu & Hong Yih Chu, 2007. "Is health care really a luxury? A demand and supply approach," Applied Economics, Taylor & Francis Journals, vol. 39(9), pages 1127-1131.
  5. David Han-Min Wang & Tiffany Hui-Kuang Yu, 2007. "The role of interest rate in investment decisions: a fuzzy logic framework," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 9(4), pages 448-457.
  6. Wang, David Han-Min & Lin, Jer-Yan & Yu, Tiffany Hui-Kuang, 2006. "A MIMIC approach to modeling the underground economy in Taiwan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 536-542.
  7. Yu, Tiffany Hui-Kuang & Wang, David Han-Min & Chen, Su-Jane, 2006. "A fuzzy logic approach to modeling the underground economy in Taiwan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 471-479.
  8. Huarng, Kunhuang & Yu, Tiffany Hui-Kuang, 2006. "The application of neural networks to forecast fuzzy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 481-491.
  9. Huarng, Kunhuang & Yu, Hui-Kuang, 2005. "A Type 2 fuzzy time series model for stock index forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 445-462.
  10. Yu, Hui-Kuang, 2005. "A refined fuzzy time-series model for forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 657-681.
  11. Chen, Cathy W.S. & Yu, Tiffany H.K., 2005. "Long-term dependence with asymmetric conditional heteroscedasticity in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 413-424.
  12. Yu, Hui-Kuang, 2005. "Weighted fuzzy time series models for TAIEX forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 609-624.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Wang, David Han-Min & Yu, Tiffany Hui-Kuang & Hu, Heng-Chang, 2012. "On the asymmetric relationship between the size of the underground economy and the change in effective tax rate in Taiwan," Economics Letters, Elsevier, vol. 117(1), pages 340-343.

    Cited by:

    1. Andreev A.S. & Andreeva O.V. & Bondareva G.V. & Osyak V.V., 2018. "Understanding the Underground Economy," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 814-822.
    2. Anbarci, Nejat & Gomis-Porqueras, Pedro & Marcus, Pivato, 2012. "Formal and informal markets: A strategic and evolutionary perspective," MPRA Paper 42513, University Library of Munich, Germany.
    3. Nejat Anbarci & Pedro Gomis-Porqueras & Marcus Pivato, 2018. "Evolutionary stability of bargaining and price posting: implications for formal and informal activities," Journal of Evolutionary Economics, Springer, vol. 28(2), pages 365-397, April.

  2. Yu, Tiffany Hui-Kuang, 2011. "Heterogeneous effects of different factors on global ICT adoption," Journal of Business Research, Elsevier, vol. 64(11), pages 1169-1173.

    Cited by:

    1. Yu, Tiffany Hui-Kuang & Wang, David Han-Min & Wu, Kuo-Lun, 2015. "Reexamining the red herring effect on healthcare expenditures," Journal of Business Research, Elsevier, vol. 68(4), pages 783-787.
    2. Shi-Woei Lin & Yu-Cheng Liu, 2012. "The effects of motivations, trust, and privacy concern in social networking," Service Business, Springer;Pan-Pacific Business Association, vol. 6(4), pages 411-424, December.
    3. Chen, Yi-Min & Yang, De-Hsin & Lin, Feng-Jyh, 2013. "Does technological diversification matter to firm performance? The moderating role of organizational slack," Journal of Business Research, Elsevier, vol. 66(10), pages 1970-1975.
    4. Huarng, Kun-Huang, 2015. "Configural theory for ICT development," Journal of Business Research, Elsevier, vol. 68(4), pages 748-756.
    5. Díaz-Chao, Ángel & Sainz-González, Jorge & Torrent-Sellens, Joan, 2016. "The competitiveness of small network-firm: A practical tool," Journal of Business Research, Elsevier, vol. 69(5), pages 1769-1774.
    6. Tiffany Yu & Michael Willoughby, 2012. "Innovations in service business. An introduction to the special issue from the Global Entrepreneurship and Services Conference, Taiwan, 2011," Service Business, Springer;Pan-Pacific Business Association, vol. 6(4), pages 405-409, December.
    7. Seo, Joo Hwan & Perry, Vanessa G. & Tomczyk, David & Solomon, George T., 2014. "Who benefits most? The effects of managerial assistance on high- versus low-performing small businesses," Journal of Business Research, Elsevier, vol. 67(1), pages 2845-2852.
    8. Wang, David Han-Min & Chen, Pei-Hua & Yu, Tiffany Hui-Kuang & Hsiao, Chih-Yi, 2015. "The effects of corporate social responsibility on brand equity and firm performance," Journal of Business Research, Elsevier, vol. 68(11), pages 2232-2236.
    9. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2015. "Forecasting ICT development through quantile confidence intervals," Journal of Business Research, Elsevier, vol. 68(11), pages 2295-2298.
    10. Chih-Wen Wu & Kun-Huang Huarng & Surya Fiegantara & Pai-Chi Wu, 2012. "The impact of online customer satisfaction on the yahoo auction in Taiwan," Service Business, Springer;Pan-Pacific Business Association, vol. 6(4), pages 473-487, December.
    11. Paniagua, Jordi & Figueiredo, Erik & Sapena, Juan, 2015. "Quantile regression for the FDI gravity equation," Journal of Business Research, Elsevier, vol. 68(7), pages 1512-1518.
    12. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2014. "A new quantile regression forecasting model," Journal of Business Research, Elsevier, vol. 67(5), pages 779-784.

  3. Tiffany Hui-Kuang Yu & Hong Yih Chu, 2007. "Is health care really a luxury? A demand and supply approach," Applied Economics, Taylor & Francis Journals, vol. 39(9), pages 1127-1131.

    Cited by:

    1. Fabrizio Iacone & Steve Martin & Luigi Siciliani & Peter C. Smith, 2012. "Modelling the dynamics of a public health care system: evidence from time-series data," Applied Economics, Taylor & Francis Journals, vol. 44(23), pages 2955-2968, August.
    2. Nilgun Yavuz & Veli Yilanci & Zehra Ozturk, 2013. "Is health care a luxury or a necessity or both? Evidence from Turkey," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(1), pages 5-10, February.
    3. Ousmane Traoré, 2020. "Economic Growth and Human Capital Accumulation across Countries: Evidence from WAEMU Region," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(2), pages 147-159, May.

  4. David Han-Min Wang & Tiffany Hui-Kuang Yu, 2007. "The role of interest rate in investment decisions: a fuzzy logic framework," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 9(4), pages 448-457.

    Cited by:

    1. Faris Alshubiri, 2022. "The Impact of the Real Interest Rate, the Exchange Rate and Political Stability on Foreign Direct Investment Inflows: A Comparative Analysis of G7 and GCC Countries," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(3), pages 569-603, September.
    2. Muhammad Waqas Chughtai & Muhammad Waqas Malik & Rashid Aftab, 2015. "Impact of Major Economic Variables on Economic Growth of Pakistan," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 11(2), pages 94-106, April.
    3. Mushtaq, Saba & Siddiqui, Danish Ahmed, 2015. "Effect of interest rate on economic performance: Evidences from Islamic and Non-Islamic Economies," MPRA Paper 68298, University Library of Munich, Germany.

  5. Wang, David Han-Min & Lin, Jer-Yan & Yu, Tiffany Hui-Kuang, 2006. "A MIMIC approach to modeling the underground economy in Taiwan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 536-542.

    Cited by:

    1. Soheila Kaghazian & Isa Zaghi Jojadeh & Yazdan Naghdi, 2015. "Underground Economy Estimation in Iran by Mimic Method," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 90-109.
    2. Bennihi, Aymen Salah & Bouriche, Lahcene & Schneider, Friedrich, 2021. "The informal economy in Algeria: New insights using the MIMIC approach and the interaction with the formal economy," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 470-491.

  6. Yu, Tiffany Hui-Kuang & Wang, David Han-Min & Chen, Su-Jane, 2006. "A fuzzy logic approach to modeling the underground economy in Taiwan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 471-479.

    Cited by:

    1. Mohammad Hossien Pourkazemi & Mohammad Naser Sherafat & Delfan Azari, 2015. "Modeling Iran`s Underground Economy: A Fuzzy Logic Approach," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 91-106, Winter.
    2. Soheila Kaghazian & Isa Zaghi Jojadeh & Yazdan Naghdi, 2015. "Underground Economy Estimation in Iran by Mimic Method," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 90-109.
    3. Günçavdi, Öner & Küçük, Ali Erhan, 2013. "Investment expenditure and capital accumulation in an inflationary environment: The case of Turkey," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 554-571.

  7. Huarng, Kunhuang & Yu, Tiffany Hui-Kuang, 2006. "The application of neural networks to forecast fuzzy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 481-491.

    Cited by:

    1. Kaur, Gurbinder & Dhar, Joydip & Guha, Rangan Kumar, 2016. "Minimal variability OWA operator combining ANFIS and fuzzy c-means for forecasting BSE index," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 122(C), pages 69-80.
    2. Dombi, József & Jónás, Tamás & Tóth, Zsuzsanna Eszter, 2018. "Modeling and long-term forecasting demand in spare parts logistics businesses," International Journal of Production Economics, Elsevier, vol. 201(C), pages 1-17.
    3. Pal, Shanoli Samui & Kar, Samarjit, 2019. "Time series forecasting for stock market prediction through data discretization by fuzzistics and rule generation by rough set theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 162(C), pages 18-30.
    4. Chen, Tai-Liang & Cheng, Ching-Hsue & Jong Teoh, Hia, 2007. "Fuzzy time-series based on Fibonacci sequence for stock price forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 377-390.
    5. Kun-Huang Huarng & Tiffany Hui-Kuang Yu & Francesc Solé Parellada, 2010. "An innovative regime switching model to forecast Taiwan tourism demand," The Service Industries Journal, Taylor & Francis Journals, vol. 31(10), pages 1603-1612, March.
    6. Chen, Tai-Liang & Cheng, Ching-Hsue & Teoh, Hia-Jong, 2008. "High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 876-888.
    7. Vedide Rezan USLU & Eren BAS & Ufuk YOLCU & Erol EGRIOGLU, 2013. "A New Fuzzy Time Series Analysis Approach By Using Differential Evolution Algorithm And Chronologically-Determined Weights," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 2(1), pages 18-30, JULY.
    8. Cheng, Ching-Hsue & Wei, Liang-Ying, 2014. "A novel time-series model based on empirical mode decomposition for forecasting TAIEX," Economic Modelling, Elsevier, vol. 36(C), pages 136-141.
    9. Cheng, Ching-Hsue & Wei, Liang-Ying & Liu, Jing-Wei & Chen, Tai-Liang, 2013. "OWA-based ANFIS model for TAIEX forecasting," Economic Modelling, Elsevier, vol. 30(C), pages 442-448.
    10. Aladag, Cagdas Hakan & Yolcu, Ufuk & Egrioglu, Erol, 2010. "A high order fuzzy time series forecasting model based on adaptive expectation and artificial neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(4), pages 875-882.
    11. Tai-Liang Chen, 2012. "Forecasting the Taiwan Stock Market with a Novel Momentum-based Fuzzy Time-series," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 38-50, February.
    12. Lahmiri, Salim, 2016. "Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 388-396.
    13. Dong, Ruijun & Pedrycz, Witold, 2008. "A granular time series approach to long-term forecasting and trend forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3253-3270.
    14. Wei, Liang-Ying, 2013. "A hybrid model based on ANFIS and adaptive expectation genetic algorithm to forecast TAIEX," Economic Modelling, Elsevier, vol. 33(C), pages 893-899.
    15. Tai Vovan, 2019. "An improved fuzzy time series forecasting model using variations of data," Fuzzy Optimization and Decision Making, Springer, vol. 18(2), pages 151-173, June.

  8. Huarng, Kunhuang & Yu, Hui-Kuang, 2005. "A Type 2 fuzzy time series model for stock index forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 445-462.

    Cited by:

    1. Pal, Shanoli Samui & Kar, Samarjit, 2019. "Time series forecasting for stock market prediction through data discretization by fuzzistics and rule generation by rough set theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 162(C), pages 18-30.
    2. Chen, Tai-Liang & Cheng, Ching-Hsue & Jong Teoh, Hia, 2007. "Fuzzy time-series based on Fibonacci sequence for stock price forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 377-390.
    3. Jilani, Tahseen Ahmed & Burney, Syed Muhammad Aqil, 2008. "A refined fuzzy time series model for stock market forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2857-2862.
    4. Ni, Yensen & Wu, Manhwa & Day, Min-Yuh & Huang, Paoyu, 2020. "Do sharp movements in oil prices matter for stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    5. Chen, Tai-Liang & Cheng, Ching-Hsue & Teoh, Hia-Jong, 2008. "High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 876-888.
    6. Zhou, Qin & Shang, Pengjian, 2020. "Weighted multiscale cumulative residual Rényi permutation entropy of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    7. Tai Vo-Van & Ha Che-Ngoc & Nghiep Le-Dai & Thao Nguyen-Trang, 2022. "A New Strategy for Short-Term Stock Investment Using Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 887-911, February.
    8. Huarng, Kunhuang & Yu, Tiffany Hui-Kuang, 2006. "The application of neural networks to forecast fuzzy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 481-491.
    9. Tai-Liang Chen, 2012. "Forecasting the Taiwan Stock Market with a Novel Momentum-based Fuzzy Time-series," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 38-50, February.
    10. Zhou, Pengfei & Luo, Jie & Cheng, Fei & Yüksel, Serhat & Dinçer, Hasan, 2021. "Analysis of risk priorities for renewable energy investment projects using a hybrid IT2 hesitant fuzzy decision-making approach with alpha cuts," Energy, Elsevier, vol. 224(C).

  9. Yu, Hui-Kuang, 2005. "A refined fuzzy time-series model for forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 657-681.

    Cited by:

    1. Singh, S.R., 2008. "A computational method of forecasting based on fuzzy time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 539-554.
    2. Siyu Zhang & Liusan Wu & Ming Cheng & Dongqing Zhang, 2022. "Prediction of Whole Social Electricity Consumption in Jiangsu Province Based on Metabolic FGM (1, 1) Model," Mathematics, MDPI, vol. 10(11), pages 1-14, May.
    3. Chen, Tai-Liang & Cheng, Ching-Hsue & Jong Teoh, Hia, 2007. "Fuzzy time-series based on Fibonacci sequence for stock price forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 377-390.
    4. Jilani, Tahseen Ahmed & Burney, Syed Muhammad Aqil, 2008. "A refined fuzzy time series model for stock market forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2857-2862.
    5. Ni, Yensen & Wu, Manhwa & Day, Min-Yuh & Huang, Paoyu, 2020. "Do sharp movements in oil prices matter for stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    6. Chen, Tai-Liang & Cheng, Ching-Hsue & Teoh, Hia-Jong, 2008. "High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 876-888.
    7. Huarng, Kunhuang & Yu, Hui-Kuang, 2005. "A Type 2 fuzzy time series model for stock index forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 445-462.
    8. Huarng, Kunhuang & Yu, Tiffany Hui-Kuang, 2006. "The application of neural networks to forecast fuzzy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 481-491.
    9. Tai-Liang Chen, 2012. "Forecasting the Taiwan Stock Market with a Novel Momentum-based Fuzzy Time-series," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 38-50, February.

  10. Chen, Cathy W.S. & Yu, Tiffany H.K., 2005. "Long-term dependence with asymmetric conditional heteroscedasticity in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 413-424.

    Cited by:

    1. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Gomes, Luís M. P. & Soares, Vasco J. S. & Gama, Sílvio M. A. & Matos, José A. O., 2018. "Long-term memory in Euronext stock indexes returns: an econophysics approach," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(4), pages 862-881, August.

  11. Yu, Hui-Kuang, 2005. "Weighted fuzzy time series models for TAIEX forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 609-624.

    Cited by:

    1. Singh, S.R., 2008. "A computational method of forecasting based on fuzzy time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 539-554.
    2. Judith Jazmin Castro Pérez & José Eduardo Medina Reyes, 2021. "Fuzzy Portfolio Selection with Sugeno Type Fuzzy Neural Network: Investing in the Mexican Stock Market," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(TNEA), pages 1-25, Septiembr.
    3. Sulandari, Winita & Subanar, & Lee, Muhammad Hisyam & Rodrigues, Paulo Canas, 2020. "Indonesian electricity load forecasting using singular spectrum analysis, fuzzy systems and neural networks," Energy, Elsevier, vol. 190(C).
    4. Jilani, Tahseen Ahmed & Burney, Syed Muhammad Aqil, 2008. "A refined fuzzy time series model for stock market forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2857-2862.
    5. Ni, Yensen & Wu, Manhwa & Day, Min-Yuh & Huang, Paoyu, 2020. "Do sharp movements in oil prices matter for stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    6. Adam Fadlalla & Farzaneh Amani, 2014. "Predicting Next Trading Day Closing Price Of Qatar Exchange Index Using Technical Indicators And Artificial Neural Networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 209-223, October.
    7. Chen, Tai-Liang & Cheng, Ching-Hsue & Teoh, Hia-Jong, 2008. "High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 876-888.
    8. Vedide Rezan USLU & Eren BAS & Ufuk YOLCU & Erol EGRIOGLU, 2013. "A New Fuzzy Time Series Analysis Approach By Using Differential Evolution Algorithm And Chronologically-Determined Weights," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 2(1), pages 18-30, JULY.
    9. Huarng, Kunhuang & Yu, Hui-Kuang, 2005. "A Type 2 fuzzy time series model for stock index forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 445-462.
    10. Cheng, Ching-Hsue & Wei, Liang-Ying, 2014. "A novel time-series model based on empirical mode decomposition for forecasting TAIEX," Economic Modelling, Elsevier, vol. 36(C), pages 136-141.
    11. Kuo-Ping Lin & Ching-Lin Lin & Yu-Ming Lu & Ping-Feng Pai, 2013. "Rule Generation Based on Novel Two-Stage Model," Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management,, ToKnowPress.
    12. Kavitha Ganesan & Udhayakumar Annamalai & Nagarajan Deivanayagampillai, 2019. "An integrated new threshold FCMs Markov chain based forecasting model for analyzing the power of stock trading trend," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-19, December.
    13. Cheng, Ching-Hsue & Wei, Liang-Ying & Liu, Jing-Wei & Chen, Tai-Liang, 2013. "OWA-based ANFIS model for TAIEX forecasting," Economic Modelling, Elsevier, vol. 30(C), pages 442-448.
    14. Chih-Chung Yang & Yungho Leu & Chien-Pang Lee, 2014. "A Dynamic Weighted Distancedbased Fuzzy Time Series Neural Network with Bootstrap Model for Option Price Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 115-129, June.
    15. Sadaei, Hossein Javedani & de Lima e Silva, Petrônio Cândido & Guimarães, Frederico Gadelha & Lee, Muhammad Hisyam, 2019. "Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series," Energy, Elsevier, vol. 175(C), pages 365-377.
    16. Surendra Singh Gautam & Abhishekh & S. R. Singh, 2020. "A modified weighted method of time series forecasting in intuitionistic fuzzy environment," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 1022-1041, September.
    17. Huarng, Kunhuang & Yu, Tiffany Hui-Kuang, 2006. "The application of neural networks to forecast fuzzy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 481-491.
    18. Altan, Aytaç & Karasu, Seçkin & Bekiros, Stelios, 2019. "Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 325-336.
    19. Madeline Hui Li Lee & Yee Chee Ser & Ganeshsree Selvachandran & Pham Huy Thong & Le Cuong & Le Hoang Son & Nguyen Trung Tuan & Vassilis C. Gerogiannis, 2022. "A Comparative Study of Forecasting Electricity Consumption Using Machine Learning Models," Mathematics, MDPI, vol. 10(8), pages 1-23, April.
    20. Tai-Liang Chen, 2012. "Forecasting the Taiwan Stock Market with a Novel Momentum-based Fuzzy Time-series," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 38-50, February.
    21. Wei, Liang-Ying, 2013. "A hybrid model based on ANFIS and adaptive expectation genetic algorithm to forecast TAIEX," Economic Modelling, Elsevier, vol. 33(C), pages 893-899.
    22. Tai Vovan, 2019. "An improved fuzzy time series forecasting model using variations of data," Fuzzy Optimization and Decision Making, Springer, vol. 18(2), pages 151-173, June.
    23. Lu, Ya-Nan & Li, Sai-Ping & Zhong, Li-Xin & Jiang, Xiong-Fei & Ren, Fei, 2018. "A clustering-based portfolio strategy incorporating momentum effect and market trend prediction," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 1-15.

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