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Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis

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  • Michael McAleer
  • John Suen
  • Wing Keung Wong

Abstract

This paper explores the characteristics associated with the formation of bubbles that occurred in the Hong Kong stock market in 1997 and 2007, as well as the 2000 dot-com bubble of Nasdaq. It examines the profitability of Technical Analysis (TA) strategies generating buy and sell signals with knowing and without trading rules. The empirical results show that by applying long and short strategies during the bubble formation and short strategies after the bubble burst, it not only produces returns that are significantly greater than buy and hold strategies, but also produces greater wealth compared with TA strategies without trading rules. We conclude these bubble detection signals help investors generate greater wealth from applying appropriate long and short Moving Average (MA) strategies.
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  • Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.
    • Handle: RePEc:bla:jecrev:v:67:y:2016:i:3:p:257-279
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    Cited by:

    1. Nguyen Huu Hau & Tran Trung Tinh & Hoa Anh Tuong & Wing-Keung Wong, 2020. "Review of Matrix Theory with Applications in Education and Decision Sciences," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(1), pages 28-69, March.
    2. Kai-Yin Woo & Chulin Mai & Michael McAleer & Wing-Keung Wong, 2020. "Review on Efficiency and Anomalies in Stock Markets," Economies, MDPI, vol. 8(1), pages 1-51, March.
    3. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Tinbergen Institute Discussion Papers 18-024/III, Tinbergen Institute.
    4. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    5. Ayesha Liaqat & Mian Sajid Nazir & Iftikhar Ahmad, 2019. "Identification of multiple stock bubbles in an emerging market: application of GSADF approach," Economic Change and Restructuring, Springer, vol. 52(3), pages 301-326, August.
    6. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2015. "Behavioural, Financial, and Health & Medical Economics: A Connection," Documentos de Trabajo del ICAE 2015-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    8. Ayesha Liaqat & Mian Sajid Nazir & Iftikhar Ahmad & Hammad Hassan Mirza & Farooq Anwar, 2020. "Do stock price bubbles correlate between China and Pakistan? An inquiry of pre‐ and post‐Chinese investment in Pakistani capital market under China‐Pakistan Economic Corridor regime," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 323-335, July.
    9. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, And Big Data: Connections," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 36-94, December.
    10. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.

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    • C0 - Mathematical and Quantitative Methods - - General
    • G1 - Financial Economics - - General Financial Markets

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