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Improving the Estimation Accuracy Based on Wavelet Transform

Author

Listed:
  • Abdallah Abu Abdallah

    (School of Administration and Finance, The University of Jordan, Jordan)

  • Mousa Mohammad Abdullah Saleh

    (Department of Financial and Administrative Sciences, Al-Balqa Applied University, Jordan)

  • Sadam Al-Wadi

    (Department of Risk Management and Insurance. The University of Jordan, Jordan)

  • Firas Al Rawashdeh

    (Department of Risk Management and Insurance. The University of Jordan, Jordan)

Abstract

This article aims to improving and drawing inferences about population characteristic estimation, some of mathematical methods were used in content of stock market data are collected from Amman stock exchange (ASE) using three methods; point, interval estimation and Wavelet transform (WT) combined with interval estimation. Point estimate can be ambiguous because it may or may not be close to the number actuality estimated. Themethodology is to compare between the point and interval estimations then the estimation has improved by combining WT with theinterval estimation in order to reduce the error. The results show that (WT) with interval estimation is the best method, (SPSS) and mat lab 2010a have used in this study.

Suggested Citation

  • Abdallah Abu Abdallah & Mousa Mohammad Abdullah Saleh & Sadam Al-Wadi & Firas Al Rawashdeh, 2019. "Improving the Estimation Accuracy Based on Wavelet Transform," Journal of Social Sciences (COES&RJ-JSS), , vol. 8(4), pages 544-557, October.
    • Handle: RePEc:jso:coejss:v:8:y:2019:i:4:p:544-557
    DOI: 10.25255/jss.2019.8.4.544.557
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    References listed on IDEAS

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    1. V. Filimonov & G. Demos & D. Sornette, 2017. "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1167-1186, August.
    2. Ramsey, James B. & Zhang, Zhifeng, 1997. "The analysis of foreign exchange data using waveform dictionaries," Journal of Empirical Finance, Elsevier, vol. 4(4), pages 341-372, December.
    3. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Differentiating intraday seasonalities through wavelet multi-scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 543-556.
    4. Marmer, Vadim, 2008. "Nonlinearity, nonstationarity, and spurious forecasts," Journal of Econometrics, Elsevier, vol. 142(1), pages 1-27, January.
    5. Abramovich, Felix & Besbeas, Panagiotis & Sapatinas, Theofanis, 2002. "Empirical Bayes approach to block wavelet function estimation," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 435-451, June.
    6. 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.
    7. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    8. Raéf Bahrini, 2017. "Efficiency Analysis of Islamic Banks in the Middle East and North Africa Region: A Bootstrap DEA Approach," IJFS, MDPI, vol. 5(1), pages 1-13, February.
    Full references (including those not matched with items on IDEAS)

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