Approach of Maximal Overlap Discrete Wavelet Transforms to Stock Return in the Iran Capital Market
Subject Areas : Financial AccountingRoghayeh Samadi 1 , Mohammad Ezazi 2 , Reza Tehrani 3 , Seyed aligholi Roshan 4 , Mohammad Nabi Shahiki Tash 5
1 - PhD student, Faculty of Management and Economics, Sistan and Baluchestan University, Zahedan, Iran
2 - Assistant Professor, Faculty of Management and Economics, Sistan and Baluchestan University, Zahedan, Iran
3 - Management and Insurance Group, Faculty of Management, Tehran University, Tehran, Iran
4 - Faculty of Management and Economics, Sistan and Baluchestan University, Zahedan, Iran
5 - Faculty of Management and Economics , University of Sistan and Baluchestan, Faculty of Economics
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Abstract :
[1] Allahyaribeik, N., Nikoomaram, H., Allahyaribeik, S., Rahnamay rood-posht, F., A Quantum Model for the Stock Market, Advances in mathematical finance & applications, 2022, 7(1), P. 217-228.Doi: 10.22034/AMFA.2020.1882182.1323
[2] Boubaker, H., Raza, S. A., A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets, Energy Economic , 2017, 64, P.105-117, Doi: 10.1016/j.eneco.2017.01.026 .
[3] Croce, M. M., Long-run productivity risk: A new hope for production-based asset pricing? Journal of Monetary Economics, 2014 , 66, P.13-31M , Doi:10.1016/j.jmoneco.2014.04.001 .
[4] Das, D., Bhowmik , P., Jana, R.K., A Multiscale Analysis of Stock Return Co-movements, Statistical Mechanics and Its Applications , 2018, 502, P. 379-393, Doi: 10.1016/j.physa.2018.02.143 .
[5] Dinarzehi, K., Shahiki Tash, M., Zamanian, G., Investigating the concurrence of Tehran stock market and global macroeconomic indicators using frequency analysis, Quarterly Journal of Financial Engineering and Securities Management, 2021,48, P.223-252, Doi:20.1001.1.22519165.1400.12.48.10.0.
[6] Ehteshami , S., Hamidian , M., Hajiha , Z., and Shokrollahi , S., Forecasting Stock Trend by Data Mining Algorithm, Advances in mathematical finance& applications, 2018, 3(1), P. 97-105.
[7] Fallahi, F., Poorabadollah, M., Sadeghi, S., Shokri, T., Study of the Relationship between Economic Growth and Environmental Quality in Iran: New Evidence Based on Continuous Wavelet Transformation, Journal of Economic Growth and Development Research, 2019, Doi: 10.30473/egdr.2020.49586.5499.
[8] Hoevenaars, R. P., Molenaar, R. D., Schotman, P. C., and Steenkamp, T., Strategic Asset Allocation for Long‐Term Investors: Parameter Uncertainty and Prior Information, Applied Econometrics, 2014, 29(3), P. 353-376, Doi: 10.1002/jae.2331.
[9] Hossein Kurd, M., Sharifi, A., Presenting an improved version of the local linear neural-fuzzy model based on discrete wavelet transform to predict financial time series, International Conference on Computer Engineering and Information Technology, 2016.
[10] Jurek, J. W., Viceira, L. M., Optimal value and growth tilts in long-horizon portfolios, Review of Finance, 2010, 15(1), P. 29-74, Doi:10.1093/rof/rfq013
[11] Kazemzadeh, A. Karimi Petanlar, S., Jafari Samimi, A., Analysis of the tensile and anti-tensile effect on the Iranian economy: Discrete wavelet converter approach and threshold vector autoregression model. Journal of Macroeconomics, 2020, 15(29), P.13-37, Doi: 10.22080/iejm.2020.16858.1701.
[12] Gallegati , M ., Wavelet analysis of stock returns and aggregate economic activity, Computational Statistics & Data Analysis , 2008, 52(6), P. 3061-3074 , Doi: 10.1016/j.csda.2007.07.019 .
[13] Ismail , M , Audu , B and Tumala , M ., Volatility forecasting with the wavelet transformation algorithm GARCH model: Evidence from African stock markets, Finance and Data Science, 2016, 2(2), P.125-135, Doi:10.1016/j.jfds.2016.09.002 .
[14] Masih, M., Majid, H. A., Comovement of Selected International Stock Market Indices: A Continuous Wavelet Transformation and Cross Wavelet Transformation Analysis, 2013.
[15] Mensi, W., Rehman, M., Maitra, D., Hamed Al, K., and Xuan Vinh Vo, Y., Oil, Natural Gas and Brics Stock Markets: Evidence of Systemic Risks and Co- Movements in The Time –Frequency Domain, Resource Policy, 2021, 72, Doi: 10.1016/j.resourpol.2021.102062.
[16] Nadami, Y., Khochiani, R., Co-movement in the Stock, Currency and Gold Markets of Iran: An Econophysical Analysis, Financial Engineering and Securities Management, 2017, 31, P. 149-166, Doi: 20.1001.1.22519165.1396.8.31.7.5.
[17] Osu, B.O., Okonkwo, C.U., Uzoma, P.U., and Akpanibah., E.E., Wavelet analysis of the international markets: A look at the next eleven (N11), Scientific African, 2020, 7, P.1-16, Doi: 10.1016/j.sciaf. 2020.e00319.
[18] Ramzi Radchoobeh, Z., ezazade, A., Kazemi, H., Ambiguity Theory and Asset Pricing: Empirical Evidence from Tehran Stock Exchange, Advances in mathematical finance & applications, 2018, 3(4), P. 101-114, Doi:10.22034/AMFA.2019.579558.1143.
[19] Rostami, M. R., Benjar, M., and Nouri Jafarabad, D., comparing the correlation between the returns of various industries' index in the Tehran Stock Exchange with the returns of oil, gold, dollar and euro markets using wavelet analysis. Investment Knowledge, 2016, 5 (17), P. 227-251.
[20] Saiti, B, Bacha, O. I., and Masih, M., Testing the conventional and Islamic financial market, Emerging Markets Finance and Trade, 2016, 52(8) , P.1832-1849 , Doi:10.1080/1540496X.2015.1087784
[21]Sousa, R. M., What is the impact of wealth shocks on asset allocation?, Quantitative Finance, 2015, 15(3), P.493-508 , Doi:10.1080/14697688.2011.647053 .
[22] Tiwari, A. K., Cunado, J., Gupta, R., and Wohar, M. E., Are Stock Returns an Inflation Hedge for the UK? Evidence from a Wavelet Analysis Using Over Three Centuries of Data, Operational Research, 2017, 187(3), P.1380-1401, Doi: 10.1515/snde-2017-0049.
[23] Yilmaz, A., Unal, G., Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach, International Journal of Financial Engineering, 2016, 3(04), Doi:10.1142/S242478631650033.
[24] Nasr, N., Farhadi Sartangi, M., Madahi, Z., A Fuzzy Random Walk Technique to Forecasting Volatility of Iran Stock Exchange Index, Advances in Mathematical Finance and Applications, 2019, 4(1), P.15-30. Doi:10.22034/amfa.2019.583911.1172
[25] Zhu , L , Wang ,Y and Fan , Q., Modwt-Arma Model for Time Series Prediction, Applied Mathematical Modelling, 2014, 38, P.1859-1865, Doi:10.1016/j.apm.2013.10.002.