1 |
Ayub, Q. M. Y. (2017). The stock market reaction to extreme events: The evidence from Pakistan. Business and Management, 9(4), 111-127. https://doi.org/10.21251/1479263
DOI
|
2 |
Banz, R. W. (1981). The relationship between return and market value of common stocks. Journal of Financial Economics, 9(1), 3-18. https://doi.org/10.1016/0304-405X(81)90018-0
DOI
|
3 |
De Bondt, W. F., & Thaler, R. H. (1985). Does the stock market overreact? The Journal of Finance, 40(3), 793-805. https://doi.org/10.1111/j.1540-6261.1985.tb05004.x
DOI
|
4 |
Cakici, N., Fabozzi, F. J., & Tan, S. (2013). Size, value, and momentum in emerging market stock returns. Emerging Markets Review, 16, 46-65. https://doi.org/10.1016/j.ememar.2013.03.001
DOI
|
5 |
Fama, E. F., & French, K. R. (2012). Size, value, and momentum in international stock returns. Journal of Financial Economics, 105(3), 457-472. https://doi.org/10.1016/j.jfineco.2012.05.011
DOI
|
6 |
Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22. https://doi.org/10.1016/j.jfineco.2014.10.010
DOI
|
7 |
Pastor, L., & Stambaugh, R. F. (2003). Liquidity risk and expected stock returns. Journal of Political Economy, 111(3), 642-685. http://doi.org/10.1086/374184
DOI
|
8 |
Pearl, J. (2003). Causality: Models, reasoning, and inference. Econometric Theory, 19, 675-685. https://doi.org/10.1017/S0266466603004109
DOI
|
9 |
Reddy, K., Qamar, M. A. J., & Rao, M. (2019). Return reversal effect in Shanghai: Share market. Managerial Finance, 45(6), 698-715. https://doi.org/10.1108/MF-04-2018-0140
DOI
|
10 |
Ross, S. A. (1976). Options and efficiency. The Quarterly Journal of Economics, 90(1), 75-89. https://doi.org/10.2307/1886087
DOI
|
11 |
Scutari, M. (2009). Learning Bayesian networks with the bnlearn R package. Journal of Statistical Software, 35(3), 1-22. https://arxiv.org/abs/0908.3817
|
12 |
Carhart, M. M. (1997). On persistence in mutual fund performance. The Journal of Finance, 52(1), 57-82. https://doi.org/10.1111/j.1540-6261.1997.tb03808.x
DOI
|
13 |
Abhyankar, A., Copeland, L. S., & Wong, W. (1997). Uncovering nonlinear structure in real-time stock-market indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100. Journal of Business & Economic Statistics, 15(1), 1-14. https://doi.org/10.2307/1392068
DOI
|
14 |
Pearl, J., Geiger, D. D., & Verma, D. T. (2001). Identifying independence in bayesian networks. Networks, 20(5), 507-534. https://doi.org/10.1002/net.3230200504.
DOI
|
15 |
Shoaib, A., & Siddiqui, M. A. (2017). Long-run adjustment of size, value, momentum, and growth premium in equity returns: Evidence from South Asian emerging markets. Investment analyst's Journal, 46(2), 97-116. https://doi.org/10.1080/10293523.2016.1275427
DOI
|
16 |
Wang, Z., Wang, L., & Tan, S. (2008). Emergent and spontaneous computation of factor relationships from a large factor set. Journal of Economic Dynamics and Control, 32(12), 3939-3959. https://doi.org/10.1016/j.jedc.2008.04.005
DOI
|
17 |
Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461-464. https://www.jstor.org/stable/2958889
DOI
|
18 |
Shaharuddin, S. S., Lau, W. Y., & Ahmad, R. (2018). Is the Fama French three-factor model relevant? Evidence from Islamic unit trust funds. The Journal of Asian Finance, Economics, and Business, 5(4), 21-34. https://doi.org/cite/10.13106/jafeb.2018.vol5.no4.21
DOI
|
19 |
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x
DOI
|
20 |
Zong, F., Xu, H., & Zhang, H. (2013). Prediction for traffic accident severity: comparing the Bayesian network and regression models. Mathematical Problems in Engineering, 20(3), 15-27. https://doi.org/10.1155/2013/475194
DOI
|
21 |
Hou, K., Xue, C., & Zhang, L. (2015). Digesting anomalies: An investment approach. The Review of Financial Studies, 28(3), 650-705. https://doi.org/10.1093/rfs/hhu068
DOI
|
22 |
Geiger, D., & Yuille, A. (1991). A common framework for image segmentation. International Journal of Computer Vision, 6(3), 227-243.
DOI
|
23 |
Ho, R. Y. W., Strange, R., & Piesse, J. (2008). Corporate financial leverage and asset pricing in the Hong Kong market. International Business Review, 17(1), 1-7. https://doi.org/j.ibr2008.17.1.17
DOI
|
24 |
Hongsakulvasu, N., & Liammukda, A. (2020). Asian stock markets analysis: The new evidence from a time-varying coefficient autoregressive model. Journal of Asian Finance, Economics, and Business, 7(9), 95-104. https://doi.org/10.13106/jafeb.2020.vol7.no9.095
DOI
|
25 |
Liammukda, A., Khamkong, M., Saenchan, L., & Hongsakulvasu, N. (2020). The time-varying coefficient Fama-French five-factor model: A case study in the return of Japan portfolios. The Journal of Asian Finance, Economics, and Business, 7(10), 513-521. https://doi.org/10.13106/jafeb.2020.vol7.no10.513
DOI
|
26 |
Malin, M., & Bornholt, G. (2013). Long-term return reversal: Evidence from international market indices. Journal of International Financial Markets, Institutions, and Money, 25, 1-17. https://doi.org/10.1016/J.INTFIN.2013.01.002
DOI
|
27 |
Merton, R. C. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867-887. https://doi.org/10.2307/1913811
DOI
|
28 |
Ticknor, J. L. (2013). A Bayesian regularized artificial neural network for stock market forecasting. Expert Systems with Applications, 40(14), 5501-5506. http://doi.org/10.1016/j.eswa.2013.04.013
DOI
|
29 |
De Oliveira, F. A., Nobre, C. N., & Zarate, L. E. (2013). Applying artificial neural networks to prediction of stock price and improvement of the directional prediction index: A case study of PETR4, Petrobras, Brazil. Expert Systems with Applications, 40(18), 7596-7606. http://doi.org/10.1016/j.eswa.2013.06.071
DOI
|