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Manuscript ID : 22610 Visit : 140 Page: 32 - 53

10.30495/jfksa.2023.22610

Article Type: Original Research

Risk modeling in the stock exchange with the approach of nonlinear Bayesian models-time-varying parameters

Subject Areas : Financial Knowledge of Securities Analysis

Fatemeh Ragh 1 (Department of Financial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Mahdi Madanchi Zaj 2 (Department of Financial Management, Electronic Branch , Department of Financial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran (Corresponding Author))
Hossein Panahian 3 (Associate Professor، department of accounting and management ، Azad University of Kashan ،kashan،Iran)

Received: 2022-06-18 Accepted : 2023-02-06 Published : 2023-07-23

Keywords: systematic risk, Unsystematic Risk, Stock Returns, Bayesian Models Averaging,

Abstract :

Traditional models do not have sufficient ability to predict the return on investor portfolio due to changes in the external environment (systematic risk) and the internal environment (non-systematic) and this is mainly due to the identification of the explanatory variables and the experimental design of the model.Therefore, the present research, while explaining this issue and in order to adjust the uncertainty problem of the model, by averaging all the models (Bayesian averaging), has determined the effective risks on stock returns in Iran.The present study expresses this failure in identifying explanatory variables and empirical model design. The statistical sample of the research includes 138 listed companies in the period 1390 to 1399.In this study, 62 risks affecting stock returns in the form of 31 indicators in the field of systematic risk and 31 non-systematic indicators entered into nonlinear Bayesian models with time-varying parameters.The results show that among BMA, TVP-DMA, TVP-DMS, BVAR and OLS models, the TVP-DMA model is the most efficient model. According to the TVP-DMA model, 10 non-fragile risks include systematic risks (real GDP growth rate, unofficial market currency, inflation rate, interest rate) non-systematic risks (instantaneous ratio, liabilities, cash flows from operations, return on equity, debt ratio, and price-to-earnings ratio) as the most important risks affecting stock returns. All the mentioned risks, except interest rate and debt ratio, have a positive effect on stock returns.

References:

دهقان خاوری, سعید, میر جلیلی, سید حسین. (1398). تعامل ریسک سیستماتیک با بازده سهام در بورس اوراق بهادار تهران. اقتصاد مالی، 7(49)13, 257-282.

سلیمی, محمدجواد, علیزاده, جواد, دوست جباریان, جواد, هوشنگی, زهره. (1400). تاثیر ریسک غیرسیستماتیک سهام بر رفتار گروهی سرمایه‌گذاران در بورس اوراق بهادار تهران. مطالعات تجربی حسابداری مالی, (71)18, 33-56.

کاویانی, میثم, سعیدی, پرویز, دیده خانی, حسین, فخرحسینی, سید فخرالدین. (1398). مقاله پژوهشی: شبیه‌سازی تأثیر شوک‎های نفتی و ارزی بر ریسک سیستماتیک و بازده قیمتی سهام شرکت‎ها: رویکرد DSGE. راهبرد مدیریت مالی, 7(2), 123-154.

Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.

  1. Rosenberg, K. Reid, R. Lanstein Persuasive evidence of market inefficiency J. Portfolio Manag., 11 (1985), pp. 9-17.
    2.
  2. Asness, A. Frazzini The devil in HML’s details J. Portfolio Manag., 39 (4) (2013), pp. 49-68.
    3.
  3. Asness, T. Moskowitz, L. Pedersen Value and momentum everywhere J. Finance, 68 (3) (2013), pp. 929-985.
    4.

Chinh DucPhamabLe TanPhuocc, 2020, An augmented capital asset pricing model using new macroeconomic determinants, Volume 6, Issue 10, October 2020, e05185.

  1. Fama, K. French A five-factor asset pricing model J. Financ. Econ., 116 (1) (2015), pp. 1-22.
    2.
  2. Fama, K. French Choosing Factors J. Financ. Econ., 128 (2) (2018), pp. 234-252.
    3.
  3. Fama, K. French Common risk factors in the returns on stocks and bonds J. Financ. Econ., 33 (1993), pp. 3-56.
    4.
  4. Fama, K. French Dissecting Anomalies J. Finance, 63 (4) (2008), pp. 1653-1678.
    5.
  5. Fama, K. French Dissecting anomalies with a five-factor model Rev. Financ. Stud., 29 (1) (2016), pp. 69-103.
    6.
  6. Fama, K. French International tests of a five-factor asset pricing model J. Finance Econ., 123 (3) (2017), pp. 441-463.
    7.
  7. Fama, K. French Size and book-to-market factors in earnings and returns J. Finance, 50 (1) (1995), pp. 131-155.
    8.
  8. Fama, K. French The cross-section of expected stock returns J. Finance, 47 (1992), pp. 427-465.
    9.
  9. Barillas, J. Shanken Comparing asset pricing models J. Finance, 73 (2018), pp. 715-754.
    10.
  10. Barillas, J. Shanken Which alpha? Rev. Financ. Stud., 30 (2017), pp. 1316-1338.
    11.
  11. Aharoni, B. Grundy, Q. Zeng Stock returns and the Miller Modigliani valuation formula: revisiting the Fama French Analysis J. Financ. Econ., 110 (2) (2013), pp. 347-357.
    12.

Graham, J. R., & Harvey, C. R. (2001). The theory and practice of corporate finance: Evidence from the field. Journal of Financial Economics 60: 187-243.

Koop, G. (2003). “Bayesian Econometrics”. England, John Wiley & Sons Ltd.

  1. Bhandari Debt/Equity ratio and expected common stock returns: empirical evidence J. Finance, 43 (2) (1988), pp. 507-528.
    2.
  2. Zhang The investment CAPM Eur. Financ. Manag., 23 (2017), pp. 545-603
    3.
  3. Carhart On persistence in mutual fund performance J. Finance, 52 (1997), pp. 57-82.
    4.
  4. Zhang Labor-technology substitution: implications for asset pricing J. Finance, 74 (2019), pp. 1793-1839.
    5.
  5. Jegadeesh, S. Titman Returns to buying winners and selling losers: implications for stock market efficiency J. Finance, 48 (1993), pp. 65-91.
    6.
  6. Barroso, P. Santa-Clara Momentum has its moments J. Financ. Econ., 116 (1) (2015), pp. 111-120.
    7.
  7. Banz The relationship between return and market value of common stocks J. Financ. Econ., 9 (1981), pp. 3-18.
    8.
  8. Novy-Marx The other side of value: the gross profitability premium J. Financ. Econ., 108 (1) (2013), pp. 1-28.
    9.
  9. Stambaugh, Y. Yuan Mispricing Factors Rev. Financ. Stud., 30 (4) (2017), pp. 1270-1315.
    10.
  10. Basu The relationship between earnings yield, market value, and return for NYSE common stocks: further evidence J. Financ. Econ., 12 (1983), pp. 129-156.
    11.
  11. Gungor, R. Luger Exact inference in long-horizon predictive quantile regressions with an application to stock returns J. Financ. Econom. (2019), pp. 1-43.
    12.
  12. Lee Money, asset prices, and the liquidity premium J. Money Credit Bank., 52 (6) (2019), pp. 1435-1466.
    13.
  13. Titman, K. Wei, F. Xie Capital investments and stock returns J. Financ. Quant. Anal., 39 (4) (2004), pp. 677-700.
    14.
  14. Moskowitz, Y. Ooi, L. Pedersen Time series momentum J. Financ. Econ., 104 (2) (2012), pp. 228-250.
    15.

W.F. Sharpe Capital asset prices: a theory of market equilibrium under conditions of risk J. Finance, 19 (1964), pp. 425-442.

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