Unlocking the puzzle: Corporate hedging’s ripple effect on investor sentiments amid asymmetries

Sayyed Sadaqat Hussain Shah, Iqra Mujataba, Muhammad Asif Khan, Hossam Haddad, Nidal Mahmoud Al-Ramahi

Article ID: 3524
Vol 8, Issue 8, 2024

VIEWS - 1101 (Abstract)

Abstract


Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.


Keywords


hedging; asymmetric information; investors’ sentiments; a two-step GMM model

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References

  1. Abdi, H., & Williams, L. J. (2010). Principal component analysis. WIREs Computational Statistics, 2(4), 433–459. https://doi.org/10.1002/wics.101
  2. Afza, T., & Alam, A. (2011). Corporate derivatives and foreign exchange risk management. The Journal of Risk Finance, 12(5), 409–420. https://doi.org/10.1108/15265941111176145
  3. Agarwal, V., & Ren, H. (2023). Hedge funds: Performance, risk management, and impact on asset markets. Oxford Research Encyclopedia of Economics and Finance. https://doi.org/10.1093/acrefore/9780190625979.013.841
  4. Ahmad, B., Warraich, U. A., & Saeed, S. (2014). Impact of investor sentiments on future trading. IBT Journal of Business Studies (JBS), 2(2).
  5. Ahmed, Z., Saleem, Q., Bhatti, A. Q., et al. (2020). Corporate leverage transmission under information asymmetry: Evidence from non-financial firms of Pakistan. International Journal of Economics and Financial Issues, 10(4), 176–184. https://doi.org/10.32479/ijefi.9710
  6. Baker, M., Ruback, R. S., & Wurgler, J. (2007). Behavioral corporate finance. In: Handbook of Empirical Corporate Finance. Elsevier. pp. 145–186.
  7. Baker, M., & Wurgler, J. (2000). The equity share in new issues and aggregate stock returns. The Journal of Finance, 55(5), 2219–2257. https://doi.org/10.1111/0022-1082.00285
  8. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance, 61(4), 1645–1680. https://doi.org/10.1111/j.1540-6261.2006.00885.x
  9. Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129–151. https://doi.org/10.1257/jep.21.2.129
  10. Bashir, H., Sultan, K., & Jghef, O. K. (2013). Impact of derivatives usage on firm value: Evidence from non financial firms of Pakistan. Journal of Management Research, 5(4), 108.
  11. Baum, C. F. (2006). An introduction to modern econometrics using Stata. Stata Press.
  12. Bello, A., Smolarski, J., Soydemir, G., et al. (2017). Investor behavior: Hedge fund returns and strategies. Review of Behavioral Finance, 9(1), 14–42. https://doi.org/10.1108/rbf-09-2015-0036
  13. Bharath, S. T., Pasquariello, P., & Wu, G. (2009). Does asymmetric information drive capital structure decisions? Review of Financial Studies, 22(8), 3211–3243. https://doi.org/10.1093/rfs/hhn076
  14. Bond, S. R., Hoeffler, A., & Temple, J. R. (2001). GMM estimation of empirical growth models. RePEc.
  15. Breeden, D. T., & Viswanathan, S. (1998). Why do firms hedge? An asymmetric information approach. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2642396
  16. Brown, G. W., & Cliff, M. T. (2005). Investor sentiment and asset valuation. The Journal of Business, 78(2), 405–440. https://doi.org/10.1086/427633
  17. Caselli, F., Esquivel, G., & Lefort, F. (1996). Reopening the convergence debate: A new look at cross-country growth empirics. Journal of Economic Growth, 1(3), 363–389. https://doi.org/10.1007/bf00141044
  18. Cevik, E., Kirci Altinkeski, B., Cevik, E. I., & Dibooglu, S. (2022). Investor sentiments and stock markets during the COVID-19 pandemic. Financial Innovation, 8(1), 69. https://doi.org/10.1186/s40854-022-00375-0
  19. Culp, C. L., Miller, M. H., & Neves, A. M. P. (1998). Value at risk: Uses and abuses. Journal of Applied Corporate Finance, 10(4), 26–38. https://doi.org/10.1111/j.1745-6622.1998.tb00307.x
  20. DaDalt, P., Gay, G. D., & Nam, J. (2002). Asymmetric information and corporate derivatives use. Journal of Futures Markets, 22(3), 241–267. https://doi.org/10.1002/fut.2216
  21. De Wet, W. A. (2004). The role of asymmetric information on investments in emerging markets. Economic Modelling, 21(4), 621–630. https://doi.org/10.1016/j.econmod.2003.09.002
  22. DeMarzo, P. M., & Duffie, D. (1995). Corporate incentives for hedging and hedge accounting. Review of Financial Studies, 8(3), 743–771. https://doi.org/10.1093/rfs/8.3.743
  23. Doukas, J. A., & Mandal, S. (2018). CEO risk preferences and hedging decisions: A multiyear analysis. Journal of International Money and Finance, 86, 131–153. https://doi.org/10.1016/j.jimonfin.2018.04.007
  24. Elbadry, A., Gounopoulos, D., & Skinner, F. (2015). Governance quality and information asymmetry. Financial Markets, Institutions & Instruments, 24(2–3), 127–157. https://doi.org/10.1111/fmii.12026
  25. Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34. https://doi.org/10.1086/294743
  26. Fama, E. F., & French, K. R. (2001). Disappearing dividends: Changing firm characteristics or lower propensity to pay? Journal of Financial Economics, 60(1), 3–43.
  27. Fosu, S., Danso, A., Ahmad, W., et al. (2016). Information asymmetry, leverage and firm value: Do crisis and growth matter? International Review of Financial Analysis, 46, 140–150. https://doi.org/10.1016/j.irfa.2016.05.002
  28. Friedman, M. (1953). Choice, chance, and the personal distribution of income. Journal of Political Economy, 61(4), 277–290. https://doi.org/10.1086/257390
  29. Froot, K. A., Scharfstein, D. S., & Stein, J. C. (1993). Risk management: coordinating corporate investment and financing policies. The Journal of Finance, 48(5), 1629–1658. https://doi.org/10.1111/j.1540-6261.1993.tb05123.x
  30. Gay, G. D., & Nam, J. (1998). The underinvestment problem and corporate derivatives use. Financial Management, 27(4), 53. https://doi.org/10.2307/3666413
  31. Géczy, C., Minton, B. A., & Schrand, C. (1997). Why firms use currency derivatives. The Journal of Finance, 52(4), 1323–1354. https://doi.org/10.1111/j.1540-6261.1997.tb01112.x
  32. Ghosh, A., Gupta, S., Dua, A., et al. (2020). Security of cryptocurrencies in blockchain technology: State-of-art, challenges and future prospects. Journal of Network and Computer Applications, 163, 102635. https://doi.org/10.1016/j.jnca.2020.102635
  33. Glaser, M., & Weber, M. (2009). Which past returns affect trading volume? Journal of Financial Markets, 12(1), 1–31. https://doi.org/10.1016/j.finmar.2008.03.001
  34. Graham, J. R., & Rogers, D. A. (2002). Do firms hedge in response to tax incentives? The Journal of Finance, 57(2), 815–839. https://doi.org/10.1111/1540-6261.00443
  35. Grossman, S. J., & Stiglitz, J. E. (1976). Information and competitive price systems. The American Economic Review, 66(2), 246–253.
  36. Heflin, F., Subramanyam, K. R., & Zhang, Y. (2001). Stock return volatility before and after regulation FD. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.292879
  37. Ivković, Z., & Weisbenner, S. (2005). Local does as local is: information content of the geography of individual investors’ common stock investments. The Journal of Finance, 60(1), 267–306. https://doi.org/10.1111/j.1540-6261.2005.00730.x
  38. Khan, M. A., & Ahmad, E. (2018). Measurement of investor sentiment and its bi-directional contemporaneous and lead-lag relationship with returns: Evidence from Pakistan. Sustainability, 11(1), 94. https://doi.org/10.3390/su11010094
  39. Klomp, J., & Hoogezand, B. (2018). Natural disasters and agricultural protection: A panel data analysis. World Development, 104, 404–417. https://doi.org/10.1016/j.worlddev.2017.11.013
  40. Knopf, J. D., Nam, J., & Thornton, J. H. (2002). The volatility and price sensitivities of managerial stock option portfolios and corporate hedging. The Journal of Finance, 57(2), 801–813. https://doi.org/10.1111/1540-6261.00442
  41. Koshoev, A. (2020). Dissection of investor sentiments: Evidence from Taiwan. Review of Integrative Business and Economics Research, 9(1), 26–37.
  42. Kumar, A., & Lee, C. M. (2006). Retail investor sentiment and return comovements. The Journal of Finance, 61(5), 2451–2486. https://doi.org/10.1111/j.1540-6261.2006.01063.x
  43. Kuzmina, J. (2010). Emotion’s component of expectations in financial decision making. Baltic Journal of Management, 5(3), 295–306. https://doi.org/10.1108/17465261011079721
  44. Lee, C. M., Shleifer, A., & Thaler, R. H. (1991). Investor sentiment and the closed‐end fund puzzle. The Journal of Finance, 46(1), 75–109. https://doi.org/10.1111/j.1540-6261.1991.tb03746.x
  45. Lux, T. (2012). Estimation of an agent-based model of investor sentiment formation in financial markets. Journal of Economic Dynamics and Control, 36(8), 1284–1302. https://doi.org/10.1016/j.jedc.2012.03.012
  46. Ma, T., Tee, K. H., & Li, B. (2022). On hedge fund inceptions in a competitive market. The European Journal of Finance, 1–26.
  47. Macedoni, L. (2022). Asymmetric information, quality, and regulations. Review of International Economics, 30(4), 1180–1198. https://doi.org/10.1111/roie.12599
  48. Manos, R., Murinde, V., & Green, C. J. (2012). Dividend policy and business groups: Evidence from Indian firms. International Review of Economics & Finance, 21(1), 42–56. https://doi.org/10.1016/j.iref.2011.05.002
  49. Massa, M., & Simonov, A. (2006). Hedging, familiarity and portfolio choice. The Review of Financial Studies, 19(2), 633–685. https://doi.org/10.1093/rfs/hhj013
  50. Mello, A. S., & Parsons, J. E. (2000). Hedging and liquidity. The Review of Financial Studies, 13(1), 127–153. https://doi.org/10.1093/rfs/13.1.127
  51. Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory of investment. The American Economic Review, 48(3), 261–297.
  52. Morgado, A., & Pindado, J. (2003). The underinvestment and overinvestment hypotheses: An analysis using panel data. European Financial Management, 9(2), 163–177. https://doi.org/10.1111/1468-036x.00214
  53. Mulyadi, M. S., & Anwar, Y. (2012). Impact of corporate social responsibility toward firm value and profitability. The Business Review, Cambridge, 19(2), 316–322.
  54. Myers, S. C., & Majluf, N. S. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics, 13(2), 187–221.
  55. Nance, D. R., Smith Jr, C. W., & Smithson, C. W. (1993). On the determinants of corporate hedging. The Journal of Finance, 48(1), 267–284. https://doi.org/10.1111/j.1540-6261.1993.tb04709.x
  56. Nath, P., & Mukherjee, A. (2012). Complementary effects of relational bonds in information asymmetry contexts. Journal of Services Marketing, 26(3), 168–180. https://doi.org/10.1108/08876041211223979
  57. Neal, R., & Wheatley, S. M. (1998). Adverse selection and bid-ask spreads: Evidence from closed-end funds. Journal of Financial Markets, 1(1), 121–149.
  58. Nguyen, H. Q. (2021). Factors impacting on income inequality in Vietnam: GMM model estimation. The Journal of Asian Finance, Economics and Business, 8(2), 635–641.
  59. Pernamasari, R. (2022). The effect of earnings management and profitability on stock prices future: Information asymmetry as moderating. Asian Journal of Economics, Business and Accounting, 22(16), 9–16. https://doi.org/10.9734/ajeba/2022/v22i1630631
  60. Petersen, M. A., & Thiagarajan, S. R. (2000). Risk measurement and hedging: With and without derivatives. Financial Management, 29(4), 5. https://doi.org/10.2307/3666367
  61. Qu, W., Wongchoti, U., Wu, F., & Chen, Y. (2018). Does information asymmetry lead to higher debt financing? Evidence from China during the NTS Reform period. Journal of Asian Business and Economic Studies, 25(1), 109–121. https://doi.org/10.1108/jabes-04-2018-0006
  62. Raza, S. A., Mansoor, M., & Iraqi, K. M. (2019). Influence of investor sentiments on stock market capitalization of different economic sectors in a developing economy: Evidence from Pakistan. Journal of Finance and Economics Research, 4(1), 31–43. https://doi.org/10.20547/jfer1904103
  63. Ryu, D., Ryu, D., & Yang, H. (2020). Investor sentiment, market competition, and financial crisis: Evidence from the Korean stock market. Emerging Markets Finance and Trade, 56(8), 1804–1816. https://doi.org/10.1080/1540496x.2019.1675152
  64. Sajjad, F., Noreen, U., & Zaman, K. (2013). Impact of derivatives on financial services sector and risk management. Middle-East Journal of Scientific Research, 18(6), 748–758.
  65. Seng, C. K., & Thaker, H. M. T. (2018). Determinants of corporate hedging practices: Malaysian evidence. Report on Economics and Finance, 4(4), 199–220. https://doi.org/10.12988/ref.2018.8418
  66. Shah, S. S. H., Khan, M. A., Ahmed, M., et al. (2024). A Micro-Level Evidence of how Investor and Manager Herding Behavior Influence the Firm Financial Performance. SAGE Open, 14(1), 21582440231219358
  67. Shah, S. S. H., Khan, M. A., Meyer, N., et al. (2019). Does herding bias drive the firm value? Evidence from the Chinese equity market. Sustainability, 11(20), 5583.
  68. Shah, S. S. H., Xinping, X., Khan, M. A., & Harjan, S. A. (2018). Investor and manager overconfidence bias and firm value: Micro-level evidence from the Pakistan equity market. International Journal of Economics and Financial Issues, 8(5), 190.
  69. Shao, W. (2003). Hedging, information asymmetry and financing cost: Evidence from seasoned equity offering announcements.
  70. Shleifer, A., & Summers, L. H. (1990). The noise trader approach to finance. Journal of Economic Perspectives, 4(2), 19–33. https://doi.org/10.1257/jep.4.2.19
  71. Smales, L. A. (2017). The importance of fear: Investor sentiment and stock market returns. Applied Economics, 49(34), 3395–3421. https://doi.org/10.1080/00036846.2016.1259754
  72. Smith, C. W., & Stulz, R. M. (1985). The determinants of firms’ hedging policies. Journal of Financial and Quantitative Analysis, 20(4), 391–405. https://doi.org/10.2307/2330757
  73. Smith, D. M., Wang, N., Wang, Y., & Zychowicz, E. J. (2016). Sentiment and the effectiveness of technical analysis: Evidence from the hedge fund industry. Journal of Financial and Quantitative Analysis, 51(6), 1991–2013. https://doi.org/10.1017/s0022109016000843
  74. Sofia, I. P., & Murwaningsari, E. (2019). The role of corporate diversification, capital structure determinant, and structure of ownership on earning management with information asymmetry as moderating variable. Small, 10(14).
  75. Stiglitz, J. E., & Weiss, A. (1981). Credit rationing in markets with imperfect information. The American Economic Review, 71(3), 393–410.
  76. Stulz, R. (2013). How companies can use hedging to create shareholder value. Journal of Applied Corporate Finance, 25(4), 21–29. https://doi.org/10.1111/jacf.12038
  77. Stulz, R. M. (1984). Optimal hedging policies. Journal of Financial and Quantitative Analysis, 19(2), 127–140. https://doi.org/10.2307/2330894
  78. Su, C. W., Liu, Y., Chang, T., & Umar, M. (2023). Can gold hedge the risk of fear sentiments? Technological and Economic Development of Economy, 29(1), 23–44. https://doi.org/10.3846/tede.2022.17302
  79. Szu, W. M., & Yang, W. R. (2015). Influence of individual investor sentiment on Taiwan option prices during 2007-2010 financial crisis. Managerial Finance, 41(5), 437–464. https://doi.org/10.1108/mf-02-2014-0028
  80. Tinta, A. A. (2022). Financial development, ecological transition, and economic growth in Sub-Saharan African countries: The performing role of the quality of institutions and human capital. Environmental Science and Pollution Research, 29(25), 37617–37632. https://doi.org/10.1007/s11356-021-18104-y
  81. Ur Rehman, M. (2013). Investor’s sentiments and stock market volatility: An empirical evidence from emerging stock market. Pakistan Journal of Commerce and Social Sciences (PJCSS), 7(1), 80–90.
  82. Wang, J. (1993). A model of intertemporal asset prices under asymmetric information. The Review of Economic Studies, 60(2), 249–282. https://doi.org/10.2307/2298057
  83. Wang, J., Yi, S., Wang, X., et al. (2021). How do mutual funds in China exploit investor sentiment? Emerging Markets Finance and Trade, 57(14), 4020–4035. https://doi.org/10.1080/1540496x.2020.1784715
  84. Yang, C. Y., Jhang, L. J., & Chang, C. C. (2016). Do investor sentiment, weather and catastrophe effects improve hedging performance? Evidence from the Taiwan options market. Pacific-Basin Finance Journal, 37, 35–51. https://doi.org/10.1016/j.pacfin.2016.03.002


DOI: https://doi.org/10.24294/jipd.v8i8.3524

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