The effect of ambiguity on the UK stock market: evidence from a new empirical approach
-
DOIhttp://dx.doi.org/10.21511/imfi.14(4).2017.12
-
Article InfoVolume 14 2017, Issue #4, pp. 133-147
- 829 Views
-
146 Downloads
This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
This study developed a new ambiguity measure using the bid-ask spread. The results suggest that the degree of ambiguity has an impact on the daily UK stock market returns, but ambiguity does not cause changes in the returns. This implies that UK stock prices or returns cannot be predicted using variation in the degree of ambiguity through linear models, such as the VAR model, which was used in the study. The two sets of results in the study show that the degree of ambiguity from the previous two days might affect stock market returns. The authors observe that an increase in the degree of ambiguity two days ago is associated with a positive premium required by the investors. On the other hand, the degree of ambiguity tends to be affected by its past five-day values. Thus, the degree of ambiguity seems to persist for five days until investors update their priors. The intuition behind the result is that the degree of ambiguity can affect the returns of the UK stock market and UK stock market returns can in turn have an impact on the degree of ambiguity. The authors also observe that the degree of ambiguity does not seem to predict stock market returns in the UK when one applies linear models. However, this does not mean that there is no non-linear relationship between the degree of ambiguity and stock market returns or stock returns.
- Keywords
-
JEL Classification (Paper profile tab)D81, D83, G11, G12
-
References36
-
Tables8
-
Figures5
-
- Figure 1. Histogram of spread and return
- Figure 2. Histogram of natural logarithm of spread
- Figure 3. Time series plots of volume, natural logarithm of spread and return
- Figure 4. Orthogonalized impulse-response function (VAR with 5 lags)
- Figure 5. Orthogonalized impulse-response function (VAR with 13 lags)
-
- Table 1. Contingency table of Ellsberg’s experiment
- Table 2. Decisions, outcomes and payoffs of ambiguous urn (Urn 1) and risky urn (Urn 2)
- Table 3. Summary statistics
- Table 4. Regression result with Newey-West standard errors
- Table 5. Augmented Dickey-Fuller test result
- Table 6. Information criteria for lag selection
- Table 7. VAR result with 5 lags
- Table 8. VAR result with 13 lag
-
- Anderson, E. W., Hansen, L. P., & Sargent, T. J. (2003). A quartet of semigroups formodel specification, robustness, prices of risk, and model detection. Journal of The European Economic Association, 1(1), 68-123.
- Barillas, F., Hansen, L. P., & Sargent, T. J. (2009). Doubts or variability? Journal of Economic Theory, 144(6), 2388-2418.
- Bernoulli, D. (1738). Specimen theoriae novae de mensura sortis. Commentarii Academiae Scientiarum Imperialis Petropolitanae, 5, 175-192.
- Boyarchenko, N. (2012). Ambiguity shifts and the 2007–2008 financial crisis. Journal of Monetary Economics, 59(5), 493-507.
- Chen, Z., & Epstein, L. (2002). Ambiguity, risk, and asset returns in continuous time. Econometrica, 70(4), 1403-1443.
- Chen, H., Ju, N., & Miao, J. (2014). Dynamic asset allocation with ambiguous return predictability. Review of Economic Dynamics, 17(4), 799-823.
- Conte, A., & Hey, J. D. (2013). Assessing multiple prior models of behaviour under ambiguity. Journal of Risk and Uncertainty, 46(2), 113-132.
- Cochrane, J. H. (2009). Asset Pricing (Revised Edition). Princeton University press.
- Dimmock, S. G., Kouwenberg, R., Mitchell, O. S., & Peijnenburg, K. (2016). Ambiguity aversion and household portfolio choice puzzles: Empirical evidence. Journal of Financial Economics, 119(3), 559-577.
- Dow, J., & Werlang, S. R. da Costa (1992). Uncertainty aversion, risk aversion, and the optimal choice of portfolio. Econometrica, 60(1), 197-204.
- Duffie, D., & Epstein, L. G. (1992). Stochastic differential utility. Econometrica, 60(2), 353-394.
- Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms. The Quarterly Journal of Economics, 75(4), 643-669.
- Epstein, L. G., & Wang, T. (1994). Intertemporal asset pricing under Knightian uncertainty. Econometrica, 62(2), 283-322.
- Epstein, L. G., & Schneider, M. (2008). Ambiguity, information quality, and asset pricing. The Journal of Finance, 63(1), 197-228.
- Epstein, L. G., & Schneider, M. (2010). Ambiguity and asset markets. Annual Review of Financial Economics, 2, 315-346.
- Etner, J., Jeleva, M., & Tallon, J. M. (2012). Decision theory under ambiguity. Journal of Economic Surveys, 26(2), 234-270.
- Garlappi, L., Uppal, R., & Wang, T. (2007). Portfolio selection with parameter and model uncertainty: A multi-prior approach. Review of Financial Studies, 20(1), 41-81.
- Gilboa, I., & Schmeidler, D. (1989). Maxmin expected utility with non-unique prior. Journal of mathematical economics, 18(2), 141-153.
- Grossman, S. J., & Miller, M. H. (1988). Liquidity and market structure. The Journal of Finance, 43(3), 617-637.
- Guidolin, M., & Rinaldi, F. (2013). Ambiguity in asset pricing and portfolio choice: A review of the literature. Theory and Decision, 74(2), 183-217.
- Hansen, L. P., & Sargent, T. J. (2001). Robust control and model uncertainty. The American Economic Review, 91(2), 60-66.
- Illeditsch, P. K. (2009). Ambiguous Information, Risk Aversion, and Asset Pricing (No 802, 2009 Meeting Papers from Society for Economic Dynamics).
- Jeong, D., Kim, H., & Park, J. Y. (2015). Does ambiguity matter? Estimating asset pricing models with a multiple-priors recursive utility. Journal of Financial Economics, 115(2), 361-382.
- Ju, N., & Miao, J. (2012). Ambiguity, learning, and asset returns. Econometrica, 80(2), 559-591.
- Klibanoff, P., Marinacci, M., & Mukerji, S. (2005). A smooth model of decision making under ambiguity. Econometrica, 73(6), 1849-1892.
- Klibanoff, P., Marinacci, M., & Mukerji, S. (2009). Recursive smooth ambiguity preferences. Journal of Economic Theory, 144(3), 930-976.
- Knight, F. H. (1921). Risk, uncertainty and profit. New York: Hart, Schaffner and Marx.
- Liu, H. (2011). Dynamic portfolio choice under ambiguity and regime switching mean returns. Journal of Economic Dynamics and Control, 35(4), 623-640.
- Lütkepohl, H. (2006). Forecasting with VARMA Models. Handbook of Economic Forecasting, 1, 287-325.
- Maccheroni, F., Marinacci, M., & Rustichini, A. (2006). Ambiguity aversion, robustness, and the variational representation of preferences. Econometrica, 74(6), 1447-1498.
- Miao, J. (2009). Ambiguity, risk and portfolio choice under incomplete information. Annals of Economics and Finance, 10(2), 257-279.
- Ozsoylev, H., & Werner, J. (2011). Liquidity and asset prices in rational expectations equilibrium with ambiguous information. Economic Theory, 48(2), 469-491.
- Routledge, B. R., & Zin, S. E. (2009). Model uncertainty and liquidity. Review of Economic dynamics, 12(4), 543-566.
- Strzalecki, T. (2011). Axiomatic foundations of multiplier preferences. Econometrica, 79(1), 47-73.
- Teräsvirta, T. (1994). Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical association, 89(425), 208-218.
- Viale, A. M., Garcia-Feijoo, L., & Giannetti, A. (2014). Safety First, Learning Under Ambiguity, and the Cross-Section of Stock Returns. The Review of Asset Pricing Studies, 4(1), 118-159.