The effect of ambiguity on the UK stock market: evidence from a new empirical approach Cover Image

The effect of ambiguity on the UK stock market: evidence from a new empirical approach
The effect of ambiguity on the UK stock market: evidence from a new empirical approach

Author(s): Run Qing Tan, Viktor Manahov, Jacco Thijssen
Subject(s): Economy, Business Economy / Management, Micro-Economics, Financial Markets, Accounting - Business Administration
Published by: ТОВ “Консалтингово-видавнича компанія “Ділові перспективи”
Keywords: ambiguity aversion; ambiguity measure; uncertain probabilities;

Summary/Abstract: 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.

  • Issue Year: 14/2017
  • Issue No: 4
  • Page Range: 133-147
  • Page Count: 15
  • Language: English