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Articles

A new proposal for efficiency quantification of capital markets in the context of complex non-linear dynamics and chaos

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Pages 1669-1692 | Received 10 Feb 2016, Accepted 16 Aug 2017, Published online: 12 Oct 2017

Figures & data

Table 1. Interpretation of the results.

Table 2. The presentation of indices series.

Figure 1. Informational entropy. Source: According to the authors' calculations.

Figure 1. Informational entropy. Source: According to the authors' calculations.

Table 3. The run test for the emerging capital markets indices.

Table 4a. Descriptive statistics for Hurst exponent (applied on GARCH residuals, rolling window of 100 observations) – BRIC capital markets.

Table 4b. Descriptive statistics for Hurst exponent (applied on GARCH residuals, rolling window of 100 observations) – European emergent capital markets.

Table 4c. Descriptive statistics for Hurst exponent (applied on GARCH residuals, rolling window of 100 observations) – European developed capital markets.

Table 5. Tests of normality for the series of Hurst exponents.

Figure 3. The situation of capital markets according to Hurst exponent values. Source: According to the authors' calculations.

Note: R/S analysis: rolling sample, GARCH residuals.
Figure 3. The situation of capital markets according to Hurst exponent values. Source: According to the authors' calculations.

Table 6. Test for equality of medians between series.

Table 7. Indices classification according to the value of Hurst exponent, correlation coefficient and fractal dimension.

Figure 4. Capital Market Efficiency Exponent. Source: According to the authors’ calculations.

Figure 4. Capital Market Efficiency Exponent. Source: According to the authors’ calculations.