# Country Risk Ratings and Stock Market Returns in Brazil, Russia, India, and China (BRICS) Countries: A Nonlinear Dynamic Approach

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## Abstract

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## 1. Introduction

## 2. Literature Review

## 3. Methodology

_{max}= q

_{max}= 12 and then drop all of the insignificant stationary regressors sequentially. Next, we test the presence of cointegration among the variables of the final specification to identify the long-run relationships between the dependent and the independent variables. To achieve this, the significance of the lagged levels of the variables in the underlying NARDL model specification is tested while using the F-statistic (denoted as FPSS test) where the null hypothesis of no cointegration is that the coefficients on the level variables are jointly equal to zero. For example, the null hypothesis for Model 1 in Equation (4) is stated as ${H}_{0}:\rho ={\theta}_{S}={\theta}_{\mathrm{SD}}={\theta}_{\mathrm{P}}^{+}\text{}={\theta}_{\mathrm{P}}^{-}\text{}={\theta}_{\mathrm{F}}^{+}={\theta}_{\mathrm{F}}^{-}\text{}={\theta}_{\mathrm{E}}^{+}\text{}={\theta}_{\mathrm{E}}^{-}\text{}=0$.

## 4. Data and Empirical Results

#### 4.1. Data

#### 4.2. Empirical Results from the NARDL Models

_{CM}across all BRICS markets with the exception of Brazil. This confirms our prior argument that commodity market movements indeed act as a systematic catalyst for stock market movements in this bloc of major global importer and exporters. Interestingly, the L

_{CM}values are estimated to be positive regardless of the importer or exporter classification, implying a positive long-run relationship between the commodity and BRICS stock markets. When considering that oil carries a significant weight in the commodity index, a positive trend in commodity markets may indicate an improving demand for energy (and other raw materials for production) due to favorable global economic fundamentals, which also means good news for emerging countries as investors would be more willing to divert their funds into emerging stock markets in order to ride the wave of global growth expectations. On the other hand, a significant long-run equilibrium relationship with developed stock markets is only observed in the case of India, with weaker results for South Africa. These observations imply that, in the long-run, the commodity market acts as a catalyst for these emerging stock markets as opposed to developed stock markets.

_{P+}, L

_{P−}, L

_{F+}, and L

_{F−}for this country. The negative effect on the stock market may be a manifestation of the increased uncertainty these shocks bring to the market as retail investors who dominate this emerging stock market scramble to make sense of what the rating change truly means in terms of future growth expectations. In fact, we observe a similar negative effect of rating changes in the case of Russia and partially in South Africa as well, regardless of the sign of the change. To that end, the prevalent negative effect of financial and political rating changes may be due to informational inefficiencies in the stock market that hinders the processing of new information in a fundamental way, thus leading investors to take a cautious stand in their investments.

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## Appendix A. Detailed Specification of the NARDL Models Estimated

#### The NARDL Models

Variables | Mean | Median | Maximum | Minimum | Standard Deviation | CV | Skewness | Kurtosis | Jarque-Bera | Probability |
---|---|---|---|---|---|---|---|---|---|---|

Brazil_CR | 67.855 | 68.250 | 77.250 | 56.540 | 4.061 | 0.060 | −0.375 | 2.624 | 7.382 | 0.025 |

Brazil_ER | 34.655 | 35.000 | 41.000 | 25.060 | 2.988 | 0.086 | −0.487 | 3.139 | 10.179 | 0.006 |

Brazil−FR | 35.050 | 35.000 | 45.500 | 23.500 | 4.849 | 0.138 | −0.318 | 2.583 | 6.085 | 0.048 |

Brazil_PR | 66.000 | 66.000 | 71.000 | 59.500 | 2.546 | 0.039 | −0.246 | 2.475 | 5.438 | 0.066 |

Brazil_MSCI | 1.25 × 10^{11} | 1.12 × 10^{11} | 2.81 × 10^{11} | 1.66 × 10^{10} | 8 × 10^{10} | 0.640 | 0.142 | 1.425 | 26.910 | 0.000 |

Russia_CR | 68.717 | 70.000 | 82.000 | 45.000 | 7.820 | 0.114 | −0.829 | 3.342 | 30.101 | 0.000 |

Russia_ER | 36.830 | 38.500 | 45.500 | 16.000 | 6.639 | 0.180 | −1.048 | 3.410 | 47.848 | 0.000 |

Russia_FR | 39.579 | 42.500 | 47.500 | 22.000 | 6.439 | 0.163 | −0.871 | 2.554 | 33.934 | 0.000 |

Russia_PR | 60.893 | 62.000 | 69.000 | 42.000 | 5.768 | 0.095 | −0.818 | 3.329 | 29.258 | 0.000 |

Russia_MSCI | 554.690 | 520.846 | 1539.354 | 31.221 | 362.081 | 0.653 | 0.486 | 2.445 | 13.141 | 0.001 |

India_CR | 67.909 | 68.500 | 72.500 | 60.030 | 2.622 | 0.039 | −0.301 | 2.329 | 8.514 | 0.014 |

India_ER | 34.091 | 34.000 | 37.500 | 29.560 | 1.600 | 0.047 | −0.318 | 2.417 | 7.828 | 0.020 |

India_FR | 41.161 | 41.500 | 45.000 | 35.500 | 2.722 | 0.066 | −0.434 | 1.898 | 20.667 | 0.000 |

India_PR | 60.536 | 61.000 | 69.000 | 52.000 | 3.252 | 0.054 | −0.274 | 2.580 | 5.007 | 0.082 |

India_MSCI | 424.631 | 287.242 | 1111.045 | 100.851 | 300.412 | 0.707 | 0.535 | 1.892 | 24.942 | 0.000 |

China_CR | 75.087 | 74.625 | 80.500 | 68.500 | 2.414 | 0.032 | 0.136 | 2.501 | 3.396 | 0.183 |

China_ER | 39.541 | 39.500 | 42.000 | 32.000 | 1.713 | 0.043 | −1.714 | 8.717 | 466.571 | 0.000 |

China_FR | 45.435 | 46.000 | 48.500 | 38.000 | 3.040 | 0.067 | −1.402 | 3.947 | 91.973 | 0.000 |

China_PR | 65.177 | 66.000 | 71.000 | 56.000 | 4.254 | 0.065 | −0.575 | 2.274 | 19.434 | 0.000 |

China_MSCI | 47.751 | 54.250 | 100.662 | 13.752 | 20.537 | 0.430 | −0.084 | 1.894 | 13.147 | 0.001 |

South Africa_CR | 70.699 | 70.000 | 76.500 | 65.500 | 2.834 | 0.040 | 0.262 | 1.866 | 16.401 | 0.000 |

South Africa_ER | 35.141 | 35.500 | 38.500 | 29.000 | 2.047 | 0.058 | −0.373 | 2.606 | 7.476 | 0.024 |

South Africa_FR | 38.069 | 38.000 | 42.000 | 31.500 | 1.996 | 0.052 | −0.493 | 2.955 | 10.236 | 0.006 |

South Africa_PR | 68.139 | 67.500 | 77.000 | 61.500 | 3.640 | 0.053 | 0.558 | 2.585 | 14.861 | 0.001 |

South Africa_MSCI | 538.146 | 375.284 | 1432.465 | 137.224 | 355.219 | 0.660 | 0.789 | 2.501 | 28.738 | 0.000 |

Developed Markets_MSCI | 1184.746 | 1178.420 | 1779.307 | 608.263 | 294.215 | 0.248 | 0.173 | 2.225 | 7.559 | 0.023 |

S&P GSCI Commodity Spot Price Index | 379.791 | 348.328 | 832.304 | 131.751 | 188.518 | 0.060 | 0.422 | 1.801 | 22.587 | 0.000 |

(a) | ||||||
---|---|---|---|---|---|---|

Level | ||||||

Variable | ADF | PP | NP | |||

Constant | Constant + Trend | Constant | Constant + Trend | Constant | Constant + Trend | |

Brazil_CR | −1.635 | −1.545 | −1.911 | −1.934 | −6.016 * | −6.334 |

Brazil_ER | −2.936 ** | −2.905 | −2.928 ** | −2.956 | −7.940 * | −16.03 * |

Brazil−FR | −2.188 | −2.875 | −2.241 | −2.982 | −8.000 * | −8.716 |

Brazil_PR | −2.412 | −2.355 | −2.412 | −2.355 | −12.28 ** | −13.283 |

Brazil_MSCI | −1.637 | −1.519 | −1.637 | −1.577 | 0.335 | −6.310 |

Russia_CR | −2.214 | −2.104 | −2.141 | −2.017 | −4.184 | −8.738 |

Russia_ER | −2.445 | −2.481 | −2.512 | −2.555 | −7.393 * | −9.486 |

Russia_FR | −2.480 | −2.570 | −2.523 | −2.803 | −0.632 | −7.984 |

Russia_PR | −2.476 | −2.290 | −2.666 | −2.484 | −1.742 | −4.058 |

Russia_MSCI | −2.243 | −2.842 | −1.940 | −2.692 | −1.225 | −14.669 * |

India_CR | −2.417 | −2.545 | −2.364 | −2.495 | −10.926 ** | −11.185 |

India_ER | −3.783 ** | −3.795 ** | −3.804 ** | −3.822 ** | −17.008 *** | −25.341 *** |

India_FR | −2.243 | −2.527 | −2.316 | −2.381 | −1.110 | −10.360 |

India_PR | −2.860 * | −2.832 | −2.682 * | −2.642 | −6.229 * | −10.682 |

India_MSCI | −0.468 | −2.762 | −0.538 | −2.971 | 0.710 | −6.805 |

China_CR | −2.794 * | −2.458 | −2.795 * | −2.414 | −0.849 | −2.081 |

China_ER | −4.749 *** | −4.722 *** | −4.749 *** | −4.715 *** | −0.050 | −3.565 |

China_FR | −2.071 | −2.070 | −2.064 | −2.054 | −0.019 | −5.740 |

China_PR | −0.746 | −1.678 | −0.514 | −1.529 | −1.993 | −4.984 |

China_MSCI | −1.530 | −1.913 | −1.629 | −1.983 | −2.706 | −3.213 |

South Africa_CR | −2.619 * | −3.141 * | −2.523 | −3.042 | −2.726 | −18.075 ** |

South Africa_ER | −2.701 * | −2.966 | −2.688 * | −3.007 | −13.943 *** | −16.045 * |

South Africa_FR | −4.291 *** | −4.280 *** | −4.426 *** | −4.414 *** | −33.194 *** | −32.647 *** |

South Africa_PR | −2.308 | −2.538 | −2.424 | −2.766 | −0.797 | −8.168 |

South Africa_MSCI | −0.330 | −3.067 | −0.242 | −3.079 | 1.254 | −10.501 |

Developed Markets_MSCI | −2.122 | −2.383 | −2.261 | −2.719 | 0.425 | −4.964 |

S&P GSCI Commodity Spot Price Index | −1.513 | −1.280 | −1.484 | −1.280 | −1.277 | −8.470 |

(b) | ||||||
---|---|---|---|---|---|---|

First Difference | ||||||

Variable | ADF | PP | NP | |||

Constant | Constant + Trend | Constant | Constant + Trend | Constant | Constant + Trend | |

Brazil_CR | −13.954 *** | −13.945 *** | −13.954 *** | −13.945 *** | −123.228 *** | −123.077 *** |

Brazil_ER | −10.699 *** | −10.739 *** | −16.416 *** | −16.420 *** | −265.278 *** | −267.574 *** |

Brazil−FR | −15.371 *** | −15.341 *** | −15.371 *** | −15.341 *** | −124.937 *** | −124.842 *** |

Brazil_PR | −14.366 *** | −14.360 *** | −14.334 *** | −14.315 *** | −123.935 *** | −123.979 *** |

Brazil_MSCI | −15.810 *** | −15.874 *** | −15.810 *** | −15.875 *** | −40.119 *** | −124.007 *** |

Russia_CR | −16.831 *** | −16.835 *** | −16.874 *** | −16.852 *** | −124.450 *** | −124.437 *** |

Russia_ER | −16.339 *** | −16.306 *** | −16.351 *** | −16.318 *** | −124.834 *** | −124.831 *** |

Russia_FR | −12.357 *** | −12.390 *** | −13.274 *** | −13.267 *** | −183.011 *** | −183.631 *** |

Russia_PR | −15.790 *** | −15.868 *** | −15.866 *** | −15.911 *** | −124.999 *** | −124.997 *** |

Russia_MSCI | −13.629 *** | −13.630 *** | −13.590 *** | −13.588 *** | −7.48776 * | −19.8712 ** |

India_CR | −15.429 *** | −15.402 *** | −15.527 *** | −15.498 *** | −124.950 *** | −124.927 *** |

India_ER | −16.408 *** | −16.387 *** | −16.924 *** | −17.230 *** | −124.790 *** | −124.786 *** |

India_FR | −13.688 *** | −13.706 *** | −13.564 *** | −13.571 *** | −122.614 *** | −121.793 *** |

India_PR | −13.109 *** | −13.102 *** | −16.686 *** | −16.715 *** | −170.486 *** | −170.648 *** |

India_MSCI | −14.741 *** | −14.719 *** | −14.747 *** | −14.725 *** | −29.557 *** | −122.479 *** |

China_CR | −16.489 *** | −16.718 *** | −16.482 *** | −16.758 *** | −124.748 *** | −124.688 *** |

China_ER | −16.083 *** | −16.155 *** | −16.083 *** | −16.155 *** | −124.963 *** | −124.952 *** |

China_FR | −16.172 *** | −16.215 *** | −16.174 *** | −16.225 *** | −124.944 *** | −124.966 *** |

China_PR | −17.253 *** | −17.316 *** | −17.379 *** | −17.545 *** | −124.009 *** | −123.866 *** |

China_MSCI | −14.061 *** | −14.066 *** | −14.015 *** | −14.008 *** | −5.917 * | −116.973 *** |

South Africa_CR | −13.822 *** | −13.793 *** | −13.723 *** | −13.689 *** | −122.948 *** | −122.651 *** |

South Africa_ER | −16.529 *** | −16.501 *** | −16.770 *** | −16.741 *** | −124.709 *** | −124.705 *** |

South Africa_FR | −16.228 *** | −16.201 *** | −16.837 *** | −16.801 *** | −124.859 *** | −124.986 *** |

South Africa_PR | −14.068 *** | −14.054 *** | −14.070 *** | −14.056 *** | −123.372 *** | −123.397 *** |

South Africa_MSCI | −15.824 *** | −15.792 *** | −15.896 *** | −15.899 *** | −1.851 | −36.2192 *** |

Developed Markets_MSCI | −13.925 *** | −13.917 *** | −14.032 *** | −14.022 *** | −122.520 *** | −123.040 *** |

S&P GSCI Commodity Spot Price Index | −11.018 *** | −11.066 *** | −11.069 *** | −11.079 *** | −110.133 *** | −109.161 *** |

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1 | In 2010, South Africa joined this group of countries and formed the BRICS. |

2 | Mensi et al. (2017) also used this approach to carry out a similar analysis for Gulf Cooperation Council (GCC) countries. |

3 | Sari et al. (2013) have also used the autoregressive distributed lag (ARDL) model to study the impact of country risk ratings on the Turkish stock market. |

4 | The parameter ρ is assumed to be negative in order to have a cointegration relationship among the variables. |

5 | According to Granger and Yoon (2002), two times series are hidden cointegrated if their positive and negative components are cointegrated with each other. |

6 | For the bounds testing procedure, two sets of critical values are provided. The upper critical bound assumes that there is a cointegration relationship among the variables, while the lower critical bound assumes that no cointegration relationship exists between the variables. If the F-statistic is greater than the upper level critical value, then the null hypothesis of no-cointegration is rejected (i.e., all variables are cointegrated). Conversely, if the computed F-statistic falls below the lower bound critical value, then the null hypothesis cannot be rejected (i.e., no cointegration). Finally, if the F-statistic falls between the bounds, the test is inconclusive. |

7 | Results of the BDM test for all equations are available upon request. |

8 | Based on the suggestions of an anonymous referee, in order to account for bearish and bullish stock markets, we also estimated a quantiles-based version of the NARDL model, i.e., a QNARDL model as developed by Greenwood-Nimmo et al. (2013). Our results, which are available upon request, however. suggested that estimates of the parameters of model are not statistically different across the various quantiles. This result is an indication of the fact that our NARDL model is not misspecified across bear and bull markets and the QNARDL model does not necessarily bring in new information in our context. Having said this, we must also be cautious of the fact that this result could purely be driven by our relatively small sample size, which is not large enough to handle the overparameterized QNARDL model. |

Brazil | China | India | Russia | South Africa | |
---|---|---|---|---|---|

Model 1 | 4.097 ** | 5.247 *** | 3.292 | 5.192 *** | 2.772 |

Model 2 | 3.384 * | 6.581 *** | 1.734 | 5.495 *** | 2.747 |

Model 3 | 4.935 *** | 2.973 | 5.664 *** | 9.238 *** | 2.902 |

Model 4 | 8.381 *** | 3.288 | 5.146 *** | 3.523 * | 6.833 *** |

Model 5 | 4.113 ** | 3.283 | 4.816 *** | 8.649 *** | 5.230 *** |

Model 6 | 3.310 | 4.326 ** | 2.098 | 2.040 | 4.573 ** |

Brazil | China | India | ||||||
---|---|---|---|---|---|---|---|---|

Variable | Coeff. | S.E. | Variable | Coeff. | S.E. | Variable | Coeff. | S.E. |

$c$ | 0.464 | 0.511 | $c$ | −0.095 | 0.252 | $c$ | −0.370 | 0.239 |

${S}_{t-1}$ | −0.020 | 0.024 | ${S}_{t-1}$ | −0.089 *** | 0.020 | ${S}_{t-1}$ | −0.055 ** | 0.027 |

$C{M}_{t-1}$ | 0.044 * | 0.026 | $C{M}_{t-1}$ | 0.128 *** | 0.032 | $C{M}_{t-1}$ | 0.038 * | 0.023 |

$S{D}_{t-1}$ | −0.033 | 0.026 | $S{D}_{t-1}$ | −0.055 | 0.042 | $S{D}_{t-1}$ | 0.067 * | 0.039 |

${P}_{t-1}^{+}$ | −0.192 | 0.175 | ${P}_{t-1}^{+}$ | −0.222 | 0.135 | ${P}_{t-1}^{+}$ | 0.091 | 0.111 |

${F}_{t-1}^{+}$ | −0.134 ** | 0.054 | ${F}_{t-1}^{+}$ | −0.339 * | 0.173 | ${F}_{t-1}^{+}$ | 0.339 * | 0.179 |

${E}_{t-1}^{+}$ | −0.027 | 0.077 | ${E}_{t-1}^{+}$ | 0.563 * | 0.287 | ${E}_{t-1}^{+}$ | −0.235 | 0.202 |

${P}_{t-1}^{-}$ | −0.359 * | 0.202 | ${P}_{t-1}^{-}$ | −0.590 ** | 0.269 | ${P}_{t-1}^{-}$ | 0.090 | 0.131 |

${F}_{t-1}^{-}$ | −0.075 | 0.102 | ${F}_{t-1}^{-}$ | −0.651 | 0.649 | ${F}_{t-1}^{-}$ | 0.225 | 0.137 |

${E}_{t-1}^{-}$ | −0.062 | 0.088 | ${E}_{t-1}^{-}$ | 1.230 *** | 0.251 | ${E}_{t-1}^{-}$ | −0.123 | 0.114 |

$\Delta {S}_{t-1}$ | −0.120 ** | 0.048 | $\Delta C{M}_{t}$ | 0.318 *** | 0.089 | $\Delta {S}_{t-5}$ | −0.125 ** | 0.050 |

$\Delta {S}_{t-2}$ | −0.111 ** | 0.049 | $\Delta C{M}_{t-4}$ | −0.378 *** | 0.091 | $\Delta {S}_{t-7}$ | −0.124 ** | 0.048 |

$\Delta C{M}_{t}$ | 0.179 ** | 0.071 | $\Delta C{M}_{t-7}$ | −0.243 ** | 0.093 | $\Delta C{M}_{t}$ | 0.227 *** | 0.075 |

$\Delta S{D}_{t-1}$ | 1.144 *** | 0.092 | $\Delta C{M}_{t-10}$ | −0.250 *** | 0.090 | $\Delta C{M}_{t-8}$ | −0.218 *** | 0.075 |

$\Delta {P}_{t-6}^{+}$ | −0.838 ** | 0.353 | $\Delta S{D}_{t-1}$ | 1.142 *** | 0.114 | $\Delta S{D}_{t-1}$ | 0.726 *** | 0.091 |

$\Delta {P}_{t-10}^{+}$ | 0.844 ** | 0.349 | $\Delta S{D}_{t-7}$ | 0.324 *** | 0.114 | $\Delta S{D}_{t-4}$ | 0.190 ** | 0.088 |

$\Delta {P}_{t-11}^{+}$ | 1.000 *** | 0.375 | $\Delta S{D}_{t-8}$ | 0.338 *** | 0.114 | $\Delta S{D}_{t-5}$ | −0.235 *** | 0.088 |

$\Delta {P}_{t-12}^{+}$ | −0.712 ** | 0.349 | $\Delta {P}_{t-2}^{+}$ | 1.410 ** | 0.552 | $\Delta S{D}_{t-9}$ | 0.202 ** | 0.089 |

$\Delta {F}_{t-1}^{+}$ | 0.373 ** | 0.159 | $\Delta {F}_{t-6}^{+}$ | 1.415 *** | 0.480 | $\Delta {P}_{t-3}^{+}$ | −0.687 ** | 0.295 |

$\Delta {F}_{t-11}^{+}$ | −0.391 *** | 0.149 | $\Delta {E}_{t-10}^{+}$ | 1.098 ** | 0.483 | $\Delta {P}_{t-7}^{+}$ | 0.732 ** | 0.293 |

$\Delta {E}_{t-3}^{+}$ | 0.407 ** | 0.177 | $\Delta {F}_{t-3}^{-}$ | 2.632 ** | 1.185 | $\Delta {P}_{t-9}^{+}$ | −0.792 *** | 0.296 |

$\Delta {E}_{t-6}^{+}$ | 0.574 *** | 0.204 | $\Delta {F}_{t}^{+}$ | 0.936 ** | 0.442 | |||

$\Delta {P}_{t-1}^{-}$ | 0.969 ** | 0.484 | $\Delta {F}_{t-6}^{+}$ | 0.821 ** | 0.401 | |||

$\Delta {F}_{t-7}^{-}$ | 0.430 *** | 0.162 | $\Delta {F}_{t-10}^{+}$ | −1.049 *** | 0.386 | |||

$\Delta {F}_{t-11}^{-}$ | 0.860 *** | 0.185 | $\Delta {P}_{t-11}^{-}$ | 1.106 *** | 0.337 | |||

$\Delta {E}_{t-3}^{-}$ | 0.447 ** | 0.188 | $\Delta {F}_{t-9}^{-}$ | 1.180 *** | 0.453 | |||

$\Delta {E}_{t-5}^{-}$ | 0.496 ** | 0.196 | $\Delta {E}_{t}^{-}$ | 0.519 ** | 0.241 | |||

$\Delta {E}_{t-1}^{-}$ | 1.090 *** | 0.246 | ||||||

$\Delta {E}_{t-1}^{-}$ | −0.633 *** | 0.234 | ||||||

Long−run effects | $\Delta {E}_{t-12}^{-}$ | −0.716 *** | 0.243 | |||||

${L}_{CM}$ | 2.214 | 2.436 | ${L}_{CM}$ | 1.434 *** | 0.391 | ${L}_{CM}$ | 0.688 ** | 0.297 |

${L}_{SD}$ | −1.660 | 2.726 | ${L}_{SD}$ | −0.611 | 0.537 | ${L}_{SD}$ | 1.234 ** | 0.501 |

${L}_{{P}^{+}}$ | −9.626 | 16.577 | ${L}_{{P}^{+}}$ | −2.484 * | 1.357 | ${L}_{{P}^{+}}$ | 1.656 | 1.995 |

${L}_{{F}^{+}}$ | −6.705 | 9.345 | ${L}_{{F}^{+}}$ | −3.803 ** | 1.705 | ${L}_{{F}^{+}}$ | 6.201 | 4.793 |

${L}_{{E}^{+}}$ | −1.364 | 4.728 | ${L}_{{E}^{+}}$ | 6.313 ** | 2.983 | ${L}_{{E}^{+}}$ | −4.301 | 5.027 |

${L}_{{P}^{-}}$ | −18.026 | 25.062 | ${L}_{{P}^{-}}$ | −6.618 * | 3.775 | ${L}_{{P}^{-}}$ | 1.655 | 1.971 |

${L}_{{F}^{-}}$ | −3.755 | 7.658 | ${L}_{{F}^{-}}$ | −7.303 | 6.644 | ${L}_{{F}^{-}}$ | 4.116 | 3.246 |

${L}_{{E}^{-}}$ | −3.120 | 6.054 | ${L}_{{E}^{-}}$ | 13.790 *** | 4.067 | ${L}_{{E}^{-}}$ | −2.244 | 2.079 |

Statistics and Diagnostics | ||||||||

$BDM$ | −0.818 | $BDM$ | −4.537 ** | $BDM$ | −2.040 | |||

$WL{R}_{P}$ | 0.247 | [0.620] | $WL{R}_{P}$ | 1.275 | [0.260] | $WL{R}_{P}$ | 0.000 | [0.999] |

$WL{R}_{F}$ | 0.304 | [0.582] | $WL{R}_{F}$ | 0.292 | [0.589] | $WL{R}_{F}$ | 0.779 | [0.379] |

$WL{R}_{E}$ | 0.350 | [0.555] | $WL{R}_{E}$ | 2.963 | [0.087] | $WL{R}_{E}$ | 0.194 | [0.660] |

$WS{R}_{P}$ | 0.548 | [0.460] | $WS{R}_{P}$ | 6.518 | [0.011] | $WS{R}_{P}$ | 9.183 | [0.003] |

$WS{R}_{F}$ | 16.788 | [0.000] | $WS{R}_{F}$ | 0.919 | [0.339] | $WS{R}_{F}$ | 0.350 | [0.555] |

$WS{R}_{E}$ | 0.011 | [0.916] | $WS{R}_{E}$ | 5.161 | [0.024] | $WS{R}_{E}$ | 0.237 | [0.627] |

${\overline{R}}^{2}$ | 0.524 | ${\overline{R}}^{2}$ | 0.466 | ${\overline{R}}^{2}$ | 0.518 | |||

$SC\left(12\right)$ | 13.373 | [0.342] | $SC\left(12\right)$ | 15.598 | [0.210] | $SC\left(12\right)$ | 8.053 | [0.781] |

$RRT$ | 5.155 | [0.023] | $RRT$ | 0.020 | [0.886] | $RRT$ | 0.267 | [0.605] |

$JB$ | 4.644 | [0.098] | $JB$ | 31.498 | [0.000] | $JB$ | 0.239 | [0.887] |

$HT$ | 43.365 | [0.000] | $HT$ | 0.122 | [0.727] | $HT$ | 0.010 | [0.921] |

Russia | South Africa | ||||
---|---|---|---|---|---|

Variable | Coeff. | S.E. | Variable | Coeff. | S.E. |

$c$ | −0.208 | 0.346 | $c$ | 0.260 * | 0.143 |

${S}_{t-1}$ | −0.103 *** | 0.029 | ${S}_{t-1}$ | −0.119 *** | 0.027 |

$C{M}_{t-1}$ | 0.132 *** | 0.038 | $C{M}_{t-1}$ | 0.028 * | 0.015 |

$S{D}_{t-1}$ | 0.017 | 0.055 | $S{D}_{t-1}$ | 0.032 * | 0.019 |

${P}_{t-1}^{+}$ | 0.089 | 0.151 | ${P}_{t-1}^{+}$ | 0.072 | 0.095 |

${F}_{t-1}^{+}$ | 0.134 | 0.183 | ${F}_{t-1}^{+}$ | 0.017 | 0.072 |

${E}_{t-1}^{+}$ | −0.226 ** | 0.091 | ${E}_{t-1}^{+}$ | 0.164 * | 0.088 |

${P}_{t-1}^{-}$ | 0.196 | 0.228 | ${P}_{t-1}^{-}$ | 0.206 * | 0.117 |

${F}_{t-1}^{-}$ | −0.340 ** | 0.138 | ${F}_{t-1}^{-}$ | −0.122 * | 0.072 |

${E}_{t-1}^{-}$ | 0.062 | 0.059 | ${E}_{t-1}^{-}$ | 0.171 ** | 0.072 |

$\Delta {S}_{t-1}$ | 0.105 ** | 0.049 | $\Delta C{M}_{t}$ | 0.146 *** | 0.052 |

$\Delta {S}_{t-10}$ | 0.110 ** | 0.044 | $\Delta C{M}_{t}$ | 0.611 *** | 0.071 |

$\Delta C{M}_{t}$ | 0.242 ** | 0.119 | $\Delta {P}_{t}^{+}$ | −0.708 ** | 0.294 |

$\Delta S{D}_{t-1}$ | 1.355 *** | 0.155 | $\Delta {P}_{t-4}^{+}$ | −0.660 ** | 0.292 |

$\Delta {P}_{t-7}^{+}$ | −0.950 ** | 0.422 | $\Delta {P}_{t-9}^{+}$ | 0.970 *** | 0.296 |

$\Delta {F}_{t}^{+}$ | −0.869 *** | 0.328 | $\Delta {P}_{t-1}^{-}$ | −1.029 ** | 0.416 |

$\Delta {F}_{t-10}^{+}$ | −0.860 *** | 0.326 | $\Delta {P}_{t-10}^{-}$ | −1.083 ** | 0.419 |

$\Delta {E}_{t-7}^{+}$ | 0.382 ** | 0.177 | $\Delta {F}_{t-3}^{-}$ | −0.386 ** | 0.162 |

$\Delta {P}_{t}^{-}$ | 2.624 *** | 0.433 | $\Delta {F}_{t-5}^{-}$ | 0.353 ** | 0.155 |

$\Delta {F}_{t}^{-}$ | 1.271 *** | 0.258 | $\Delta {E}_{t-12}^{-}$ | 0.655 *** | 0.189 |

$\Delta {F}_{t-4}^{-}$ | 0.989 *** | 0.246 | |||

$\Delta {F}_{t-5}^{-}$ | −1.049 *** | 0.302 | |||

$\Delta {F}_{t-8}^{-}$ | −0.521 ** | 0.234 | |||

$\Delta {F}_{t-12}^{-}$ | −0.735 *** | 0.274 | |||

$\Delta {E}_{t-1}^{-}$ | −0.519 *** | 0.137 | |||

$\Delta {E}_{t-3}^{-}$ | 0.424 *** | 0.127 | |||

$\Delta {E}_{t-5}^{-}$ | 0.557 *** | 0.163 | |||

$\Delta {E}_{t-10}^{-}$ | 0.288 ** | 0.134 | |||

Long−run effects | |||||

${L}_{CM}$ | 1.289 *** | 0.351 | ${L}_{CM}$ | 0.236 ** | 0.115 |

${L}_{SD}$ | 0.168 | 0.509 | ${L}_{SD}$ | 0.269 * | 0.143 |

${L}_{{P}^{+}}$ | 0.869 | 1.356 | ${L}_{{P}^{+}}$ | 0.606 | 0.809 |

${L}_{{F}^{+}}$ | 1.305 | 1.701 | ${L}_{{F}^{+}}$ | 0.141 | 0.599 |

${L}_{{E}^{+}}$ | −2.194 ** | 0.983 | ${L}_{{E}^{+}}$ | 1.374 * | 0.768 |

${L}_{{P}^{-}}$ | 1.908 | 2.003 | ${L}_{{P}^{-}}$ | 1.730 * | 0.992 |

${L}_{{F}^{-}}$ | −3.304 * | 1.727 | ${L}_{{F}^{-}}$ | −1.024 * | 0.584 |

${L}_{{E}^{-}}$ | 0.600 | 0.610 | ${L}_{{E}^{-}}$ | 1.434 *** | 0.533 |

Statistics and Diagnostics | |||||

$FPSS$ | 5.495 *** | $FPSS$ | 2.747 | ||

$BDM$ | −3.598 | $BDM$ | −4.488 ** | ||

$WL{R}_{P}$ | 0.242 | [0.623] | $WL{R}_{P}$ | 1.997 | [0.159] |

$WL{R}_{F}$ | 4.252 | [0.040] | $WL{R}_{F}$ | 34.555 | [0.000] |

$WL{R}_{E}$ | 5.881 | [0.016] | $WL{R}_{E}$ | 0.007 | [0.932] |

$WS{R}_{P}$ | 31.652 | [0.000] | $WS{R}_{P}$ | 4.941 | [0.027] |

$WS{R}_{F}$ | 4.434 | [0.036] | $WS{R}_{F}$ | 0.020 | [0.887] |

$WS{R}_{E}$ | 1.053 | [0.306] | $WS{R}_{E}$ | 12.053 | [0.001] |

${\overline{R}}^{2}$ | 0.617 | ${\overline{R}}^{2}$ | 0.487 | ||

$SC\left(12\right)$ | 12.230 | [0.427] | $SC\left(12\right)$ | 9.651 | [0.647] |

$RRT$ | 2.735 | [0.098] | $RRT$ | 3.550 | [0.060] |

$JB$ | 5.720 | [0.057] | $JB$ | 3.491 | [0.175] |

$HT$ | 0.334 | [0.564] | $HT$ | 30.155 | [0.000] |

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Ben Nasr, A.; Cunado, J.; Demirer, R.; Gupta, R.
Country Risk Ratings and Stock Market Returns in Brazil, Russia, India, and China (BRICS) Countries: A Nonlinear Dynamic Approach. *Risks* **2018**, *6*, 94.
https://doi.org/10.3390/risks6030094

**AMA Style**

Ben Nasr A, Cunado J, Demirer R, Gupta R.
Country Risk Ratings and Stock Market Returns in Brazil, Russia, India, and China (BRICS) Countries: A Nonlinear Dynamic Approach. *Risks*. 2018; 6(3):94.
https://doi.org/10.3390/risks6030094

**Chicago/Turabian Style**

Ben Nasr, Adnen, Juncal Cunado, Rıza Demirer, and Rangan Gupta.
2018. "Country Risk Ratings and Stock Market Returns in Brazil, Russia, India, and China (BRICS) Countries: A Nonlinear Dynamic Approach" *Risks* 6, no. 3: 94.
https://doi.org/10.3390/risks6030094