**3. Data**

Our empirical analysis on quantile dependence between renewable-energy and low-carbon stocks in the European and USA stock markets is based on the respective stock market indices. Specifically, we consider the Europe STOXX Low Carbon Select 50 Index (LC-EU) and the USA STOXX Low Carbon Select 50 Index (LC-USA) for the European and USA stock markets, respectively. These indices, which exclude all companies involved in the coal sector, capture the performance of low carbon emissions stocks with low volatility and high dividends selected from the universe of companies included in the STOXX Europe 600 Index and in the STOXX Global 1800 index, respectively. The 50 assets included in the index are weighted according to the inverse of their volatility, with a cap at 10%, and the index is reviewed quarterly.

To account for the performance of renewable-energy stocks, we take the European Renewable Energy index (ERIX) and the Wilder Hill Clean Energy index (ECO) for Europe and USA, respectively. ERIX is comprised of the largest European renewable-energy companies with wind, solar, biomass, and water energy generation as their main activities. ECO is an equal-dollar-weighted index of a set of companies that develop activities related to clean energies and conservation.

The sample covered the period 1 January 2010 to 31 July 2019, with the start date of the sample period determined by the availability of data for low-carbon indices. Data was sourced from Bloomberg on a daily basis. Figure 1 displays the temporal dynamics of renewable-energy and low-carbon markets in the European and USA markets, showing that these markets follow similar trends, with price changes harmonized in Europe, but not synchronized in the USA. We computed daily price returns as the first difference for the (log) value of those indices. Table 1 presents the main statistical features of the daily returns. For all markets under study, average daily returns are close to zero and standard deviations are greater for the renewable-energy stocks than for the low-carbon stocks. Higher volatility in renewable-energy markets is also confirmed by the maximum and minimum values of returns. All price returns exhibit negative skewness and the price return distributions have fat tails. In fact, the Jarque–Bera (JB) test rejects normality. The evidence of serial dependence provided by the Ljung–Box (LJ) statistic is mixed: although most of the series exhibit serial independence, low-carbon series for Europe show serial dependence. Finally, the ARCH test points to the presence of conditional heteroskedasticity in the series.

**Figure 1.** Time series plot for daily renewable-energy and low-carbon indices.

Data for the pricing factors and the risk-free interest rates to compute excess returns in renewable-energy and low-carbon markets in Europe and the USA were sourced from the Kenneth French data library (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data\_library.html). Table 2 presents descriptive statistics for those pricing factors in both markets, showing that their behaviors differ across stock markets.


**Table 1.** Descriptive statistics for renewable-energy and low-carbon indices.

Note. The table presents descriptive statistics for price returns in low-carbon markets in the EU (LC-EU) and the USA (LC-USA) and in the corresponding renewable-energy markets, ERIX and ECO, respectively. Data cover daily periods from 1 January 2010 to 31 July 2019. JB denotes the Jarque–Bera statistic for the null hypothesis of normality; an asterisk denotes rejection of the null hypothesis. Finally, ARCH denotes Engle's Lagrange multiplier test for conditional heteroskedasticity and Q(20) denotes Ljung–Box statistics for serial correlation in the price return series. Both tests were computed with 20 lags and their *p* values are reported in square brackets.

**Table 2.** Descriptive statistics for pricing factors.


Note. The table presents descriptive statistics for pricing factors, MKT, SMB, HML, RMW and CMA, in the EU and USA markets for the period 1 January 2010 to 31 July 2019. JB denotes the Jarque–Bera statistic for the null hypothesis of normality; rejection of the null hypothesis is indicated with an asterisk. Finally, ARCH denotes Engle's Lagrange multiplier test for conditional heteroskedasticity and Q(20) denotes Ljung–Box statistics for serial correlation in the price return series. Both tests were computed with 20 lags and their *p* values are reported in square brackets.
