Renewable Energy

Table 15 reports my regression results for the traditional tracking error from Equations (15) and (16). I observe traditional tracking errors of about 2 to 13 percent for all renewable energy indexes on a monthly basis. Asian, European, North American, and Global renewable energy equity indexes have positive tracking error volatility. This means that their total volatility is larger than that of the conventional energy firms. To be specific, I find for about 70 percent of my sample of renewable energy indexes that they are more volatile than their conventional energy peers. Similarly, when using my adjusted measure for relative volatilities, my results show that downside tracking errors are positive and tend to be somewhat larger in magnitude than traditional tracking errors. Downside tracking error volatilities range from 2.5 to 15.4 percent on a monthly basis. This finding indicates that, on average, downside variance is greater and that renewable energy indexes tend to be more volatile than traditional energy index benchmarks.

I argue that there are three reasons behind the relatively high volatilities for renewable energy indexes. First, as previous studies note, renewable energy companies are risky because they seem to relate very closely to technology-intensive companies due to the similarities in their core businesses, which is to develop innovative technologies to produce renewable sources of energy (Sadorsky, 2012b). Second, renewable energy index returns also are driven by changes in macroeconomic factors such as carbon and oil prices89. Particularly the carbon price, as a fundamental influence to stock returns of renewable energy companies, has been very low during the second phase of the EU ETS and arguably appears to be

89 _{Kumar et al. (2012) test the contemporaneous relationship between carbon prices and renewable energy prices} and find carbon prices to be significantly related to renewable energy prices, using a multifactor model. While the carbon price correlates negatively with the returns of the Wilderhill New Energy Global Innovation Index

systematically undervalued (Creti et al., 2012). During the first phase of the EU ETS, generous permit allocations depressed the carbon price even further to almost zero Euros in 2007, down from about 20 Euros per ton of carbon dioxide at the beginning of the scheme in 2005 (Ellerman and Buchner, 2008). Clearly, the carbon price measured by the EU ETS applies to carbon emitted in European countries, as a truly global carbon emission scheme does not exist, at this moment in time. However, recent mandatory regional developments in North America and Asia show that more governments are willing and committed to put a price on carbon (Haug et al., 2014). For example, the Regional Greenhouse Gas Initiative was the first mandatory carbon emission trading scheme in the US and covers companies in nine90 federal states since 2009. This was followed by the Western Climate Initiative, a carbon trading system covering the four91 largest Canadian provinces and California in the US (Haug et al., 2014). Mandatory emission trading schemes also exist in Asia since 2010. Japan and Korea (being the second biggest after the EU ETS) were the first Asian countries to launch such schemes, with China's mandatory ETS following in 2016 (Haug et al., 2014). Third, although public capital investments in the renewable energy sector are crucial, they have been stagnating due to the lasting recession which restrained governments to continue with public funding for that sector (International Energy Agency, 2012, 2013). In the recent past, major capital investments for the construction and development of renewable energy technologies have originated from public finance. Yet, governments find it increasingly difficult to support the sector due to the lasting recession. A recent report highlights this situation: "The current economic crisis has reduced the amount of public finance available to support low-carbon energy technologies" (International Energy Agency, 2012: 68). With lacking capital investments from public finances and insufficient demand from the private sector, uncertainty will remain high and as a result investment risks as well.

On closer inspection of my empirical results, I find four out of fourteen (about 30 percent) renewable energy indexes to have substantially lower tracking errors (less return volatility), these are Daxglobal Alternative, S&P Global Alternative, Nasdaq Renewable Edge, and S&P Global Renewable Energy. The first three indexes invest in global renewable energy businesses and the last one in purely US-based renewable energy technology firms. Tracking errors for those four range from 2.68 to 8.46 percent. Surprisingly, the returns of these four indexes have been previously found to generate positive annualised mean returns

90 _{Including Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode} Island, Vermon (Haug et al., 2014).

as well as correlate more strongly with traditional energy indexes (see Panel A of Table 13 and Table 14, respectively). Interestingly, Nasdaq Renewable Edge, a highly technology oriented index, reports the lowest tracking error volatility among my sample of renewable energy indexes. Sector screens, highlight that this index only includes renewable energy firms from three very specific business areas including solar photovoltaics, biofuels, and advanced batteries. As such, these findings suggest that more concentrated renewable energy indexes tend to have lower relative investment risks compared to broader renewable energy indexes. Although this finding contradicts Modern Portfolio Theory and what would be expected of a less diversified portfolio, recent related studies on portfolio concentration in the mutual fund environment show that investment managers with more concentrated holdings in specific market sectors report better financial performance than broadly diversified funds (Huij and Derwall, 2011; Kacperczyk et al., 2005). Furthermore, Statman (2006) finds industry concentration to be the major reason for low tracking errors between socially responsible and conventional equity indexes.