Accounting for Geographic Exposure in Performance and Risk Reporting for Equity Portfolios

Accounting for Geographic Exposure in Performance and Risk Reporting for Equity Portfolios — March 2015

Section 3: Application to Performance Attribution

performance of STOXX Europe 600 than stocks with high exposure to emerging markets (-2.63%). For FTSE Developed Asia Pacific, we note that during bull markets, when the return of emerging market equity is higher than that of developed market equity, stocks with high exposure to emerging markets contributed significantly more (9.42%) than stocks with low exposure to emerging markets (3.42%). Similarly, during bear

In Table 15 below, we report the conditional performance attribution of the STOXX Europe 600. As in the previous case, we note that in the bull market phase, stocks with high exposure to emerging markets contributed more (7.83%) than stocks with low exposure to emerging markets (5.47%). However, during bear markets, when the return on emerging markets was lower than on developed markets, stocks with low emerging market exposure contributed less (-3.16%) to the

Table 16: Return contribution to FTSE Developed Asia Pacific of stocks with varying Emerging Market exposure (Conditional Analysis based on Emerging vs. Developed market return spread): The table below reports the breakdown of the annualised excess returns of FTSE Developed Asia Pacific into the performance of three portfolios formed by sorting stocks based on their sales exposure to emerging market. We report performance attribution separately for bull and bear markets, wherein bull (or bear) market is defined as calendar year quarters where the spread between emerging and developed market returns is positive (or negative). The benchmarks for emerging and developed markets are MSCI Emerging and MSCI World, respectively. To form portfolios, we sort stocks by their emerging markets sales exposures. We then select the top stocks up to 33% of cumulative market cap (High), and the bottom stocks up to 33% cumulative market cap (Low), and form cap-weighted high and low exposure portfolios based on these sorts. Stocks which are not included in either extreme portfolio form the medium portfolio (Mid). The portfolios are formed at the end of June every year, using geographic segmentation data for the previous fiscal year. The statistics are based on daily total return series (with dividends reinvested) in USD. The portfolio constituents are weighted by their total market capitalisation in (USD) at the end of June every year. The figures for High and Low portfolios are highlighted in bold. For performance attribution, we use OLS regression, wherein the dependent variable is the excess return on FTSE Developed Asia Pacific and independent variables are excess returns on High, Mid and Low portfolios. All returns are in excess of the risk-free rate. The risk-free rate in US Dollars is measured using the return on the Secondary Market US Treasury Bills (3M). The source of geographic segmentation data is DataStream (Worldscope) supplemented by Bloomberg. In the event that the excess return on the index is negative, we do not calculate % contribution as it gives a less meaningful figure. Such figures are replaced by NA. FTSE Dev. APAC High Mid Low Unexplained Contr. % Contr. Contr. % Contr. Contr. % Contr. Contr. % Contr. Bull Market 17.71% 9.42% 53.17% 6.14% 34.66% 3.42% 19.32% -1.27% -7.14% Bear Market -9.80% -4.59% NA -4.23% NA -0.25% NA -0.72% NA Table 15: Return contribution to STOXX Europe 600 of stocks with varying Emerging Market exposure (Conditional Analysis based on Emerging vs. Developed market return spread): The table below reports the breakdown of the annualised excess returns of STOXX Europe 600 into the performance of three portfolios formed by sorting stocks based on their sales exposure to emerging markets. We report performance attribution separately for bull and bear markets, wherein bull (or bear) market is defined as calendar year quarters where the spread between emerging and developed market returns is positive (or negative). The benchmarks for emerging and developed markets are MSCI Emerging and MSCI World, respectively. To form portfolios, we sort stocks by their emerging markets sales exposures. We then select the top stocks up to 33% of cumulative market cap (High), and the bottom stocks up to 33% cumulative market cap (Low), and form cap-weighted high and low exposure portfolios based on these sorts. Stocks which are not included in either extreme portfolio form the medium portfolio (Mid). The portfolios are formed at the end of June every year, using geographic segmentation data for the previous fiscal year. The statistics are based on daily total return series (with dividends reinvested) in USD. The portfolio constituents are weighted by their total market capitalisation in (USD) at the end of June every year. The figures for High and Low portfolios are highlighted in bold. For performance attribution, we use OLS regression, wherein the dependent variable is excess return on the STOXX Europe 600 and independent variables are excess returns on High, Mid and Low portfolios. All returns are in excess of the risk-free rate. The risk-free rate in US Dollars is measured using the return on the Secondary Market US Treasury Bills (3M). The source of geographic segmentation data is DataStream (Worldscope). In the event that the excess return on the index is negative, we do not calculate % contribution as it gives a less meaningful figure. Such figures are replaced by NA. STOXX Europe 600 High Mid Low Unexplained Contr. % Contr. Contr. % Contr. Contr. % Contr. Contr. % Contr. Bull Market 21.50% 7.83% 36.41% 7.69% 35.76% 5.47% 25.46% 0.51% 2.37% Bear Market -9.97% -2.63% NA -4.43% NA -3.16% NA 0.25% NA

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