Used Python to construct a minimized tracking error ETF to SSGA SHE with both large-cap stocks and random selection within portfolio. Gained insightful conclusions on indexing products towards ESG investing.

1. Research Project
C o m p u t e r S i m u l a t i o n s 2 0 1 9 . 1 1 . 2 2
Jie He

2. Project 1
Minimizing Tracking Errors
Index Selection: SHE | State Street Global Advisors Gender Diversity Index ETF
SSGA Gender Diversity Index:
Track the performance of US large-cap companies that lead their industry
sectors in advancing women by promoting gender diversity on their
boards and in senior leadership positions.
Gender Diversity matrix:
• Portion of female executives and members of the board to all
executives and members of the board
• Portion of female executives to all executives
• Portion of female executives excluding board members to all executives
excluding board members
Number of stocks: 178
Index Weighted Average Market Cap: $118,365.42M

3. Top 10 Holdings
Slide / 01
SHE:
Inception time: 03/07/2016
Number of stocks: 178
Est. 3-5 Year EPS Growth: 10.3%
Price/Book Ratio: 3.09
Price/Earnings Ratio FY1: 18.54
Weighted Average Market Cap: $116,921.00M

4. 03/19/2008 –
03/20/2018
SHE S&P 500
Return 19.9% 9.4%
Volatility 21.0% 20.3%
Sharpe Ratio 0.83 0.34
VaR(5%) 1.9% 1.9%
ES(5%) 3.2% 3.2%
Why invest in SHE:
• Historical annualized return: higher than market
• Historical annualized risk: similar to market
• Gender Diversity companies:
Higher employees’ engagement
Better corporate governance
Stronger innovation
Higher stock return
07/01/2008 –
02/01/2009
SHE S&P 500
Return -29.6% -61.11%
Volatility 51.76% 51.75%
Sharpe Ratio -0.64 -1.24
VaR(5%) 5.7% 5.6%
ES(5%) 7.0% 7.4%

5. SHE ETF:
Criteria Screening: 127 stocks
Return period: 03/19/2008 – 03/20/2018
Number of stocks: 60
• Top 60 companies with highest market cap weights
• Random 60 companies
Rolling window: 252 days
Volatility forecasting method: EWMA

6. SHE ETF:
60 companies with top market cap
weights:
• Forecasted TE: 25~75 bps
• Forward realized TE: 75~175 bps
• Differences: 50~100 bps
• Financials, Industrials, IT, Healthcare,
Consumer Staples
Top 60 companies with highest market cap weights

7. SHE ETF:
Random 60 stocks
Python package: CVXPY, solver: CPLEX
Limitation:
• Covariance matrix must be very small number
• Different solving speed with different covariance matrix
• Objective function will be easier to solve in certain format

8. SHE ETF:
• Smallest tracking error: 0.007 bps
• Actual number of stocks with assigned weights: 56
• Stocks included:
• Consumer Discretionary, Healthcare, Financials, IT
• Stocks with lower / higher correlation are included
market weight 1-30: 23
market weight 31-60: 12
market weight 61-90: 9
market weight 91-120: 10
market weight 121-127: 2

9. https://equileap.org

10. In order to select 10% market capitalization in each sector to form the index, some
companies with higher gender ratio but big market cap weight are excluded from the
SSGA Gender Diversity Index.

11. Tra d e O ff ?
Equileap Best Gender
Diversity Practice
Public source ESG data
19 gender equality matrix
Global public companies
ESG standpoint
SHE
Third-Party ESG data
3 gender equality matrix
Large Cap US public companies
Return standpoint
VS.
ES G vs . Ret u r n ?

12. 03/19/2008 –
03/20/2018
SHE GE
Return 19.9% 14.34%
Volatility 21.0% 21.36%
Sharpe Ratio 0.83 0.67
VaR(5%) 1.9% 1.9%
ES(5%) 3.2% 3.3%
07/01/2008 –
02/01/2009
SHE GE
Return -29.6% -41.75%
Volatility 51.76% 55.12%
Sharpe Ratio -0.64 -0.76
VaR(5%) 5.7% 5.6%
ES(5%) 7.0% 7.7%

13. A s a n ES G i nve sto r
E m b ra c e Wo m e n Powe r !
Negative Correlation with MSFT: -0.03
Sharpe Ratio of new portfolio: 0.06
GE
Public source ESG data
19 gender equality matrix
Global public companies
ESG standpoint
SHE
Third-Party ESG data
3 gender equality matrix
Large Cap US public companies
Return standpoint

14. Thank you so much