American Depository Receipts Sherry Chen Andrew Frankel Christina Nitz Jean Yu NYFC Partners February 27, 2002

Agenda ADR Basics Hypothesis Methodology Data Set Regression Results Concluding Remarks Future Research Topics

ADR Basics Generally represent a non-U.S. company’s publicly traded equity Overcome many inherent operational and custodial hurtles of international investing Growth of the market primarily driven by institutional investors 75% of U.S. institutional investors own ADRs

Hypothesis Abnormal ADR trading volume possesses predictive power for associated index returns due to the fact that ADRs are primarily invested in by more sophisticated institutional investors

Regression Methodology Moving Average Over Past Twelve Months Dependent variable Country return Independent variable Monthly ADR volume minus past twelve month average trading volume

Regression Methodology Residuals Against S&P 500 Trading Volume First Regression Dependent variable –ADR trading volume Independent variable –S&P 500 trading volume Second Regression Dependent variable –Country return Independent variable –Residuals of first regression

Data Set 17 countries –7 developing –10 developed Pulled all available data from 1970 through ADR issues selected Source: Data Stream and Compustat

Regression Results

Abnormal Trading Over Twelve Month Moving Average

Abnormal Trading Over S&P 500 Index

3% 23% 2% 57% 27% 9% 17% 84% 40% 30% 79% 70% 14% 85% 19% 60% 77% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Argentina Brazil Chile China India Mexico South Africa Australia France Germany Ireland Italy Japan Netherlands Spain Switzerland United Kingdom P-Value of ADR Trading Volume Developing CountriesDeveloped Countries

Concluding Remarks Abnormal ADR trading does posses predictive power for index returns in some markets. The predictive power is more predominant for developing countries than developed countries. One possible explanation of our observation is that developing markets are less transparent.

Future Research Topics Future research might include: –Data refinement –Multi-variant regression –Out of sample testing