1. Abdullah Al-Ashi Jungha Woo Muna Albasman Talha Yasin

2.  The disposition effect implies that stock pri ces under-react to bad news when more c urrent holders are facing a capital loss, an d under-react to good news when more cu rrent holders are facing a capital gain.  Leads to return predictability.

3. Test Data (WRDS) CARCAR, G_t IF CAR > 0 Bad newsGood news Perform trading strategies to test hypothesis PEAD, monthly alphas Overhang Spread and Negative Overhang Spread Monthly Alphas by Overhang Spread Alphas and Factor Loading YesNo

4. Progress  SAS  Learning and getting comfortable with the SAS command line interface as web interface not adequate for merging/linking tables and calculations etc.  Major data processing done in SAS using different procedures like SQL, SAS Interactive Matrix Language (IML)  Computing Cumulative Abnormal Returns (CAR)  Get the relevant data and compute the values for some famous stocks  Computing Capital Gains Overhand (Gt)  Computed using the mutual fund holdings for some subset of stocks/MFs  Details follow

5.  A measure of the earning news surprises, calculated around the most recent earnings announcement date  where r h is the stock return on day h, with  the earnings announcement date being at h= 0, and‾r i,h is the CRSP equally weighted NYSE/AMEX/NASDAQ index.

6.  Extracting the following from WRDS:  Earning released dates under COMPUSTAT-Fundam ental Quarterly dataset for every company identifie d by GVKEY  Daily return values under CRSP-dsf (daily stock file) for every company identified by PERMNO  PERMNO-GVKEY merged link table under CCM data set  S&P 500 index daily returns

8.  A means of quantifying the FIFO ‘mental accounti ng’ at anchor points  Defined as the percentage deviation of the aggre gate cost basis from the current price.

9.  where Vt,t−n is the number of shares purchased at date t −n that are still held by the original purchaser at date t  Pt is the stock price at the end of the month t  φ is a normalizing constant

10.  Shows aggregate holdings for a group of mutual f unds of a particular stock(MSFT) over time Volume vector with time t-8t-7t-6t-5t-4t-3t-2t-1t Volume Quarter186600 000000 Quarter2152400 89000 0 Quarter3100000 99000 Quarter4000000000 Quarter5000000000 Quarter6000000000 Quarter7000000000 Quarter8000000000 Quarter9000000000 Quarter10000000000 Quarter110311000 Quarter12000000000 Quarter13000000000 Quarter14000000000 Quarter15000000000 Quarter16000000000 Quarter170000000550000

11.  If positive, investor is in gains  If negative, investor has unrealized loss  Thus, efficient way to guess his mental account  Need to know the mutual fund holdings of stocks at particular dates(quarterly data available)  We are getting the data from the CRSP mutual fu nd database which is from 2003 onwards.

13. Next Steps  Sanity checks on CAR and Gt  Integration of code and calculation of CAR and Gt over all the available data set  Implementing the rolling portfolios in SAS  Calculation of returns and alphas to test the hypothesis