creator Li, Tingting advisor Cooper, Ricky This research develops a portfolio volatility forecasting method for absolute return equity strategies with consideration of managers’ investment skills. Besides the portfolio holdings and prices that are commonly used by existing volatility forecast methodologies, the method proposed in this research takes account of investment skills and their volatility attribution. Investment skills are indicated by decisions of constructing portfolio overtime. Portfolio volatility is attributed to investment decisions through use of decision-based performance attribution model. It is shown that tracking the information contained in the time series of investment decision attribution leads to better volatility forecasts than commonly used forecasting methods which directly use returns and holdings. The forecasting method proposed has advantage of explaining risk forecast in terms of actual investment decisions, and changes to those decisions in real time. Submitted by Erma Thomas (thomase@iit.edu) on 2016-07-14T21:00:41Z No. of bitstreams: 1 etdadmin_upload_409450.zip: 460820 bytes, checksum: e9bd1a66df567718ef836f9e8cbfcc3e (MD5) Made available in DSpace on 2016-07-14T21:00:41Z (GMT). No. of bitstreams: 1 etdadmin_upload_409450.zip: 460820 bytes, checksum: e9bd1a66df567718ef836f9e8cbfcc3e (MD5) Previous issue date: 2016-05 Ph.D. in Management Science, May 2016 2016 2016-05 http://hdl.handle.net/10560/3837 en decision-based attribution Heterogeneous Autoregressive model manager investment skill portfolio construction portfolio volatility forecast realized volatility Dissertation born digital application/pdf In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access SSB / Stuart School of Business Illinois Institute of Technology Affiliated department