Using out-of-sample forecast error in portfolio optimization

 

 

Speaker: Konark Saxena, UNSW

 

Portfolio optimization usually struggles in realistic out of sample contexts. We de-construct this stylized fact comparing historical estimates of the inputs of portfolio optimization with their subsequent out of sample counterparts. We confirm that historical forecasts are often very imprecise guides of subsequent values but also find this lack of persistence varies significantly both across inputs and sets of assets. The resulting forecast errors are not entirely random. They have predictable patterns and can be partially reduced using their own history. Correcting inputs using past forecast errors results in portfolio performance that reinforces the case for optimization versus naive allocation rules. 

 

A light lunch will be provided at 1 p.m. Please RSVP for catering purposes to Mala Kapahi by 12 noon on Monday 4th June 2018.

 

Time: 12.00 – 1.00 p.m.

Venue: University of Technology, Sydney

             Building 8, Room 8.002, Dr Chau Chak Wing Building
             Dr Chau Chak Wing Building

            14 - 28 Ultimo Road, Ultimo

 

 

Enquiries: Mala Kapahi (Ph: +61 2 9514 7777