Risk and multi-asset investing
How is risk measured and how do investors respond to losses? What is standard deviation really telling us, and can volatility really be managed? Besides, we can’t forecast the future… can we? In this series, we review investment research to provide some answers to these questions.
Risk measures and loss aversion
What are the common ways of measuring risk in the investment industry, and what are their strengths and weaknesses? In this session we review the usage of both relative measures (tracking error) and absolute measures (volatility). We put this into context by looking at historical data on some of the major asset classes. Finally, we review psychological research on the extent to which investors feel the pain of losses relative to gains.
Portfolio theory and volatility
Portfolio theory is often talked about as an exact science, but in practice is heavily reliant on its inputs. In this session we examine these inputs with a particular focus on correlation coefficients and real world data. Finally, we review how volatility targeting can be modelled on these approaches.
Long term predictability of returns
Are long term investment returns predictable? There remains much debate on this issue. In this module we look at some differing viewpoints, with a particular focus on the extent to which historical equity returns have been a reliable predictor of future returns. Finally we review some metrics used in assessing where long term value may exist.
Understanding the Information Ratio
Is your manager outperformıng theır benchmark? And how much rısk are they takıng ın doıng so? Ideally managers want to generate as much return as possıble for any gıven level of rısk. In one number, the ınformatıon ratıo tells you the abılıty of a manager to successfully generate rısk-adjusted returns. In thıs sessıon we explore the factors that drıve the ratıo