I have just finished leasing a discussion amongst strategic macro hedge fund managers about the concepts of diversification and conviction in managing a portfolio.
Traditional quants in fund management will build models to predict returns over a given horizon say 6 months.
Traditional quants in fund management will build models to predict returns over a given horizon say 6 months.
They will also predict risk of each asset class and the inter-relationships between the asset classes.
Then they employ a risk model to determine the likely worst outcome for any given set of percentage asset allocations
Then they employ a risk model to determine the likely worst outcome for any given set of percentage asset allocations
An efficient allocation is one which maximises the predicted return for given level of risk (say likelihood of an excessive drawdown)
By deciding how much drawdown can be tolerated, the produce a target allocation and move the portfolio towards it, recognising that because
By deciding how much drawdown can be tolerated, the produce a target allocation and move the portfolio towards it, recognising that because
of changing predictions of return and market moves, the target allocation is never static.
This works for well behaved assets with similar ranges of predicted returns and symmetric risks
But it doesn't work for #BTC . And in the next set of tweets I will explain why....
This works for well behaved assets with similar ranges of predicted returns and symmetric risks
But it doesn't work for #BTC . And in the next set of tweets I will explain why....
and why it's a problem for macro-land
• • •
Missing some Tweet in this thread? You can try to
force a refresh
