Volatility dollars
Any insights on volatility dollars for GMV at MMs? Heard Balyasny talk about it on a podcast, but would appreciate any more color
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Based on the most helpful WSO content, here are some insights on volatility dollars for GMV at multi-manager (MM) hedge funds:
Risk vs. AUM: Most MMs think in terms of risk rather than assets under management (AUM). When the market is more volatile, the risk is higher, and consequently, the AUM is lower. In a normal environment (VIX 20), an average pod at a top MM is probably working with $1.5 billion or more.
GMV Allocation: Sometimes a pod has access to a larger amount, such as $2 billion, but often there aren't enough ideas to deploy the full amount. This results in an average gross market value (GMV) over a year being around $1.5 billion, which helps smooth out volatility.
Leveraging Allocations: If a pod is allocated $250 million, it can potentially be levered up to $1 billion. However, it's important to note whether the allocation is already levered, as this affects the returns made on the initial $250 million.
These points should provide a clearer understanding of how volatility dollars and GMV are managed at MMs.
Sources: Performance of the best PM’s at MM’s?, Are we at peak pod shop?, Volatility -- good for S&T bonuses?, MM to SM is it possible, Finishing 1st Year as HF Analyst - Ask Anything
When MM funds allocates to a PM they give him an amount (let’s say USD 200m) with expectations that he trades at a particular annualized vol.. let’s say 5-10%. This translate into USD 10-20m of annualized volatility.
In other worlds it’s a way to translate fund annualized target volatility ( assuming they have one) into how much money they give to a PM to run they own strategy. Fund have incentives to have PMs always investing/trading, while PMs would prefer to run higher vol when there are opportunities and don’t trade or trade small amounts when there are no opportunities and this is often matter of discussion.
Long story short is a way to translate fund size and fund annualized volatility into USD allocation to a PM and its expected volatility (both in % and in USD).
The hard limits / stops are measured in terms of drawdown, but it’s initially easier to communicate an expected volatility as measure of risk to be taken by a PM as max DD is super difficult to estimate ahead particularly with high sharpe and negative skew strategies that often MM funds prefer.
The fact that BAM has only recently realized that it's important to measure performance in terms of annual volatility and pitching it as some type of differentiator among their peers likely explains why they are perennially at the bottom of MM performance lists
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