Forecasting Bridgewater All Weather Performance in November’s Bond Storm

We use Bridgewater All Weather, one of the largest hedge funds, to illustrate how to quantitative techniques could provide investors with a more dynamic understanding of the potential fund behavior intra-month using only monthly fund data.

December 06, 2016

November’s government bond sell-off resulted in one of the sharpest increases in Treasury yields in recent history and an uptick in fixed income volatility. While this may be particularly bad news for traditional fixed income funds, risk parity funds should, in theory anyway and to the extent that other asset classes have held their ground, be able to weather such a downturn without major losses.

While the returns of mutual funds employing a risk parity strategy are available on a daily basis, Bridgewater All Weather, the largest risk parity fund in terms of AUM with a reported $70 billion, typically only makes returns available on a monthly basis with a lag following the month’s end. Given the limited public availability of asset class and/or region concentration – and scant information on tactical decisions that drive risk and asset allocation – associated with typically opaque hedge fund reporting, it becomes very hard for investors in risk parity funds to reconcile ongoing market moves with realized returns. While looking at risk parity funds or a 60/40 portfolio can provide guidance, the range of returns observed may be too wide for investors seeking timely month end or intra-month insights into risk parity hedge fund performance. For example, during the month of November, risk parity mutual funds, which report performance daily, lost between -0.47% and -3.62%, while a 60/40 portfolio (60% S&P 500 Index / 40% Bloomberg Barclays US Aggregate Bond Index) experienced a 1.25% gain.

In an effort to provide investors and consultants with a more dynamic understanding of the potential behavior in the largest risk parity vehicle, we employ surveillance methods using MPI’s proprietary analytics and an award-winning technique aimed at providing estimates of daily hedge fund performance using monthly data.

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