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I am very happy with the following equivalent formulation for the risk budgeting problem (as presented in Bruder, Roncalli, 2012, Managing Risk Exposures using the Risk Budgeting Apporach): Let $b_i$, $\Sigma_{i=1}^n b_i =1$ be the risk budgets, $y_i$ the unscaled portfolio weights and $S$ the variance covariance matrix and $c$ arbitrary. $$ y^* = ...


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Backtesting on a past realization does not provide any meaningful "estimate", as the variance of the "estimate" would be undefined. More meaningful would be to make distributional assumptions and get estimates through extensive Monte Carlo simulations. Clearly, the estimates that you get would be "meaningful" under your specific distributional assumption, ...


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This sounds like risk parity to me. For example, instead of a traditional portfolio of 60% equity + 40% fixed income, you'd allocated 50% of ex-ante risk to equity and 50% of ex-ante risk to fixed income. This strategy is extremely well studied. Just google "risk parity" and you'll find a lot of literature.


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In general, Absolute Return is from pure price appreciation, Total Return includes all related asset cashflows (dividends, coupons etc.) aswell. According to the ESMA document, it has nothing to do with that: A Total Return Fund is a fund with a return target to be achieved at smallest possible (but unbounded) risk, an Absolute Return Fund has a Risk (VaR) ...



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