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Question 1 (how to set asset level risk budgets as well as portfolio level target volatility) is discussed in Modern Portfolio Optimization by Bernd Scherer and Douglas Martin in section 3.1.1 on risk budgeting constraints. They set upper and lower bounds for their risk budget constraints in a mean variance optimization. The recent work by James Sefton, ...

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Actually, neither of your two results are quite correct. As explained in the Details for the Return.calculate function, most of the PerformanceAnalytics functions use discrete returns, not log returns. To get the correct results, you will have to convert your data from log returns to simple returns. Compare the charts from the following: ...

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Black Litterman might be a good solution to your problem, since it suffers less from corner solutions (concentrated portfolios). You already have active views in the form of return expectations, and you can control the confidence in your views explicitly; see for example Meucci's Risk and Asset Allocation chapter 9.2 for a description. Since you have a ...

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First the easy solution: Define the continuous weights of each asset: $w_i \in [0,1],i=1,\ldots,N$ and choose some meaningful lower bound for each weight. Then you have the objective $$w\mu - \lambda w^T \Sigma w \rightarrow Max,$$ all your constraints that you already apply and the additional (linear/box) constraint $$w_i \ge l, i=1,\ldots,N.$$ ...

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I think the model you are presenting is trying to capture the pro-forma performance of a collection of stocks. However, it is not that 'flexible' and is accurate if: You are fully invested throughout the time window you are considering You do not place new trades during this time window A portfolio value is simply the sum of your assets, so at time $t$ ...

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