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How to solve this, you can generate random portfolios based on constraints see method="random" in optimize.portfolio in PortfolioAnalytics in R See (1) as those would solve the above, however you do not have an objective function so ANY solution that meets your constraints would be accepted, see below for examples of objective functions as they would give ...


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I have found the slides from Yollin very useful for portfolio optimization using R such as mean-variance, max-sharpe ratio portfolio etc. http://www.rinfinance.com/RinFinance2009/presentations/yollin_slides.pdf Also, there are some packages in R for this such as $PortfolioAnalytics$ I believe : http://www.rinfinance.com/agenda/2014/workshop/RossBennett.pdf ...


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I'll assume the rest of the world doesn't have access to a similar oracle. Indeed if it did future returns would converge to the risk free rate instantly. In this case, I would prefer holding the AAA bond instead of the stock because the rest of the world would consider it to be much less risky. As a financial institution, reducing the risk of your ...


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Maybe I'm missing the tricky part of this trick question: If the device is 100% accurate it doesn't matter as both will yield 5% with certainty. This is the same unless you want to take into account coupons or dividends.


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Here is a guide by morningstar: " A step by step guide to the black litterman model" https://corporate.morningstar.com/ib/documents/MethodologyDocuments/IBBAssociates/BlackLitterman.pdf


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I would distinguish between Bayesian inference versus Bayesian portfolio management techniques. Inference includes estimating parameters and credible intervals (the Bayesian version of confidence intervals, which are actually far more intuitive) and forecast. If you want to learn about Bayesian inference, get a solid foundation in frequentist methods ...



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