manhapf

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    • Tue Mar 25th 18:53 PM | Rating: 0 0
      Commented on:
      Fixing Target Date Strategies: 'Target Date Folios'
      Wow! Very well written article Geoff! Concise, comprehensive and persuasive.
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    • Wed Mar 12th 15:53 PM | Rating: 0 0
      Commented on:
      Using Default Risk to Limit Downside in Individual Stock Investing
      Also, in addition to a future article about QPP suggesting future Moody's downgrades, is it a valid presumption that AXP might enjoy a Moody's upgrade in the next 3 years according to the QPP projections?
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    • Wed Mar 12th 15:45 PM | Rating: 0 0
      Commented on:
      Using Default Risk to Limit Downside in Individual Stock Investing
      Realized my mistake, baa1 is a better risk than baa3; the reverse sort in the last graph threw me...
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    • Wed Mar 12th 15:02 PM | Rating: 0 0
      Commented on:
      Using Default Risk to Limit Downside in Individual Stock Investing
      I found the article useful as a QPP user as another criteria to use while filtering stock selections. One question though, wouldn't C be a better risk selection assuming all other things being equal?
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    • Fri Dec 28th 08:20 AM | Rating: 0 0
      Commented on:
      The Do-It-Yourself Market-Neutral Portfolio
      Hello Geoff,

      Thanks for your software and articles; they've been insightful and helpful. I've been interested in portfolio asset allocation for many years and am a user of some complex software tools; love QPP's format, nicely done! I've been trial using your software and have some questions/observations...

      Rebalancing/Optimizati... of Allocations:
      One of the implementation details in using QPP is when to future adjust and at what frequency the 'final' asset/security allocations? At present, you either define an allocation weighting of equal or some proportion that 'suits' the investor's preferences for risk/return ideally based on empirical knowledge; eg, 70% equities/30% bonds.

      I'm not a fan of software optimization in general as applied to portfolio allocations, I'm quite familiar with the pitfalls and the bad results that typically are produced from even excellent out-of-sample and supposedly robust models. However, since with QPP we're using monte carlo simulations of forward looking return possibilities and 'experimenting' with various assets/security combinations/allocatio... weightings anyways, there is a temptation to use Excel's built-in Solver tool to optimizatize. For example, we can maximize the forward returns by modifying the asset/security allocation weights constrained by the forward looking standard deviation for example.

      Ideally, the optimized forward returns/SD yield the best weights and are robust in the sense that they deliver similar optimized/simulated results compared to the historical results over 1, 3 & 5 year time horizons; would you consider longer time horizons? I've attached a before/after example using your market-neutral article to demonstrate the effect of optimizing the allocation weights which appears quite compelling since it also improves on the portfolio beta and diversification values.

      So, what frequency of re-running the simulations to adjust the allocation weightings do you normally recommend once they're established to ensure the expected return/SD results are still meaningful; annually? What's your opinion of optimizing the weightings in this manner?

      Disclaimers:
      1) To what index is Beta used to capture correlation; am assuming S&P500, but should be stated.
      3) Based on research I've done, asset/security returns are not normally distributed. I realize that this makes the programming/math easier, but this is an area that could be improved and make QPP a more valuable tool and one that I'd be willing to pay more for!
      6) Based on your articles, I assume that this refers to the 1:1 relationship normally displayed between returns and standard deviation; is this correct?

      Thanks much for your time and consideration of my questions/observations...

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    • Thu Nov 15th 18:14 PM | Rating: 0 0
      Commented on:
      Getting the Most Return For Your Risk, Part 2
      Geoff,

      Really good articles; very thought provoking which I've been following for a while. In your 'do it yourself market neutral portfolio' you're able to do better than the 1:1 return:risk performance and still provide the benefits associated with a diversified portfolio of various assets; so, does this conflict your premise in 'getting the most return for your risk2' article?

      Also, you cleverly base your QPP projections on forward-looking projections. When it comes to determining which asset classes and associated weights to include in a diversified, non-correlated portfolio, are you saying that the weights are altered based on their forward looking projections to maintain the 1:1 performance or are the classes and weights constant once you've determined them? If not, how often to you look ahead and rebalance the portfolio accordingly?

      Thanks much,
      Pete
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