Mebane, love your work and look forward to receiving your book!
Quick question... using the SMA strategy works great when you have relatively few investment options in your portfolio, but how do you handle rebalancing with 10+ positions?
Let's say I build a portfolio that uses sector ETFs and has 10 equity positions, 10% each. If I use the SMA strategy to move in and out of classes, how would someone go about rebalancing such a portfolio when some positions are naturally going to be in cash, and other positions are going to be riding strong momentum?
For example, if 1 of those positions is still showing "hold" status, but now has grown to 15% of the portfolio, do you wait until a sell to cash to rebalance the position or simply ignore rebalancing altogether?
Mebane, love your work and look forward to getting your book!
Question, when using your SMA strategy, what if you use individual sectors (ETFs primarily)? How would you rebalance such a portfolio?
I guess this would be the same question if you were using individual stocks. Let's say I have 10 stocks that comprise 10% of the portfolio each. If the SMA trend calls for 3 of these stocks to liquidate to cash, and I let the other 7 ride the momentum, when 1 of these cash positions says to get back in, how do I determine the amount of that position?
It seems the SMA strategy works when you have just a few investments (SPY, QQQQ, a REIT, etc) but gets quite complicated when handling a 10-15 security portfolio.
Would you say, then, that reducing volatility as measured by standard deviation, by default reduces risk as measured by downside deviation?
If so, constructing a portfolio that maximizes return for risk, as measured by standard deviation, would still be inherently efficient.
In regards to TAA, which the article is about, have you read "A Quantitative Approach to Tactical Asset Allocation" by Mebane T. Faber (it is available on cambriainvestments.com I believe)? Just wondered what you thought of the research.
Geoff, since Vernl brought it up, why does QPP use standard deviation to measure/analyze risk as opposed to downside deviation? It seems to me that an investment that has a high standard deviation but low downside deviation would be quite different than an investment with identical standard deviation but higher downside deviation. If you are using normal distribution of returns, as I believe QPP is, then standard deviation and normal distribution may not paint the most accurate picture. Just curious.
Sort by:
Latest | Highest ratedTiming the Nasdaq Composite [View article]
Timing the Nasdaq Composite [View article]
Quick question... using the SMA strategy works great when you have relatively few investment options in your portfolio, but how do you handle rebalancing with 10+ positions?
Let's say I build a portfolio that uses sector ETFs and has 10 equity positions, 10% each. If I use the SMA strategy to move in and out of classes, how would someone go about rebalancing such a portfolio when some positions are naturally going to be in cash, and other positions are going to be riding strong momentum?
For example, if 1 of those positions is still showing "hold" status, but now has grown to 15% of the portfolio, do you wait until a sell to cash to rebalance the position or simply ignore rebalancing altogether?
Thoughts?
Timing the Nasdaq Composite [View article]
Question, when using your SMA strategy, what if you use individual sectors (ETFs primarily)? How would you rebalance such a portfolio?
I guess this would be the same question if you were using individual stocks. Let's say I have 10 stocks that comprise 10% of the portfolio each. If the SMA trend calls for 3 of these stocks to liquidate to cash, and I let the other 7 ride the momentum, when 1 of these cash positions says to get back in, how do I determine the amount of that position?
It seems the SMA strategy works when you have just a few investments (SPY, QQQQ, a REIT, etc) but gets quite complicated when handling a 10-15 security portfolio.
Thoughts?
Tactical Asset Allocation, Part I [View article]
Would you say, then, that reducing volatility as measured by standard deviation, by default reduces risk as measured by downside deviation?
If so, constructing a portfolio that maximizes return for risk, as measured by standard deviation, would still be inherently efficient.
In regards to TAA, which the article is about, have you read "A Quantitative Approach to Tactical Asset Allocation" by Mebane T. Faber (it is available on cambriainvestments.com I believe)? Just wondered what you thought of the research.
Thanks Again! Keep up the great work!
Tactical Asset Allocation, Part I [View article]