| |The latest performance numbers for Ivy League endowments have been nicely displayed in the chart below along with the 60/40 stock/bond portfolio. Since the development of the “endowment” model associated with Yale and the attention on Harvard, the largest endowment, there has been an unusual focus on these funds. There is a fair amount of dispersion between the best and worst managers in the group … Read more Ivy League Performance – Competing With Top Tier Endowments Can Be Done
| |Implied volatility is usually higher than realized volatility so there is a positive volatility risk premium, except when there is a crisis or volatility spike at which time the volatility premium turns negative. A recent CBOE seminar presented a chart on the volatility premium to illustrate the risk. … Read more Being Short Volatility is Risky in a Crisis – Do You Know Your Volatility Premium Exposure?
| |Investors should be concerned about the unintended behavior from low volatility. Low volatility will lead to higher volatility in the future when investors become complacent about risk, the “Volatility Paradox”. This paradox has been discussed by Richard Bookstaber as early as 2011 and recently referred to in a post on his blog, Our low risk (low volatility) world … Read more The Growing Danger from a Market that is Complacent of Risk – A Variation on Minksy
| |Dan Fuss, the Loomis Sayles bond guru, has been working in fixed income for decades. He has developed a set of four “P’s” with central bank behavior for looking at the macro fixed income environment and his read is suggesting that caution should be applied to any forecast that believes bonds are safe. … Read more Dan Fuss’s 4 “P’s” for Global Fixed Income – Watch Out If You Are a Bond Holder
| |And not only the pride of intellect, but the stupidity of intellect. And, above all, the dishonesty, yes, the dishonesty of intellect. Yes, indeed, the dishonesty and trickery of intellect. -Leo Tolstoy … Read more Are You Honest With Your Investment Intellect? Avoid Biases and Follow the Data
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