Here are some things I think I am thinking about.

1 . Wall Street’s Biggest Lie. Jason Zweig had a piece earlier this week that I highly recommend. There are a number of good nuggets in there. He also refers to “The big lie on Wall Street” being the promise that advisors or portfolio managers can conjure the returns needed to meet your financial goals. This is a version of promising higher returns than most managers or advisors are actually capable of generating. After all, the markets generate the return they return, not the return we want.

I’d phrase his “big lie” a bit more bluntly. Wall Street sells you the dream of high returns in exchange for high fees. Often times the higher the fee the bigger the dream. If you see someone promising “market beating” returns you should immediately be skeptical. If they’re charging you more than 1.5% for that return you should probably run, not walk, in the other direction.

2. Philip Tetlock says we are all forecasters. This was a very good interview from Shane Parrish with Philip Tetlock who wrote the popular new book Superforecasters. Tetlock says “we are all forecasters”. He elaborates by highlighting that the most important aspect of being a super forecaster is the commitment to understanding probability analysis.

This is essentially what I was writing about the other day on the topic of forecasting. It’s become very fashionable these days to bash forecasters.  Especially with all the automation that is coming to the world. But as Tetlock notes, it’s impossible to make decisions about the future without building implicit forecasts. Tetlock found that the best forecasters don’t just understand this, but embrace it in their probabilistic models of the world. I couldn’t agree more.

3. Economists suck at investing, or do they? Noah Smith discusses a very good point over at Bloomberg about how economists tend to be very bad investors. I think Noah is being too hard on his fellow economists. Yes, there have been some high profile blow-ups at firms run by economists.  But a few high profile disasters are hardly a valid data set from which to generate conclusions.