Charlie Munger says, "always invert." Warren Buffet asks "..and then what?" Profoundly powerful tools. It could be argued one of the things leading to the current crisis was a lack of imagination in risk control and value. Unfortunately in banking imagination typically shows up around compensation package structures or fraud.
While the quants at banks and ratings agencies built correlation models, added their lemmas and tweaked their Garches, the hustlers of the world ran like wild with the free money that the models said wasn't free. Read Janet Tavakoli's excellent book to learn more about that.
In march 2008 when the dow was at 12,000 I posted an article hinting that US equities seemed high and fair value was closer to 8,800. The argument was put forward in terms of Price to Earnings ratios and required a bit of work to understand for many. In 2008 as an associate portfolio manager I returned 19.8% with a 1.02 Sharpe ratio and am now looking for a larger PM role.
The market now looks more fairly priced if one assumes earnings estimates today reflect the future. But, a downward estimate of earnings indicates that S&P 500 below 500 and DJIA below 5,000 are within the normal range of trading possibilities sometime in the next 2-3 years.
PHaT(Priced w/Historical Attributes)charts
Due to over familiarity with recent market levels, people's anchoring bias means that thinking in terms of history objectively becomes challenging. This problem is due to 2 psychological flaws.
- Price relevance Anchoring. Because we are used to seeing price in a relative way, ie. DJIA at 8,000 etc. it is difficult for us to internalize relative values such as 30% mispricing based on historical yield. The human mind is poor at absolute values, but great at relative values. Think about when you travel abroad, you always think in terms of home currency as the relative price. If you live in the US the difficulties in the metric system mean you are constantly converting back to "understand/internalize" the metric values put forward. In the English Imperial system, many are challenged to think about their own weight in anything but the Stone system even though everything else is in pounds for them. Internalizing another relative value metric system takes time. Few think about equity yields, it a price game.
- Recency bias. Because we just experienced something or have experienced it multiple times in the recent past we believe it to be the appropriate metric and to reflect truth. This is Taleb's fed turkey model, or the concept of thinking your house is worth close to what you just paid for it. Value investors work at overcoming this by constantly trying to separate price and intrinsic value.
To overcome theses 2 biases and provide a useful tool for equity valuation at the market level, one can create a chart of historical price adjusted backwards by another attribute such as the historical PE ratio what I call a PHaT chart. The 2 charts above are for the S&P 500 and DJIA using a recent earnings forecast of $50 for the forward S&P 500 and then adjusting the price back in time based on the variance from historical PE ratio. The show the median and 1 standard deviation from current price based on historical yield. Typical variance assuming a static earnings environment could see trading down to 4,400 for the dow and below 500 for the S&P 500. If the longer term earnings outlook declines, the price range shift down as well. You can download the tool and play with your own assumptions by moving the sliding bar. and putting in the most recent price for the Dow and S&P 500.
Data visualization often uses the reverse technique. Think of 2 variables scaled to 100 at some fixed point in the past and then plotted to the current point to show divergence from a scaled growth perspective. The PHaT (Price w/Historical Attribute) graph plots historical price using the most recent price as the scale point. This can be done with any variable set and helps understand relative value, beyond price. If you are an engineer think of it as similar to regressive transform.
Once the end users wrap their imaginations around the PHaT chart it becomes easier to use their inbuilt recency bias and Price anchoring to understand what things look like from a historical perspective.
Feel free to use the excel data and tool here, derived from Robert Shiller's work on a CC Non-commercial with Attributions basis. Use it for free and tell them Nick Gogerty built it.
PHaT graph by Nick Gogerty is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.
Permissions beyond the scope of this license may be available at http://www.gogerty.com.
