Watch what they do, not just what they say

Preface: Explaining our market timing models
We maintain several market timing models, each with differing time horizons. The "Ultimate Market Timing Model" is a long-term market timing model based on the research outlined in our post, Building the ultimate market timing model. This model tends to generate only a handful of signals each decade.

The Trend Model is an asset allocation model which applies trend following principles based on the inputs of global stock and commodity price. This model has a shorter time horizon and tends to turn over about 4-6 times a year. In essence, it seeks to answer the question, "Is the trend in the global economy expansion (bullish) or contraction (bearish)?"

My inner trader uses the trading component of the Trend Model to look for changes in the direction of the main Trend Model signal. A bullish Trend Model signal that gets less bullish is a trading "sell" signal. Conversely, a bearish Trend Model signal that gets less bearish is a trading "buy" signal. The history of actual out-of-sample (not backtested) signals of the trading model are shown by the arrows in the chart below. Past trading of the trading model has shown turnover rates of about 200% per month.

The latest signals of each model are as follows:

• Ultimate market timing model: Buy equities*
• Trend Model signal: Risk-on*
• Trading model: Bearish*

* The performance chart and model readings have been delayed by a week out of respect to our paying subscribers.

Update schedule: I generally update model readings on my site on weekends and tweet mid-week observations at @humblestudent. Subscribers will also receive email notices of any changes in my trading portfolio.



Great expectations
Bloomberg recently highlighted the huge gap between expectations and reality. As the chart below shows, soft (expectations) data has been surging, but hard (actual) data has risen, but it has not caught up with expectations.

The markets are pricing for perfection, which sets up a situation where minor disappointments could spark a market sell-off. BCA Research found that such divergences between "soft" expectations data and "hard" economic data has seen equity corrections in the past.

This week, I examine the details of how expectations have diverged from actual data on a number of dimensions.

• Small business confidence
• Corporate confidence
• Consumer confidence
• Federal reserve expectations
• Wall Street's tax reform expectations

The full post can be found at our new site here.