February 23, 2020

The ValueTiming approach provides a possible causal relationship going from policy changes to the relative performance of different asset classes. However, explaining the past does not mean that one can forecast the future. There is on simple way to test whether a framework, such as ValueTiming, can on average deliver a performance that exceeds the GME benchmark in a statistically significant way. It is a two-step process. First, our quantitative model estimates the probability that one asset class will outperform another. Second, we tilt the asset class benchmark allocation in direct proportion to the probability estimates. Over the last two decades we have been publishing on a quarterly basis the result of the process. Each quarter we report the asset allocation recommended by the LJE process and compute the performance of the portfolio during the previous quarter. We have kept a record of the performance. The response we always got when reporting these numbers is that this was a paper track record. Then about 10 years ago we decided to put our money where our mouth was and began implementing the ValueTiming strategy in order to develop a true track record.

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