On Predicting the Future

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On Predicting the Future

I’ve long admired ECRI for their timely and accurate forecasts, and their willingness to stick by their models when things don’t seem to be immediately going their way.  I have also appreciated their lack of willingness to divulge their model elements; my thoughts were, “Hey, it’s probably a simple model that no one has ever thought of.  Would I reveal the model if I were in their shoes.  No.”

But I’m not in their shoes, and I know one of the ECRI pair, so I asked for some insight into the models, which he coldly refused.  Okay, fair enough, I’m not a paying subscriber, but we had had good conversations in the past, so I thought I might have some relational capital, but no.

Tonight, I bring you my kludge that should be close to the ECRI Weekly leading index.  I am not saying that I reverse-engineered it because in econometrics there may be many fits with equal probability that explain the dependent variable well.  But here we go.

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Yesterday, I read a post at the Bonddad Blog that said it had all of the variables for ECRI’s Weekly Leading Index.  I decided to gather the data, or reasonable proxies of it, and I ended up using the following variables to estimate the ECRI WLI:

  1. M2 YOY % increase, SA
  2. AAA yields from Moody’s
  3. BAA yields from Moody’s
  4. S&P 500 price YOY % increase
  5. Initial Jobless Claims SA
  6. Real Estate Loans from all Commercial Banks, SA YOY % increase
  7. PPI for Industrial Commodities

I realized the the independent variables had to go up and down because the WLI does as well.  I normalized the variables against their long run averages, which would have no impact on the fit if the regression, but would enable sorting out the size effects.  Anyway here are the results:

That’s a really high R-squared (normalized F), with highly significant t-coefficients.  What is more, the coefficients sum to materially one in this regression that constrains the intercept to zero.

So, we have a good guess at what drives the ECRI WLI: two items, Corporate interest rates and industrial commodity prices.  The other items are significant, but less material.   BAA bond yields could be expressed as spreads against AAA yields, but the mathematical results would be the same.

So how does my model fit against the ECRI WLI:

If anything, my estimated model is more sensitive than ECRI’s model.  I could have a new business here, except that I have given the model away for free.

Comments are welcome.

M2 AAA BAA S&P 500 ICSA WREALLN PPI-IC

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David J. Merkel, CFA, FSA — 2010-present, I am working on setting up my own equity asset management shop, tentatively called Aleph Investments. It is possible that I might do a joint venture with someone else if we can do more together than separately. From 2008-2010, I was the Chief Economist and Director of Research of Finacorp Securities. I did a many things for Finacorp, mainly research and analysis on a wide variety of fixed income and equity securities, and trading strategies. Until 2007, I was a senior investment analyst at Hovde Capital, responsible for analysis and valuation of investment opportunities for the FIP funds, particularly of companies in the insurance industry. I also managed the internal profit sharing and charitable endowment monies of the firm. From 2003-2007, I was a leading commentator at the investment website RealMoney.com. Back in 2003, after several years of correspondence, James Cramer invited me to write for the site, and I wrote for RealMoney on equity and bond portfolio management, macroeconomics, derivatives, quantitative strategies, insurance issues, corporate governance, etc. My specialty is looking at the interlinkages in the markets in order to understand individual markets better. I no longer contribute to RealMoney; I scaled it back because my work duties have gotten larger, and I began this blog to develop a distinct voice with a wider distribution. After three-plus year of operation, I believe I have achieved that. Prior to joining Hovde in 2003, I managed corporate bonds for Dwight Asset Management. In 1998, I joined the Mount Washington Investment Group as the Mortgage Bond and Asset Liability manager after working with Provident Mutual, AIG and Pacific Standard Life. My background as a life actuary has given me a different perspective on investing. How do you earn money without taking undue risk? How do you convey ideas about investing while showing a proper level of uncertainty on the likelihood of success? How do the various markets fit together, telling us us a broader story than any single piece? These are the themes that I will deal with in this blog. I hold bachelor’s and master’s degrees from Johns Hopkins University. In my spare time, I take care of our eight children with my wonderful wife Ruth.

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