iMarketSignals – improve investment performance

We provide unbiased guidance to market direction. Our models can be classed into following  groups:

  • Leading recession indicators:
    • BCI is a Business Cycle Indicator optimised to identify a looming recession constructed from economic data series.
    • COMP is a recession indicator model constructed by combining third party leading indicators.
  • Buy and Hold investing. These models are macro by nature; trading signals from the models occur infrequently and are un-hedged – one does not have to trade constantly in and out of the markets.
    • MAC-US is a moving average crossover model for the S&P500.
    • MAC-AU is a moving average crossover model for the Australia All Ordinaries Index.
    • BVR is a bond market model based on mathematics alone.
    • Yield-Curve is a trend-following model.
    • GOLD is a rate-of-change trend-following model.
    • SILVER is a rate-of-change trend-following model.
  • Active weekly trading models based on a proprietary ranking system updated each week to generate un-biased and un-hedged buy- and sell-signals.
    • iM-BestX are weekly trading models based on the S&P 500, S&P1500 and Russell 1000 stock index series.
    • iM-Best(SPY-SH) is a market timing model, updated weekly on Sundays for the coming week.
    • iM-Best1(Sector SPDR) is a rotation system for the Select Sector SPDR® ETFs that divide the S&P500 into 9 sectors.
    • iM-Best(SSO-TLT) is a ETF switching system based on market timing.
    • iM-Best Combo3 is a combination model of Best(SPY-SH) + Best1(Sector SPDR) + Best(SSO-TLT), updated weekly on Sundays for the coming week.

The models are updated weekly and the charts depict the state of the various markets. They can be seen by registered/logged-in members.

The models have all been published. Before the models were available on the internet, weekly updates for the IBH, MAC, BVR and Yield-Curve were sent by email to subscribers for about two years – here are some of their comments:


This model and your fine work has been quite remarkable (and profitable). I have been enjoying your observations for quite some time. Job well done.
Edward Chrusciel

Your system looks pretty good. In fact, I was amazed by the high percentage winning trades and the very low drawdowns. I’ve never seen anything like that in a MA system.
Tom Swiatek

Regardless of which version one uses, it’s a powerful system. And it answers one of the most troubling worries that investors have. It efficiently gets them out of harm’s way when the market crashes.
Erik Conley

Thank you for your unique and excellent work. We will appreciate receiving your Modelling updates. Thanks!
Chuck Szkalak

The average investor reads the financial news and thinks that gives him an edge. That only tells him what everyone else knows and is worried about. We follow the excellent work of Georg Vrba, who has a top-rated coincident recession indicator as well as a successful stock/bond asset allocation model. Here is his most recent comment:  “My own composite short leading economic indicator, which has the  highest score of all indicators so far tested, does not support the notion of a recession anytime soon.” I listen to Georg, and you should too.
Jeffrey A. Miller, PhD, President NewArc Investments, Inc.

I took that S&P buy signal of yours with a little $50K futures contract and am very happy thank you.
Dwaine van Vuuren – CEO of PowerStocks

I have read and studied all your articles with interest. I have learned much from your perspectives and will continue to follow your work.
David Hamilton

Thank you for all your outstanding analysis. Let me say that I couldn’t agree more that data beats opinion.
Dave Lincoln

Georg Vrba asks whether the ECRI is still relevant. Great analysis and charts.
Jeffrey A. Miller, PhD, President NewArc Investments, Inc.


I very much liked the write up on your models, and if I may add these have a particular appeal and interest having been developed by a fellow engineer.
Paul Willis

Have seen so many manipulate data to fit their predetermined biases and love the way you methodically deconstructed the moving averages to debunk this one. It shows the difference between intellectual laziness and intellectual rigor which you fit to a tee.
Kuosen Fung, CFP®

Your work is really interesting and I’d love to receive your updates or any other information you publish. I honestly think your results indicate there is a way to time stock and bond market exposure. Most likely people will remain human and many will follow their “gut feel” or let fear or greed override any mathematical analysis. This is why your methods will most likely continue to work.
James Schwartz, CFP®

Georg Vrba, whose excellent work on recession forecasting has helped our readers, has two different market-timing methods. His most recent article explains that the next great bull market might already be here.
Jeffrey A. Miller, PhD, President NewArc Investments, Inc.

… as always love your analysis! Always eager for Friday’s just to receive your reports!
Jose R Barcelo

I agree with your viewpoint that mathematical models provide better guidance to market directions than financial experts. Thanks so much!
C.T. Wu, PhD in EECS

I just read your article on identifying recessions. Great work!
Richard G Greenwald, AAMS, CRPC

I appreciate using math to model financial behaviour and appreciate your good work.
Richard E. Hamrick, CFA®

This time it is perma-bear Albert Edwards warning investors about the “Ultimate Death Cross” taking the S&P 500 back to 666. Georg Vrba takes the analysis even further. He shows that Edwards’ prediction is almost impossible to accomplish if you actually do the math on the moving averages involved. In addition, he demonstrates that the current indicator conditions are actually bullish based on historical data.
Jeffrey A. Miller, PhD, President NewArc Investments, Inc.

I have great respect for your work and am grateful to be included on your list.
Marvin Snyder

I have your historical charts going back and it is great material. I appreciate your insights. Steve Wenstrup


I have been following your work for some time and have been very impressed.
Steve McCarthy, CPA, CFP®

I’m impressed that you provide this much analysis each week. Thank you for your insights. Your charts are beautiful & clear.
Brett Bowman

I am really impressed by your work and liked very much your last research on gold and silver. It’s good to see that you are expanding the scope of possible investments.
Nicolas Tabourdeau

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The iM Minimum Volatility (USMV) – Investor

  • Since the launch of IM-Best12(USMV)Qx (x=1,2,3,or 4) in 2014, these models converged to a combined holding of 18 stocks, thus future performance of each of the models is expected to be very similar.
  • There is not much to be gained by following four similar models and these are now replaced by the iM Min Volatility(USMV)-Investor.
  • This model holds 10 equal weighted stocks and the simulated performance since 1/3/2013 shows an annualized return of 22.0% versus 14.3% for SPY and an annual turnover ratio of 60%
  • As from Sunday 7 July we will disseminate to Gold Subscribers any buy/sell signals this model generates.

Is the Stock Market Overvalued? – Update July 2019, and 10-Year Real Forward Return Estimate

  • The average of S&P 500 for Jun-2019 was 2,890. A 20% decline from this level would bring it to the Jan-2020 level of the long-term trend line.
  • The Shiller Cyclically Adjusted Price to Earnings Ratio (CAPE) is at a relatively high level of 28.9, and the CAPE’s 35-year moving average (MA35) is at 23.9.
  • The CAPE-MA35 ratio is 1.21, forecasting a 10-year annualized real return of 6.2%. This would indicate that for long-term investors the S&P 500 is currently not overvalued.
  • Investing in equities for the long-haul when the CAPE-MA35 ratio is below 1.30 should produce reasonable returns as this level of the ratio does not signifies overvaluation of the market.

The iM-SuperTimer – Simulated on Portfolio 123

  • For a detailed model description of the system please read the original description, update No.1 and update No.2
  • We have transferred the excel data onto Portfolio 123 and will in future be providing signals and performance for the weekly, monthly and 3-month models running on Portfolio 123, all updated weekly.
  • The models’ holdings alternate between ETF (SPY) and ETF (IEF), being proxies for investments during up- and down stock market periods.

A Winning Strategy to Profit from the Seasonal Effect in Equities

  • The seasonal effect that equities do better from November through April is well-known. Here we provide a rigorous statistical test of this and a trading strategy to profits from it.
  • From 1960 the S&P 500 with dividends returned on average 1.92% for the six months May to October, the “bad-periods”, while the “good-periods”, November to April, returned 8.47% on average.
  • Statistics provide a 65% probability that good-periods will produce higher returns than the average of all good- and bad-periods, and a similar probability that the bad-periods will produce lower returns.
  • This anomaly can be exploited by tactically shifting from more aggressive “good-period portfolios” to lower risk portfolios at the end of every April, and reversing the process end of October.
  • Switching accordingly between the S&P 500 and 10-Year Treasuries would have provided an annualized return of 12.1% from 1960 to 2019 versus 9.4% for buy-and-hold the S&P 500.

How Good Are Target-Date Glidepath Savings Programs During the Accumulation Phase Towards Retirement?

  • This study analyzes Yale’s Qualified Default Investment Alternative, a retirement plan with a target-date strategy. The findings also apply in principle to target-date strategy models from Vanguard, Fidelity, and others.
  • Yale University’s new retirement plan provides a “Glidepath” Target-Date Plus Service and also allows participants to opt out from it to pick their own investments from a few select funds.
  • Backtests (1999-2019) show that Yale’s Glidepath strategy would not have performed particularly well; one would have done better selecting one’s own funds, or by following the traditional 60%Stock-40%Bond constant allocation.
  • Retirement savings were calculated for a hypothetical individual making contributions to a retirement fund from Jan-2000 onwards using various allocation strategies, including Yale’s Glidepath and also a reverse glide-path strategy.
  • Much higher savings with relatively low risks can be obtained by employing a dynamic investment strategy using models which have moderately different allocations for up- and down-market conditions.