Some time ago, I noticed that CL’s (WTI light sweet crude oil futures) three important tops since 2008 were almost the same number of days apart. This cycle certainly caught my eye.After tugging on that thread, I found a similar situation regarding CL’s lows. The 2001-2009 cycle was only 31 days longer than the 2009-2016 cycle — a 1.2% difference.
This is exciting stuff for many reasons. In addition to supporting the fact that markets often move in cycles, it offers some very strong suggestions regarding financial markets over the next few years.
I gave up on the Efficient Market Hypothesis about the time that central banks and other wealth-effect proponents began directly and indirectly propping up stock and bond prices in the wake of the Great Financial Crisis.
The first few rounds of QE were effective — but expensive and difficult to fine tune. There had to be a better way than throwing trillions of dollars into stocks and bonds.
Since fundamental discretionary traders account for only 10% of trading volume, it turns out it is much easier and infinitely cheaper to “influence” the instruments (the tails) which signal the machines (the dogs) to buy stocks.
The 90% of trading volume which is, in turn, driven by machines (indexers, ETFs, etc.) is only too happy to let the tail wag the dog. Since it typically drives stocks higher, very few investors complain.
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I had traded in most of what I believed before 2007 for a mélange of chart patterns, harmonics, analogs and technical analysis. By mid-2011, it became apparent that patterns and cycles could be at least as valuable as fundamental economic data in forecasting markets.
But, as machine-based trading gathered steam, these patterns often broke down. In some cases, the patterns actually marked opportunities to force short covering by predatory algorithms — giving rise to such “strategies” as Buy the F-ing Dip.
I devoted more effort to understanding algorithms and the factors they used to drive stock prices — a pursuit which has paid big dividends. Price movements in the factors themselves are much easier to anticipate if one knows how and when they’ll be utilized. And, by accurately forecasting the factors, it is much easier to forecast the broader markets.
We saw in 2018 what can happen when markets aren’t supported: an 11.8% plunge in February and a 20.2% nose-dive between October and December. The latter decline so alarmed the market’s caretakers that the Fed backpedaled on its plans to normalize rates and the Treasury Secretary convened the Plunge Protection Team.
Since then, stocks have recovered most of their losses, causing some participants to exclaim that the worst is over and we’re one trade deal press conference away from new highs. Yet, many others see lingering cracks in the market’s veneer — cracks that presage new lows. Which is more likely? Can our new models offer any guidance?
This post will attempt to elucidate the macro factors at work, how and when they are utilized to effect desired outcomes in the markets, and what they suggest about the next few years.
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