{"id":237,"date":"2022-09-29T20:27:29","date_gmt":"2022-09-29T20:27:29","guid":{"rendered":"https:\/\/wosscapital.com\/articles\/?p=237"},"modified":"2024-12-10T22:28:17","modified_gmt":"2024-12-10T22:28:17","slug":"game-of-fractals","status":"publish","type":"post","link":"https:\/\/wosscapital.com\/articles\/game-of-fractals\/","title":{"rendered":"Game of Fractals"},"content":{"rendered":"\n

Fractals in Price Action can be dangerous things. <\/p>\n\n\n\n

On their own they lack context and in trading context is generally key to decision making when we’re attempting to play probabilities looking for an edge. While it’s absolutely true that there are patterns that repeat on all timeframes, including the Macro, we need to consider the larger context around these repeating phenomena rather than just look for fractals in price that look similar. This is what led me to the idea for this article.<\/p>\n\n\n\n

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Time and Price<\/h4>\n\n\n\n

Ok, so lets get this out of the way, I am a fan of ICT concepts. Despite what anyone may think of Michael himself (I actually like his approach) I have taken the time to learn, test and work with his concepts and in my view having done that there’s no question to me that he’s come up with some outstanding, applicable theory. It’s not the only thing I use by any means, but I appreciate it all the same.<\/p>\n\n\n\n

One of the foundations of his process involves using Time as a key pair to Price. From an Intraday level using sessions (or Kill Zones) or from a Macro perspective using Seasonality to aid in probability, Time is a key component in working with Price, from a trade probability perspective.<\/p>\n<\/div>\n\n\n\n

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I am also a fan of Bob Loukas, who does some outstanding work on cycles and cycle analysis, another application of Time working alongside Price to aid in decision making and probability analysis. Bob has a very different approach to ICT, though there are some similarities in their 60 day cycles and lookback\/caste forward, but the main point here is that both leverage the Time component as a key element of their analysis.<\/p>\n\n\n\n

This has been something I have been testing, from Intraday and m1 charts all the way up to M12 charts and yearly macro analysis across asset classes. I have found the results of that testing truly fascinating, to the point that they are starting to shape my thinking on all timeframes. And thus, we get to the crux of this article: The dreaded 2008 Fractal!<\/p>\n\n\n\n

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The 2008 SPX Fractal<\/h4>\n\n\n\n

The 2008 SPX fractal has become increasingly prevalent on Social Media (mine at least) over the last few months as people look for a potential roadmap for where markets may be headed as we reach the end of 2022.<\/p>\n\n\n\n

The image to the left (click to enlarge) shows the current SPX chart, with the fractal in question added, no resizing or tweaking, just copy and place at the high.<\/p>\n\n\n\n

I can absolutely see why this has become interesting to people, the fractal, from the top at least, is compelling in terms of how Price has moved. But, I have some real issues with this as a theory and, if you’ve been paying attention you may have an inkling as to why. Time!<\/p>\n<\/div>\n<\/div>\n\n\n\n

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The Fractal that Time forgot!<\/h4>\n\n\n\n

In a previous article I covered my thoughts on the Bitcoin 4 Year Cycle and whether that may, or may not, be a coincidental correlation with the Halving or simply that it slipped right into the normal SPX 4 year cycle around the US Presidential Term, as a correlated asset (BTC and SPX).<\/p>\n\n\n\n

Granted that article was focussed on BTC and the legitimacy of the Halving from a planning perspective, but for the keen reader there were a few other conclusions that may have been drawn from that piece, one of those, the SPX 4 year cycle, being the focus of our investigation here.<\/p>\n\n\n\n

So, as we covered above, the 2008 fractal is compelling. It comes from a time when Financial Markets entered turmoil, an outcome many fear and many more are predicting is in our future. The Price levels line up fairly well and it’s impossible to argue that macro economic factors linked to the War in Ukraine, rising inflation\/cost of living across the World and another potential housing bubble to name a few don’t paint a worrying picture. <\/p>\n<\/div>\n\n\n\n

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And this is before we acknowledge that most of us would question the ability of our current worldwide incumbents of financial decision making power to run a tuck shop.<\/p>\n\n\n\n

Nonetheless, I still have an issue with the 2008 Fractal and its use here. Again, I understand, as above, all the reasons why it has become popular, but I would make the case that we, as humans, are rather prone to bouts of recency bias, which is why this fractal was at the forefront of peoples minds in the first place. 2008 was only 14 years ago and most of us lived through it. As a parallel, it fits with that bias:<\/p>\n\n\n\n

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Recency bias<\/strong>\u00a0is a\u00a0cognitive bias<\/a>\u00a0that favours recent events over historic ones; a\u00a0memory bias<\/a>. Recency bias gives “greater importance to the most recent event”, such as the final lawyer’s closing argument a jury hears before being dismissed to deliberate.<\/p>\n<\/blockquote>\n\n\n\n

But if we look at the data, going back to 1928 (nearly 100 years), it doesn’t fit with Time<\/mark><\/strong>.<\/p>\n\n\n\n

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The 4 Year SPX cycle, 2008 and why it is an odd fit<\/h4>\n\n\n\n

So, we return again to my fascination with the SPX’s 4 Year Presidential Cycle. As I covered in my last article around Bitcoin Halvings, the SPX has been running in a fairly consistent 4 year cycle around the Presidential Cycle for as far back as I have been able to gather data.<\/p>\n\n\n\n

The image to the right (click to enlarge) shows the general makeup of this cycle. Up in Year 1, down in Year 2, up into Year 3 with consolidation before continuation and consolidation again into Year 4.<\/p>\n\n\n\n

Broadly speaking, this has been the case.<\/p>\n\n\n\n

So let’s cut straight to the chase. 2008 was Year 4 of the Presidential Cycle (2004-2008) and we are currently, in 2022, in Year 2, the Mid-Term year. From a cycle perspective, Time doesn’t match up. Further, within the context of the cycle, the tops don’t match up in time either. The top that preceded the crash was in October 2007, whereas in 2022 the Top was in January 2022 (right where the Year 2 cycle top should have been).<\/p>\n<\/div>\n\n\n\n

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So, to confirm, we have the wrong year of the cycle going back ~100 years with all the data we have AND the months are out by a full quarter as well.<\/p>\n\n\n\n

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Raw Data | Mid Term Year<\/h4>\n\n\n\n

So 2008 doesn’t appear to fit with Time from a cycle perspective and has to be jimmied a little to fit with time (+3 months) from a fractal perspective. Is there anything else within the 4 year cycle that is interesting to us, data wise.<\/p>\n\n\n\n

Well, yes, indeed (or at least to me!). <\/p>\n\n\n\n