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Risk profile analysis part 3

Since this is a very important subject, it is worth stretching the topic over three articles or more. Make sure to check the first article on risk profiles to get the basics before jumping further into this article:

As already outlined, the risk profile analysis is a combination of looking at what the global capital is doing, or more specifically trying to identify whether global capital is in a defensive or offensive stance.

If every asset on yields/bonds/USD/SPY/VIX aligns with risk-ON we know that global capital is easing and pushing into risk-seeking assets. That is generally what we want to see for an optimal bullish environment on equities. So that our intraday leveraged longs work out better and our (hopefully not) bags get a rescue from plunge protection team swooping in.

-yields down-bonds up-USD down-SPY up-VIX down=RISK ON. "The holy grail of longing in markets."

When you are thinking about whether to create bullish or bearish plans for any asset you trade on the day, make sure to use a risk profile to adjust the thesis accordingly. This means YOUR thesis is adjusted correctly to global institutional capital flows of "THEM". Unlike where some traders live inside their heads not bothering with what institutional capital is doing on the day and trading plan is derived from some random technical analysis outside of capital flow context=avoid such behavior.

Using risk profile analysis to create better trading plan

For example, if the day begins near market open with a strong risk-ON score due to how the key asset chain is positioned, one should look for longs more in large or small-caps of equities. If the score is softer then stepping back on bias is a good idea to avoid getting trapped. When the risk-ON score is high in the market open or in the mid-day generally demand in equities will be more aggressive.

An example of where an opening score of risk-ON is solid but not the highest (Dec 6th). On the left side of the chart are key risk profile assets, and on the right side, there is a basket of large and medium-cap equity tickers (GME, SCHW, CVNA, AMD).

Now lets compare the performance of those same equity tickers on the day where risk-ON score was much higher and clearer into market open (November 14th):

Notice that there was night and day difference in performance of those same assets on those two days. Look on right side of chart to notice:

1. Volatility % differences: On strong risk-ON score day the % deliveries doubled up versus prior reference. 2. Much cleaner consistency of uptrending action: On strong risk-ON score the chances are higher for tickers to sustain bull trends intraday.

While those two are just two examples, the point is to establish above as good reference on how to think about thesis formation on tickers on the day, before the market even opens.

Therefore the score strength impacts:

-the chances of high % squeezes vs low %

-chances of sustaining bull trends through the day and how clean they are

-tightness in liquidity and spreads which impacts traders RRs by default regardless of side one trades at

My scoring system is personal with some subjective inputs, ill leave for every reader to decide how to implement that for yourself. If you study history over enough samples it should be clear in which direction the scoring needs to be adjusted.

Using prior days behaviors and ATR (volatility adjusted changes). What matters really the most ,is just how significant the change is on the day versus prior day or versus prior multiple days. Its that what defines the contribution to score the most. The softer the change the softer the contribution to changing the score. The bigger the change the more contribution (both for risk-ON and risk-OFF). But keep in mind as well higher time frames impact, which was outlined in prior articles.

2023 risk ON / OFF cycles

To keep context of entire article in mind, use this yearly risk ON / OFF cycle to use the context of examples below:

Smallcaps risk ON/OFF cycle typical dynamics and cycle specific behaviors

February Risk off cycle in smallcaps

To summarize February somewhat on the smallcap side:

-Lack of activity and presence of heavy squeezers,

-Lack of MDRs (multiday runners) and sustained durations,

-Increased fades early and lack of volumes

"Lack" is a context phrase, if we compare it to January (risk-ON cycle) and some other risk-ON cycles it would definitely be fair to use that phrase. Just in case anyone is thinking "Hey but what about this one ticker that did go X".

It's the context that matters as a whole, average behavior across the entire basked of tickers on that month.

Below is the highlight of some small-caps performances in the February risk-OFF cycle. There is common behavior in small-caps within risk-OFF cycles that tickers will much less likely turn into proper multiday runners and will have lower chances of squeezing past d1 highs. The liquidity and volumes are lacking compared to risk-ON cycles but the volumes are typically not at all reliable input. It is per-cycle behaviors that provide much more clues, as even strongly fading tickers can for at least a short while trade on very high volumes.

First batch of February tickers:

Another batch of February tickers. Notice again, heavier fades with only one MDR ticker.

Now lets contrast above February samples with opposite cycle of risk-ON in mid March, and lets see how common behaviors differentiate between above 2 risk-OFF examples versus the lower risk-ON example. Notice how within just two weeks behaviors switch to night and day. And you think this does not impact edge of traders? Of course it does.

One can notice from the image above how very high % squeezers were present more commonly in the risk-ON cycle versus risk-OFF (notice on the right side of the chart that % rates have doubled up from the prior risk-OFF example, which shows the difference in average performances as well from 60% avg frontside delivery to 180% frontside delivery jump between risk-OFF and risk-ON cycle. This impacts edges of traders in many ways, especially for short sellers who tend to underestimate just how much more the ranges will open up in % terms when risk-ON is active.

To put it conceptually smallcap average performances in two different global risk profile cycles:

Lets use another example of May risk-ON cycle performance in smallcaps on image below. Notice strong deliveries (presence of hot AI sector). Its significant contrast to February risk-OFF cycle.

Rigged behaviors of smallcap stocks in two different cycles

Now let's discuss rigged/manipulated activities in smallcaps, and how those relate to liquidity cycles. Another important subject to discuss is to anticipate the right kind of action in small-caps on a daily basis.

When liquidity increases and volatility increases (always in risk-ON) the rigged activities in small-caps have a significant uptick.

For example, while in colder markets of risk-OFF, one might see every third or every fifth ticker being manipulated, those stats will jump up significantly when in risk-ON cycles. It shouldn't be surprising why. More liquidity and volatility increase competition in order flow and give leading market makers (which corner the float) more ability to toy around with everyone who is participating. Unlike in lower liquid markets where they have to be more defensive with aggressive rigged action, because dry tape could trap MMs positions easier (problem getting out).

Let's highlight some of the clear rigged behaviors in May and then contrast that with February intraday behaviors. In case you are unfamiliar with the subject, make sure to check older articles on the smallcap rigged behaviors.

Mays rigged behaviors in small caps (risk-ON cycle):

Contrasted versus February much more organic/fade behaviors (risk-OFF cycle):

Above is highly statistically relevant example, because the difference in how many tickers fade cleanly (ADF) on dry liquidity (and not being rigged) is quite higher in risk-OFF cycles than it is in risk-ON cycles. At the same time, the chances of ticker to be rigged with plenty of traps and short squeezes will be higher in risk-ON cycles. There are huge implications on edge and how this impacts all traders no matter bulls or bears.

Example of recent strong cycle in smallcaps correlating with risk-ON global cycle in December, leading to highly rigged behaviors on December the 6th and strong frontside squeezes on tickers SSNT SERA and MLGO all within few days of span:

Keep in mind this performance of MLGO SSNT and SERA has not been at all common in many prior months of 2023 (as we had a very cold market due to risk-OFF presence), yet those rigged behaviors with strong frontside squeezes popped up all of sudden at near 2021 levels! This shows just how much small-caps are sensitive to risk-ON flows and how important it is to protect those higher volatile moves in advance using the risk profile to avoid major losses (if playing on the short side).

Be adaptive, play long and short depending on what suits the more likely directional side on the day, using cycle flows as context

I believe that being highly adaptive with bias in small-caps is the best way to go. This means being bearish-biased some days and having bull bias the other days when cycle flows dictate the switch.

December the 6th was clearly one of the days where initial bullish bias made sense. Its understandable why traders prefer static approach, because it takes long time to grasp the concept of cycles. And being adaptive without knowing how to adapt well can be very slippery road. However...over long run that is 100% a better choice, with more control over performance and most importantly making trading less frustrating ("what the hell is going on??!!). The key is that trader needs to make intentional decision to get better at reading cycles (inputing time into studying subject) and slowly over time adjusting strategies to be more adaptive rather than too static. Its a process that takes time (months if not a year).

Some personal comments on the day in the trading community using cycle flows to form plans for those tickers (to highlight that this analysis is not about hindsight but can be applied in real-time):

December 6th=stronger risk-ON, bias bullish especially on low % gappers

-ALT expecting upside squeeze

-MLGO avoids shorting fake breakouts in the first 30 minutes because the cycle flows suggest it will reclaim fake breakouts and squeeze higher

-SERA longing into clearout swipe of 5 and selling into squeeze (and no interest in shorts due to potential overperformance on the upside from cycle flows)

We should also highlight one common factor for smallcaps: The longer the risk-ON is established in global market, the more chances that strong cycles in smallcaps repeat. Meaning one week there is very hot action, but the next week might be more neutral, and then the next week after that its very hot action once again. Thats pretty much what happened between November 15 and December 6 so far.

In almost all cases when risk-OFF global cycle is present strong cycles in smallcaps do NOT re-ignite soon after. There is typically one month or more delay before next one shows up.

Above two counter examples again show how much of expectations on strong cycles in samllcaps and the frequency of cycles are completely correlated to the actual global risk-ON/OFF.

In risk-OFF global cycles strong cycles of smallcaps still happen sometimes but generally they do not last long. In risk-ON global cycles strong cycles happen more than just once and generally last longer than just 3 days. That is very important dynamic to keep in mind as it impacts projections and expectations. Random? Of course not, risk-ON globally explains that. To keep in mind November/December risk-ON cycle was on par with many 2020-21 months in terms of how large inflows in equities have happened and how large the bounce to upside in credit/bond markets was:

Novembers carry in bonds

Bond market recovery (carry and backbone of the risk-ON rally for November and December so far):

Heavy short squeezes in equities not seen since start of the year:

The theme since early 2022 has been that bond markets dictate what happens next. Crush the bonds and you crush everything else by the majority. Rally in bonds and you lift everything else along with it. But that is not the key signal.

The key is prolonged carry in credit market that matters (bounce that lasts more than just one week). Meaning that the more the uptrend in TLTs sustains the more it increases the chances that equities step into a prolonged risk-ON cycle. The quicker the bull recovery in bond fails, the more likely it will be to sink everything along with it. So there is good reason to pay attention closely to what credit markets are doing, whether they are moving up fast on recovery rallies (very bullish short term) and if they are over higher time frames also holding bull trends (bullish with long term exposure duration). Both of those two conditions matter. Whether you trade small caps or any other exotic collection item such as NFT, you should pay attention to that. And for those that trade large-cap equities hopefully, they already know that.

Smallcaps strong/weak cycles are not the same as risk ON/OFF cycles

And again to be clear, this has nothing to do with smallcap strong-weak cycles (a term I often use). We are placing small-caps (micro) inside of global asset cycles (macro) to highlight those lessons. Obviously, strong cycles of small-caps are correlated to global risk-ON cycles but they are not present through the entire duration of that big cycle! This means for example that the global risk-ON cycle can last for 2 months, but actual "strong" cycles in small-caps have typically only 20 or 30% of that presence in very strong momentum, equaling the "strong cycle".

To present this conceptually, how big global risk ON/OFF cycles fit within the smallcap market cycles (Matryoshka style):

As we can see from the above conceptual example, smallcap cycles (micro cycles) fit within the frame of larger global liquidity cycles. Not every day when risk-ON is present the small caps will have hot action, but it is likely however that tickers will be more resilient to fades even when the technically strong cycle is not in play in smallcaps because risk-ON will help to stabilize the demand. And vice versa for risk-OFF situations. If you havent traded smallcaps for quite a long time you might not notice those differences quickly.

Impact of yields in 2022 on equity markets and especially risk-ON cycles in small-caps

dropping yields create easing conditions, for best easing conditions yields should decline as fast and as much as possible. Bond yields respond to central bank comments and policy updates. Typically market will re-price credit markets over the duration of one or two months, which creates the buffer for risk ON/OFF cycles with prolonged durations (more than just a few days). Credit cycles are generally not super short lasting like smallcaps sometimes can be, which gives us much better big picture clarity and something firm to hold on.

Impact of sharp increases of yields on smallcap activity

Speaking from hot flows potential:

Yield spike to upside: yuck! Yield dump to downside: mmm...

Paying attention to yield movements as mentioned above should be split into two directions.

1. is trend, and which direction it is going.

2. view is whether there have been significant short-term changes in spike direction.

Both contribute to impacting the chances of risk-profile changing. However, keep in mind that smallcaps operate with delay! It's not as if small caps will react to bond yields intraday or have changed within a day. Generally, there is a delay of about 5 days or more for bonds to translate into risk profile changing enough so that it starts to impact small-caps because small-caps are the last asset in the chain. This means that bonds first (quickly) impact bigger asset classes first, and then there is a delay on the chain all the way down to small caps within a few days. Signal transmission has latency sort of speaking.

Catch the risk-ON cycle early!

Many traders hibernate and fall asleep during risk-OFF cycles which makes them then be late in the early risk-ON cycle! All of this removes the point of tracking cycles in the first place because the value is in fast recognition of cycle changes.

This means tracking daily changes even in the dry market is very key, to recognizing the risk-ON cycle early. This is what most traders do not go about doing.

This is possibly one of the most common dynamic, because traders are often so frenzy oriented (they show up at trading desk when things are hot, and when they get dry they completely stop tracking all markets) it creates the disconnect effect when market kicks into risk-OFF. And then when early ignition of risk-ON begins, because they no longer track most markets closely at all, they miss the ignition! Again, this should be re-read 10 times if necessary as its weight cannot be understated.

Average risk-ON/OFF cycle duration 2022-23:

Typically risk ON/OFF global cycles do not start and end within just few days. They last for month or more. This gives us solid foundation to build expectations on. This is explained through the longer and slower moves in credit markets and the fact that credit moves like tanker and not a speedboat. This creates the backbone for risk ON/OFF cycles. But for anyone willing to do deeper research on that, make sure to use as much as history over past decades to research how this works, and how it translates into equity markets.

"Key story" could change

Each year risk ON/OFF flows have one key story to focus on. Last two years that story was rate hikes and inflation. But going forward this could change. Time will tell what the next story will be. This should be outlined so that the reader understands why so much attention and relationship dynamics between bonds/yields and equities have been shown in the article because that has been "the key story".

Whatever the next key story will be shall be seen, although it's very likely the interest rates and inflation will remain a likely key story going forward. We can draw such a projection using the past two higher inflationary cycles (especially the one in the 1970s) as a guide, to say that generally inflation problems don't just come and go as quick one-year stories. They stick, for years if not decades (once problem ignites-2021).

Crypto altcoins performance outside of risk-ON cycles

This can be a good exercise to make to see the value of fundamental per-asset analysis versus cycle flows.

Often 100 different traders will find 100 different reasons why certain assets should be long. This or that is good news, low float, recent ICO, etc...

We could make a huge list and there is typically never a lack of "why to buy" reasons.

A lot of those reasons are highly speculative, difficult to prove their deliveries over 100 samples (due to too many conflicting variables). And lets not forget that many market participants just find the reasons on why going long something without actually checking that "reason" even has any decent delivery over 100 samples in past.

But what we can do instead is to overlap the tickers into risk profile and market cycles, and see what happens then.

The result is much higher clarity. It highlights just how much positive news doesn't matter in the wrong cycles. And how no news in the right cycle can be good enough to squeeze ticker up a lot!

Re-read the above, and re-confirm the statement through outlined charts to see just how much that is true.

Market in "bullish cycles" as risk-ON typically won't need much-helping catalysts to push risk-seeking assets higher, such as altcoins. And vice versa, any positive catalyst in the "bear cycle" or risk-OFF will get eaten up and ignored, while the ticker keeps tanking lower.

Or to really simplify everything said above. Whenever there is hot risk-ON market in crypto, large chunk of altcoins will have uptrending performance, regardless of underlaying asset structure. Which shows us just how little the details about each asset class matter in hot market, versus how much actual cycle flows and liquidity influx contributes to their performance:

If we isolate altcoin performances per cycle we can start to notice how much creating a valid quality thesis on the asset (for a long) requires one to understand the cycle you are in, and to time that cycle as early as possible, because your extracted RR will highly depend on it! The analysis of each particular asset is far less important, than it is to know which cycle you are in!!!

We can do a similar exercise and plot some smallcaps of equity markets to highlight how in risk-ON cycles smallcaps like to turn into multiday runners, as already shown on prior articles. At the same time, we can highlight how in risk-OFF cycles MDRs are in OFF switch, rare.


This brings us to the end of another article on market cycles. As we can see the cyclicality of markets should not be taken lightly, and for one to create valid plans current cycles should be taken into account. It is necessary to venture out and explore different markets to observe how each asset class impacts another. Or more importantly how the hierarchy of markets works with flows trickling down from bonds to currency, from currency to stock, from larger stocks to smaller stocks etc...


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