Author: Benjamin Usachi

Deep Current Guide: This is a textbook-level "misguided expectation" trade. The market saw weak CPI and thought everything was fine, pushing the Nasdaq to 30060, but the 30-year real interest rate broke a 20-year high that night—short-end easing, long-end refusal, technology stocks couldn’t borrow cheap long-term funds, and the upper limit of valuation had already been locked down. Traders took five batches of short positions to profit from the drop from 30060 to 28768, with the core methodology being: Don’t just look at the data itself; consider how the market thinks the data will transmit, and then examine whether the transmission mechanism is still effective.

Case File

• Case Number: 002
• Trade Prototype: Transmission expectation error/Old response function invalidation
• Market Status: Duration pressure high, tightening again; short-end easing, long-end refusal; credit stable; illiquidity crisis
• Market Implied Causal Chain: Weak CPI → Policy easing → Long-term fund price decline → NQ valuation expansion
• Breakage Location: Between policy path and long-term fund price
• Veto Variables: Ten-year and thirty-year real interest rates
• Crossection Confirmation: NQ turned weak after being strong relative to ES; ASML, TSM good earnings reports followed by price drops
• Cleanest Expression: Short NQ, rather than indiscriminately short ES
• Entry Structure: Fast variable repairing price, slow variable refusing to repair pricing conditions
• Falsification Condition: Long-end real interest rates continuing to decline; dollar and funding environment easing in tandem; credit stable and broadly diffused; NQ regaining relative strength
• Monetization Condition: The misguided expectation has been corrected, and credit has not deteriorated enough to support a comprehensive risk-off
• Execution Defect: External opinions did not change the evidence, but interfered with confirmation of positions; target adjustments need to be defined as new decisions
• Case Status: Periodically archived, final statistics will supplement after remaining positions are closed
• One-Sentence Experience: Trade misguided expectations, waiting for market prices to conflict with its own implied causal chain.

The most illustrative trade I executed recently is the short-selling of NQ starting early Wednesday from Tuesday night.

First batch of short positions entered at 30060. Second batch entered at 30040, expecting the price to drop to 29700. Within two hours, the price rose to about 29880, then the market began to rebound with the PPI data, soaring to 29990. At this point, influenced by some opinions, my conviction started to waver, afraid that betting too heavily would bury me, so I closed my short position at 30040 for a profit at 29992. After observing for ten minutes, confirming the downward trend, I re-entered a short at 29950, partially for NQ hold and partially for MNQ for easier staggered profit-taking, while setting MNQ to automatically take profit at 29700. On Wednesday night, I changed my view, believing this wave could drop to around 29000, so I placed a new MNQ short position at 29000 to test the waters. A total of five batches of short positions were executed; the earliest at 30060 has not yet taken profit, the 30040 failed due to wavering confidence, the 29950 NQ was manually closed at 28500, the 29950 MNQ took profit automatically at 29700, and the newly added MNQ short at 29000 has yet to take profit. On Friday, NQ closed at 28768.25.

This set of trades might seem very unclean to many experts, back and forth, but for me, it shows clear progress. Firstly, timing-wise. In the past, I focused solely on direction, poorly timing the entry and exit points, comforting myself that it was about leveraging strengths while avoiding weaknesses. However, this time, my entry time, entry point, and profit-taking were all more efficient and less risky than before, which is progress. Secondly, as this was a classic "valuation overhaul" and "misguided expectation," the market provided me with ample time windows to gradually validate my macro framework, validate indicators, and conditions assumptions as correct, allowing prices to move towards my anticipated timeframe.

Looking back, as I said, this trade was a very typical expectation error. A portion of people in the market had positive expectations for the new data, leading to price increases, but the actual price setters in the market did not recognize this expectation, resulting in a significant price drop. The purpose of this review and sharing is because I feel this trade can be deconstructed into a typical expectation trading methodology and can be reused, which is why I am documenting it here.

What is a market's misguided expectation?

The most common or frequently discussed aspect is data expectations, including event expectations. How much is the non-farm payroll, what is the CPI, what is the EPS in the earnings report? Or whether the Federal Reserve's tone is dovish or hawkish, whether the US and Iran will temporarily cease fire. After the data or event results are announced, a difference, a surprise, may arise between the actual value and the consensus. Many trades revolve around this layer, which is why we see many voices debating whether rates will fall or whether AI spending will be cut to seek a reversal. This is indeed the most basic yet also the most difficult aspect.

However, what truly determines prices are the latter two layers of expectations.

The second layer, which I call transmission expectations. After data emerges, how will the market alter the policy path, real interest rates, the dollar, credit, and risk premiums? Does weak CPI only affect the two-year rate, or is it sufficient to lower the prices of ten-year or thirty-year long-term funds? After a company beats expectations, does it merely increase current profits, or can it improve future cash flows and capital returns? Data can impact different aspects of the market, with some parts being benign and others malignant, while some may show no volatility at all. Hence, we also see many good earnings reports followed by declines, or weak data resulting in rises, as the transmission mechanism affects various facets differently.

The third layer is asset expectations. After changes in the first two layers, how much price should the market assign to a certain asset? Is it an increase in valuation multiples, or merely an increase in profit expectations? Is it buying NQ or buying ES? Is it buying long bonds or buying gold?

The so-called misguided expectation either comes from a direct misestimation of the first layer, for example last year when everyone thought rates would continuously drop, but suddenly there was a halt. Or it can lead to significant accumulation in the second layer: an expectation that hasn’t been fully interpreted, with the market failing to reasonably assess how this new event or data will transmit across different aspects of the market, directly jumping past the second layer to try and price the third layer. Thus, the market produced an erroneous price completely at odds with the actual situation. The time for arbitrage has arrived.

In summary: The trader correctly comprehended a fact, yet mistakenly believed the old transmission mechanism was still valid.

In last week's report, I noted the need to observe two important data points this week: Tuesday's CPI will determine the market's pricing for interest rate trades and whether there is a possibility of rate relaxation, thus altering the trend of funding prices breaking through 20-year highs for four or five consecutive times two weeks ago; Thursday's retail data will help explain the market's revenue and sentiment aspects, observing whether consumers, after facing previous price shocks, can continue to maintain strong consumption to provide cash flow for companies.

Once the CPI data was released, indeed, interest rates plummeted, prices rose, with Nasdaq leading the gain. The market sighed in relief, and so did I. However, for me, the observation window did not end there, as I understood that the market still needed to genuinely traverse the transmission layer; short-term price movements could not determine the final direction. Indeed, that night, just over an hour before I began my talk show, the 30-year real interest rate rebounded, breaking a 20-year high once more. I knew the timing to short had probably arrived. The morning’s weak CPI led the market to develop a misguided expectation, believing weak data would fully support the market, but in reality, the market's narrative had already shifted, and the transmission mechanism had changed, so the comprehensive rise that day was a mispricing.

This particular indicator's rebound has two significances. Firstly, under below-expectation CPI data, the market would generally expect comprehensive easing of funds, with rates expected to fall across the board. But that night, we saw short-end rates ease, while long-end durations, like 10-year, 20-year, and 30-year rates, all rebounded. This proved that the market's reaction to weak CPI merely eased the recent interest rate hike expectations, but did not relax the long-duration rates, which define funding prices and future risks. This confirmed my main line over the past month: due to the various macro factors I mentioned, long-duration fund prices remain high and cannot decline. The second significance is in terms of the shorting targets and entry points. The high price of long-duration funds means tech stocks would suffer the most, as tech companies require a large sum of money borrowing for ten, twenty, or thirty years ahead. If weak CPI results in declining short-end rates but long-end rates remain elevated, then the Nasdaq would be the first to face backlash; conversely, the S&P, due to its wide diversification and not all companies requiring substantial borrowings, would find support in short-end rate declines, while the long-end rises won’t equally devastate the S&P. I actively stated these two conclusions during my show that night, one being that the Nasdaq was surging too much, and I would be cautious; the other regarding the new market mechanism, that good news would no longer provide the same strong supportive effect for tech sectors as in the past.

Regarding point selection, there are two layers of validation. The last high for NQ was at 30060. Since the long-duration rate broke previous highs, it signified that the entire market’s valuation was contracting again, which led me to judge that unless there was positive news on the numerator side, the price should not easily breach 30060. So, I placed two batches of orders at 30060 and 30040, the latter being to avoid missing the order.

The second validation layer comes from ASML's earnings report that night. Good report but a decline, visibly demonstrating a notable numerator pressure over denominator, indicating that despite strong earnings expectations, high rates dragged good profits down. This secondary confirmation fortified my confidence to short.

This actually has a slightly comedic element. Logically, I had confirmed my trades from the narrative level, the transmission mechanism level, the indicator trajectory level, and the earnings performance level, and I had a strong chance of winning. However, I inexplicably had an intuition, suggesting that PPI data simply could not push stock prices up again. First, the previous weak CPI had already priced in part of the weak PPI, and if such a condition still caused long-end rates to reach new highs, then the actual confirmation of weak PPI would not produce real positives. If short-term prices rise, it is actually the best shorting opportunity. Secondly, "the saint cannot be defeated by the same trick twice." The market already allowed retail investors to earn money on one day due to the data, so how could it allow them to earn money again the next day using the same method?

Thus, I executed the operation mentioned at the beginning of this article. Afterwards, TSM's price drop post-earnings further confirmed my bearish trend, with the reasoning being similar, so I moved the profit-taking point down, adjusting the large order’s profit-taking point from 29700 to 29000. This selection was based on over a month of observation of interest rates and the Nasdaq, aligning the high points of rates with corresponding low points of the Nasdaq within a few days, observing absolute positions and changes in slopes, finally determining to initially focus on 29000.

Can this method be transferred to the next market condition?

Probably. I summarized five methods and thoughts that can be reused.

I have previously written about my losses regarding the relative relationship between the numerator and denominator leading to missed opportunities. In other words, to what extent does the tightening of the denominator delay or obstruct the growth of the numerator, preventing the overall price from rising? How "thick" is a relatively high numerator at the price level? To what degree must the numerator rise to break through this valuation ceiling? Ultimately, what relative changing relationship do these two play in the final price behavior?

Firstly, absolute position determines valuation ceiling, change in slope dictates short-term shocks, and relative position indicates which one will encounter issues first. Absolute position and changing speed should be assessed separately. A very high but stable interest rate allows the market to gradually adapt; conversely, an absolute level not necessarily extreme, but rapidly rising interest rate can more easily create short-term shocks. The former dictates long-term constraints, while the latter decides if there’s an immediate need for rapid repricing.

At the moment I shorted, the absolute position of fund prices had already locked in the valuation ceiling, with a very steep slope. Meanwhile, NQ was nearing 30,000 points, with the market still trading on strong AI earnings, restored risk appetites, and the valuation recovery brought on by weak CPI. This created an asymmetric price, with significant downside risks, highly encouraging profit-taking and shorting.

Secondly, when expecting a quick drop, one should look at previous highs and lows while also examining position structures.

Misguided expectations do not encourage entering the market immediately when discovering discrepancies. Misguided expectations might persist for a long time. The market can be more optimistic than you imagine, relying on positions, options, and sentiments moving in one direction. If one only believes the market is wrong without a good price, no catalyst, and no clear falsification conditions, one might merely be correctly early, and then get beat by the market.

Returning to fast variables and slow variables. The best entry point occurs when prices have repaired, but pricing conditions have not. Or stated differently, when fast variables push prices back up but the constraints of slow variables remain unchanged.

Returning to the moment of shorting. At that time, for the bulls to continue, two conditions needed to be met simultaneously: first, AI earnings and growth expectations continue to upward; second, long-term fund prices cannot continue tightening. The first condition was unfavorable, and the second condition did not exist at all. Conversely, the bears do not need to prove AI is a bubble, nor that the US economy is in recession. The bears only need one of the conditions to fail: long-end real interest rates remaining elevated or continuing to rise.

How to create erroneous expectations in the transmission layer and pricing layer? My answer, akin to many prominent bears, is to assess whether expectations are entirely based on a key assumption and then see if this key assumption is correctly priced.

First, write out the currently implied causal chain in the market. Don’t just say the market is bullish or bearish, but clarify: the market believes if A occurs, why it will lead to B, and why B will then lead to C. This time the chain is: weak CPI → policy easing → long-term fund price decrease → tech valuation expansion.

Second, identify the variables holding veto power in this chain. Every narrative has a market that must ultimately be confirmed. For long-duration tech stocks, long-term real interest rates and necessary returns hold veto power.

Third, observe whether this variable refuses confirmation. The market fighting is not necessarily an opportunity because different assets may be trading different themes. Only when the rise of a particular asset relies on this variable and that variable explicitly refuses to cooperate can the contradiction become tradable.

Fourth, wait for prices to continue following the old script. After erroneous expectations have been completely corrected, being correct yields no profits. The best opportunity occurs when underlying variables have changed, yet prices still adhere to past scripts due to inertia, quick money, and old response functions.

Fifth, choose the expression most sensitive to this error with the least impurities. Don’t indiscriminately short all assets just because of a bearish macro outlook on fund prices. Identify which asset depends most on the now-invalid causal chain.

Sixth, define two exit conditions in advance. One is falsification: the veto variable reaffirms the market narrative, indicating one's mistake; the other is monetization: the erroneous expectation has been corrected, and prices have completed their necessary return. Many people can only exit when they are wrong but do not exit when logic has already been realized.

Of these six steps, the most challenging is distinguishing whether "the market is truly wrong" or "the market is merely not operating as I envisioned at this moment."

Alpha may not necessarily come from information asymmetry, but also from response function discrepancies

Information in the market is becoming increasingly abundant. CPI, earnings reports, positions, capital flows, everyone sees it almost simultaneously. Independent investors find it quite challenging to gain an edge over major institutions by knowing a fact earlier.

However, just because everyone sees the same fact doesn’t mean everyone will interpret it correctly.

The market will form habits. Bad data equals rate cuts, rate cuts equal tech rises; gold equals safe haven; long bonds equal stock hedge; strong AI demand equates to all AI assets should rise. Once these causal chains are valid over a long period, they become automatic responses. After macro conditions change, if data remains the same, and asset structures do not shift, the old response functions may already have invalidated.

This is where the real value of erroneous expectations lies.

The biggest opportunity in the market may not come from information that others are unaware of, but rather from the fact that others still trade according to an old world, while you have realized the world has changed.

This time, the market correctly understood CPI but misunderstood CPI's significance on long-term funding prices. The stock market rose according to the old response function, while the long-end bond market refused to confirm, placing a nonexistent "denominator easing" into pricing for NQ.

So, if this article leaves only one question in the end, I hope it will be this one:

What causal chain does the market’s first response rely on, and is that causal chain still valid today?