Quarterly Theory Market Cycles: Key Concepts and Trading Profiles
Quarterly Theory, as taught by Day and confirmed through personal study, posits that everything can be divided into quarters to understand market cycles. This theory emphasizes that time is fractal, meaning the same concepts apply across all timeframes. The number four is central to this theory, appearing in various aspects of life such as seasons, Olympic cycles, and the division of an hour into 15-minute quarters. This perspective suggests that nothing is random, and every event has a cause, adhering to the law of cause and effect.
Market Profiles in Quarterly Theory
There are two primary market profiles within Quarterly Theory:
- AMDX (Accumulation, Manipulation, Distribution, Reversal/Continuation): This profile describes a cycle where assets accumulate, are manipulated, distributed, and then either reverse or continue their trend.
- XAMD (Reversal/Continuation, Accumulation, Manipulation, Distribution): This profile is the inverse, starting with a reversal or continuation of the previous cycle, followed by accumulation, manipulation, and distribution.
The Role of News and Economic Calendars
Contrary to common advice, news events are not to be avoided but rather used as a roadmap for the trading week. The economic calendar helps anticipate market profiles. For example, a week with a bank holiday on Monday (Q1), PMI on Tuesday (Q2), NFP on Wednesday (Q3), and unemployment claims on Thursday (Q4) would suggest an AMDX profile. In such a scenario, Monday might exhibit low-probability price action, making it unsuitable for trading, while Tuesday, Wednesday, Thursday, and Friday would be considered tradable days.
True Opens
True Opens are critical components of Quarterly Theory, representing opening prices at specific times. They are used to validate swings and gauge premium or discount.
- Validation of Swings: If a true open is not involved, a swing is not considered a "true swing."
- Premium/Discount: Traders look to buy below true opens and sell above them.
- Support and Resistance: True opens can also act as support and resistance levels.
It is crucial to align the correct true open with the appropriate timeframe:
- True Year Open: Weekly timeframe
- True Month Open: Daily timeframe
- True Week Open: 4-hour timeframe
- True Day Open: 1-hour timeframe
- True Session Open: 5-minute timeframe
Sequential SMT (SSMT)
Sequential SMT refers to an SMT (Smart Money Technique) that occurs between quarters. It is considered the key to any point of reversal, meaning that every price reversal is preceded by a sequential SMT.
- Triads: Sequential SMT is often present within a Triad (e.g., NQ, YM, ES). If not, it will be found between Triads, which can cause the high or low of the week.
- Example: In a sequential SMT, the highs that create the SMT occur between separate quarters. The asset that fails to take the high will likely have a larger proportion of liquidity and fall lower.
- Confirmation: A higher timeframe sequential SMT must be confirmed by a lower timeframe sequential SMT.
- Between Quarters: Sequential SMT can occur between any quarter, including between Thursday and Friday. Friday can be referred to as Q0, leading to a "TGF setup" where price is expected to retrace 20-30% of the weekly range.
Hidden Sequential SMT
Hidden sequential SMT is a variation where candle bodies, rather than wicks, are used. If one asset closes above the close of another high, but a different asset closes below the close of another high, this indicates a hidden sequential SMT. This is considered equally powerful and warrants careful study.
Intermarket Sequential SMT
Intermarket sequential SMT involves SMTs between market Triads. Examples of market Triads include:
- Forex Triad: EUR/USD, GBP/USD, Dollar Index
- Index Triad: NASDAQ, S&P 500, Dow Jones
- Interest Rate Triad: T-Bond, 10-Year Note, 5-Year Note
If sequential SMT occurs within a Triad, there must already be intermarket SMT, and there's no need to refer to another Triad. However, if not, traders look for sequential SMT between Triads. The interest rate Triad is considered the most powerful and controls everything. When the DXY (Dollar Index) moves in the same direction as interest rates, market conditions are low probability, leading to "high resistance liquidity runs" (HRLR).
SMTF (SMT with Fair Value Gap)
SMTF is a cracking correlation that does not use highs or lows. It is an SMT where a fair value gap forms after a sequential SMT. One asset will trade into this fair value gap, while another asset fails to trade into the same gap formed at the same time. This must always follow a sequential SMT.
- Example: In an index Triad, if NQ trades into a fair value gap while ES fails to, and both followed a sequential SMT, this is an SMTF. The assets that failed to take the high (creating the sequential SMT) had a larger proportion of liquidity, explaining why other assets might not trade as far down.
SMT MSS (SMT with Market Structure Shift)
SMT MSS is an SMT combined with a market structure shift, again following a sequential SMT. One asset will create a market structure shift, while another asset fails to create a market structure shift with the same candle on the same low or high. This highlights the crucial role of sequential SMT.
- Example: If NQ fails to take a low from a previous cycle, but ES and YM do, and then ES creates a market structure shift while NQ and YM do not with the same candle, this is an SMT MSS. This can occur around a session true open and may also be a "turtle soup" setup. Another cracking correlation might be present if NQ and ES trade below the true open, but YM fails to.
The Function of Q1
Q1 is not merely a period of consolidation to be ignored; it has its own function. Q1 can be divided into three thirds: T1, T2, and T3. The first third (T1) is ignored. The range formed between T2 and T3 is then identified. Using a Fibonacci retracement tool, one standard deviation above and below this range indicates where price is likely to be drawn.
All credit for founding these concepts goes to Day, with the presented information being a result of personal study confirmed by his teachings.
Takeaways
- Quarterly Theory divides market activity into four quarters, asserting that time is fractal and the number four appears in many natural cycles, implying no randomness and a cause‑effect structure.
- The theory defines two market profiles—AMDX (Accumulation, Manipulation, Distribution, Reversal/Continuation) and its inverse XAMD—guiding traders on expected price behavior within each quarter.
- True Opens at specific timeframes (year, month, week, day, session) serve as validation points for swings and act as premium/discount, support, and resistance levels.
- Sequential Smart Money Techniques (SMT), including hidden, intermarket, SMTF, and SMT MSS variations, occur between quarters and must be confirmed across higher and lower timeframes to signal reversals.
- Economic calendar events map onto the four quarters, allowing traders to anticipate tradable days and to use Q1’s internal thirds and Fibonacci analysis for precise price targets.
Frequently Asked Questions
What does the AMDX market profile describe in Quarterly Theory?
The AMDX profile outlines a four‑stage cycle—Accumulation, Manipulation, Distribution, then Reversal or Continuation—showing how an asset moves from building positions to being sold and finally changing direction or extending the trend. Traders use this sequence to anticipate price behavior for each quarter and align entries with the expected stage.
Why must a Sequential SMT be confirmed on a lower timeframe?
A Sequential SMT must be confirmed on a lower timeframe because the higher‑timeframe signal only indicates a potential reversal, while the lower‑timeframe confirmation shows actual market participation and liquidity taking place. Without this lower‑level validation, the setup may be a false signal, leading traders to misinterpret price action.
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trades into
fair value gap while ES fails to, and both followed a sequential SMT, this is an SMTF. The assets that failed to take the high (creating the sequential SMT) had a larger proportion of liquidity, explaining why other assets might not trade as far down.
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