CryptoZeno

Before shipping containers became standard, global trade was surprisingly inefficient. Goods moved across oceans, but every port handled cargo differently. Loading was slow, costs were unpredictable, and entire supply chains depended on countless manual processes that nobody paid much attention to until something went wrong.
The container itself was not revolutionary because it created new products. Its impact came from standardizing how value moved between completely different participants. Once that problem was solved, global commerce expanded far beyond what most people expected.
That comparison came to mind while reading about #OpenLedger - Discussions around AI usually focus on models, outputs, and capabilities. The spotlight almost always stays on what gets produced. Far less attention goes toward the systems connecting contributors, datasets, applications, and the economic activity generated between them.
That is where @OpenLedger stands out to me. The project keeps pulling attention toward the movement of value rather than only the creation of value. Information, contributions, attribution, and rewards all need a way to travel across an ecosystem without becoming disconnected from the people and resources that helped create them in the first place.
The reason this interests me is that technology history often rewards the layer nobody initially finds exciting. Consumers remember websites, apps, and devices. Entire industries, however, are frequently built on invisible standards operating underneath everything else. Those standards rarely attract headlines, but they quietly determine which ecosystems scale and which ones struggle.
$OPEN less like a bet on a single AI trend and more like a bet on the infrastructure required for increasingly complex digital economies. The biggest opportunities sometimes emerge not from building the next destination, but from improving how value travels between destinations that already exist.

I’ve longed resistance and shorted support for 9 years… This is the exact opposite of what every trader tries to do.
In this article, I will share my entire strategy so you can skip years of testing and losses.
This is something you will want to bookmark, take notes on, and set time aside to think about.
Lesson 1: The Only 2 Trading Strategies
Before you can identify good momentum setups, you need to understand what momentum trading actually is.
Momentum and mean reversion are opposite strategies based on opposite assumptions.
The Two Trading Styles
Momentum (where you take a trade betting on a continuation of the current trend)Mean Reversion (where you take a trade betting on a reversal of the current trend)
One assumes strength continues; the other assumes strength exhausts.
Let’s consider this through a visual example.
Suppose price is approaching a resistance level (in other words, a level where there was previously selling pressure, preventing the price from moving higher).
Momentum assumes the level will break.
You’re betting on continuation.Price approaches resistance, you buy, expecting it to push through and keep running.The level becomes support once broken.
Mean reversion assumes the level will hold.
You’re betting on rejection.Price approaches resistance, you short, expecting it to bounce back down.The level acts as a ceiling.
Same chart. Same resistance level. Opposite strategies.
There is no right or wrong. The key is to understand when you are in a momentum trade environment, such that momentum strategies are highly aligned.
The next section shows you exactly how to identify when the environment favours momentum (my best strategy).
Lesson 1 Summary
There are 2 trading styles: momentum and mean reversionMean reversion bets levels will hold; momentum bets levels will breakOne is not better than the other; it depends entirely on the trade environment
Lesson 2: Optimal Trade Environment
Just opening a long every time price hits resistance won't make us any money.
Without the right conditions, momentum dies immediately after the breakout.
You enter. It reverses. You're stopped out.
That's not bad luck, that's a bad trading environment.
The Rowing Analogy
Imagine you’re rowing a boat.
You either row against or with the current.
One makes it easier to row while the other takes a lot more effort.
Your boat, or rowing technique, didn’t change… Only your environment did.
Trading is the same.
Your strategy is your boat.
Your optimal trade environment is the current.
Now use this 3-filter checklist to ensure you only take trades where a breakout is likely (with the current).
Filter 1: How Did Price Approach the Level?
What you WANT:
A slow, grinding staircase pattern approaching resistance.Each candle makes incremental progress.Higher lows are stacking up.Controlled, deliberate movement.
What you DON’T want:
A fast vertical spike into resistance.Price shoots up in one or two large candles.After a spike, buyers' strength is depleted and price typically consolidates or reverses.This is exhaustion, not momentum.
The staircase pattern shows sustained buying pressure building gradually. When this breaks through resistance, buyers are still engaged and ready to push further.
Common mistake: Traders see a strong candle break resistance and assume momentum is strong. But these fast moves often reverse quickly.
→ Do this instead: Take momentum trades when price approaches resistance in a slow, grinding staircase over multiple candles.
Real Trade Example:
Slow clear grind into resistance showing an optimal ‘price approach to level’ for momentum.
Filter 1: slow grindy staircase ✅
Filter 2: What Did Volume Look Like?
Volume confirms whether the price movement has conviction behind it.
What you WANT:
Gradual increase in volume as price approaches resistanceThis pattern shows controlled, sustainable momentum.
What you DON’T want:
Flat volume (no conviction) or sudden volume spikes (exhaustion).Flat volume means the move lacks participation.Volume spikes often mark climax points where momentum exhausts.Decreasing volume (why would price break out of resistance now, if volume was lower than before?)
Volume should mirror the price pattern, steady and building, not erratic.
This strategy works because momentum continuation is most likely when participation is sustained, supply is absorbed gradually, and structure remains intact.
Real Trade Example:
Around the time the grindy staircase begins to emerge, we see a slow, consistent increase in volume.
Filter 1: slow grindy staircase ✅Filter 2: clearly increasing volume ✅
Lastly,
Filter 3: Moving Average Crossovers
This filter distinguishes trending markets (good for momentum) from choppy, indecisive markets (bad for momentum).
What you WANT to see: Moving averages with minimal crossovers. This indicates a directional trend.
What you DON’T want to see: Frequent crossovers. This signals chop and indecision.
Fewer crossovers = cleaner trend or range = better momentum continuation.
Use the 30SMMA (Smoothed Moving Average).
✍️Quick Actionable Step:
To add the 30SMMA on your charts:
Search for the Smoothed Moving Average Indicator in TradingViewAdd it to your chartGo into settings and change the "Length" to "30"
Real Trade Example:
Filter 1 (Price Action): slow grindy staircase ✅
Filter 2 (Volume): clearly increasing volume ✅
Filter 3 (Crossovers): minimal MA crossovers ✅
🎓Lesson 2 Summary
Slow grinding staircase approaches have better follow-through than fast spikesVolume should be gradual (increasing or decreasing), not flat or spikingFewer MA crossovers indicate cleaner directional conditions for momentum
Lesson 3: Identifying Setups
Now you know what momentum is.
You also know the optimal conditions for it.
Next, you need to know where to execute these trades.
Step 1: Draw Support and Resistance Levels
Momentum trades happen at these key levels. You need to identify them consistently.
I've already written an in-depth masterclass on how to set these levels. I'll link it at the end of this article.
Common mistake: Traders draw levels randomly or inconsistently, leading to missed setups or false signals.
Do this instead: Use my step-by-step approach at the end of this article.
Step 2: Await Your Entry Trigger on the 1-Minute Chart
Once you’ve identified a resistance level on your primary timeframe, switch to the 1-minute chart for precise entry timing.
Why 1-minute chart?
You learn faster.
More trades, more chart exposure and more oppurtunities to practice psychology.
I’ve added a bonus guide on why you should be trading the 1-minute chart at the end of this article.
Real Trade Example:
Step 3: Three Filters
Before entering, check the three filters from Section 2:
Is price approaching resistance in a slow staircase pattern?Is volume gradually increasing or decreasing (not flat or spiking)?Are there minimal MA crossovers (not choppy)?
If any filter fails, reduce your risk on the trade. Only take full risk on A-grade setups, not forcing trades in poor conditions.
🎓Lesson 3 Summary
Draw levels using the ZCT masterclass approach at the end of this articleUse your entry trigger on the 1-minute timeframe: 2 candle closes above for confirmationCheck all three filters before entering, allocate risk and size accordingly
Lesson 4: Strategy Logic: Stop Loss, and Take Profit
You've drawn your levels. You've confirmed the setup aligns with optimal momentum conditions.
Now you need precise execution.
Entry timing, stop placement, and profit targets determine whether you capture the momentum move or get stopped out on a good setup.
This is where most traders lose, not in analysis, but in execution.
Step 4: Entry Trigger
We have established to wait for two consecutive 1-minute candles to close fully above the resistance level. This confirms the level broke and momentum is continuing.
Critical execution detail: After the second candle closes above resistance, place a limit order AT the resistance level (now acting as support), not above it. Price often pulls back slightly after breaking out. Your limit order gets filled on the pullback without chasing.
Common mistake: Traders wait for confirmation, then market-buy above resistance as price runs away. They enter late with a wider stop and worse risk/reward.
→ Do this instead: Preset your limit order AT resistance after the second candle closes. Let price come back to you.
Real Trade Example:
Step 5: Stop Loss
A swing low is:
the lowest wick in a pullback.
Your stop loss goes at the most recent swing low before the breakout.
Common mistake: Traders place stops at the nearest swing low, even if it’s only 0.3% away, leading to frequent stop-outs from normal volatility
Do this instead: Always measure the distance of your stop loss using the ruler tool on TradingView. If it’s less than 1%, use the next swing low down.
Step 6: Take Profit 1R (Equal Distance to Stop)
Your take profit target is 1R, the same distance as your stop loss, but in the profit direction
If your stop loss is 1.982% away from entry, your target is also 1.982% away, but on the upside. This gives you a 1:1 risk/reward ratio.
Why 1R? It’s conservative and achievable. Momentum trades often hit 1R quickly because the breakout has follow-through. You’re not trying to catch the entire move, you’re taking a high-probability piece of it.
Over time, as you get data in your journal, you can start extending your profit targets when you see how far your average winning trades go beyond 1R. This way, you’re not guessing where to take profits, but following a systematic approach.
Real Trade Example:
🎓Lesson 4 summary
Enter after two 1-minute candle closes above resistance, using a limit order at prior resistance (now support) to avoid chasing price.Place stop losses at the most recent valid swing low, ensuring enough distance to avoid normal volatility and minor stop hunts.Set initial profit targets at 1R to capture high-probability momentum continuation in a repeatable, systematic way.
Immediate Next Steps✍️:
Read the Support and Resistance Masterclass to learn how to draw levels (shared at end of article)Look at 3 charts using the 3 filter checklist to identify a momentum trade environmentUse the strategy steps to enter your tradeGather 30 trades using this method, journalled and reviewed against the criteria
🎓 Final Summary
Lesson 1: Momentum vs Mean Reversion
Momentum trades bet that price will continue through a level, while mean reversion trades bet that a level will hold and reject price.Both strategies are valid, but performance depends entirely on matching the strategy to the correct trade environment.
Understanding this distinction prevents applying breakout logic in conditions where it has no edge.
Lesson 2: Optimal Trade Environment
High-quality breakouts form when price approaches resistance in a slow, grinding staircase rather than fast vertical spikes.Volume should build gradually to confirm sustained participation, not remain flat or spike from exhaustion.Minimal moving average crossovers indicate cleaner directional conditions where momentum continuation is more likely.
Lesson 3: Identifying Setups
Momentum trades should be executed at consistently drawn support and resistance levels.Entries are triggered on the 1-minute chart using two consecutive candle closes above resistance for confirmation.All three environment filters must align before taking full risk; weaker conditions require reduced sizing or passing the trade.
Lesson 4: Stop Loss and Take Profit
Enter using a limit order at prior resistance (now support) after two confirmed 1-minute candle closes to avoid chasing price.Stop losses should be placed at the most recent valid swing low with enough distance to avoid normal volatility and minor stop hunts.Initial profit targets are set at 1R to capture high-probability momentum continuation in a repeatable way.
🎓What Changes From Here
The next time price approaches resistance, you won’t have to guess if it will break out.
You’ll know when a breakout has real momentum, when volume confirms it, and when conditions support follow-through.
You’ll also execute with defined entries, stops, and targets.
#CryptoZeno #tradingStrategy #NomuraLaserDigitalOCCApproval

I’ve longed resistance and shorted support for 9 years… This is the exact opposite of what every trader tries to do.
In this article, I will share my entire strategy so you can skip years of testing and losses.
This is something you will want to bookmark, take notes on, and set time aside to think about.
Lesson 1: The Only 2 Trading Strategies
Before you can identify good momentum setups, you need to understand what momentum trading actually is.
Momentum and mean reversion are opposite strategies based on opposite assumptions.
The Two Trading Styles
Momentum (where you take a trade betting on a continuation of the current trend)Mean Reversion (where you take a trade betting on a reversal of the current trend)
One assumes strength continues; the other assumes strength exhausts.
Let’s consider this through a visual example.
Suppose price is approaching a resistance level (in other words, a level where there was previously selling pressure, preventing the price from moving higher).
Momentum assumes the level will break.
You’re betting on continuation.Price approaches resistance, you buy, expecting it to push through and keep running.The level becomes support once broken.
Mean reversion assumes the level will hold.
You’re betting on rejection.Price approaches resistance, you short, expecting it to bounce back down.The level acts as a ceiling.
Same chart. Same resistance level. Opposite strategies.
There is no right or wrong. The key is to understand when you are in a momentum trade environment, such that momentum strategies are highly aligned.
The next section shows you exactly how to identify when the environment favours momentum (my best strategy).
Lesson 1 Summary
There are 2 trading styles: momentum and mean reversionMean reversion bets levels will hold; momentum bets levels will breakOne is not better than the other; it depends entirely on the trade environment
Lesson 2: Optimal Trade Environment
Just opening a long every time price hits resistance won't make us any money.
Without the right conditions, momentum dies immediately after the breakout.
You enter. It reverses. You're stopped out.
That's not bad luck, that's a bad trading environment.
The Rowing Analogy
Imagine you’re rowing a boat.
You either row against or with the current.
One makes it easier to row while the other takes a lot more effort.
Your boat, or rowing technique, didn’t change… Only your environment did.
Trading is the same.
Your strategy is your boat.
Your optimal trade environment is the current.
Now use this 3-filter checklist to ensure you only take trades where a breakout is likely (with the current).
Filter 1: How Did Price Approach the Level?
What you WANT:
A slow, grinding staircase pattern approaching resistance.Each candle makes incremental progress.Higher lows are stacking up.Controlled, deliberate movement.
What you DON’T want:
A fast vertical spike into resistance.Price shoots up in one or two large candles.After a spike, buyers' strength is depleted and price typically consolidates or reverses.This is exhaustion, not momentum.
The staircase pattern shows sustained buying pressure building gradually. When this breaks through resistance, buyers are still engaged and ready to push further.
Common mistake: Traders see a strong candle break resistance and assume momentum is strong. But these fast moves often reverse quickly.
→ Do this instead: Take momentum trades when price approaches resistance in a slow, grinding staircase over multiple candles.
Real Trade Example:
Slow clear grind into resistance showing an optimal ‘price approach to level’ for momentum.
Filter 1: slow grindy staircase ✅
Filter 2: What Did Volume Look Like?
Volume confirms whether the price movement has conviction behind it.
What you WANT:
Gradual increase in volume as price approaches resistanceThis pattern shows controlled, sustainable momentum.
What you DON’T want:
Flat volume (no conviction) or sudden volume spikes (exhaustion).Flat volume means the move lacks participation.Volume spikes often mark climax points where momentum exhausts.Decreasing volume (why would price break out of resistance now, if volume was lower than before?)
Volume should mirror the price pattern, steady and building, not erratic.
This strategy works because momentum continuation is most likely when participation is sustained, supply is absorbed gradually, and structure remains intact.
Real Trade Example:
Around the time the grindy staircase begins to emerge, we see a slow, consistent increase in volume.
Filter 1: slow grindy staircase ✅Filter 2: clearly increasing volume ✅
Lastly,
Filter 3: Moving Average Crossovers
This filter distinguishes trending markets (good for momentum) from choppy, indecisive markets (bad for momentum).
What you WANT to see: Moving averages with minimal crossovers. This indicates a directional trend.
What you DON’T want to see: Frequent crossovers. This signals chop and indecision.
Fewer crossovers = cleaner trend or range = better momentum continuation.
Use the 30SMMA (Smoothed Moving Average).
✍️Quick Actionable Step:
To add the 30SMMA on your charts:
Search for the Smoothed Moving Average Indicator in TradingViewAdd it to your chartGo into settings and change the "Length" to "30"
Real Trade Example:
Filter 1 (Price Action): slow grindy staircase ✅
Filter 2 (Volume): clearly increasing volume ✅
Filter 3 (Crossovers): minimal MA crossovers ✅
🎓Lesson 2 Summary
Slow grinding staircase approaches have better follow-through than fast spikesVolume should be gradual (increasing or decreasing), not flat or spikingFewer MA crossovers indicate cleaner directional conditions for momentum
Lesson 3: Identifying Setups
Now you know what momentum is.
You also know the optimal conditions for it.
Next, you need to know where to execute these trades.
Step 1: Draw Support and Resistance Levels
Momentum trades happen at these key levels. You need to identify them consistently.
I've already written an in-depth masterclass on how to set these levels. I'll link it at the end of this article.
Common mistake: Traders draw levels randomly or inconsistently, leading to missed setups or false signals.
Do this instead: Use my step-by-step approach at the end of this article.
Step 2: Await Your Entry Trigger on the 1-Minute Chart
Once you’ve identified a resistance level on your primary timeframe, switch to the 1-minute chart for precise entry timing.
Why 1-minute chart?
You learn faster.
More trades, more chart exposure and more oppurtunities to practice psychology.
I’ve added a bonus guide on why you should be trading the 1-minute chart at the end of this article.
Real Trade Example:
Step 3: Three Filters
Before entering, check the three filters from Section 2:
Is price approaching resistance in a slow staircase pattern?Is volume gradually increasing or decreasing (not flat or spiking)?Are there minimal MA crossovers (not choppy)?
If any filter fails, reduce your risk on the trade. Only take full risk on A-grade setups, not forcing trades in poor conditions.
🎓Lesson 3 Summary
Draw levels using the ZCT masterclass approach at the end of this articleUse your entry trigger on the 1-minute timeframe: 2 candle closes above for confirmationCheck all three filters before entering, allocate risk and size accordingly
Lesson 4: Strategy Logic: Stop Loss, and Take Profit
You've drawn your levels. You've confirmed the setup aligns with optimal momentum conditions.
Now you need precise execution.
Entry timing, stop placement, and profit targets determine whether you capture the momentum move or get stopped out on a good setup.
This is where most traders lose, not in analysis, but in execution.
Step 4: Entry Trigger
We have established to wait for two consecutive 1-minute candles to close fully above the resistance level. This confirms the level broke and momentum is continuing.
Critical execution detail: After the second candle closes above resistance, place a limit order AT the resistance level (now acting as support), not above it. Price often pulls back slightly after breaking out. Your limit order gets filled on the pullback without chasing.
Common mistake: Traders wait for confirmation, then market-buy above resistance as price runs away. They enter late with a wider stop and worse risk/reward.
→ Do this instead: Preset your limit order AT resistance after the second candle closes. Let price come back to you.
Real Trade Example:
Step 5: Stop Loss
A swing low is:
the lowest wick in a pullback.
Your stop loss goes at the most recent swing low before the breakout.
Common mistake: Traders place stops at the nearest swing low, even if it’s only 0.3% away, leading to frequent stop-outs from normal volatility
Do this instead: Always measure the distance of your stop loss using the ruler tool on TradingView. If it’s less than 1%, use the next swing low down.
Step 6: Take Profit 1R (Equal Distance to Stop)
Your take profit target is 1R, the same distance as your stop loss, but in the profit direction
If your stop loss is 1.982% away from entry, your target is also 1.982% away, but on the upside. This gives you a 1:1 risk/reward ratio.
Why 1R? It’s conservative and achievable. Momentum trades often hit 1R quickly because the breakout has follow-through. You’re not trying to catch the entire move, you’re taking a high-probability piece of it.
Over time, as you get data in your journal, you can start extending your profit targets when you see how far your average winning trades go beyond 1R. This way, you’re not guessing where to take profits, but following a systematic approach.
Real Trade Example:
🎓Lesson 4 summary
Enter after two 1-minute candle closes above resistance, using a limit order at prior resistance (now support) to avoid chasing price.Place stop losses at the most recent valid swing low, ensuring enough distance to avoid normal volatility and minor stop hunts.Set initial profit targets at 1R to capture high-probability momentum continuation in a repeatable, systematic way.
Immediate Next Steps✍️:
Read the Support and Resistance Masterclass to learn how to draw levels (shared at end of article)Look at 3 charts using the 3 filter checklist to identify a momentum trade environmentUse the strategy steps to enter your tradeGather 30 trades using this method, journalled and reviewed against the criteria
🎓 Final Summary
Lesson 1: Momentum vs Mean Reversion
Momentum trades bet that price will continue through a level, while mean reversion trades bet that a level will hold and reject price.Both strategies are valid, but performance depends entirely on matching the strategy to the correct trade environment.
Understanding this distinction prevents applying breakout logic in conditions where it has no edge.
Lesson 2: Optimal Trade Environment
High-quality breakouts form when price approaches resistance in a slow, grinding staircase rather than fast vertical spikes.Volume should build gradually to confirm sustained participation, not remain flat or spike from exhaustion.Minimal moving average crossovers indicate cleaner directional conditions where momentum continuation is more likely.
Lesson 3: Identifying Setups
Momentum trades should be executed at consistently drawn support and resistance levels.Entries are triggered on the 1-minute chart using two consecutive candle closes above resistance for confirmation.All three environment filters must align before taking full risk; weaker conditions require reduced sizing or passing the trade.
Lesson 4: Stop Loss and Take Profit
Enter using a limit order at prior resistance (now support) after two confirmed 1-minute candle closes to avoid chasing price.Stop losses should be placed at the most recent valid swing low with enough distance to avoid normal volatility and minor stop hunts.Initial profit targets are set at 1R to capture high-probability momentum continuation in a repeatable way.
The next time price approaches resistance, you won’t have to guess if it will break out.
You’ll know when a breakout has real momentum, when volume confirms it, and when conditions support follow-through.
You’ll also execute with defined entries, stops, and targets.
#CryptoZeno #BNBBreaks740USDTUp12Percent

There’s a far deeper level of understanding in the market than most people realize. Beyond technical analysis, there’s something few truly consider, and that, my friends, is the mathematics behind trading. Many enter this space with the wrong mindset, chasing quick moves, seeking fast gains, and using high leverage without a proper system. But when leverage is applied correctly within a structured, math-based system, that’s precisely how you outperform the entire market.
Today, I’ll be discussing a concept that can significantly amplify trading returns when applied correctly, a methodology leveraged by institutional capital and even market makers themselves. It enables the strategic sizing of positions while systematically managing and limiting risk.
Mastering Market Structure: Trading Beyond Noise and News
When employing an advanced market strategy like this, a deep understanding of market cycles and structure is essential. Traders must remain completely objective, avoiding emotional reactions to noise or news, and focus solely on execution. As I often say, “news is priced in”, a lesson honed over six years of market experience. Headlines rarely move prices; more often, they serve as a justification for moves that are already in motion. In many cases, news is simply a tool to distract the herd.
To navigate the market effectively, one must understand its clinical, mechanical nature. Assets generally experience predictable drawdowns before retracing, and recognizing the current market phase is critical. This requires a comprehensive view of the higher-timeframe macro structure, as well as awareness of risk-on and risk-off periods, when capital inflows are driving market behavior. All of this is validated and reinforced by observing underlying market structure.
A Simple Illustration of the Bitcoin Market Drawdown:
As we can observe, Bitcoin exhibits a highly structured behavior, often repeating patterns consistent with what many refer to as the 4 year liquidity cycle. In my view, Bitcoin will decouple from this cycle and the diminishing returns effect, behaving more like gold, silver, or the S&P 500 as institutional capital, from banks, hedge funds, and large investors, flows into the asset. Bitcoin is still in its early stages, especially when compared to the market cap of larger asset classes.
While cycle timings may shift, drawdowns are where institutions capitalize making billions of dollars. This example is presented on a higher time frame, but the same principles apply to lower time frame drawdowns, provided you understand the market’s current phase/trend. Multiple cycles exist simultaneously: higher-timeframe macro cycles and lower-to-mid timeframe market phase cycles, where price moves through redistribution and reaccumulation. By understanding these dynamics, you can apply the same approach across both higher and lower time frame cycles.
Examining the illustration above, we can observe a clear evolution in Bitcoin’s market drawdowns. During the first cycle, Bitcoin declined by 93.78%, whereas the most recent drawdown was 77.96%. This represents a meaningful reduction in drawdown magnitude, indicating that as Bitcoin matures, its cycles are producing progressively shallower corrections. This trend is largely driven by increasing institutional adoption, which dampens volatility and reduces the depth of pullbacks over time.
Using the S&P 500 as a reference, over the past 100 years, drawdowns have become significantly shallower. The largest decline occurred during the 1929 crash, with a drop of 86.42%. Since then, retracements have generally remained within the 30–60% range. This historical pattern provides a framework for estimating the potential maximum drawdown for an asset class of this scale, offering a data-driven basis for risk modeling.
Exploiting Leverage: The Mechanism Behind Multi-Billion Dollar Gains
This is where things start to get interesting. When applied correctly, leverage, combined with a solid mathematical framework, becomes a powerful tool. As noted at the start of this article, a deep understanding of market dynamics is essential. Once you have that, you can optimize returns by applying the appropriate leverage in the markets.
By analyzing historical price retracements, we can construct a predictive model for the likely magnitude of Bitcoin’s declines during bear markets aswell as LTF market phases. Even if market cycles shift or Bitcoin decouples from the traditional four-year cycle, these downside retracements will continue to occur, offering clear opportunities for disciplined, math-driven strategies.
Observing Bitcoin’s historical cycles, we can see that each successive bear market has produced progressively shallower retracements compared to earlier cycles. Based on this trend, a conservative estimate for the potential drawdown in 2026 falls within the 60–65% range. This provides a clear framework for identifying opportunities to capitalize when market conditions align.
While this estimate is derived from higher-timeframe retracements, the same methodology can be applied to lower-timeframe cycles, enabling disciplined execution across different market phases.
For example, during a bull cycle with an overall bearish trend, one can capitalize on retracements within the bull phases to position for the continuation of upward moves. Conversely, in a bearish trend, the same principle applies for capturing downside movements, using historical price action as a guide.
We already know that retracements are becoming progressively shallower, which provides a structured framework for planning positions. Based on historical cycles, Bitcoin’s next retracement could reach the 60–65% range. However, large institutions do not aim for pinpoint entry timing, it’s not about catching the exact peak or bottom of a candle, but rather about positioning at the optimal phase. Attempting excessive precision increases the risk of being front-run, which can compromise the entire strategy.
Using the visual representation, I’ve identified four potential zones for higher-timeframe long positioning. The first scaling zone begins around –40%. While historical price action can help estimate future movements, it’s important to remember that bottoms cannot be predicted with 100% accuracy, especially as cycles evolve and shift.
This is why it is optimal to begin scaling in slightly early, even if it occasionally results in positions being invalidated.
In the example above, we will use 10% intervals to define invalidation levels. Specifically, this setup is for 10x leverage. Based on historical cycle retracements, the statistical bottom for Bitcoin is estimated around $47K–$49K. However, by analyzing market cycles and timing, the goal is to identify potential trend shifts, such as a move to the upside, rather than trying to pinpoint the exact entry.
Applying this framework to a $100K portfolio, a 10% price deviation serves as the invalidation threshold. On 10x leverage, a 10% drop would trigger liquidation; with maintenance margin, liquidation might occur slightly earlier, around a 9.5% decline. It is crucial to note that liquidation represents only a fraction of the allocated capital, as this strategy operates on isolated margin. For a $100K portfolio, each leveraged position risks $10K.
This approach is what I refer to as “God Mode,” because, when executed with a thorough understanding of market phases and price behavior, it theoretically allows for asymmetric risk-reward opportunities and minimizes the chance of outright losses.
The Mathematics
Now, if we run a mathematical framework based on $100K, each position carries a fixed risk of $10K. We have six entries from different price levels. If you view the table in the top left-hand corner, you can see the net profit based on the P&L after breaking the current all-time high.
Considering inflation and continuous money printing, the minimum expected target after a significant market drawdown is a new all-time high. However, this will occur over a prolonged period, meaning you must maintain conviction in your positions. At different price intervals, the lower the price goes, the greater the profit potential once price breaks $126K.
Suppose you were extremely unlucky and lost five times in a row. Your portfolio would be down 50%, with a $50K loss. Your $100K pool would now sit at $50K. Many traders would become frustrated with the risk, abandon the system, and potentially lose everything.
However, if you follow this mathematical framework with zero emotion, and the sixth entry hits, even while being down 50%, the net profit achieved once price reaches a new all-time high would be $193,023. Subtracting the $50K loss, the total net profit is $143,023, giving an overall portfolio of $243,023, a 143% gain over 2–3 years, outperforming virtually every market.
On the other hand, if the third or fourth entry succeeds, losses will be smaller, but you will still achieve a solid ROI over time. Never underestimate the gains possible on higher timeframes.
It is important to note that experienced traders with a strong understanding of market dynamics can employ higher leverage to optimize returns. This framework is modeled at 10x leverage; however, if one has a well-founded estimate of Bitcoin’s likely bottom, leverage can be adjusted to 20x or even 30x. Such elevated leverage levels are typically employed only by highly experienced traders or institutional participants.
Many of the swing short and long setups I share follow a consistent methodology: using liquidation levels as position invalidation and leverage to optimize returns. Traders often focus too rigidly on strict risk-reward ratios, but within this framework, the mathematical approach dictates that the liquidation level serves as the true invalidation point for the position.
This is how the largest institutions structure their positions, leveraging deep market insights to optimize returns through strategic use of leverage.
Extending the same quantitative methodology to lower-timeframe market phases:
Using the same quantitative methodology, we can leverage higher-timeframe market cycles and trend positioning to inform likely outcomes across lower-timeframe phases and drawdowns. As previously noted, this requires a deep understanding of market dynamics, the specific phases, and our position within the cycle.
Recognizing when the market is in a bullish trend yet experiencing distribution phases, or in a bearish trend undergoing bearish retests, enables precise application of the framework at lower timeframes. This systematic approach is why the majority of my positions succeed because its a market maker strategy.
This methodology represents the exact structure I employ for higher-timeframe analysis and capitalization. By analyzing trend direction, if I identify a structural break within a bullish trend, or conversely, within a downtrend, I can apply the same leverage principles at key drawdown zones, using market structure to assess the most probable outcomes.
#CryptoZeno #NomuraLaserOCCTrustApproval

If you’re a trader, you can’t afford to miss this.
I will show you how to use Claude to review your Trade Journal (journal + prompts included).
What you'll have when you're done:
A repeatable monthly review process that turns raw trade data into rules you can actually tradeA clear path from observation → hypothesis → tested ruleOptional: Claude reading your trading journal directly off your laptop to speed up the analysis (no context limit failures, no matter how big the journal gets)
Difficulty: Beginner. No coding required. You'll be writing prompts in plain English.
Let's begin.
Why journal insights even matter
You’re right to ask this question.
Time is valuable. So why should you, as an aspiring trader, spend it reviewing your journal for insights?
Why not, for example, spend it taking more trades?
The reason is that a good journal review process starts an improvement chain:
A good journal review process starts an improvement chain
You can also understand the importance of journal reviews through an inversion exercise. I got this idea from Charlie Munger.
So far, I've discussed why you should be reviewing your journal. Now, let's take a different approach:
How would I guarantee I fail for as long as possible as a trader?
To guarantee failure as a trader, I would:
Never keep a trade journalBlame losses on luckAttribute wins to skillNever change my strategy based on data
If our goal is to avoid guaranteed failure, then we should do the opposite of the above.
Now you understand the why, let’s move on to the how.
Part 1: Get your free journal, 1:1 review session and custom Claude assistant
I’ve put together a few things to help you.
My 2026 free trading journal. You need a journal to complete a journal review. I’ve built one you can use with all the necessary features.A free 1:1 journal review session with my team. Yes, a real call with a real human. In case you’d like some 1 on 1 help with your journal review.A custom Claude assistant to edit your journal. Go beyond the default view access. Claude will be able to edit your journal and write formulas for you.
(If you have your own journal you want to use, that’s fine. Just make sure it covers the key inputs in Part 3)
Part 2: Connect Claude (Optional)
You can run this entire process manually if you want. The goal of using Claude is to speed up your review and go deeper into pattern recognition.
If you want to use it, here's the setup (5 minutes):
Step 1: Open Claude ChatStep 2: Download your journal as an excel file (File → Download → Microsoft Excel) and save it into the folder.Step 3: Paste your file into a chat
That’s it for now.
Part 3: Key inputs
These are the key pieces of data we need to track for a good journal review:
The key pieces of data we need to track for a good journal review
I'll break down how you can use these to build profitable strategies in step 2.
Part 4: The monthly review
You should do a big research review once a month. This is different to your lighter, maintenance style weekly review.
Maintenance review = Weekly review. Easy quick review: opening screenshots, seeing what's working and what's not in the current week/market condition.Research review = Monthly review that is more in-depth, diving into data, finding ways to improve your strategy, rules, and framework.
30 is the golden number of trades for a review.
30 is the golden number of trades for a review.
This gives you enough data for patterns to emerge without waiting so long that you've accumulated months of unexamined mistakes.
(For the maths nerds: 30 is the minimum threshold for statistical significance.)
If you have fewer than 30, you can still do your review, but know that your data is less reliable.
Step 1: Begin with the most important statistics
Before you dive into specific patterns or individual trades, you need to answer a fundamental question: is your system making money, losing money, or breaking even?
If you’re on my free journal, head over to the analytics tab and use the ‘Last Month’ feature.
The most important statistics here are:
Expected Value or Expectancy: This tells you if your strategy is profitable.Trade Frequency: This tells you if your strategy gives you enough opportunities.
The most important statistics are: Expectancy and Trade Frequency
Your expectancy is built from two things:
Win rate: What percentage of your trades are winners?Risk-reward ratio (R:R): When you win, how much do you win relative to what you lose?
Once you've calculated your expectancy, you can identify whether your problem is:
Win rate too low: You're taking too many losing trades. The fix lives in trade selection and asset selection.Average loss too large: Your losers are bigger than they should be. The fix lives in trade management.Average win too small: You're cutting winners short or your targets are too tight. The fix lives in trade management and target optimisation.
To improve trade frequency, you can do:
Horizontal expansion: Test and iterate your same strategy in different markets. Trade new assets and markets.Vertical expansion: Build new strategies to trade the same assets.
With Claude (helpful if your journal does not have an analytics tab similar to mine, or you want to sense check which of your statistics is currently dragging down your profitability)
Paste to chat:
Read my trading journal in this folder. Look at the last 30 trades.
Calculate:
1. Expected value per trade
2. Win rate
3. Average win, average loss, and risk-reward ratio
4. Trade frequency (trades per week)
Show me the numbers, then tell me in one paragraph: is my main
problem win rate, average loss, or average win?
Example:
Step 2: Filter by strategy and market
Your overall expectancy might look mediocre. But that single number hides critical information.
It's possible that one strategy is highly profitable while another is bleeding you.
Or that you're profitable in certain markets but consistently losing in others.
Market (Coin).
You will often find a select few assets responsible for most of your gains or losses.
Trade those more.
You will often find a select few assets responsible for most of your gains or losses.
Strategy.
Focus on the ONE strategy that makes you the most money and ignore everything else until you have mastered that.
Without a journal, you’ll never know what that one strategy is.
Focus on the ONE strategy that makes you the most money
With Claude (this is helpful if you don’t want to be tabbing between the filters to grab each metric and just want one clear snapshot. It’s also useful to grab the specific 30 number rather than a time duration view):
Paste to chat:
From the last 30 trades in my journal, pull only the rows where
Win/Loss is W or L. Show me trade count, win rate, and net P/L
broken down by:
1. Strategy
2. Market
3. Long/Short
4. Setup Grade
5. Strategy × Direction
6. Strategy × Market
Flag any group where N ≥ 5 and win rate is above 55% or below 40%.
For each flag, give me a one-line hypothesis for why that might
be happening.
The flag list at the bottom is the important part. Those are the cuts worth investigating in Step 4.
Example:
Step 3: Trade Management
Position Size and Emotional Journal.
Pay close attention to these two; they’re often correlated. If you're risking a consistent percentage on every trade, your results reflect your strategy's true performance.
But if your position sizes vary based on how you're feeling, your equity curve becomes unreliable.
Daily Report Card.
Find and eliminate your weak points. Look for repeat patterns and behaviours.
E.g. When I lose 3 trades in a row my execution goes down the drain, new trading rule: I stop trade after 3 losses
Find and eliminate your weak points. Look for repeat patterns and behaviours.
R:R.
I’ve actually seen a wide range of performance here.
Some traders kill it on 1:1 risk to reward ratios. Don’t think you need high ratios to win.
Reason for Cutting The Trade & Cut Result
Find ways to cut your losers quicker and keep them smaller than your winners. Track why you exited and whether it was the right call (over time, the patterns become obvious)
Trade Duration.
Every trade you take has a duration: the time between entry and exit. How long is your average winner? How long is your average loser?
Turn this info into alpha.
With Claude (This is Claude’s superpower. Reading through written insights, spotting correlations and patterns. If you tried this manually, it would take you all day, and you wouldn’t be able to retain the patterns at scale. I’ve written you example commands, but my goal is that after running this, you know how to write whatever commands you like. Whatever pattern you want to spot, you can run a similar analysis):
Patterns in language are exactly what Claude is good at finding. Paste to chat:
From the full journal history (not just the last 30 trades), look
at the Position Size and Daily Report Card / Emotional Journal
columns.
1. Surface any recurring language around emotional state — words
like "revenge," "hesitated," "overconfident," "FOMO," "tired,"
"rushed." For each pattern, give me the dates it appeared and
whether trades on those days were net winners or losers.
2. Check if position size correlates with emotional state.
3. Look at trade duration — what's the average duration of my
winners versus losers?
4. From the "Reason for Cutting" column, surface the most common
exit reasons and whether they led to good or bad outcomes.
5. Analyze my daily trade count to understand performance by trades of the day.
6. Analyze average daily performance of winning/losing days to introduce more optimal risk management guidelines.
Example:
I'm using the full history here, not just the last 30 trades. So you need to give Claude some time to cook.
Behavioural patterns need more data to surface, they cluster around specific events like losing streaks and big wins that might only appear a few times across a longer window.
If a word keeps showing up on losing days, that's your trigger. Once you can name it, you can build a rule around it, which is exactly where Step 4 starts.
Step 4: The insight formalisation process
Every insight follows the same path from observation to implemented rule:
Observation → Hypothesis → Specific Rule → Tracking Mechanism → Evaluation
Here's how each step works:
Observation: "I noticed my momentum trades seem to lose more often when price spikes into the level."Hypothesis: "Momentum trades perform better when price grinds into the level versus when it spikes."Specific Rule: "Do not take momentum trades when price approaches the level via a fast vertical spike (defined as: a single candle moving 2%+ into the level within 1-2 candles)."Tracking Mechanism: Add a column to your journal that records whether each trade met or violated this rule. Track the outcome.Evaluation: After 30 trades, compare the win rate of trades that followed the rule versus trades that would have been filtered out by it.
Notice how the rule is specific enough to be testable. "Don't trade spikes" is vague. "Don't take momentum trades when a single candle moves 2%+ into the level" is precise. You can look at any trade and definitively say whether it met the criteria or not.
With Claude (here you are using Claude as a second brain. This targets the trading psychology aspect. Sometimes we want to force patterns and rules. Or we are more inclined to find reasons why they work rather than to invalidate them. Claude keeps you in check).
Use Claude as a pressure-tester. Paste:
I have a fuzzy observation from my journal review:
"[your observation, e.g. Mean Reversion shorts seem to be my best setup]."
Walk it through this framework:
1. Pressure-test it. Is it likely real or sample noise? Is the
variable I think is driving it actually doing the work, or is
there a confound?
2. Translate it into a falsifiable rule. Every clause must answer:
what counts, what doesn't.
3. Suggest journal columns I should add to track it.
4. Propose a sample size and pass/fail thresholds.
5. Define what action I should pre-commit to if it passes, and
what I'll change if it fails.
Push back on any of my clauses if they're vague. Don't let me get
away with words like "often" or "usually."
One last thing: when Claude proposes the rule, ask it the question most traders never ask themselves:
#CryptoZeno #SuiMainnetResumes

VWAP doesn't need to be complicated.
I'll use my 9 years of trading experience to give you the most practical VWAP guide on the internet.
This is a full guide with real examples, not just theory.
Let’s begin.
Lesson 1: What is VWAP?
VWAP = Volume Weighted Average Price
Instead of treating every price move equally, it weights the price by trading volume to show you the real average price of the day
Think of it as an anchor price that the market is gravitating around
Here’s what VWAP looks like on the charts:
The blue line is VWAP: the true average price adjusted for volumeThe purple bands expand 1 standard deviation above (upper band) and 1 standard deviation below (lower band) the VWAP to show how far the price is stretching from that average
Why VWAP matters
Random spikes/dumps can trick you if no volume is behind them
VWAP filters that noise and shows where the real market commitment is
Example: if 90% of trades happen at $10 but the price briefly spikes to $12, VWAP stays near $10. Reflecting the fact that the upward move was only a quick deviation from the overall trend.
Here are my TradingView settings for VWAP
Anchor: Session (resets daily)Bands: ±1 standard deviationStyle: VWAP in light blue and bands in dark blue/ purple
VWAP acts as the anchor price for the day, while the bands show how far the price is deviating from that anchor
This is our base before applying VWAP in real trades
3 Key Signals of VWAP
When it comes to VWAP, isolate 3 key signals for your analysis.
1. Position of VWAP <> Price: Breakouts or breakdowns?
Price trending above VWAP = strong uptrend = favours breakouts (momentum longs)Price trending below VWAP = strong downtrend = favours breakdowns (momentum shorts)
BONUS: We can also consider the position of price relative to the lower and upper bands. In an uptrend, if the price is above both the VWAP and the upper band, there is even more strength in the uptrend. Similarly, in a downtrend, if the price is below both the VWAP and the lower band, there is more strength in the downtrend.
2. The slope of the VWAP: Is price trending or ranging?
This shows you the direction and conviction behind a move. The steeper the slope, the more aggressive a trend is, making it simpler to take trades in that direction.
Steeper slope = price trending = favours momentum tradesFlat slope = price ranging = favours reversal trades
BONUS: another observation we can make with the slope of the VWAP is the number of crossovers. How many times does the VWAP cross over the price? This is an additional confluence point whereby fewer crossovers favour momentum.
3. VWAP Bands = Is continuation or reversal more likely?
When bands widen, it means price is pulling away from VWAP with momentum. When bands tighten, it means the market is hesitating, and momentum is fading.
Wide bands = strength behind the move = favours continuation = trade momentumTight bands = weakness behind the move = favours reversals = trade mean reversion
Lesson 1: VWAP Summary
VWAP (Volume Weighted Average Price) = the true average price of the day, weighted by volume, not just price movementActs as an anchor price the market gravitates around, filtering out low-volume spikes and noiseThe bands sit ±1 standard deviation above/below VWAP, showing how far the price is stretching from the average3 Key Signals:Price vs. VWAP. Above = uptrend, below = downtrendSlope. Steeper = price trending, flat = price rangingBandwidth. Wide = strength behind the move, tight = weakness behind the move
BONUS: Find Out Your Trading Level
Just a quick note here to say I recommend that traders introduce indicators like VWAP when they reach level 3 in my trader roadmap.
If you want:
To find out your personal trading levelA personalised gameplan from my team on how to improve (for free)
Lesson 2: VWAP for Breakout Strategies
When you take a momentum trade, you are essentially betting on a continuation of the trend
In a breakout strategy, that is, a continued uptrend
In a breakdown strategy, that is, a continued downtrend
So we look to the VWAP for clues of strength in the trend. Recapping what was covered in the last section:
1. Directional bias
Price trending above VWAP = strong uptrend = favours breakouts (momentum longs)Price trending below VWAP = strong downtrend = favours breakdowns (momentum shorts)
2. Strategy bias
Steeper VWAP slope = price trending = favours momentum tradesWide VWAP bands = strength behind the move = favours continuation = trade momentum
Now, let’s consider some real trade examples
Super clean breakdown trade from Brandon here
Directional bias is a downtrend with price trending below both the VWAP and the lower band too
In terms of strategy bias, we can see that right as price approaches the previous day's low, the slope of the VWAP steepens, and the bands of the VWAP widen
This example is from coach Josh on my team
Some traders may have thought they ‘missed’ the move here. However, in crypto, a lot of the time, the price continues to run higher
By observing the steep slope of the VWAP and the continued widening of the bands, Josh was able to grab a momentum trade in this uptrend (as indicated by price trending above both VWAP and the upper band).
Lesson 2: VWAP for Breakout Strategies Summary
Momentum trades = betting on trend continuation. Uptrend in a breakout, downtrend in a breakdownLook to VWAP for signs of trend strength before enteringTwo key signals that favour continuation:1. Steeper VWAP slope = price trending = favours momentum trades2. Wide VWAP bands = strength behind the move = favours continuation = trade momentumPrice position confirms direction. Above VWAP for longs, below for shorts
Lesson 3: VWAP for Reversal Strategies
When you take a reversal trade, you are basically betting on a reversal of the trend
So in the VWAP, we want to see evidence of weakening of the trend.
Strategy bias:
Flat slope = price ranging = favours reversal tradesTight bands = weakness behind the move = favours reversals = trade mean reversion
VWAP is telling you that the market is choppy, and this is where reversal trades perform best
Now, let’s consider some real trade examples
Brandon captured an excellent reversal short here.
You can see that the bands of the VWAP are tight, forming a close range and the slope of the VWAP is almost entirely flat
In this trade example, Kim avoided the fakeout
Despite the price moving higher in what may have looked like a continuation play, he observed that the VWAP stayed in a tight range with a flat slope. Notice in this example that there are also multiple crossovers of the VWAP with the price
He was able to appropriately classify this as a reversal play
#CryptoZeno #SolsticeInstitutionsCryptoInfra

My job everyday is to come to the table, look around and decide where could certain hands move price or force itself into the books in order to move price.
At least on the lower time frames I do this through tools like open interest, funding rates, live liquidations, delta, plus some intuition from repeatedly seeing the same patterns of liquidity repeated after years of watching the same market. These are the tools which give me the ability across a fragmented BTC market to identify where people are positioning, which side they are on, and which moves could force their hand.
I like to frame my thinking around a single quesiton before getting into a position:
Has the market priced this in yet?
If it hasn't been priced in then there's edge in what i'm trying to execute from. If I see the market has priced it in already then the edge has diminished and the trade is no longer there.
A good example of this is when looking for trapped traders, specifically looking at whether open interest has decreased or not to spot whether those "trapped positions" have forced their position back into the market.
The end goal is to position myself into the market early enough to exploit something Ive seen which I believe the market hasn't priced in yet.
Another great example of this, is through understanding liquidity in particular how thin books can allow for exaggerated price movements. If you pair that alongside trapped positioning you will very often get a very nice mean reversion setup.
A common misconception is that "thin books" can only be identified in real time and through looking at the dom. This is not true. Using volume candles or looking at how far price moved in relation to how much volume pushed it can help answer this question too. Alongside identifying surges in open interest to help identify trapped positions.
It's about finding your thesis for why you should get paid from the trade you want to take, then going to the technical board and figuring out which tools will help identify this in real time.
Don't pick random tools and use them because they look fancy, think about where your edge comes from (at route level) then decide which tools allow you to spot that mispriced event faster and in a more reliable manner than anyone else could.
A fast move into a predictable stop/tp zone that happens unusually fast relative to local regime is one thing I commonly look for. These moves are often engineered, meaning someone/group of people have forced price to a certain local level for liquidity purposes.
> Force price up
> Stops/liquidations triggered
> Limit sell orders filled
> No real conviction
> Price reverses
This requires some level of intuition to reliably identify, but in essence upon a break of a level I want to see excessive buying in the form of aggressive stops being hit or liquidations being forced into the book. Both offer up opportunity for opposing side limits to be filled, and if the move was manufactured or deliberately pushed up in this manner, theres no real conviction behind it, allows for a easy reversal.
It all comes down the fact that if I know why i'm looking for something at a certain location, that can be transferred over much easier than just punting random levels without reasoning.
Think about who you are trading against and how you can profit off that info before it is priced in, you are in the research business.
#CryptoZeno #SuiMainnetResumes

In my 9 years trading crypto, this is the most profitable indicator I've used
This is a full guide with real examples, not just theory.
Let's begin:
Lesson 1: Market Conditions
Every strategy has an environment where it thrives and an environment where it bleeds.
A momentum trade in a choppy range gets stopped out.A mean reversion trade in a clean trend gets run over.
The main problem is that “conditions” feel subjective.
After reading this, you will be able to classify any chart as ideal, average, or poor conditions for your trading style.
First, let's understand the tool that enables classification:
Moving Averages
Raw price action is noisy.
Two traders can look at the same chart and disagree about whether it’s trending or choppy.
A moving average solves this by compressing recent price history into a single line.
More specifically, we focus on the 30SMMA.
Why 30 Specifically?
After testing multiple periods, 30 provides the best balance between responsiveness and stability.
Shorter periods (like 7) react too quickly and create noise in the indicator itself.Longer periods (like 100) react too slowly and miss changes in conditions.
The 30MA sits in the middle. It paints a clear picture of when trends start, flatten, and reverse, without overreacting to every candle.
How does the 30SMMA work?
The 30 Smoothed Moving Average (30 SMMA) calculates the average closing price of the last 30 candles.
It takes the close of each of those 30 candles, adds them together, and divides by 30
The result is a single point on the chart.
As each new candle closes, the oldest candle drops off, and the newest one enters the calculation.
This creates a continuously updating line.
The 30MA uses only price data in its formula.
The 30MA is a price-derived indicator.
This distinguishes it from counting indicators like volume or open interest, which measure market activity independent of price.
What the 30MA Shows You
The 30MA filters short-term noise and reveals the general direction of price.
Think of it like viewing a river from a helicopter instead of standing in it:
While standing in the river, every ripple feels significant.From above, you see only the overall direction of flow.The MA smooths out the ripples so you can see where the price is generally heading.
What does the "30" mean?
The “30” means 30 candles, but what those candles represent depends on your chart timeframe.
On a 1-minute chart, the 30MA shows the average price over the last 30 minutes.On a 1-hour chart, the same indicator shows the average price over the last 30 hours.
The calculation is identical, but the timeframe changes what those 30 candles represent.
The Three MA Directions
In its simplest form, the 30MA shows you the smoothed price direction. There are only three possibilities:
Upward: The line slopes up. Price has generally been rising.Sideways: The line is flat or nearly flat. No clear direction.Downward: The line slopes down. Price has generally been falling.
Common mistake: Many traders expect the MA to tell them where price will go next.
It won’t.
The MA only summarises what already happened.
Lesson 2: Setting Up the 30 SMMA and Reading Crossovers
You now understand what the 30MA is and why it matters.
Next, we will cover:
How to configure it correctly on TradingViewHow to count crossovers, the specific measurement you’ll use to classify conditions in Lessons 3 and 4
By the end, you will be able to set up the 30 SMMA with the correct settings and count crossovers on any chart using standardised rules.
Follow these steps exactly for the Setup:
Click the “Indicators” button on TradingView.Search for “SMMA.”Select “Smoothed Moving Average” and add it to your chart.Click the settings gear icon on the indicator.Change “Length” from the default to 30.Verify “Source” is set to Close.Verify “Timeframe” is set to Chart (not a fixed timeframe).Click OK.
Remember: Always verify length = 30 after adding the indicator. This setting is "7" by default, and using this will change your MA.
Now that your MA is setup, let's explore what it's behaviour means:
What Is a Crossover?
A crossover occurs when price moves from one side of the 30MA to the other.
If price is above the MA and moves below it, that’s one crossover.If price then moves back above, that’s another.
Each yellow circle represents one crossover. The total count on this chart is three.
Crossovers matter because they measure how much price is fighting the MA versus respecting it.
A low count means price is staying on one side. One group (buyers or sellers) is in control.A high count means price keeps switching sides. Neither group has control.
That distinction is the foundation of the classification system you’ll learn next.
Cross Counting Rules
These three rules ensure every trader counts crossovers the same way:
Every cross counts, including wicks.
If a candle’s wick pokes through the MA, even briefly, it counts as a cross. Don’t ignore wicks.Dwell time matters.
If price crosses the MA and stays on the other side for 10 or more minutes, count it as a full cross, even if the move looks small.
Brief touches that immediately reverse still count too.Start counting after structure breaks, not during consolidation.
When price is moving sideways in a tight range, it will naturally cross the MA repeatedly. These crosses don’t tell you anything useful.
Begin your count only after price breaks out of the consolidation and starts trending.
Visual Marking System
When analysing charts, use a highlighter tool to mark each crossover point.
This makes your count verifiable and helps you spot patterns. Yellow highlights or circles work well.
Action Step✍️:
Open TradingView and add a moving average.
Watch how the line’s slope changes as you scroll through different periods of price action. Notice how it lags behind actual price turns. That lag is a feature, not a bug. It filters out the noise you don’t need.
2. Practice counting crossovers.
Open a chart and mark each crossover you see with a yellow circle or highlighter, then count them up.
You’ll use that number in the next two lessons:
Lesson 3: Classifying Momentum Conditions
You can now count crossovers and identify MA direction.
Next, let's combine the two to classify whether conditions are ideal, average, or poor for momentum trades.
This will finally let you look at a chart and determine if your momentum strategy will make money on it or not.
The Core Logic🧠
Momentum trading means trading with the trend. You’re betting that price will continue in its current direction.
For this to work, you need two things:
A clear trend (the MA slopes in one direction).Minimal back-and-forth (price stays on one side of the MA).
👉Fewer crossovers means one side (buyers or sellers) is clearly winning.
👉More crossovers mean price keeps switching sides and neither side has control.
Remember: A trending MA confirms that direction exists and a sideways MA means there’s no trend to ride.
The Crossover Count
Your first input is how many times price crossed the 30MA since the last structure break.
This count is only one-half of the classification.
The other half is the direction of the MA.
Look at the 30MA line itself.
Is it:
Trending: Sloping upward or downward. Price is moving directionally.Sideways: Flat or nearly flat. No clear direction.
You need both pieces of information (cross count + MA direction) to classify conditions.
The Momentum Spectrum
Before looking at the full table, understand the spectrum.
Conditions range from best to worst for momentum based on both variables together.
The further right you go, the worse the conditions are for momentum.
Use this spectrum the next time you're trying to "grade" the conditions of your momentum setup.
The Momentum Classification Table
Combine your cross count with the MA direction:
Notice two patterns:
Sideways MA = automatically poor for momentum. If there’s no trend, there’s nothing to ride. It doesn’t matter how few crosses there are.7+ crosses = automatically poor for momentum. Too much back-and-forth means the trend isn’t clean enough to trade with confidence.
Why Each Classification Makes Sense
Ideal (0-3 crosses, trending MA): This looks like a slow, grindy staircase where each leg behaves similarly. Price is staying on one side of the MA while the MA slopes in a clear direction. Momentum trades have the highest probability here✅Average (4-6 crosses, trending MA): There’s a trend, but it’s not perfectly clean. Some back-and-forth is happening. Momentum trades can still work, but expect tighter management✍️Poor (sideways MA or 7+ crosses): Either there’s no trend to ride, or the trend is so choppy that momentum entries will get stopped out repeatedly. Avoid momentum trades in these conditions❌
How to Use This
Before taking any momentum trade:
Add the 30MA to your chart.Identify where the current trend started (structure break from consolidation).Count crossovers from that point to now.Check MA direction (trending or sideways).Classify using the table above.If conditions are poor, skip the trade or look for a different setup.
Momentum Trade Examples
Ideal Conditions:
Price stays predominantly on one side of the 30MA.The MA slopes clearly in one direction.Crossover count is low.
This is where momentum trades thrive✅
Average Conditions:
There’s still a trend, but you can see more interaction with the MA and more crosses.Momentum trades can work here, but require more patience and tighter management.
Poor Conditions:
Price crosses the MA constantly while the MA is flat.Neither buyers nor sellers have control. Momentum trades in these conditions will get chopped up.
Common mistakes to avoid with Momentum trades
Taking momentum trades when the MA is sideways. You might see a “breakout” and jump in, but without a trending MA, you’re trading into range-bound conditions.
Do this instead: Confirm the MA is sloping in your trade direction before entering.Ignoring repeated rejections at highs or lows. If price keeps failing to break through a level, that’s a sign of choppy conditions, even if your cross count looks okay.
Do this instead: Combine cross-counting with visual assessment. Repeated rejections signal mean reversion conditions, not momentum.Forcing momentum trades in 7+ cross environments because you “see a trend.” High cross counts mean the trend isn’t clean. Your edge is diminished.
Do this instead: Accept that some trends aren’t tradable with momentum strategies. Wait for cleaner conditions or switch to mean reversion.
Lesson 4: Classifying Mean Reversion Conditions
Now that you now know how to classify momentum conditions, it's simpler to classify mean reversion conditions.
Mean reversion uses the same two inputs (crossover count and MA direction) but with opposite logic.
The Core Logic🧠
Mean reversion trading means trading against the current move. You’re betting that price will snap back after an extreme push.
For this to work, you need:
Range-bound conditions (price bouncing between levels).Lots of back-and-forth (price crossing the MA repeatedly).
More crossovers mean the price keeps reverting to the mean. It pushes one direction, then snaps back. Pushes the other direction, snaps back again. This is exactly what mean reversion strategies exploit.
A sideways MA confirms there’s no dominant trend:
Price is oscillating around a central point rather than marching in one direction. This is ideal for buying dips and selling rips.
The Mean Reversion Spectrum
The spectrum is the mirror image of momentum.
What was worst for momentum is now best for mean reversion.
What was best for momentum is now worst for mean reversion.
The Mean Reversion Classification Table
Notice how this is the opposite of momentum?
More crosses = better for mean reversion (opposite of momentum).Sideways MA = ideal for mean reversion (opposite of momentum).0-3 crosses = poor for mean reversion regardless of MA direction (ideal for momentum).
Why Each Classification Makes Sense
Ideal (7+ crosses, sideways MA): Price is bouncing back and forth constantly with no directional trend, and every push gets faded.
Mean reversion trades have the highest probability here✅Average (7+ crosses trending, or 4-6 crosses sideways): There’s reversion behaviour, but it’s not perfectly clean.
Either there’s a slight trend making reversions less reliable, or the range isn’t fully established yet✍️Poor (0-3 crosses, or 4-6 with trending MA): Price is trending cleanly. Trying to fade moves in these conditions means fighting the trend.
You’ll get run over❌
The Key Insight: Opposite Conditions
This means the same chart can be classified differently depending on which strategy you’re considering.
A “terrible” momentum chart might be a “perfect” mean reversion chart.
How to Use This
Before taking any mean reversion trade:
Add the 30MA to your chartCount crossovers over the relevant periodCheck MA direction (trending or sideways)Classify using the table aboveIf conditions are poor, skip the trade or look for a different setup
Mean Reversion Trade Examples:
Ideal Conditions (7+ Crosses, Sideways MA):
Price crosses the MA constantly and the MA is flat.Every push in one direction gets faded.
This is where mean reversion trades thrive✅
Average Conditions (7+ Crosses, Trending MA):
There’s reversion behaviour, but the MA direction is trending rather than sideways.Mean reversion can work, but setups need to be higher quality.
Poor Conditions (0-3 Crosses, Trending MA)
Clean trend with few crossovers.Fading moves here means fighting a one-sided market.
This is where mean reversion trades get run over❌
Common Mean Reversion Mistakes
Taking mean reversion trades in clean trending conditions (0-3 crosses, trending MA): You’ll get stopped out repeatedly as the trend continues.
Do this instead: Confirm the MA is sideways or that the cross count is high before fading moves.Applying momentum criteria to mean reversion trades. Thinking “this chart is too choppy” when choppiness is exactly what you want.
Do this instead: Remember, the criteria are opposite. Embrace the chop for mean reversion.Getting frustrated by choppy price action instead of recognising it as your ideal environment.
Do this instead: When you see a mess of crossovers and a flat MA, get excited. That’s your edge.
Next Steps✍️
Now it's your turn to test this article against your strategy:
Add the 30MA to your charts using the setup instructions from Lesson 2.Practice counting crossovers on 5-10 recent charts, marking each cross with a highlighter.Classify each chart twice: once for momentum, once for mean reversion.Before your next trade, run the classification and only proceed if conditions match your strategy type.
If you can do this, you will never make a mistake when aligning the perfect market environment with your strategy.
By the way, the opposite is also true:
When you skip trades that don't fit your strategy, your trading system becomes more profitable💵
Bookmark this article so you can revisit it and master these concepts until you're profitable.
#CryptoZeno #StocksCryptoDecoupling

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