Bitcoin’s bruising November slide may be nearing its end, according to a simulation-based AI model that projects a local bottom forming this week and a gradual recovery stretching into 2026.
After setting fresh all-time highs in October, Bitcoin has spent November in clear bear-market territory. The drawdown from those October peaks has reached roughly 36%, while month-to-date losses hover around 20% at a price near 87,500 dollars. On a historical basis, this places the current performance among the worst Novembers Bitcoin has seen, and the weakest since the post-bull-run fallout in 2018, when the market was digesting the previous cycle’s peak around 20,000 dollars.
Worst November Since 2018 – And What That Means
Data on monthly returns shows that this kind of November weakness is extremely rare. Since 2013, Bitcoin has typically delivered robust gains in November, with average returns above 40%. By contrast, this year’s near-20% decline stands out sharply against that backdrop of historical strength.
Equally notable is a recurring pattern around “red Novembers”: every time Bitcoin has closed November in the red, December has also finished negative. This tendency doesn’t guarantee a repeat performance, but it does show that deep November drawdowns have often been followed by continued pressure into year-end rather than V-shaped reversals.
December itself has historically been much more subdued than November from a performance standpoint. On average, Bitcoin has added only about 5% in December, compared with the far stronger November average. That asymmetry suggests that, in typical years, the bulk of Q4 upside tends to arrive early; when that upside fails to materialize in November, market sentiment frequently remains fragile heading into the holidays.
AI Model Flags a Local Bottom “This Week”
Against this gloomy backdrop, an AI-driven simulation model offers a more constructive short-term outlook. According to the tool’s projections, Bitcoin has either already registered a local bottom or is poised to do so within the current week. After that, the model anticipates a slow, uneven recovery into the end of the year, rather than a dramatic melt-up.
The architect of the model emphasized that the simulation focuses on price dynamics and historical patterns; it does not attempt to factor in external shocks, such as sudden macroeconomic events, regulatory surprises, or broader risk-off moves in global markets. In other words, the AI is extrapolating from Bitcoin’s internal behavior and past cycles, not trying to foresee black swan events.
Earlier analyses by the same economist compared 2024’s price path with that of 2015, finding striking similarities. In that historic analogue, Bitcoin was in a very similar position at roughly the same time of year — trading weakly but forming an important cyclical low. From that point in 2015, the asset rallied about 45% into year-end, closing the year with gains around 33%. The comparison has been described even by its author as “hopium” rather than a deterministic forecast, but it illustrates the potential for sharp rebounds once a cyclical floor is in place.
Echoes of 2015 and 2018: Two Very Different Outcomes
The references to 2015 and 2018 highlight two different paths Bitcoin has taken in previous cycles.
– In 2015, the market was grinding through the later stages of a brutal bear market. Price action was lethargic and sentiment was depressed, but the eventual breakout laid the groundwork for the massive 2016–2017 bull run.
– In 2018, the situation was far more explosive on the downside. After spending much of the year in a slow bleed, Bitcoin capitulated violently in November, experiencing a steep, sudden sell-off that extended into December before stabilizing.
The current environment borrows elements from both episodes. Like 2015, the market seems to be working through a longer-term normalization phase after a powerful rally. Yet the magnitude of the November drop and the proximity to all-time highs has revived memories of 2018’s post-peak capitulation. Which precedent will prove more relevant remains an open question, but the AI simulation leans closer to the “2015-style bottom and slow recovery” scenario than to a fresh collapse.
Seasonality: How Much Does It Really Matter?
Bitcoin’s seasonal tendencies are often debated. Supporters of seasonality analysis point to historical averages: strong Q4 performance, especially in November, and more moderate gains or consolidation in December. Critics counter that a market as young and structurally evolving as Bitcoin may not obey simple calendar-based patterns, and that outlier years can easily overwhelm weak statistical relationships.
The current year is already an outlier with respect to November performance. That alone warns against blindly extrapolating from past averages. Still, seasonal data can provide context: if Bitcoin typically thrives in November but fails to do so, it may indicate that broader macro or structural forces are overpowering the usual tailwinds.
What seasonality does not provide is precise timing for inflection points. A historically “strong month” can still begin with steep volatility and ultimately finish higher, or vice versa. This is where tools like AI simulations, on-chain data, and macro analysis are often combined to build a more nuanced view.
“Slow Recovery” Into 2026: What That Could Look Like
The AI model’s mention of a “slow recovery” through the end of the year and into 2026 implies a base-building phase rather than an immediate new parabolic move. Practically, this could involve:
– Range-bound trading: Price oscillating between support and resistance zones as market participants reassess fair value.
– Diminishing volatility over time: Spikes remain, but their magnitude gradually shrinks as the market digests prior moves.
– More selective participation: Short-term speculators capitulate, while longer-horizon investors step in selectively on dips.
– Gradual shift in sentiment: From fear and capitulation to cautious optimism, as repeated retests of support hold.
Such a recovery path would align with post-bear-market behavior seen previously, where Bitcoin spends many months, and sometimes years, constructing a higher floor before embarking on the next sustained advance.
Macro and Liquidity: The Wild Cards the Model Ignores
The model’s creator explicitly notes that the AI simulation does not incorporate external volatility drivers. That omission is crucial, because Bitcoin today trades in an environment heavily influenced by:
– Interest rate expectations and central bank policy
– Liquidity conditions across global risk assets
– Regulatory developments and political uncertainty
– Shifts in institutional adoption and derivatives positioning
Any of these factors could either amplify or invalidate the AI’s path. A dovish turn in monetary policy, for example, might accelerate a recovery, while a major regulatory crackdown or systemic shock could trigger another leg lower. This highlights a core limitation of purely price-based models: they can map out probable paths under “normal” conditions, but are inherently vulnerable to regime changes.
Short-Term Pain, Long-Term Narratives
Despite the sharp pullback, long-term narratives around Bitcoin remain in play. The asset is still framed by many as a form of “digital gold,” a scarce asset with a pre-programmed supply schedule that periodically tightens via halving events. These structural features have historically underpinned multi-year bull markets, even though the path between them has been marked by severe corrections, sometimes in the range of 70–80% from peak to trough.
The present 36% drawdown from October’s all-time highs is substantial but not unprecedented. From a cycle perspective, some analysts interpret such corrections as periodic resets within a broader uptrend. Others argue that each cycle is unique, and that past behavior offers limited guidance in a market increasingly influenced by institutional flows and macro forces.
Different high-profile market participants are also drawing their own conclusions. One well-known trader recently argued that the sub-80,000-dollar zone marked a major bottom, contending that forced liquidations and over-leveraged positions had been largely flushed out. Whether that assessment proves correct will depend on how price reacts to future stress tests and macro news.
Risk Management in a High-Volatility Environment
For traders and investors, the combination of historical analogies, AI-based projections, and macro uncertainty underscores the importance of risk management. No model or seasonal pattern can guarantee outcomes in a market as volatile as Bitcoin. Among the considerations often discussed by market participants are:
– Position sizing: Keeping exposure aligned with one’s risk tolerance and time horizon.
– Diversification: Avoiding overconcentration in a single asset or sector.
– Scenario planning: Being mentally and strategically prepared for both further downside and sharp upside reversals.
– Emotional discipline: Recognizing that fear near apparent bottoms and euphoria near tops are recurring psychological traps.
A potential local bottom, even if correctly identified, does not preclude additional volatility. Markets frequently revisit and test key support levels multiple times before a durable uptrend emerges.
What to Watch Next
As the month draws to a close, several signposts may help gauge whether a local bottom is indeed forming:
– Monthly close dynamics: How Bitcoin behaves into and immediately after the November close can offer clues about positioning and sentiment.
– Volume and order flow: Signs of capitulation (high-volume sell-offs followed by strong buying) or, conversely, low-liquidity drifts can help identify exhaustion.
– Derivatives metrics: Funding rates, open interest, and options skew can reveal whether leveraged traders are still heavily positioned one way or another.
– Correlation with other risk assets: A decoupling from equities or other high-beta assets may indicate a shifting narrative, while tight correlations can signal ongoing macro dependence.
If the AI model is correct, the coming days could mark an important inflection point, followed by a period of rebuilding rather than fireworks.
Final Note
The evolving picture is one of tension between near-term weakness and longer-term structural optimism. On the one hand, Bitcoin is experiencing its harshest November since the depths of the 2018 bear market, with a drawdown of around 20% for the month and roughly 36% from October’s peak. On the other, historical analogies to 2015, AI-driven simulations, and some market commentators’ views all suggest that a local bottom may be close, if not already in.
Regardless of which camp one leans toward, any decision to buy, sell, or hold Bitcoin remains inherently risky. Digital assets are volatile and can move sharply in either direction in response to both internal dynamics and external shocks. Anyone considering exposure should carefully evaluate their own financial situation, objectives, and risk tolerance, and be prepared for the possibility that the market may not conform to even the most compelling models or historical patterns.