Don’t Celebrate Bitcoin Yet: The Trend Is Still Bearish, And This Is Why

bitcoinistPublished on 2026-03-21Last updated on 2026-03-21

Abstract

Based on technical analysis, Bitcoin's recent rally above $75,000 is insufficient to confirm a bullish reversal, as the overall structure remains bearish. The daily chart shows BTC is consolidating within a rising channel, identified as a bear flag pattern, following a prior downtrend. This pattern previously led to a breakdown to $60,000 in early February 2026. A key resistance zone exists around $76,000, where BTC faced rejection. Currently trading near $70,000, a weekly close below this level could trigger a further decline toward $65,000. Analysis of the weekly timeframe using the Gaussian Channel indicator, which has accurately signaled major cycle bottoms in the past, suggests that the February low may not be the final market bottom. The indicator turned bearish after that low, a deviation from historical patterns where the transition preceded the bottom. Consequently, the trend remains cautiously bearish despite short-term rallies.

Bitcoin’s brief rally above $75,000 this week led to bullish optimism in some corners of the crypto market, but technical analysis shows the trend might still be bearish. A close look at BTC’s daily and weekly charts tells a more sobering story, one that shows that the crypto king might continue on a lower correction move in the coming days.

Bitcoin Is Still Trapped Inside A Bear Flag

Bitcoin’s price recovery into the mid-$70,000s this week is not enough on its own to confirm that Bitcoin is out of danger. According to crypto analyst CrypFlow, the bigger trend is starting to look constructive on higher timeframes, but the daily chart still shows a bearish structure that has not been invalidated. Until that changes, the latest bounce may be nothing.

The daily candlestick timeframe chart shows that BTC has spent the past several weeks since early February consolidating within a rising channel structure. This is a pattern that, in the context of a prior downtrend, is technically classified as a bear flag.

Source: Chart from CrypFlow on X

The chart shows Bitcoin rallying into the upper boundary of the flag near the $76,000 area before getting rejected. That same region also lines up with a major resistance band marked on the chart, reinforcing the idea that bulls have not yet done enough to flip the structure. The BTC price has since fallen back toward the middle of the channel, leaving the leading cryptocurrency at a short-term decision point.

As seen in the chart below, a similar bear flag was formed from mid-November 2025 to late January 2026, and this eventually led to the breakdown to $60,000 in early February 2026.

The $70,000 To $76,000 Zone Now Matters More Than Ever

The current battle is taking place between the midline of the flag and the recent rejection zone is at $76,000. At the time of writing, Bitcoin is trading at $70,610, which places it close to support around $70,000. If BTC closes the week below $70,000, then the bear flag projects the price on the path to at least $65,000.

In a separate analysis, CrypFlow turned attention to the weekly timeframe and raised a more macro-level concern using Bitcoin’s Gaussian Channel indicator. This model looks at how Bitcoin has behaved across full market cycles.

According to the analyst, Bitcoin has never formed its cycle bottom before the Gaussian Channel flips from green to red. Each major bottom has come after that transition has already taken place. This pattern played out consistently in 2015, 2018, and again in 2022, where the final lows only arrived once the channel had fully turned bearish.

Interestingly, the Gaussian Channel transitioned from green to red after Bitcoin’s low in early February, not before. Although the Bitcoin price is still holding above $60,000 for now, the implication is that this level may not be the final bottom.

BTC trading at $70,379 on the 1D chart | Source: BTCUSDT on Tradingview.com

Related Questions

QAccording to the technical analysis, why is Bitcoin's trend still considered bearish despite its recent rally above $75,000?

ABecause the daily chart shows a bear flag pattern that has not been invalidated, and the price was rejected at a major resistance near $76,000, indicating the bullish structure is not yet confirmed.

QWhat is the significance of the $70,000 to $76,000 price zone for Bitcoin's near-term movement?

AThis zone represents a critical battle between support and resistance. A weekly close below $70,000 could project a price drop to at least $65,000, according to the bear flag pattern.

QWhat does the Gaussian Channel indicator suggest about whether Bitcoin has reached its cycle bottom?

AThe Gaussian Channel transitioned from green to red after February's low, not before. Historically, major bottoms have only occurred after this transition, suggesting the $60,000 level may not be the final cycle bottom.

QWhat pattern from late 2025 to early 2026 does the current price action resemble, and what was its outcome?

AIt resembles a bear flag pattern that formed from mid-November 2025 to late January 2026, which eventually led to a breakdown to $60,000 in early February 2026.

QWhat key level must Bitcoin break to invalidate the current bearish structure on the daily chart?

ABitcoin must break and hold above the major resistance zone near $76,000 to invalidate the bear flag structure and signal a potential trend reversal.

Related Reads

OpenAI Post-Training Engineer Weng Jiayi Proposes a New Paradigm Hypothesis for Agentic AI

OpenAI engineer Weng Jiayi's "Heuristic Learning" experiments propose a new paradigm for Agentic AI, suggesting that intelligent agents can improve not just by training neural networks, but also by autonomously writing and refining code based on environmental feedback. In the experiment, a coding agent (powered by Codex) was tasked with developing and maintaining a programmatic strategy for the Atari game Breakout. Starting from a basic prompt, the agent iteratively wrote code, ran the game, analyzed logs and video replays to identify failures, and then modified the code. Through this engineering loop of "code-run-debug-update," it evolved a pure Python heuristic strategy that achieved a perfect score of 864 in Breakout and performed competitively with deep reinforcement learning (RL) algorithms in MuJoCo control tasks like Ant and HalfCheetah. This approach, termed Heuristic Learning (HL), contrasts with Deep RL. In HL, experience is captured in readable, modifiable code, tests, logs, and configurations—a software system—rather than being encoded solely into opaque neural network weights. This offers potential advantages in explainability, auditability for safety-critical applications, easier integration of regression tests to combat catastrophic forgetting, and more efficient sample use in early learning stages, as demonstrated in broader tests on 57 Atari games. However, the blog acknowledges clear limitations. Programmatic strategies struggle with tasks requiring long-horizon planning or complex perception (e.g., Montezuma's Revenge), areas where neural networks excel. The future vision is a hybrid architecture: specialized neural networks for fast perception (System 1), HL systems for rules, safety, and local recovery (also System 1), and LLM agents providing high-level feedback and learning from the HL system's data (System 2). The core proposition is that in the era of capable coding agents, a significant portion of an AI's learned experience could be maintained as an auditable, evolving software system.

marsbit53m ago

OpenAI Post-Training Engineer Weng Jiayi Proposes a New Paradigm Hypothesis for Agentic AI

marsbit53m ago

Your Claude Will Dream Tonight, Don't Disturb It

This article explores the recent phenomenon of AI companies increasingly using anthropomorphic language—like "thinking," "memory," "hallucination," and now "dreaming"—to describe machine learning processes. Focusing on Anthropic's newly announced "Dreaming" feature for its Claude Agent platform, the piece explains that this function is essentially an automated, offline batch processing of an agent's operational logs. It analyzes past task sessions to identify patterns, optimize future actions, and consolidate learnings into a persistent memory system, akin to a form of reinforcement learning and self-correction. The article draws parallels to similar features in other AI agent systems like Hermes Agent and OpenClaw, which also implement mechanisms for reviewing historical data, extracting reusable "skills," and strengthening long-term memory. It notes a key difference from human dreaming: these AI "dreams" still consume computational resources and user tokens. Further context is provided by discussing the technical challenges of managing AI "memory" or context, highlighting the computational expense of large context windows and innovations like Subquadratic's new model claiming drastically longer contexts. The core critique argues that this strategic use of human-centric vocabulary does more than market products; it subtly reshapes user perception. By framing algorithms with terms associated with consciousness, companies blur the line between tool and autonomous entity. This linguistic shift can influence user expectations, tolerance for errors, and even perceptions of responsibility when systems fail, potentially diverting scrutiny from the companies and engineers behind the technology. The article concludes by speculating that terms like "daydreaming" for predictive task simulation might be next, continuing this trend of embedding the idea of an "inner life" into computational processes.

marsbit54m ago

Your Claude Will Dream Tonight, Don't Disturb It

marsbit54m ago

Trading

Spot
Futures

Hot Articles

How to Buy T

Welcome to HTX.com! We've made purchasing Threshold Network Token (T) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Threshold Network Token (T) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Threshold Network Token (T)After purchasing your Threshold Network Token (T), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Threshold Network Token (T)Easily trade Threshold Network Token (T) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

11.3k Total ViewsPublished 2024.03.29Updated 2025.03.21

How to Buy T

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of T (T) are presented below.

活动图片