Pi Network price prediction: $0.20 still in play as 3 signals align

ambcrypto2026-03-03 tarihinde yayınlandı2026-03-03 tarihinde güncellendi

Özet

In mid-February, AMBCrypto cautioned that Pi Network's (PI) 58.1% rally appeared to be buyer exhaustion rather than a bullish reversal. PI was rejected at the $0.20 supply zone and is currently trading at $0.171. Despite the pullback, prices held above the $0.13 local lows, and key indicators suggest limited selling pressure. The 20 and 50-day moving averages are nearing a bullish crossover, with the 20DMA acting as dynamic support. A triangle pattern on the H4 chart indicates an impending breakout. If Bitcoin surpasses and holds above $70k, PI could retest $0.20 and challenge the $0.216 high. The short-term outlook remains cautiously optimistic, contingent on broader market momentum.

In mid-February, AMBCrypto had warned that a Pi Network [PI] rally looked more like buyer exhaustion than a bullish reversal.

During that rally, PI had moved 58.1% higher in 4 days, on the back of high Spot Volume.

However, it ran into the $0.2 supply zone and was unable to overcome it. At the time of writing, PI was trading at $0.171.

The rejection from the overhead supply has come true, but what is likely to follow in March? An argument can be made for a bullish breakout and a long-term trend shift for PI, especially if Bitcoin can push past $70k.

The chances of a PI breakout past $0.2

The rejection from $0.2 did not send PI prices below the $0.13 local lows. Such a scenario would have been a clear signal of bearish intent.

Instead, the altcoin prices fell to $0.16 and rebounded.

At the same time, the OBV did not see a steep drop-off from the mid-February rally levels. This meant that selling pressure was not high. Additionally, the 20 and 50-day moving averages were on the verge of making a bullish crossover.

Over the past week, the 20DMA has served as a dynamic support to Pi Network token prices.

The lack of selling pressure and the challenge of the $0.173 level suggested a move higher could occur in the short-term.

Pi Network short-term price prediction

The H4 local resistance at $0.1788 would likely be a firm test of bullish resolve.

At the time of writing, the altcoin was approaching the apex of a triangle pattern (orange). The direction of the breakout from this chart pattern could determine the next impulse move.

It is possible that a Bitcoin [BTC] short squeeze could give the altcoin market some temporary respite. In this case, a PI move toward $0.2 and the $0.216 local high could materialize.


Final Summary

  • PI’s short-term direction hinged on the direction of the breakout from the triangle pattern.
  • The Pi Network price prediction is a move toward $0.20 and $0.216, provided Bitcoin can climb above $70k and maintain the momentum.

Disclaimer: The information presented does not constitute financial, investment, trading, or other types of advice and is solely the writer’s opinion.

İlgili Sorular

QWhat was the main reason AMBCrypto warned that the Pi Network rally in mid-February might not be a bullish reversal?

AAMBCrypto warned that the rally looked more like buyer exhaustion than a bullish reversal.

QWhat key price level did Pi Network (PI) fail to overcome during its February rally?

API failed to overcome the $0.2 supply zone.

QWhat two technical indicators suggested a lack of significant selling pressure and a potential bullish crossover?

AThe On-Balance Volume (OBV) did not see a steep drop-off, and the 20 and 50-day moving averages were on the verge of a bullish crossover.

QWhat chart pattern's breakout direction is expected to determine Pi Network's next significant price move?

AThe direction of the breakout from the triangle pattern (orange) is expected to determine the next impulse move.

QAccording to the article, what two conditions could lead to a Pi Network price move toward $0.20 and $0.216?

AA move toward $0.20 and $0.216 could materialize if Bitcoin climbs above $70k and maintains its momentum, and if there is a Bitcoin short squeeze that gives the altcoin market respite.

İlgili Okumalar

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit1 saat önce

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit1 saat önce

İşlemler

Spot
活动图片