[Weekly Readings] BAND increased 70% of its main positions , Dogecoin (DOGE) Price Manipulated By Whales

Huobi2022-11-05 tarihinde yayınlandı2022-11-07 tarihinde güncellendi

Özet

BAND increased 70% of its main positions，Dogecoin (DOGE) Price Manipulated By Whales.

One week's beautiful article introduces the most noteworthy hot articles in the past week to help investors deeply understand the market dynamics.

1.BAND increased 70% of its main positions

BAND has stabilized and recovered in the short term, and the price has risen rapidly. It only takes 28 hours to reach a maximum of $3.199 in the 4-hour K line. In terms of amplitude, BAND short-term fluctuation reached 183%.

Click here

⠀

2.Huge Whale Activity In USDT and USDC, Bull Run Ahead?

After months of stagnation, the U.S. Department of Justice is planning to revive the investigation into Tether executives allegedly committing bank fraud. As per the Bloomberg report, U.S. Attorney Damian Williams in the Southern District of New York (SDNY) will be leading the Department of Justice’s (DOJ) probe.

Click here

⠀

3.First Time After Twitter Deal, Elon Musk Hints of DOGE Coming to The Platform

Well well, Elon Musk has spilled the beans and has hinted about Dogecoin (DOGE) coming to the Twitter platform very soon. In his recent tweet, Elon Musk shared a pic of the Shiba Inu dog breed wearing a Twitter t-shirt. Thus, this fuels the ongoing speculation that he could soon bring DOGE payments to his newly acquired social media platform.

Click here

⠀

4.Stablecoins Flowing To Spot Exchanges, Has Bitcoin Bottomed?

Bitcoin price witnessed a correction after the Fed hiked interest rates by another 75 bps, but the BTC price held strongly over $20K. Interestingly, the BTC price has rallied two times from the $20,080 level in a week, making a double bottom.

Click here

5. Dogecoin (DOGE) Price Manipulated By Whales? A Look Off And On-Chain

The Dogecoin (DOGE) price has had an incredible weekend. Following Elon Musk’s confirmed Twitter acquisition, the DOGE price jumped 95% over the last seven days. The memecoin exploded to over $0.14 at times and is currently sitting at about $0.11.

Click here

İlgili Okumalar

Those Who Wanted to Buy Have Already Bought: SpaceX Retail Frenzy Subsides, Real Selling Pressure Arrives in August

SpaceX (SPCX) debuted on June 12 at $150, soared to a record $225 by June 16 in a retail-fueled frenzy, then collapsed, losing over $600 billion in market cap in a single day this week and crashing back near its IPO price. Analysts note the initial surge was driven by record retail inflows exceeding those for major tech stocks, but momentum evaporated swiftly after the peak. The sell-off occurred with only 5% of shares freely tradable. The real pressure is yet to come: lock-up expirations starting in August could release up to 44% of insider shares by early September, potentially increasing the float ninefold. With retail buying exhausted and massive supply looming, analysts warn the path higher is now severely challenged, posing a broader risk to a market sustained by speculative momentum.

marsbit2 dk önce

Those Who Wanted to Buy Have Already Bought: SpaceX Retail Frenzy Subsides, Real Selling Pressure Arrives in August

marsbit2 dk önce

20-Year-Old Founder Hires 18-Year-Old Employee, Funded by 19-Year-Old

The AI industry is experiencing a radical youth movement. Companies are aggressively recruiting extremely young talent—interns as young as 17 with daily salaries up to $800, and recent undergraduates earning annual packages of $200k-$1M. This shift prioritizes being "AI Native"—a mindset more common in the post-2000 generation—over traditional experience. Major tech firms like ByteDance, Tencent, and Alibaba restructure to empower young researchers directly, finding that past management expertise can hinder innovation in this fast-paced field. This creates a self-reinforcing cycle: young researchers gain authority, hire peers, attract young investors, and start companies, collectively building a new power network that sidelines older professionals. The intense competition for a limited pool of top young minds has led to astronomical salaries, defensive hiring, and sophisticated early talent scouting from high school. However, this concentration of opportunity exacerbates inequality, leaving many experienced workers facing obsolescence as AI disrupts traditional tech roles. While rewarding "extraordinary" talent unprecedentedly, the industry is simultaneously delivering a harsh penalty for those perceived as ordinary or tied to outdated methods.

marsbit6 dk önce

20-Year-Old Founder Hires 18-Year-Old Employee, Funded by 19-Year-Old

marsbit6 dk önce

Micron Q2 Earnings Preview: Citi Raises Price Target

TL;DR: Ahead of Micron's Q2 FY26 earnings report on June 24, Citi raised its price target from $840 to $1,200, citing stronger-than-expected 2026 memory prices and high gross margins. The stock price had already neared $1,211, shifting focus to whether the aggressive earnings assumptions will hold. The $1,200 target is based on significantly higher FY27 EPS estimates ($114.73), driven by projections of DRAM ASPs rising 200% and NAND ASPs rising 186% in 2026. The bullish outlook hinges on the ongoing transition of spot price increases (DRAM up 52% YTD) to contract prices, with server demand being a key driver. Supply remains tight, with a projected 5% DRAM shortage in 2026, exacerbated by HBM production consuming capacity. Long-Term Agreements (LTAs) could provide stability but their specific terms are crucial. Risks include HBM yield/ramp challenges, potential industry overcapacity, and AI/data center capex fluctuations. With the stock near the target, future moves depend on the continuation of strong pricing, tight supply, and high margins.

marsbit11 dk önce

Micron Q2 Earnings Preview: Citi Raises Price Target

marsbit11 dk önce

After Missing the 20x, I've Found a 'Dumb' Method for AI Investing

**Missing the 20x Opportunity: A Simple 'Dumb' Approach to AI Investing** The AI boom, driving NVIDIA's revenue from $60B to $216B in two years, creates immense investment pressure. However, like the internet bubble of 2000, the largest AI opportunities likely lie ahead, perhaps after a correction. Instead of rushing in now or waiting paralyzed for a crash, the author proposes a third way: building a "knowledge warehouse" by systematically mapping the AI industry to be ready when opportunities arise. The core of the strategy is understanding AI's four-layer value chain: 1. **Compute Infrastructure (The "Engine"):** This foundational layer, where all money eventually flows, includes: a) **Chip Design:** NVIDIA's dominance via its CUDA ecosystem, b) **Chip Manufacturing/Packaging/Memory:** TSMC's near-monopoly in advanced manufacturing and SK Hynix's lead in High Bandwidth Memory (HBM), c) **Optical Interconnects:** Essential for large-scale AI clusters (e.g., Lumentum, Coherent), d) **Cooling & Power:** Critical for high-density AI data centers (e.g., Vertiv), e) **Servers/Data Centers & Cloud Platforms:** The physical and virtual wholesale providers. 2. **Models & Tools (The "OS"):** The competitive layer of foundation models (OpenAI, Anthropic, Google, Meta, xAI), now generating real revenue. A key shift is the center of gravity moving from **Training** models to **Inference** (running models), which demands different chip characteristics and could challenge NVIDIA's monopoly. 3. **Middleware & Platform ("The Glue"):** Connects models and applications (e.g., Scale AI, Hugging Face). This layer could explode if applications take off. 4. **Vertical Applications ("The Cash Register"):** Where AI meets end-users (e.g., enterprise AI, coding tools, medical AI, robotics). A critical cross-cutting constraint is **Energy**, as AI's massive power consumption drives investment in nuclear and other energy infrastructure. The author identifies four key questions for further research: 1) How will the shift from Training to Inference reshape the competitive landscape? 2) With tech giants spending over $600B on capex, where is the ROI from AI applications? 3) What are the under-the-radar opportunities in the "second" and "third" circles of the value chain (e.g., cooling, specialty foundries)? 4) How will geopolitics (e.g., U.S.-China chip restrictions) bifurcate the supply chain? The conclusion is that missed opportunities stem from insufficient research, not slow timing. By methodically studying each layer—its business models, competition, and valuations—investors can build the "killer intuition" needed to act decisively when the market presents its chance.

marsbit17 dk önce

After Missing the 20x, I've Found a 'Dumb' Method for AI Investing

marsbit17 dk önce

Having Raised $37 Million with a16z's Backing, Why Did Goldfinch Ultimately Fail?

The decentralized credit protocol Goldfinch, which raised $37.7 million in funding led by Andreessen Horowitz (a16z), is officially entering a shutdown process. After six years of operation and issuing approximately $100 million in loans, it faces widespread borrower defaults and frozen depositor funds. Depositors report an estimated actual loss rate of around 70%, with the protocol's governance token GFI having plummeted 99.8% from its all-time high. The current proposal involves winding down operations, halting new development, and establishing a trust to manage loan recovery over an estimated two-plus years. Founded by ex-Coinbase employees, Goldfinch aimed to channel crypto capital into loans for emerging markets via local lenders. However, it suffered significant defaults from major borrowers like Tugende Kenya, Stratos, and Lend East, leading to over $18 million in losses. The failure highlights the core challenge for DeFi-based Real-World Asset (RWA) lending: while blockchain technology improves capital fluidity, it cannot replace the critical offline components of credit underwriting, collateral management, and legal enforcement, especially in high-risk jurisdictions.

Foresight News20 dk önce

Having Raised $37 Million with a16z's Backing, Why Did Goldfinch Ultimately Fail?

Foresight News20 dk önce

İşlemler

Spot

Futures