AL

TrendTradingStrategy: Bitcoin Daily Chart Method
Master the trend and ride it with confidence. Here's a simple yet powerful Bitcoin trend trading strategy, designed for the daily timeframe.
Indicators You’ll Need
50 EMA (Exponential Moving Average) – identifies the short-term trend
200 EMA – reveals the long-term trend
ADX (Average Directional Index) – measures trend strength
Look for ADX ≥ 20 to confirm a trending market
Sweet spot: ADX between 25–50 for healthy momentum
(Optional) RSI (Relative Strength Index) – for spotting divergence or overbought/oversold conditions
Entry Rules – Long Setup Example
Confirm Trend Direction
50 EMA above 200 EMA = Bullish trend
Price trading above both EMAs = Confirmation of upward momentum
Confirm Trend Strength
ADX > 20 confirms market is trending
Ideal ADX range: 25–50
Trigger Entry
Wait for price to pull back to the 50 EMA
Look for bullish reversal candlestick patterns, such as:
Hammer
Bullish Engulfing
Alternative Trigger: Break of recent swing high after pullback
Exit Rules – Risk Management First
Take Profit
Minimum Risk-Reward Ratio: 1:2
Trailing Stop: Below each higher low as trend progresses
Alternative: Use ATR (Average True Range) to dynamically adjust target
Stop Loss
Place just below the recent swing low
Or define a fixed risk level (e.g., max -2% of trading capital)
Pro Tips
Avoid trading when ADX < 20 – indicates a weak or sideways market
Combine RSI divergence for additional confirmation during pullbacks
This strategy works best during clearly trending periods – avoid choppy ranges
Discipline, patience, and trend alignment are key. Don’t fight the trend—follow it smartly.
#Al #TrendTradingStrategy

🌟🌟 Before starting, first understand the basic contract knowledge
🧐 100 dollars with 3x leverage + going long requires a drop of over 30% to get liquidated
Generally, when an entry signal appears, such as (Dragonfly Doji W, bottom divergence W), there are few coins that continue to drop over 30%, but that does not mean it won't drop 20%, 10%, or 5%. However, all of this is within the expected volatility. Therefore, for popular altcoins, roll the position with 100 dollars at 3x long.
📢📢 For these popular altcoins, after listing on exchanges, many can be pulled up 1-2-3 times after a brief washout, do not underestimate the charm of 100 dollars at 3x leverage. Even if you go long with 100 dollars at 3x leverage without taking any rolling position actions, you can earn over 1000 dollars. If you maintain 3x rolling position throughout the process, you can make 1000-2000 dollars. Conversely, if you encounter a historic crash with a drop of over 30%, your maximum risk is only 100 dollars.

🔥🔥🔥
According to PANews, the Oasis Protocol Foundation has launched the ROFL mainnet, a framework designed for verifiable off-chain computation. This development aims to support the creation of privacy-focused AI and financial applications. ROFL utilizes Trusted Execution Environments (TEEs) to handle complex computations off-chain while maintaining blockchain-level trust. Projects like Zeph and WT3 are already leveraging ROFL to develop privacy-centric AI applications and decentralized trading tools, further advancing the integration of blockchain and AI.
In related news, the Oasis Foundation announced a $5 million grant to introduce Midas's tokenized treasury fund to the Sapphire chain.🔥🔥🔥
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The S&P 500 isn’t climbing like it should be, and three major companies are dragging it down hard. Apple, Google’s Alphabet, and Tesla are underperforming in 2025, and their weak numbers are putting a cap on the index’s growth.
This year, the S&P 500 has posted a gain of about 5%, but without these three pulling it backwards, it would be sitting two percentage points higher. That stat comes from data Bloomberg compiled, and it’s forcing investors to ask what the rally would look like without these lagging giants.
Apple Inc., the third-largest company on the S&P 500, has dropped 17% this year. The decline is tied to ongoing problems with US trade tariffs and the company’s failure to roll out functional AI services.
Apple hasn’t figured out how to integrate generative AI into its devices, even though it pushed the “AI for the rest of us” narrative more than a year ago. That campaign hasn’t translated into investor trust. Paul Marino, the chief revenue officer at Themes ETFs, said, “It makes sense that people aren’t pouring additional dollars into Apple right now until they have some kind of blueprint for what they’re going to be doing with AI.”
Investors move to other sectors as Big Tech splits
Alphabet Inc., which is worth around $2.1 trillion, is down 7% in 2025. The drop comes as more investors worry about the company’s search engine revenue. They fear AI chatbots could reduce the amount of traffic and ad dollars coming from Google Search. That threat has been hanging over Alphabet’s performance all year, and it’s pushing investors toward more aggressive AI names.
Tesla Inc. has had the worst slide of the three. Its stock is down 26%, and the reason is simple: demand for electric vehicles has fallen. Sales have slowed in multiple regions, and the company hasn’t announced anything that would change that trend. With fewer buyers for EVs and no new technology breakthroughs, Tesla hasn’t been able to stop the bleeding.
All three of these underperformers belong to the Magnificent Seven, a group of top tech stocks that helped lift the S&P 500 during the last few years. But this year, they’ve split into two groups. The gainers—Microsoft, Nvidia, and Meta Platforms—are all up more than 14%. They’ve taken full advantage of the AI boom.
Nvidia is benefiting from demand in infrastructure, while Meta is using AI tools to grow revenue faster.
Still, Apple might be looking for a way out. Shares rose over 3% this week after Bloomberg reported that the company is considering using Anthropic or OpenAI models to create a more advanced version of Siri. But so far, nothing has been confirmed, and the stock is still deep in the red for the year.
Tech dominance weakens while Congress returns to deadlock
Even though the S&P 500 is near a record high, most of the gains are coming from a few companies. Netflix, Broadcom, and Palantir have all made solid gains in 2025 and are helping support the index alongside Microsoft, Nvidia, and Meta. Meanwhile, Amazon is flat. Despite being part of the Mag 7, it hasn’t moved much this year, and it hasn’t helped the index either.
Together, the Mag 7 account for about one-third of the entire S&P 500, the same as seven of the benchmark’s eleven biggest sectors combined. That means when three of them fall, the market notices. On Tuesday, the information technology sector lost over 1%, and so did communications services.
The names that include Nvidia, Palantir, and AMD are taking the hit. Traders are now moving money into health care and materials stocks. Amgen, Johnson & Johnson, and UnitedHealth posted gains and helped the Dow Jones Industrial Average rise by 400 points on Monday. But that wasn’t enough. The S&P 500 still slipped 0.1% and the Nasdaq Composite dropped 0.8%.
Early Wednesday, the market moved only slightly. Dow futures rose 69 points, about 0.2%. S&P 500 and Nasdaq 100 futures each rose just 0.1%.
Back in Washington, President Donald Trump’s tax-and-spending bill made it through the Senate on Tuesday… barely. The legislation now heads back to the House, where resistance among Republican lawmakers is still strong.
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AI startups in China are chipping away at America’s once unquestionable lead in artificial intelligence, ushering in what could become a worldwide arms race in AI technology.
Firms from Europe to Asia and Africa are now testing or deploying large language models from Chinese players, among them newcomer DeepSeek and e‑commerce heavyweight Alibaba, as cost‑effective alternatives to US incumbents like ChatGPT.
Big firms trial Chinese models like DeepSeek
Global lenders such as HSBC and Standard Chartered have quietly begun internal trials of DeepSeek’s models, according to insiders. These tests indicate finance giants are seeking flexible, wallet‑friendly AI solutions beyond the usual American suspects.
The move suggests a growing appetite for diverse AI providers, especially when budgets and data‑security policies come into play. Big US firms have acknowledged that Chinese AI firms are fast closing in on their US peers.
Even the energy sector is jumping on board. Saudi Aramco, the world’s largest oil producer, has integrated DeepSeek into its primary data center, reflecting confidence in Chinese AI capabilities.
In a twist, major American cloud services, Amazon Web Services, Microsoft Azure and Google Cloud, now offer DeepSeek models to their customers. That’s despite the White House restricting the app on certain government devices over security worries.
Such availability marks a striking reversal: U.S. platforms distributing a Chinese AI product alongside their own homegrown solutions.
The appeal of Chinese AI isn’t just about price. A June study by Harvard researchers found that China holds strategic advantages in the raw data and skilled talent that underpin AI development.
Fast adoption will determine who sins the race between US and China
Meanwhile, Western chipmakers are already feeling the pinch: when US authorities blocked Nvidia’s export‑friendly H20 AI chip to China, analysts estimated a $10 billion revenue hit for Nvidia.
“The No. 1 factor that will define whether the US or China wins this race is whose technology is most broadly adopted in the rest of the world,” Microsoft President Brad Smith said at a recent Senate hearing.
“Whoever gets there first will be difficult to supplant.”
American champions like OpenAI have responded with an overseas push, opening new offices in Europe and Asia. On June 25, OpenAI warned that China’s Zhipu AI is targeting emerging markets in Southeast Asia, the Middle East and Africa, aiming to cement Chinese standards before US or European rivals can gain traction.
CEO Sam Altman has framed this as a battle between “democratic AI” and “authoritarian AI,” though critics note both sides court government clients.
Unlike their US counterparts, many Chinese firms prioritize immediate, tangible applications over the grand quest for artificial general intelligence. They often release their models under open‑source licenses, Alibaba’s Qwen has already spawned over 100,000 derivative versions, allowing users worldwide to tweak and deploy them freely. Such openness pressures privately held companies like OpenAI and Anthropic to explain why their proprietary models carry hefty price tags.
On platforms like Latenode, roughly one in five customers now choose DeepSeek for custom AI tools, drawn by a price tag up to 17 times lower than competing options. That’s especially true in regions where both funding and compute resources are scarce.
Yet the splintering of global AI also raises concerns. A bifurcated ecosystem could hinder the US’ ability to shape international norms, and some observers fear Chinese models might serve as vectors for state‑approved narratives.
The US also risks losing insight into China’s ambitions and AI innovations, according to Ritwik Gupta, Al policy fellow at the University of California, Berkeley.
“If they are dependent on the global ecosystem, then we can govern it,” said Gupta. “If not, China is going to do what it is going to do, and we won’t have visibility.”
Moreover, with fewer US investments and tighter immigration rules, the traditional flow of talent and insight between Silicon Valley and Beijing is drying up. As long as China’s AI sector remains partly insulated from Western oversight, analysts warn, global transparency and shared standards may be the real casualties.
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How Trump's tariffs made AI a lifeline for businesses. The aggressive trade policies pursued by Donald Trump increased the costs of importing goods and complicated trade rules, making them unpredictable.
Companies worldwide had no choice but to quickly change how they managed supply chains, pricing strategies, and selection of global partners.