XRPUSD Daily Outlook

Token Post发布于2024-08-13更新于2024-08-13

Ripple is consolidating in a narrow range between $0.4327 and $0.6580 for the past two weeks. The Securities Exchange Commission (SEC) has ordered Ripple to pay $125 million in penalties for violating laws through institutional XRP sales and the SEC reduced their initial penalty from $2 billion.

Ichimoku analysis (4- hour chart)

Tenken-Sen- $0.57062

Kijun-Sen- $0.59377

Horizontal trend line- $0.750

Downtrend channel resistance- $0.680

XRPUSD has performed well after a minor weakness.

Any daily close above $0.830 confirms further bullishness.

XRPUSD prices showed a minor sell-off after forming a double top.It hit a high of $0.6580 and is currently trading around $0.57277.

92. The pair holds above the short-term (21 and 55-day EMA) and the long-term moving average (200-day EMA).

The near-term resistance is around $0.6800, any indicative breach above will take the pair to $0.75/0.820/0.900/$1. On the lower side, immediate support is $0.5450, and any violation below targets $0.50/$0.45/$0.40.

Indicators ( 4- hour chart)

Directional movement index - Neutral

It is good to buy on dips around $0.55 with SL around $0.40 for TP of $1.

TokenPost | [email protected]

你可能也喜欢

拖更三年,北大校友翁荔最新长文刷屏

前OpenAI副总裁翁荔(Lilian Weng)发表了一篇关于AI扩展定律(Scaling Laws)的深度分析文章。文章指出,这条指导了AI行业数百亿美元投入的核心定律,远比人们想象的更为脆弱。 文章回顾了Scaling Laws的基本思想,即模型性能随规模扩大而可预测地提升。然而,OpenAI与DeepMind在关键问题上得出了相反结论:给定算力,资源应更多分配给模型还是数据?OpenAI的Kaplan团队认为模型增长应更快,而DeepMind的Chinchilla团队则认为应等比增长。后来研究发现,这一分歧源于参数统计口径的差异和实验规模不足,导致Kaplan的结论仅适用于小规模场景。 更关键的是,被行业广泛采纳的Chinchilla最优配比公式本身也存在方法论瑕疵。2024年有团队复现发现,其损失函数因取均值而非求和,导致优化器提前停止,输出并非最优解。此外,用于外推的关键参数精度不足,放大了误差。 文章进一步指出,经典Scaling Laws的根本前提——高质量数据无限供应——正在崩塌。数据重复训练不可避免,新研究引入了惩罚项来修正公式,并发现大模型对数据重复更敏感。这解释了行业为何转向强化学习、测试时计算和合成数据等新路径。 翁荔的博客以其清晰深入的技术解析著称,这篇文章历时三年完成。她于2025年联合创立了新公司Thinking Machines Lab。文章强调,下一代AI的进步不仅依赖算力规模,更取决于对这些基础定律细节更精确的理解与运用。

marsbit46分钟前

拖更三年,北大校友翁荔最新长文刷屏

marsbit46分钟前

交易

现货
合约
活动图片