U.S. Federal Reserve's Barr Holds Line on Central Bank Needing Stablecoin Powers

CoinDeskPolicyPubblicato 2023-11-06Pubblicato ultima volta 2023-11-07

Introduzione

Vice Chairman Michael Barr argued that the Fed needs regulatory and enforcement authority over stablecoin issuers – a point of contention in the debate over legislation.

The U.S. Federal Reserve needs to regulate and enforce the law against stablecoin issuers, said Federal Reserve Vice Chairman for Supervision Michael Barr, making the federal-oversight argument that has been the major sticking point as the U.S. House of Representatives debates legislation.

Republican lawmakers have leaned into a state-oversight route for companies issuing stablecoins – the steady tokens whose value is pegged to a less volatile asset such as the dollar – and Democrats have favored a dominant role for the Fed. Barr is decidedly in the latter camp.

"We need a strong federal framework," he said Tuesday at the DC Fintech Week event in Washington. "They're creating a form of private money, and private money needs to be well-regulated."

Lawmakers have moved a stablecoin bill through the House Financial Services Committee, winning some support from a handful of Democrats on that panel. The regulatory effort would still need to pass a floor vote in the House, though possibly attached to another must-pass spending bill. Then it needs Senate approval, which has so far been harder to come by.

Barr also addressed the idea of a central bank digital currency (CBDC) in the U.S., saying the Fed is still entirely in the research phase.

"We haven't made a decision on whether it would be a good idea," he said. And he repeated the recent promises from the central bank that it won't move on a digital dollar unless the White House and Congress "clearly authorize" establishing such a thing.

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Bitcoin Trading Strategy Breakdown: Celebrity Predictions and Classic Models All Fail, Only These Four Indicators Remain

Analysis of Bitcoin Trading Strategies: Why Celebrity Forecasts and Classic Models Fail, Leaving Only These Four Reliable Indicators This analysis examines the failure of common Bitcoin prediction methods and identifies four reliable indicators for constructing a trading strategy. The author reviewed all major BTC prediction approaches from 2017-2025, categorizing them into three groups: celebrity price targets (consistently over-optimistic), analytical models like Stock-to-Flow (broken post-2022), and on-chain signals. The key finding is that more data often creates confusion, not clarity. The strategy discards unreliable elements: celebrity predictions (incentivized to be extreme), pure models (invalidated by post-ETF market changes), and the Fear & Greed Index used alone (too many false signals). Four reliable indicators were selected: 1. **MVRV Z-Score:** Accurately identifies cycle bottoms when entering its green zone (e.g., 2018, 2020, 2022). Note: Its ability to call tops is now ineffective post-2024. 2. **SOPR (28-day MA):** Consistently signals bottoms when below 1.0, indicating holders are selling at a loss. 3. **ETF Net Flow:** A crucial post-2024 metric showing institutional momentum (e.g., sustained inflows = buying). 4. **Macro Liquidity (Fed policy & M2):** Sets the overall directional bias (e.g., bullish during easing cycles). The core strategy involves waiting for a multi-signal共振 (resonance). For example, a bottom signal requires MVRV in the green zone + SOPR < 1.0. A top signal requires overheated on-chain data + sustained ETF outflows. Macro policy sets the overall direction. The Fear & Greed Index is only used as a weighted confirmatory signal, never alone. Action is only taken when three or more indicators align. The author automated this into a monitoring system that sends Telegram alerts only when signals trigger. As of the article's date (April 15, 2026), the system showed a strong bottom signal: extreme fear (F&G=12), MVRV in the buy zone, and SOPR < 1.0. The only contrary signal was weak ETF flows. Historically, such triple on-chain共振 has preceded 100%+ returns. The conclusion emphasizes building a personal framework over relying on external predictions, allowing for iterative improvement and customization based on individual risk tolerance.

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Bitcoin Trading Strategy Breakdown: Celebrity Predictions and Classic Models All Fail, Only These Four Indicators Remain

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