#市场观测指标分享

The "Signal Network" that captures trends and risks: How to navigate the crypto market with core indicators?

In the rapidly changing cryptocurrency market, indicators are not a "crystal ball," but rather pieces of a puzzle—only by combining technical analysis, on-chain data, and macro signals can we approach the truth.

1. Technical aspect: Identifying key turning points

• 200-day Moving Average (MA): The watershed for Bitcoin's long-term trend. When the price breaks through $48,000 in January 2024, the slope of the 200-day MA turns from negative to positive, triggering a massive influx of institutional funds.

• RSI Divergence: When the price reaches a new high but the Relative Strength Index (RSI) weakens (for example, when BTC hit $72,000 in March 2024, the RSI was below the previous high), it often indicates short-term pullback pressure.

2. On-chain data: Tracking the real flow of funds

• Net outflow of the exchange: Over 10,000 BTC flowed out in a single day (as during the announcement of the BlackRock Bitcoin ETF in October 2023), usually indicating the behavior of major funds accumulating positions.

• MVRV Z-Score: When this indicator is below 0.5 (as at the beginning of 2023), historical data shows that the mid-term bottom-fishing success rate exceeds 80%.

3. Macro Connections: Identifying Systemic Risk

• Real yield on US Treasuries: When the real yield on 10-year Treasury Inflation-Protected Securities (TIPS) exceeds 2% (November 2023), the valuations of high-volatility assets are generally under pressure, with BTC experiencing a decline of 12% that month.

• Dollar Index (DXY): During periods of a strong dollar (such as when DXY broke 114 in September 2022), the cryptocurrency market often faces liquidity withdrawal pressure.

Beware of false indicator traps

• Data Latency: Data such as Google search popularity and exchange traffic is usually delayed by 1-2 hours and needs to be cross-validated with real-time order book depth.

• Model Overfitting: Mechanically applying the Stock-to-Flow model may overlook real-world variables such as miner selling pressure, regulatory policies, and others.