crypto-ta-analyzer

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Chinese

Crypto & Stock Technical Analysis

加密货币与股票技术分析

Multi-indicator technical analysis system that generates high-confidence trading signals by combining 29+ proven algorithms. Features divergence detection, Bollinger Band squeeze alerts, volume confirmation, and a 7-tier signal system. Ideal for cryptocurrency and stock market analysis.

这是一个多指标技术分析系统，通过结合29+种经过验证的算法生成高可信度交易信号。具备背离检测、布林带挤压警报、成交量确认以及7级信号系统，非常适合加密货币和股票市场分析。

Core Workflow

核心工作流

1. Data Acquisition

1. 数据获取

Fetch historical price data from any supported source:

CoinGecko (via MCP tools):

Use coingecko_get_historical_chart tool with:
- coin_id: Target cryptocurrency (e.g., 'bitcoin', 'ethereum')
- days: Time range ('7', '30', '90', '365', 'max')
- vs_currency: Base currency (default 'usd')

Other Supported Sources:

Exchange APIs (Binance, Coinbase, etc.) - OHLCV format
Yahoo Finance - Stock data
Any price-only data - Automatic OHLC approximation

Minimum Requirements:

At least 100 data points for reliable analysis (50 minimum)
Price data required, volume recommended
Recent data preferred for active trading signals

从任何支持的来源获取历史价格数据：

CoinGecko（通过MCP工具）：

Use coingecko_get_historical_chart tool with:
- coin_id: Target cryptocurrency (e.g., 'bitcoin', 'ethereum')
- days: Time range ('7', '30', '90', '365', 'max')
- vs_currency: Base currency (default 'usd')

其他支持的来源：

交易所API（Binance、Coinbase等）- OHLCV格式
Yahoo Finance - 股票数据
任何仅含价格的数据 - 自动近似OHLC

最低要求:

至少100个数据点以确保分析可靠性（最低50个）
需要价格数据，推荐包含成交量数据
近期数据更适合生成活跃交易信号

2. Convert Data to OHLCV Format

2. 转换数据为OHLCV格式

The generic data converter auto-detects and normalizes any supported format:

python

from scripts.data_converter import normalize_ohlcv, validate_data_quality

通用数据转换器会自动检测并标准化任何支持的格式：

python

from scripts.data_converter import normalize_ohlcv, validate_data_quality

Auto-detect format and convert

ohlcv_df, metadata = normalize_ohlcv(raw_data, source="auto")

Check conversion quality

print(f"Format detected: {metadata['detected_format']}") print(f"Rows: {metadata['original_rows']} -> {metadata['final_rows']}") print(f"Warnings: {metadata['warnings']}")

Validate data quality

quality_report = validate_data_quality(ohlcv_df)


**Backward compatible** with old CoinGecko converter:
```python
from scripts.data_converter import prepare_analysis_data
ohlcv_df = prepare_analysis_data(coingecko_json_data)

quality_report = validate_data_quality(ohlcv_df)


**向后兼容**旧版CoinGecko转换器：
```python
from scripts.data_converter import prepare_analysis_data
ohlcv_df = prepare_analysis_data(coingecko_json_data)

3. Run Technical Analysis

3. 运行技术分析

Execute the analyzer with prepared data:

python

from scripts.ta_analyzer import TechnicalAnalyzer
import json

使用预处理的数据执行分析器：

python

from scripts.ta_analyzer import TechnicalAnalyzer
import json

Initialize analyzer with OHLCV data

analyzer = TechnicalAnalyzer(ohlcv_df)

Run comprehensive analysis

results = analyzer.analyze_all()

Display results

print(json.dumps(results, indent=2))

undefined

print(json.dumps(results, indent=2))

undefined

4. Interpret Results

4. 解读结果

Analysis returns comprehensive data including new features:

json

{
  "scoreTotal": 8.5,
  "tradeSignal": "STRONG_UPTREND",
  "tradeSignal7Tier": "STRONG_BUY",
  "tradeTrigger": true,
  "currentPrice": 45234.56,
  "priceChange24h": 3.45,
  "confidence": 0.75,
  "normalizedScore": 0.42,
  "volumeConfirmation": 0.85,
  "squeezeDetected": false,
  "divergences": {
    "RSI": "NONE",
    "MACD": "NONE",
    "OBV": "NONE"
  },
  "individualScores": {
    "RSI": 1.0,
    "MACD": 1.0,
    "BB": 0.75,
    "OBV": 0.8,
    "ICHIMOKU": 1.0,
    ...
  },
  "individualSignals": {
    "RSI": "BUY",
    "MACD": "BUY",
    "BB": "BUY",
    ...
  },
  "regime": {
    "regime": "TRENDING",
    "adx": 32.5,
    "dmiDirection": "UP"
  },
  "warnings": []
}

7-Tier Signal System (NEW):

STRONG_BUY: High confidence bullish (normalized >= 0.5, confidence >= 0.7)
BUY: Moderate confidence bullish (normalized >= 0.35, confidence >= 0.5)
WEAK_BUY: Low confidence bullish (normalized >= 0.2)
NEUTRAL: No clear direction
WEAK_SELL: Low confidence bearish (normalized <= -0.2)
SELL: Moderate confidence bearish (normalized <= -0.35, confidence >= 0.5)
STRONG_SELL: High confidence bearish (normalized <= -0.5, confidence >= 0.7)

Legacy Signal Interpretation (backward compatible):

scoreTotal >= 7.0: STRONG_UPTREND - High confidence bullish signal
scoreTotal 3.0-6.9: NEUTRAL - Mixed signals, wait for clarity
scoreTotal < 3.0: DOWNTREND - Bearish signal, avoid longs

Divergence Types:

BULLISH_DIV: Price lower low + indicator higher low = potential reversal up
BEARISH_DIV: Price higher high + indicator lower high = potential reversal down
HIDDEN_BULLISH: Trend continuation signal in uptrend
HIDDEN_BEARISH: Trend continuation signal in downtrend
NONE: No divergence detected

分析返回包含新功能的全面数据：

json

{
  "scoreTotal": 8.5,
  "tradeSignal": "STRONG_UPTREND",
  "tradeSignal7Tier": "STRONG_BUY",
  "tradeTrigger": true,
  "currentPrice": 45234.56,
  "priceChange24h": 3.45,
  "confidence": 0.75,
  "normalizedScore": 0.42,
  "volumeConfirmation": 0.85,
  "squeezeDetected": false,
  "divergences": {
    "RSI": "NONE",
    "MACD": "NONE",
    "OBV": "NONE"
  },
  "individualScores": {
    "RSI": 1.0,
    "MACD": 1.0,
    "BB": 0.75,
    "OBV": 0.8,
    "ICHIMOKU": 1.0,
    ...
  },
  "individualSignals": {
    "RSI": "BUY",
    "MACD": "BUY",
    "BB": "BUY",
    ...
  },
  "regime": {
    "regime": "TRENDING",
    "adx": 32.5,
    "dmiDirection": "UP"
  },
  "warnings": []
}

7级信号系统（新增）：

STRONG_BUY: 高可信度看涨（标准化分数 >= 0.5，置信度 >= 0.7）
BUY: 中等可信度看涨（标准化分数 >= 0.35，置信度 >= 0.5）
WEAK_BUY: 低可信度看涨（标准化分数 >= 0.2）
NEUTRAL: 无明确方向
WEAK_SELL: 低可信度看跌（标准化分数 <= -0.2）
SELL: 中等可信度看跌（标准化分数 <= -0.35，置信度 >= 0.5）
STRONG_SELL: 高可信度看跌（标准化分数 <= -0.5，置信度 >= 0.7）

旧版信号解读（向后兼容）：

scoreTotal >= 7.0: STRONG_UPTREND - 高可信度看涨信号
scoreTotal 3.0-6.9: NEUTRAL - 信号混杂，等待明确方向
scoreTotal < 3.0: DOWNTREND - 看跌信号，避免做多

背离类型:

BULLISH_DIV: 价格更低低点 + 指标更高低点 = 潜在向上反转
BEARISH_DIV: 价格更高高点 + 指标更低高点 = 潜在向下反转
HIDDEN_BULLISH: 上涨趋势中的趋势延续信号
HIDDEN_BEARISH: 下跌趋势中的趋势延续信号
NONE: 未检测到背离

Available Indicators (29)

可用指标（29种）

Core Indicators (10) - Weight: 1.0

核心指标（10种）- 权重：1.0

RSI (Relative Strength Index) - Momentum oscillator with divergence detection
MACD (Moving Average Convergence Divergence) - Trend-following momentum with divergence
BB (Bollinger Bands) - NEW: Volatility bands with squeeze detection
OBV (On-Balance Volume) - NEW: Volume-price divergence indicator
ICHIMOKU (Ichimoku Cloud) - NEW: Multi-component trend system (crypto-optimized 10/30/60)
EMA (Exponential Moving Average) - Short/long crossover
SMA (Simple Moving Average) - Short/long crossover
MFI (Money Flow Index) - Volume-weighted RSI
KDJ (Stochastic with J line) - Overbought/oversold with momentum
SAR (Parabolic SAR) - Trend reversal detection

RSI（相对强弱指数）- 带背离检测的动量振荡器
MACD（指数平滑异同移动平均线）- 带背离的趋势跟踪动量指标
BB（布林带）- 新增：带挤压检测的波动带
OBV（能量潮）- 新增：量价背离指标
ICHIMOKU（一目均衡表）- 新增：多组件趋势系统（针对加密货币优化的10/30/60参数）
EMA（指数移动平均线）- 短期/长期均线交叉
SMA（简单移动平均线）- 短期/长期均线交叉
MFI（资金流量指数）- 成交量加权RSI
KDJ（随机指标带J线）- 超买/超卖与动量指标
SAR（抛物转向指标）- 趋势反转检测

Strong Indicators (5) - Weight: 0.75

重要指标（5种）- 权重：0.75

DEMA (Double Exponential MA) - Reduced lag moving average
MESA (MESA Adaptive MA) - Ehlers Hilbert Transform based
CCI (Commodity Channel Index) - Cyclical trend identification
AROON - Trend timing indicator
APO (Absolute Price Oscillator) - Trend strength

DEMA（双指数移动平均线）- 减少滞后的移动平均线
MESA（自适应移动平均线）- 基于Ehlers希尔伯特变换
CCI（商品通道指数）- 周期性趋势识别
AROON - 趋势时机指标
APO（绝对价格振荡器）- 趋势强度

Supporting Indicators (14) - Weight: 0.5

辅助指标（14种）- 权重：0.5

ADX (Average Directional Index) - Trend strength
DMI (Directional Movement Index) - Trend direction
CMO (Chande Momentum Oscillator) - Modified RSI
KAMA (Kaufman Adaptive MA) - Volatility-adjusted MA
MOMI (Momentum) - Rate of price change
PPO (Percentage Price Oscillator) - Normalized MACD
ROC (Rate of Change) - Percentage momentum
TRIMA (Triangular MA) - Smoothed moving average
TRIX (Triple Exponential MA) - Smoothed momentum
T3 (Tillson T3) - Low-lag smooth MA
WMA (Weighted MA) - Linearly weighted
VWAP (Volume Weighted Average Price) - NEW: Institutional reference
ATR_SIGNAL (ATR Volatility Signal) - NEW: Volatility-based signals
CAD (CMO with Regime-Aware Mean Reversion) - Adaptive momentum

See references/indicators.md for detailed indicator explanations.

ADX（平均趋向指数）- 趋势强度
DMI（方向移动指数）- 趋势方向
CMO（钱德动量振荡器）- 改良版RSI
KAMA（考夫曼自适应移动平均线）- 波动率调整移动平均线
MOMI（动量指标）- 价格变化率
PPO（百分比价格振荡器）- 标准化MACD
ROC（变化率指标）- 百分比动量
TRIMA（三角移动平均线）- 平滑移动平均线
TRIX（三重指数移动平均线）- 平滑动量指标
T3（Tillson T3指标）- 低滞后平滑移动平均线
WMA（加权移动平均线）- 线性加权
VWAP（成交量加权平均价格）- 新增：机构参考指标
ATR_SIGNAL（ATR波动率信号）- 新增：基于波动率的信号
CAD（带趋势感知均值回归的CMO）- 自适应动量指标

详见 references/indicators.md 获取指标详细说明。

Usage Patterns

使用模式

Quick Analysis

快速分析

For rapid assessment of a single cryptocurrency:

1. Call coingecko_get_historical_chart for target coin (7-30 days)
2. Convert data using coingecko_converter
3. Run ta_analyzer.analyze_all()
4. Present scoreTotal and tradeSignal to user

用于快速评估单一加密货币：

1. 调用coingecko_get_historical_chart获取目标币种数据（7-30天）
2. 使用coingecko_converter转换数据
3. 运行ta_analyzer.analyze_all()
4. 向用户展示scoreTotal和tradeSignal

Comparative Analysis

对比分析

To compare multiple cryptocurrencies:

1. Call coingecko_compare_coins for target coins
2. For each coin:
   - Fetch historical chart data
   - Run technical analysis
   - Store results
3. Create comparison table with scores and signals
4. Identify strongest/weakest performers

用于对比多种加密货币：

1. 调用coingecko_compare_coins获取目标币种数据
2. 对每个币种：
   - 获取历史图表数据
   - 运行技术分析
   - 存储结果
3. 创建包含分数和信号的对比表格
4. 识别表现最强/最弱的币种

Deep Dive Analysis

深度分析

For comprehensive assessment with context:

1. Fetch multiple timeframes (7d, 30d, 90d)
2. Run analysis on each timeframe
3. Check for signal agreement across timeframes
4. Review individual indicator signals for divergences
5. Cross-reference with market data (market cap, volume, dominance)
6. Provide detailed report with confidence levels

用于结合上下文的全面评估：

1. 获取多个时间框架数据（7天、30天、90天）
2. 对每个时间框架运行分析
3. 检查不同时间框架的信号一致性
4. 查看单个指标信号的背离情况
5. 与市场数据（市值、成交量、主导地位）交叉参考
6. 提供包含置信度的详细报告

Trend Monitoring

趋势监控

For ongoing market surveillance:

1. Fetch current data for watchlist
2. Run analysis on all coins
3. Filter for STRONG_UPTREND signals (score >= 7)
4. Rank by score descending
5. Present top opportunities with context

用于持续市场监控：

1. 获取观察列表的当前数据
2. 对所有币种运行分析
3. 筛选出STRONG_UPTREND信号（分数 >=7）
4. 按分数降序排名
5. 结合上下文展示顶级机会

Best Practices

最佳实践

Data Quality

数据质量

Always validate data quality before analysis using validate_data_quality()
Ensure minimum 100 data points (preferably 200+)
Check for missing values or data gaps
Use appropriate timeframe for user's trading strategy

始终验证分析前的数据质量，使用validate_data_quality()
确保至少100个数据点（优选200+）
检查缺失值或数据缺口
根据用户的交易策略选择合适的时间框架

Interpretation Guidelines

解读指南

Never rely on single indicator - the power is in consensus
Consider market context - indicators behave differently in trending vs ranging markets
Watch for divergences - when price contradicts indicators, reversal may be coming
Volume confirms price - MFI provides crucial validation
Multiple timeframes - confirm signals across different periods

绝不依赖单一指标 - 优势在于多个指标的共识
考虑市场环境 - 指标在趋势市场和震荡市场中的表现不同
关注背离 - 当价格与指标矛盾时，可能即将出现反转
成交量确认价格 - MFI提供关键验证
多时间框架 - 在不同周期确认信号

Common Patterns

常见模式

High Conviction Bullish (STRONG_BUY):

7-tier signal: STRONG_BUY or BUY
Confidence >= 0.7
RSI between 30-70 (not overbought)
MACD bullish crossover
Price above Ichimoku cloud
OBV confirms with no bearish divergence
Volume confirmation >= 0.7
ADX > 25 (strong trend)

Breakout Setup:

Bollinger Band squeeze detected (squeezeDetected: true)
ADX rising from < 20
Volume starting to increase
Watch for band expansion

Trend Exhaustion Warning:

Score > 7 BUT RSI > 80 or MFI > 90
Bearish divergence on RSI, MACD, or OBV
Price above Bollinger upper band (%B > 1.0)
Potential reversal or pullback incoming

Divergence-Based Reversal:

Bearish divergence: Prepare for potential top
Bullish divergence: Watch for potential bottom
OBV divergence is most reliable (volume precedes price)

False Breakout:

Strong price move BUT ADX < 20
Low volume (volumeConfirmation < 0.5)
OBV not confirming price move
Likely whipsaw or temporary spike

Ichimoku Confirmation:

Price above cloud + Tenkan above Kijun = Strong bullish
Price below cloud + Tenkan below Kijun = Strong bearish
Price inside cloud = No-trade zone, wait for clarity

高可信度看涨（STRONG_BUY）:

7级信号：STRONG_BUY或BUY
置信度 >=0.7
RSI在30-70之间（未超买）
MACD看涨交叉
价格在Ichimoku云上方
OBV确认趋势，无看跌背离
成交量确认 >=0.7
ADX >25（强趋势）

突破设置:

检测到布林带挤压（squeezeDetected: true）
ADX从<20开始上升
成交量开始增加
关注带宽扩大

趋势衰竭警告:

分数>7但RSI>80或MFI>90
RSI、MACD或OBV出现看跌背离
价格高于布林带上轨（%B >1.0）
可能即将出现反转或回调

背离驱动的反转:

看跌背离：准备应对潜在顶部
看涨背离：关注潜在底部
OBV背离最可靠（成交量领先价格）

假突破:

价格大幅波动但ADX<20
低成交量（volumeConfirmation <0.5）
OBV未确认价格走势
可能是洗盘或临时 spike

Ichimoku确认:

价格在云上方 + Tenkan线在Kijun线上方 = 强看涨
价格在云下方 + Tenkan线在Kijun线下方 = 强看跌
价格在云内 = 无交易区间，等待明确方向

Limitations

局限性

CoinGecko Data Considerations

CoinGecko数据注意事项

CoinGecko provides price points, not true OHLC bars
Converter approximates OHLC from adjacent prices
Works well for trend analysis, less precise for intraday patterns

CoinGecko提供价格点，而非真实OHLCK线
转换器通过相邻价格近似OHLC
适用于趋势分析，对日内模式的精确度较低

Indicator Nature

指标特性

Most indicators are lagging - calculated from past data
Can generate whipsaws in choppy, sideways markets
Overfitting risk - too many indicators can cause analysis paralysis
Market regime changes require adaptation

大多数指标是滞后性的 - 基于历史数据计算
在震荡、横盘市场中可能产生虚假信号
过拟合风险 - 过多指标可能导致分析瘫痪
市场趋势变化需要调整

Recommended Use Cases

Advanced Techniques

高级技巧

Custom Scoring Weights

自定义评分权重

Modify indicator weights based on market conditions:

Trending markets: Increase weight of MACD, EMA, ADX
Ranging markets: Increase weight of RSI, CCI, Stochastic
High volatility: Increase weight of SAR, KAMA (adaptive indicators)

根据市场条件调整指标权重：

趋势市场: 增加MACD、EMA、ADX的权重
震荡市场: 增加RSI、CCI、随机指标的权重
高波动市场: 增加SAR、KAMA（自适应指标）的权重

Multi-Timeframe Confirmation

多时间框架确认

Analyze same coin across multiple timeframes:

- 7 days (short-term trend)
- 30 days (medium-term trend)  
- 90 days (long-term trend)

Strongest signals occur when all timeframes agree.

分析同一币种的多个时间框架：

- 7天（短期趋势）
- 30天（中期趋势）  
- 90天（长期趋势）

所有时间框架信号一致时，信号强度最高。

Sector Analysis

板块分析

Analyze multiple coins in same sector to identify:

Sector-wide trends vs individual coin movements
Relative strength leaders
Laggard coins with catch-up potential

分析同一板块的多个币种，以识别：

板块-wide趋势与单个币种走势
相对强度领先者
有补涨潜力的落后币种

Troubleshooting

故障排除

Issue: Score stuck at 0 or very low

问题：分数卡在0或极低

Cause: Insufficient data or flat price action
Solution: Fetch longer historical period or check data quality

原因: 数据不足或价格走势平稳
解决方案: 获取更长周期的历史数据或检查数据质量

Issue: Conflicting signals across indicators

问题：指标信号冲突

Cause: Market in transition or ranging
Solution: Score will be neutral - wait for clearer direction

原因: 市场处于过渡阶段或震荡行情
解决方案: 分数会显示为中性 - 等待明确方向

Issue: High score but bearish user intuition

问题：分数高但用户直觉看跌

Cause: Indicators lag price, or news-driven move
Solution: Cross-reference with market context, recent news, volume

原因: 指标滞后于价格，或受消息驱动的走势影响
解决方案: 结合市场背景、近期新闻、成交量进行交叉参考

Issue: Analysis fails with NaN values

问题：分析因NaN值失败

Cause: Insufficient data for indicator calculation
Solution: Fetch minimum 100 data points, preferably 200+

原因: 指标计算所需数据不足
解决方案: 获取至少100个数据点，优选200+

Integration with CoinGecko MCP

与CoinGecko MCP集成

This skill is designed to work seamlessly with CoinGecko MCP tools:

Primary Tools Used:

```
coingecko_get_historical_chart
```
- Main data source
```
coingecko_get_price
```
- Quick current price checks
```
coingecko_compare_coins
```
- Multi-coin analysis
```
coingecko_get_market_data
```
- Context and validation

Workflow Integration:

User asks about a cryptocurrency
Use CoinGecko tools to fetch data
Convert to OHLCV format
Run technical analysis
Present results with context from market data

本工具专为与CoinGecko MCP工具无缝协作设计：

主要使用工具:

```
coingecko_get_historical_chart
```
- 主要数据源
```
coingecko_get_price
```
- 快速当前价格查询
```
coingecko_compare_coins
```
- 多币种分析
```
coingecko_get_market_data
```
- 背景信息与验证

工作流集成:

用户询问某加密货币相关问题
使用CoinGecko工具获取数据
转换为OHLCV格式
运行技术分析
结合市场数据背景展示结果

Example Outputs

示例输出

Simple Analysis Response

简单分析响应

Bitcoin Technical Analysis (7-day period)

📊 7-Tier Signal: STRONG_BUY
🎯 Confidence: 78%
💰 Current Price: $45,234.56 (+3.45% 24h)
📈 Volume Confirmation: 85%

Key Indicators:
✅ RSI: BUY (38.2 - healthy level, no divergence)
✅ MACD: BUY (bullish crossover, no divergence)
✅ Bollinger: BUY (price near upper band, no squeeze)
✅ OBV: BUY (volume confirms trend, no divergence)
✅ Ichimoku: BUY (price above cloud)
✅ Volume: ACCUMULATION (MFI bullish)

Warnings: None

Recommendation: Strong buy signal with volume confirmation.
No divergences or overbought conditions detected.

Bitcoin Technical Analysis (7-day period)

📊 7-Tier Signal: STRONG_BUY
🎯 Confidence: 78%
💰 Current Price: $45,234.56 (+3.45% 24h)
📈 Volume Confirmation: 85%

Key Indicators:
✅ RSI: BUY (38.2 - healthy level, no divergence)
✅ MACD: BUY (bullish crossover, no divergence)
✅ Bollinger: BUY (price near upper band, no squeeze)
✅ OBV: BUY (volume confirms trend, no divergence)
✅ Ichimoku: BUY (price above cloud)
✅ Volume: ACCUMULATION (MFI bullish)

Warnings: None

Recommendation: Strong buy signal with volume confirmation.
No divergences or overbought conditions detected.

Comparative Analysis Response

对比分析响应

Top 5 Cryptocurrencies by Technical Score (30-day analysis)

1. Solana (SOL): 9.0 - STRONG_UPTREND
   - All momentum indicators bullish
   - Strong volume confirmation
   
2. Ethereum (ETH): 7.5 - STRONG_UPTREND
   - Trending higher, minor overbought warning
   
3. Bitcoin (BTC): 5.0 - NEUTRAL
   - Consolidating after recent move
   
4. Cardano (ADA): 2.5 - DOWNTREND
   - Multiple bearish signals
   
5. XRP: 1.0 - DOWNTREND
   - Weak momentum and volume

Top 5 Cryptocurrencies by Technical Score (30-day analysis)

1. Solana (SOL): 9.0 - STRONG_UPTREND
   - All momentum indicators bullish
   - Strong volume confirmation
   
2. Ethereum (ETH): 7.5 - STRONG_UPTREND
   - Trending higher, minor overbought warning
   
3. Bitcoin (BTC): 5.0 - NEUTRAL
   - Consolidating after recent move
   
4. Cardano (ADA): 2.5 - DOWNTREND
   - Multiple bearish signals
   
5. XRP: 1.0 - DOWNTREND
   - Weak momentum and volume

crypto-ta-analyzer

Original

Translation

Crypto & Stock Technical Analysis

加密货币与股票技术分析

Core Workflow

核心工作流

1. Data Acquisition

1. 数据获取

2. Convert Data to OHLCV Format

2. 转换数据为OHLCV格式

Auto-detect format and convert

Auto-detect format and convert

Check conversion quality

Check conversion quality

Validate data quality

Validate data quality

3. Run Technical Analysis

3. 运行技术分析

Initialize analyzer with OHLCV data

Initialize analyzer with OHLCV data

Run comprehensive analysis

Run comprehensive analysis

Display results

Display results

4. Interpret Results

4. 解读结果

Available Indicators (29)

可用指标（29种）

Core Indicators (10) - Weight: 1.0

核心指标（10种）- 权重：1.0

Strong Indicators (5) - Weight: 0.75

重要指标（5种）- 权重：0.75

Supporting Indicators (14) - Weight: 0.5

辅助指标（14种）- 权重：0.5

Usage Patterns

使用模式

Quick Analysis

快速分析

Comparative Analysis

对比分析

Deep Dive Analysis

深度分析

Trend Monitoring

趋势监控

Best Practices

最佳实践

Data Quality

数据质量

Interpretation Guidelines

解读指南

Common Patterns

常见模式

Limitations

局限性

CoinGecko Data Considerations

CoinGecko数据注意事项

Indicator Nature

指标特性

Recommended Use Cases

推荐使用场景

Advanced Techniques

高级技巧

Custom Scoring Weights

自定义评分权重

Multi-Timeframe Confirmation

多时间框架确认

Sector Analysis

板块分析

Troubleshooting

故障排除

Issue: Score stuck at 0 or very low

问题：分数卡在0或极低

Issue: Conflicting signals across indicators

问题：指标信号冲突

Issue: High score but bearish user intuition

问题：分数高但用户直觉看跌

Issue: Analysis fails with NaN values

问题：分析因NaN值失败

Integration with CoinGecko MCP