Bitcoin Market Cycle Evaluation Using Subjective Z-Scores
Introduction: I've crafted a unique indicator for Bitcoin that synthesizes multiple market indicators into a single, actionable Z-score, aiming to offer insights into the current market cycle phase. Here's the methodology:
Methodology: Alpha Validation: Each component indicator has been tested for its predictive power (alpha) against Bitcoin's market cycle peaks and troughs from at least the last two cycles. This ensures each indicator contributes meaningfully to our model. Z-Score Synthesis: By converting each indicator's value into a Z-score, we normalize their contributions. The average of these Z-scores provides a refined signal, indicating whether Bitcoin is in an overbought or oversold state relative to historical norms.
Features: Individual Indicator Customization: Users can tweak inputs to optimize each indicator's alpha, enhancing the model's predictive accuracy. Historical Averages: The script provides visibility into how both technical and fundamental indicators have scored in the past, offering a benchmark for current conditions. ROC Flexibility: Adjust the Rate of Change (ROC) period to suit your analysis timeframe, allowing for more personalized market cycle interpretation.
Indicators Integrated: Fundamental: MVRV (Market Value to Realized Value) - Measures market sentiment vs. actual value. Bitcoin Thermocap - Relates Bitcoin's market cap to its transaction volume. NUPL (Net Unrealized Profit/Loss) - Indicates holder's profit or loss status. CVDD (Coin Days Destroyed) - Shows the movement of long-held coins. SOPR (Spent Output Profit Ratio) - Highlights whether coins are being spent at a profit or loss.
Technical: RSI (Relative Strength Index) - Identifies overbought/oversold conditions. CCI (Commodity Channel Index) - Detects cyclical turns in Bitcoin's price. Multiple Moving Averages - For trend analysis over various time frames. Sharpe Ratio - Evaluates risk-adjusted return. Pi Cycle Indicator - Predicts cycle tops based on moving average crossovers. Hodrick-Prescott Filter - Separates trend from cycle in price data. VWAP (Volume Weighted Average Price) - Provides a trading benchmark.
How It Works Together: This model uses a weighted average of Z-scores from these indicators to give a comprehensive view of Bitcoin's market cycle. The Z-scores are not just summed but considered in context; for example, when fundamental indicators like MVRV suggest an overvaluation while technical ones like RSI indicate a near-term correction, the model's output reflects this nuanced interaction.
Future Developments: The next step is to include sentiment analysis, potentially from social media or news sentiment, to further refine our cycle predictions.
Chart Example: Symbol/Timeframe: BTCUSD on a daily chart. Script Name: Bitcoin Cycle Z-Score Evaluator
Feedback Encouraged: I'm eager to receive feedback on how this model could be further tailored or expanded for better market insights.
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