威科夫点数图的绘制与应用：股票涨跌空间判断

Quantitative Models and Factor Construction Quantitative Models and Construction Process 1. Model Name: Point and Figure Chart (P&F) Model Construction Idea: The P&F chart is based on Wyckoff's "cause and effect" principle, which links the accumulation/distribution phase to subsequent price movement. It uses effective price oscillations in a consolidation range to predict the magnitude of price breakout, emphasizing "how long horizontally, how high vertically" in terms of price oscillations rather than time[1][7][9]. Model Construction Process: - Single Point P&F Chart: Records price movements without considering time. For example, if a stock price moves from 50 to 53, it records 50, 51, 52, and 53 in one column. A reversal in price direction starts a new column[16][19]. - Three-Point P&F Chart: Introduces a "reversal value" parameter (Reversal = 3), filtering out minor price movements. This chart is more focused on medium-term trends. The box size (Box Size) is dynamically adjusted based on recent price levels, e.g., a fixed 2% proportion[21][22]. - Target Price Formula: $ Target\ Price = Horizontal\ Columns \times Box\ Size \times Reversal\ Value + Starting\ Price $ Horizontal columns represent the number of columns in the trading range, excluding the initial and final trend columns. The starting price can be the lowest/highest price in the range or the last price before the breakout[30][31]. Model Evaluation: The P&F chart effectively compresses price consolidation ranges, highlights key breakout signals, and provides a quantitative framework for price target estimation. However, it lacks time dimension and is sensitive to external shocks[15][83]. 2. Model Name: Trading Range Quantification Model Construction Idea: Defines trading ranges quantitatively to ensure accurate P&F chart predictions. A trading range is identified based on price oscillations and structural rules[42][46]. Model Construction Process: - Minimum 5 columns are required for a trading range, with the width not significantly exceeding the height (to avoid extreme oscillations). - Identification Rules: - If the right-hand side (RHS) three columns overlap with the current column by more than 20%, and the fourth RHS column overlaps with the first three by more than 50%, the RHS condition is satisfied. - If the RHS four columns overlap with the left-hand side (LHS) first column by less than 20%, the LHS condition is satisfied. - If both RHS and LHS conditions are met, the five columns form a trading range. - Expansion Rules: Subsequent columns are added if they overlap with the RHS three columns and their LHS three columns by at least 50% each. - Width-Height Check: If the maximum price difference (in points) divided by the width exceeds 1.5, the range is discarded[46][49][50]. Model Evaluation: The rules effectively identify trading ranges, ensuring the P&F chart's predictive accuracy. However, extreme oscillations or complex market conditions may challenge its application[51][52]. Model Backtesting Results 1. P&F Chart: - Accuracy: - For upward targets: 20% achieved with 0-point error, 73% within ±5 points. - For downward targets: 20% achieved with 0-point error, 76% within ±5 points[62][63]. - Impact of Initial Space: - Initial space 10%-20%: 23% precision, 82% within ±5 points. - Initial space 20%-50%: 17% precision, 64% within ±5 points. - Initial space >50%: 9% precision, 38% within ±5 points. Predictions for >50% space should be conservatively adjusted by 30%[67][68]. 2. Quantitative Strategy Using P&F Chart: - Annualized Return: 18.1% (2010-2024), outperforming the Wind All A Index (3.8%) and pure timing strategy (8.5%). - Maximum Drawdown: -35.0%, compared to -56.0% for the Wind All A Index and -28.5% for the timing strategy. The strategy improves risk-return characteristics[77][80]. Quantitative Factors and Construction Process 1. Factor Name: Effective Oscillation Count Factor Construction Idea: Measures the number of effective oscillations in a trading range to estimate breakout potential. More oscillations indicate higher breakout potential[1][7]. Factor Construction Process: - Count the number of price oscillations within a defined trading range. - Use the count to estimate the breakout magnitude using the target price formula[30][31]. Factor Evaluation: Provides a robust measure of market accumulation/distribution phases, aiding in price target estimation. However, it may be less effective in highly volatile or irregular markets[15][83]. Factor Backtesting Results 1. Effective Oscillation Count: - Prediction Accuracy: - 70% of targets (upward/downward) achieved within ±5 points in the CSI 800, CSI 1000, and CSI 2000 indices. - Prediction accuracy is independent of market capitalization[62][63][66]. - Impact of Initial Space: Predictions for >50% initial space require conservative adjustments to avoid overestimation[67][68].