修正股票日线复权滚动因子口径

crates/fidc-core/src/data.rs

@@ -486,6 +486,76 @@ struct SymbolPriceSeries {
     volume_prefix: Vec<f64>,
 }
 
+#[derive(Debug, Clone)]
+struct AdjustedCloseSeries {
+    dates: Vec<NaiveDate>,
+    backward_factors: Vec<f64>,
+    back_adjusted_closes: Vec<f64>,
+}
+
+impl AdjustedCloseSeries {
+    fn new(
+        market: &SymbolPriceSeries,
+        factor_by_date: &BTreeMap<NaiveDate, Vec<Arc<DailyFactorSnapshot>>>,
+    ) -> Option<Self> {
+        let mut backward_factors = Vec::with_capacity(market.dates.len());
+        let mut back_adjusted_closes = Vec::with_capacity(market.dates.len());
+        for (date, close) in market.dates.iter().zip(&market.closes) {
+            if !close.is_finite() || *close <= 0.0 {
+                return None;
+            }
+            let factor = factor_by_date
+                .get(date)
+                .and_then(|rows| {
+                    find_arc_by_symbol(rows, &market.symbol, |row| row.symbol.as_str())
+                })
+                .and_then(|snapshot| {
+                    factor_numeric_value(snapshot, "adjustment_factor_backward1")
+                })?;
+            if !factor.is_finite() || factor <= 0.0 {
+                return None;
+            }
+            backward_factors.push(factor);
+            back_adjusted_closes.push(close * factor);
+        }
+        Some(Self {
+            dates: market.dates.clone(),
+            backward_factors,
+            back_adjusted_closes,
+        })
+    }
+
+    fn current_moving_average(&self, date: NaiveDate, lookback: usize) -> Option<f64> {
+        if lookback == 0 {
+            return None;
+        }
+        let end = match self.dates.binary_search(&date) {
+            Ok(index) => index + 1,
+            Err(0) => return None,
+            Err(index) => index,
+        };
+        if end < lookback {
+            return None;
+        }
+        let base_factor = *self.backward_factors.get(end - 1)?;
+        if !base_factor.is_finite() || base_factor <= 0.0 {
+            return None;
+        }
+        let start = end - lookback;
+        let sum = self.back_adjusted_closes[start..end]
+            .iter()
+            .copied()
+            .sum::<f64>();
+        if !sum.is_finite() {
+            return None;
+        }
+        Some(normalize_rolling_factor(
+            sum / lookback as f64 / base_factor,
+            12,
+        ))
+    }
+}
+
 impl SymbolPriceSeries {
     fn new<'a, I>(symbol: String, rows: I) -> Self
     where
@@ -701,8 +771,14 @@ impl SymbolPriceSeries {
             return None;
         }
         let start = end - lookback;
-        let sum = self.volume_prefix[end] - self.volume_prefix[start];
+        let sum = self.volumes[start..end]
-        Some(sum / lookback as f64)
+            .iter()
+            .map(|value| *value as f64)
+            .sum::<f64>();
+        if !sum.is_finite() {
+            return None;
+        }
+        Some(normalize_rolling_factor(sum / lookback as f64, 6))
     }
 
     fn decision_volume_values(&self, date: NaiveDate, lookback: usize) -> Option<Vec<f64>> {
@@ -948,6 +1024,7 @@ pub struct DataSet {
     order_book_depth_index: HashMap<(NaiveDate, String), Vec<IntradayOrderBookDepthLevel>>,
     benchmark_by_date: BTreeMap<NaiveDate, BenchmarkSnapshot>,
     market_series_by_symbol: Arc<RwLock<HashMap<String, Arc<SymbolPriceSeries>>>>,
+    adjusted_close_series_by_symbol: Arc<RwLock<HashMap<String, Arc<AdjustedCloseSeries>>>>,
     benchmark_series_cache: BenchmarkPriceSeries,
     eligible_universe_by_date: Arc<OnceLock<BTreeMap<NaiveDate, Vec<EligibleUniverseSnapshot>>>>,
     benchmark_code: String,
@@ -1158,6 +1235,7 @@ impl DataSet {
             order_book_depth_index,
             benchmark_by_date,
             market_series_by_symbol: Arc::new(RwLock::new(HashMap::new())),
+            adjusted_close_series_by_symbol: Arc::new(RwLock::new(HashMap::new())),
             benchmark_series_cache,
             eligible_universe_by_date: Arc::new(OnceLock::new()),
             benchmark_code,
@@ -1241,6 +1319,31 @@ impl DataSet {
         )
     }
 
+    fn adjusted_close_series(&self, symbol: &str) -> Option<Arc<AdjustedCloseSeries>> {
+        if let Some(series) = self
+            .adjusted_close_series_by_symbol
+            .read()
+            .expect("adjusted close series cache lock poisoned")
+            .get(symbol)
+            .cloned()
+        {
+            return Some(series);
+        }
+
+        let market = self.market_series(symbol)?;
+        let series = Arc::new(AdjustedCloseSeries::new(&market, &self.factor_by_date)?);
+        let mut cache = self
+            .adjusted_close_series_by_symbol
+            .write()
+            .expect("adjusted close series cache lock poisoned");
+        Some(
+            cache
+                .entry(symbol.to_string())
+                .or_insert_with(|| Arc::clone(&series))
+                .clone(),
+        )
+    }
+
     pub fn factor(&self, date: NaiveDate, symbol: &str) -> Option<&DailyFactorSnapshot> {
         self.factor_by_date
             .get(&date)
@@ -2308,9 +2411,9 @@ impl DataSet {
     ) -> Option<f64> {
         let field = normalize_field(field);
         match field.as_str() {
-            "close" | "prev_close" | "stock_close" | "price" => {
+            "close" | "prev_close" | "stock_close" | "price" => self
-                self.market_moving_average(date, symbol, lookback, PriceField::Close)
+                .adjusted_close_series(symbol)
-            }
+                .and_then(|series| series.current_moving_average(date, lookback)),
             "volume" | "stock_volume" => self
                 .market_series(symbol)
                 .and_then(|series| series.current_volume_moving_average(date, lookback))
@@ -2908,6 +3011,11 @@ fn prefix_sums(values: &[f64]) -> Vec<f64> {
     prefix
 }
 
+fn normalize_rolling_factor(value: f64, decimals: i32) -> f64 {
+    let scale = 10_f64.powi(decimals);
+    (value * scale).round() / scale
+}
+
 mod optional_date_format {
     use chrono::NaiveDate;
     use serde::{self, Deserialize, Deserializer, Serializer};
@@ -3307,6 +3415,96 @@ mod tests {
         );
     }
 
+    #[test]
+    fn current_close_average_uses_backward_adjustment_factor_and_current_base() {
+        let dates = [
+            NaiveDate::parse_from_str("2025-01-02", "%Y-%m-%d").unwrap(),
+            NaiveDate::parse_from_str("2025-01-03", "%Y-%m-%d").unwrap(),
+            NaiveDate::parse_from_str("2025-01-06", "%Y-%m-%d").unwrap(),
+        ];
+        let factors = [1.0, 1.0, 2.0];
+        let closes = [10.0, 11.0, 6.0];
+        let data = DataSet::from_components(
+            vec![Instrument {
+                symbol: "000001.SZ".to_string(),
+                name: "000001.SZ".to_string(),
+                board: "SZ".to_string(),
+                round_lot: 100,
+                listed_at: Some(dates[0]),
+                delisted_at: None,
+                status: "active".to_string(),
+            }],
+            dates
+                .iter()
+                .zip(closes)
+                .map(|(date, close)| market_row(&date.format("%Y-%m-%d").to_string(), close, 100))
+                .collect(),
+            dates
+                .iter()
+                .zip(factors)
+                .map(|(date, factor)| DailyFactorSnapshot {
+                    date: *date,
+                    symbol: "000001.SZ".to_string(),
+                    market_cap_bn: 10.0,
+                    free_float_cap_bn: 8.0,
+                    pe_ttm: 10.0,
+                    turnover_ratio: None,
+                    effective_turnover_ratio: None,
+                    extra_factors: BTreeMap::from([(
+                        "adjustment_factor_backward1".to_string(),
+                        factor,
+                    )]),
+                })
+                .collect(),
+            Vec::new(),
+            dates
+                .iter()
+                .map(|date| BenchmarkSnapshot {
+                    date: *date,
+                    benchmark: "000852.SH".to_string(),
+                    open: 100.0,
+                    close: 100.0,
+                    prev_close: 100.0,
+                    volume: 1_000_000,
+                })
+                .collect(),
+        )
+        .expect("dataset");
+
+        assert_eq!(
+            data.market_current_numeric_moving_average(dates[2], "000001.SZ", "close", 3),
+            Some(5.5)
+        );
+        assert_ne!(
+            data.market_current_numeric_moving_average(dates[2], "000001.SZ", "close", 3),
+            data.market_moving_average(dates[2], "000001.SZ", 3, PriceField::Close)
+        );
+    }
+
+    #[test]
+    fn adjusted_close_average_normalization_prevents_strict_crossover_drift() {
+        let pattern = [
+            2.953, 1.093, 2.717, 1.579, 1.289, 1.236, 1.617, 2.632, 1.361, 2.163,
+        ];
+        let start = NaiveDate::parse_from_str("2025-01-01", "%Y-%m-%d").unwrap();
+        let values = (0..30)
+            .map(|index| pattern[index % pattern.len()])
+            .collect::<Vec<_>>();
+        let series = AdjustedCloseSeries {
+            dates: (0..30)
+                .map(|index| start + chrono::Duration::days(index as i64))
+                .collect(),
+            backward_factors: vec![1.0; 30],
+            back_adjusted_closes: values,
+        };
+        let date = *series.dates.last().expect("last date");
+
+        assert_eq!(
+            series.current_moving_average(date, 10),
+            series.current_moving_average(date, 30)
+        );
+    }
+
     #[test]
     fn decision_volume_average_includes_paused_zero_volume_days() {
         let mut paused = market_row("2025-01-03", 11.0, 0);

crates/fidc-core/src/platform_expr_strategy.rs

@@ -20916,7 +20916,10 @@ mod tests {
                 pe_ttm: 8.0,
                 turnover_ratio: Some(1.0),
                 effective_turnover_ratio: Some(1.0),
-                extra_factors: BTreeMap::from([("Mixed_Factor".to_string(), index as f64 + 5.0)]),
+                extra_factors: BTreeMap::from([
+                    ("Mixed_Factor".to_string(), index as f64 + 5.0),
+                    ("adjustment_factor_backward1".to_string(), 1.0),
+                ]),
             })
             .collect::<Vec<_>>();
         let candidate_rows = dates
@@ -30069,7 +30072,10 @@ mod tests {
                     pe_ttm: 8.0,
                     turnover_ratio: Some(22.0),
                     effective_turnover_ratio: Some(18.0),
-                    extra_factors: BTreeMap::new(),
+                    extra_factors: BTreeMap::from([(
+                        "adjustment_factor_backward1".to_string(),
+                        1.0,
+                    )]),
                 })
                 .collect(),
             dates