修复事件跨服务序列化生成空窗口

Cargo.lock

@@ -192,6 +192,7 @@ dependencies = [
  "serde",
  "serde_json",
  "sha2",
+ "ta-lib",
  "thiserror",
 ]
 
@@ -537,6 +538,19 @@ dependencies = [
  "unicode-ident",
 ]
 
+[[package]]
+name = "ta-lib"
+version = "0.8.1"
+source = "git+https://github.com/TA-Lib/ta-lib.git?rev=dd5a90259a3f9e04e2da9f38bf0719a841b40108#dd5a90259a3f9e04e2da9f38bf0719a841b40108"
+dependencies = [
+ "ta-lib-dispatch",
+]
+
+[[package]]
+name = "ta-lib-dispatch"
+version = "0.1.2"
+source = "git+https://github.com/TA-Lib/ta-lib.git?rev=dd5a90259a3f9e04e2da9f38bf0719a841b40108#dd5a90259a3f9e04e2da9f38bf0719a841b40108"
+
 [[package]]
 name = "thin-vec"
 version = "0.2.16"

crates/fidc-core/Cargo.toml

@@ -15,3 +15,4 @@ serde.workspace = true
 serde_json.workspace = true
 sha2.workspace = true
 thiserror.workspace = true
+ta-lib = { git = "https://github.com/TA-Lib/ta-lib.git", rev = "dd5a90259a3f9e04e2da9f38bf0719a841b40108" }

crates/fidc-core/examples/factor-event-kernel.rs

@@ -0,0 +1,35 @@
+use fidc_core::factor_events::{self, Expr, Frame};
+use serde::Deserialize;
+use serde_json::{Value, json};
+use std::io::{self, Read};
+
+#[derive(Deserialize)]
+#[serde(deny_unknown_fields)]
+struct Request {
+    expressions: std::collections::BTreeMap<String, Expr>,
+    frame: Frame,
+}
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let mut input = String::new();
+    io::stdin().read_to_string(&mut input)?;
+    let output = if input.trim().is_empty() {
+        factor_events::catalog()
+    } else {
+        let request: Request = serde_json::from_str(&input)?;
+        let results = request
+            .expressions
+            .iter()
+            .map(|(id, expr)| {
+                let result = match factor_events::evaluate(expr, &request.frame) {
+                    Ok(v) => json!({"result":v}),
+                    Err(e) => json!({"error":e}),
+                };
+                (id.clone(), result)
+            })
+            .collect::<std::collections::BTreeMap<String, Value>>();
+        json!({"contract":factor_events::CONTRACT,"results":results,"read_only":true})
+    };
+    println!("{}", serde_json::to_string(&output)?);
+    Ok(())
+}

crates/fidc-core/examples/session-event-kernel.rs

@@ -0,0 +1,26 @@
+use std::io::Read;
+fn main() {
+    let mut input = String::new();
+    std::io::stdin().read_to_string(&mut input).unwrap();
+    let value: serde_json::Value = serde_json::from_str(&input).unwrap();
+    let spec: fidc_core::daily_patterns::PatternSpec =
+        serde_json::from_value(value["spec"].clone()).unwrap();
+    let bars: Vec<fidc_core::session_events::MinuteBar> =
+        serde_json::from_value(value["bars"].clone()).unwrap();
+    let result = fidc_core::session_events::evaluate(
+        &spec.validate().unwrap(),
+        value["symbol"].as_str().unwrap(),
+        &bars,
+        serde_json::from_value(value["decision_at"].clone()).unwrap(),
+    );
+    match result {
+        Ok(row) => println!(
+            "{}",
+            serde_json::json!({"contract":fidc_core::session_events::CONTRACT,"row":row,"read_only":true,"source_evidence_verified":false})
+        ),
+        Err(error) => {
+            eprintln!("{error}");
+            std::process::exit(1);
+        }
+    }
+}

crates/fidc-core/src/daily_patterns.rs

@@ -1,6 +1,6 @@
 //! Completed-session OHLCV rules shared by research and strategy execution.
 use crate::DataSet;
-use chrono::NaiveDate;
+use chrono::{FixedOffset, NaiveDate, TimeZone};
 use serde::{Deserialize, Serialize};
 use serde_json::{Value, json};
 use std::collections::{BTreeMap, BTreeSet};
@@ -9,9 +9,15 @@ pub const CONTRACT: &str = "fidc_daily_ohlcv_pattern_v1";
 
 pub fn catalog() -> Value {
     json!({"contract":CONTRACT,"templates":{
+        "expression":{"label":"指标与事件条件","parameters":{"history_window":[300,2,3000]},"stages":["selection","buy","sell","position_management"],"method":"冻结历史窗口与表达式；预热不足或未定义值不产生信号。复用共享指标事件内核，不修改既有任务。"},
+        "session_event":{"label":"已完成分钟事件","parameters":{"opening_minutes":[30,1,120],"volume_window":[5,2,120],"volume_multiple":[3.0,1,20]},"stages":["selection","buy","sell"],"method":"仅本交易日完整分钟OHLCVA，信号K线必须早于执行时点；不使用盘口快照伪造K线。"},
         "strength":{"label":"趋势强势","parameters":{"momentum_window":[25,5,120],"fast_window":[20,2,60],"slow_window":[60,20,252]},"stages":["selection","buy"],"method":"收盘价>短均线>长均线，按区间动量排序；不是当日金叉。"},
         "breakout":{"label":"前高突破","parameters":{"high_window":[60,5,252],"volume_window":[10,2,60],"volume_multiple":[1.3,1,10],"max_upper_shadow":[0.1,0,1]},"stages":["selection","buy"],"method":"收盘突破此前N日最高价，量达到此前M日均量倍数，上影比例受限；参考窗口不含当日。"},
         "volume_spike":{"label":"放量上涨","parameters":{"volume_window":[5,2,60],"volume_multiple":[3.0,1,10]},"stages":["selection","buy"],"method":"当日上涨且量达到此前N日最大量的指定倍数；不等同价格创新高。"},
+        "mean_volume_spike":{"label":"均量倍增","parameters":{"volume_window":[5,2,60],"volume_multiple":[3.0,1,10]},"stages":["selection","buy"],"method":"量达到此前N个交易日均量的M倍且当日上涨。分母不含当日；保留与最大量规则的区别。"},
+        "mean_shrink_breakout":{"label":"倍量后缩量阳线突破","parameters":{"spike_lookback":[5,2,30],"volume_window":[5,2,60],"volume_multiple":[3.0,1,10],"shrink_ratio":[0.5,0.01,1]},"stages":["selection","buy"],"method":"此前出现N日均量M倍放量，当前缩量阳线收盘突破该放量日最高价。"},
+        "breakout_retest":{"label":"突破回踩站回","parameters":{"high_window":[60,5,252],"retest_lookback":[10,2,30],"price_tolerance":[0.02,0,0.2],"shrink_ratio":[0.8,0.01,1]},"stages":["selection","buy"],"method":"观察窗先收盘突破此前N日最高价，随后低点回踩突破位容差区，今日收盘站回该位且不低于昨日、成交量收缩。突破与回踩不得同日。"},
+        "limit_consolidation":{"label":"涨停后整理（日线）","parameters":{"anchor_lag":[4,2,30],"price_band":[0.05,0,0.3],"volume_band":[0.15,0,2],"ma_window":[5,2,60]},"stages":["selection","buy"],"method":"明确T-i日按真实涨停价收盘，后续收盘和量相对锚日偏离受限，今日收盘低于完整日线均线；不是盘中动态MA条件。"},
         "shrink_breakout":{"label":"缩量突破","parameters":{"spike_lookback":[5,2,30],"volume_window":[5,2,60],"volume_multiple":[3.0,1,10],"shrink_ratio":[0.5,0.01,1]},"stages":["selection","buy"],"method":"此前观察窗有放量日，今日收盘超过该日最高价，成交量不超过其指定比例。"},
         "ma_below":{"label":"均线下方","parameters":{"ma_window":[20,2,252]},"stages":["sell"],"method":"完整收盘价低于含当日的N日均线；独立卖出条件。"},
         "volume_down":{"label":"放量下跌","parameters":{"volume_window":[5,2,60],"volume_multiple":[3.0,1,10]},"stages":["sell"],"method":"当日下跌且量达到此前N日最大量的指定倍数。"}
@@ -24,9 +30,59 @@ pub struct PatternSpec {
     pub template: String,
     #[serde(default)]
     pub parameters: BTreeMap<String, Value>,
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub expression: Option<crate::factor_events::Expr>,
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub execution_context: Option<crate::pattern_context::ExecutionContext>,
+    #[serde(default,skip_serializing_if="Option::is_none")]
+    pub session_event:Option<String>,
 }
 impl PatternSpec {
-    pub fn validate(mut self) -> Result<Self, String> {
+    pub fn validate(self) -> Result<Self, String> {
+        if self.template=="session_event" {
+            if !self.session_event.as_deref().is_some_and(|id|crate::session_events::EVENTS.contains(&id)) || self.execution_context.is_some() {return Err("session_event_contract_invalid".into());}
+        } else if self.session_event.is_some() {return Err("unexpected_session_event_id".into());}
+        let allowed = if let Some(context) = &self.execution_context {
+            context.validate(self.expression.as_ref().ok_or("pattern_context_requires_expression")?)?;
+            crate::pattern_context::CONTEXT_FIELDS
+        } else { &[] };
+        let spec = self.validate_with_context(allowed)?;
+        if let Some(context) = &spec.execution_context {
+            if context.rank_universe.len().saturating_mul(spec.history_len()) > 2_000_000 {
+                return Err("pattern_rank_window_budget_exceeded: 完整截面不得截断".into());
+            }
+        }
+        Ok(spec)
+    }
+    fn validate_with_context(mut self, context_fields: &[&str]) -> Result<Self, String> {
+        if (self.template == "expression") != self.expression.is_some() {
+            return Err("expression_template_requires_expression_only".into());
+        }
+        if let Some(expr) = &self.expression {
+            let supported = [
+                "open",
+                "high",
+                "low",
+                "close",
+                "volume",
+                "raw_open",
+                "raw_high",
+                "raw_low",
+                "raw_close",
+                "prev_close",
+                "amount",
+            ];
+            let missing = crate::factor_events::field_dependencies(expr)
+                .into_iter()
+                .filter(|f| !supported.contains(&f.as_str()) && !context_fields.contains(&f.as_str()))
+                .collect::<Vec<_>>();
+            if !missing.is_empty() {
+                return Err(format!(
+                    "expression_source_mapping_required: {}",
+                    missing.join(",")
+                ));
+            }
+        }
         let catalog = catalog();
         let definition = catalog["templates"]
             .get(&self.template)
@@ -44,7 +100,7 @@ impl PatternSpec {
             if number < bounds[1].as_f64().unwrap() || number > bounds[2].as_f64().unwrap() {
                 return Err(format!("{key}超出允许范围"));
             }
-            if key.ends_with("window") || key == "spike_lookback" {
+            if key.ends_with("window") || key.ends_with("lookback") || key == "anchor_lag" || key=="opening_minutes" {
                 if number.fract() != 0.0 {
                     return Err(format!("{key}必须是整数"));
                 }
@@ -66,11 +122,15 @@ impl PatternSpec {
     }
     pub fn history_len(&self) -> usize {
         match self.template.as_str() {
+            "session_event"=>1,
+            "expression" => self.n("history_window"),
             "strength" => self.n("slow_window").max(self.n("momentum_window") + 1),
             "breakout" => self.n("high_window").max(self.n("volume_window")) + 1,
-            "volume_spike" | "volume_down" => self.n("volume_window") + 1,
+            "volume_spike" | "volume_down" | "mean_volume_spike" => self.n("volume_window") + 1,
+            "breakout_retest" => self.n("high_window") + self.n("retest_lookback") + 1,
+            "limit_consolidation" => (self.n("anchor_lag")+1).max(self.n("ma_window")),
             "ma_below" => self.n("ma_window").max(2),
-            "shrink_breakout" => self.n("spike_lookback") + self.n("volume_window") + 1,
+            "shrink_breakout" | "mean_shrink_breakout" => self.n("spike_lookback") + self.n("volume_window") + 1,
             _ => unreachable!(),
         }
     }
@@ -85,6 +145,14 @@ pub struct PatternBar {
     pub low: Option<f64>,
     pub close: Option<f64>,
     pub volume: Option<f64>,
+    #[serde(default)]
+    pub prev_close: Option<f64>,
+    #[serde(default)]
+    pub amount: Option<f64>,
+    #[serde(default)]
+    pub upper_limit: Option<f64>,
+    #[serde(default)]
+    pub no_limit: Option<bool>,
     pub adjustment_factor_backward1: Option<f64>,
     pub paused: Option<bool>,
     #[serde(default)]
@@ -146,6 +214,17 @@ pub fn evaluate(
     days: &[NaiveDate],
     series: &PatternSeries,
 ) -> Result<PatternResult, String> {
+    evaluate_with_context(spec, days, series, &BTreeMap::new(), false)
+}
+
+pub(crate) fn evaluate_with_context(
+    spec: &PatternSpec,
+    days: &[NaiveDate],
+    series: &PatternSeries,
+    context: &BTreeMap<String, Vec<Option<f64>>>,
+    numeric_output: bool,
+) -> Result<PatternResult, String> {
+    if spec.template=="session_event" {return Err("session_event_requires_completed_minute_endpoint".into());}
     if days.len() != spec.history_len() || days.windows(2).any(|w| w[0] >= w[1]) {
         return Err("pattern_calendar_incomplete: 需要完整、唯一且递增的真实交易日窗口".into());
     }
@@ -246,6 +325,124 @@ pub fn evaluate(
     result.anchor = json!({"date":days[len-1],"raw_close":by_day[&days[len-1]].close,"factor":by_day[&days[len-1]].adjustment_factor_backward1});
     let mut score = None;
     match spec.template.as_str() {
+        "expression" => {
+            let zone = FixedOffset::east_opt(8 * 3600).unwrap();
+            let timestamps = days
+                .iter()
+                .map(|d| {
+                    zone.from_local_datetime(&d.and_hms_opt(16, 0, 0).unwrap())
+                        .single()
+                        .unwrap()
+                })
+                .collect::<Vec<_>>();
+            let anchor = by_day[&days[len - 1]].adjustment_factor_backward1.unwrap();
+            let mut fields = BTreeMap::from([
+                (
+                    "open".into(),
+                    prices.iter().map(|b| Some(b.0 / anchor)).collect(),
+                ),
+                (
+                    "high".into(),
+                    prices.iter().map(|b| Some(b.1 / anchor)).collect(),
+                ),
+                (
+                    "low".into(),
+                    prices.iter().map(|b| Some(b.2 / anchor)).collect(),
+                ),
+                (
+                    "close".into(),
+                    prices.iter().map(|b| Some(b.3 / anchor)).collect(),
+                ),
+                ("volume".into(), prices.iter().map(|b| Some(b.4)).collect()),
+            ]);
+            for (name, index) in [
+                ("raw_open", 0),
+                ("raw_high", 1),
+                ("raw_low", 2),
+                ("raw_close", 3),
+            ] {
+                fields.insert(
+                    name.into(),
+                    days.iter()
+                        .map(|d| {
+                            let b = by_day[d];
+                            [b.open, b.high, b.low, b.close][index]
+                        })
+                        .collect(),
+                );
+            }
+            let needed =
+                crate::factor_events::field_dependencies(spec.expression.as_ref().unwrap());
+            for name in ["prev_close", "amount"] {
+                if !needed.contains(name) {
+                    continue;
+                }
+                let values = days
+                    .iter()
+                    .map(|d| {
+                        let b = by_day[d];
+                        let value = number(
+                            if name == "prev_close" {
+                                b.prev_close
+                            } else {
+                                b.amount
+                            },
+                            &series.symbol,
+                            *d,
+                            name,
+                        )?;
+                        if value < 0.0 || (name == "prev_close" && value == 0.0) {
+                            return Err(format!(
+                                "pattern_input_invalid: {} {d} {name}",
+                                series.symbol
+                            ));
+                        }
+                        Ok(Some(value))
+                    })
+                    .collect::<Result<Vec<_>, String>>()?;
+                fields.insert(name.into(), values);
+            }
+            for (name, values) in context {
+                if fields.contains_key(name) || values.len() != days.len()
+                    || values.iter().flatten().any(|v| !v.is_finite()) {
+                    return Err(format!("research_context_invalid: {} {name}", series.symbol));
+                }
+                fields.insert(name.clone(), values.clone());
+            }
+            let frame = crate::factor_events::Frame {
+                symbol: series.symbol.clone(),
+                frequency: "1d".into(),
+                decision_at: *timestamps.last().unwrap(),
+                available_at: timestamps.clone(),
+                timestamps,
+                fields,
+            };
+            let values = crate::factor_events::evaluate(spec.expression.as_ref().unwrap(), &frame)?;
+            let latest = values.values.last().copied().flatten();
+            result.values["expression"] = json!(values);
+            result.values["expression_contract"] = json!(crate::factor_events::CONTRACT);
+            result.values["price_policy"] = json!("backward1_anchored_to_decision_close");
+            result.score = latest;
+            if numeric_output {
+                if values.value_type != crate::factor_events::ValueType::Number {
+                    return Err("research_rank_input_requires_numeric_expression".into());
+                }
+                return Ok(result);
+            }
+            if latest.is_none() {
+                result.exclusion = Some(
+                    json!({"reason":"expression_undefined_or_warmup","signal_date":days.last()}),
+                );
+            } else if values.value_type == crate::factor_events::ValueType::Boolean {
+                result.matched = latest == Some(1.0);
+                result
+                    .checks
+                    .push(json!({"label":"组合条件","actual":latest,"operator":"==","threshold":1,"passed":result.matched}));
+            } else {
+                return Err("expression_signal_requires_boolean: 数值因子必须显式比较或组合，不能自动视为买卖信号".into());
+            }
+            return Ok(result);
+        }
         "strength" => {
             let fast = mean(prices[len - spec.n("fast_window")..].iter().map(|b| b.3))?;
             let slow = mean(prices[len - spec.n("slow_window")..].iter().map(|b| b.3))?;
@@ -293,11 +490,12 @@ pub fn evaluate(
                 spec.v("max_upper_shadow"),
             );
         }
-        "volume_spike" | "volume_down" => {
+        "volume_spike" | "volume_down" | "mean_volume_spike" => {
-            let high = prices[len - 1 - spec.n("volume_window")..len - 1]
+            let reference = &prices[len - 1 - spec.n("volume_window")..len - 1];
+            let high = if spec.template=="mean_volume_spike" {mean(reference.iter().map(|b|b.4))?} else {reference
                 .iter()
                 .map(|b| b.4)
-                .fold(0.0, f64::max);
+                .fold(0.0, f64::max)};
             if high <= 0.0 {
                 return Err(format!(
                     "pattern_input_invalid: symbol={}, reason=zero_reference_volume",
@@ -308,20 +506,20 @@ pub fn evaluate(
             result.values["volume_ratio"] = json!(v / high);
             check(
                 &mut result.checks,
-                "最大量倍数",
+                if spec.template=="mean_volume_spike" {"均量倍数"} else {"最大量倍数"},
                 v / high,
                 ">=",
                 spec.v("volume_multiple"),
             );
             check(
                 &mut result.checks,
-                if spec.template == "volume_spike" {
+                if spec.template != "volume_down" {
                     "当日上涨"
                 } else {
                     "当日下跌"
                 },
                 change,
-                if spec.template == "volume_spike" {
+                if spec.template != "volume_down" {
                     ">"
                 } else {
                     "<"
@@ -335,14 +533,15 @@ pub fn evaluate(
             result.values["ma"] = json!(avg);
             check(&mut result.checks, "收盘低于均线", c, "<", avg);
         }
-        "shrink_breakout" => {
+        "shrink_breakout" | "mean_shrink_breakout" => {
             let mut spikes = Vec::new();
             let mut eligible = Vec::new();
             for i in len - 1 - spec.n("spike_lookback")..len - 1 {
-                let prior = prices[i - spec.n("volume_window")..i]
+                let reference=&prices[i - spec.n("volume_window")..i];
+                let prior = if spec.template=="mean_shrink_breakout"{mean(reference.iter().map(|b|b.4))?}else{reference
                     .iter()
                     .map(|b| b.4)
-                    .fold(0.0, f64::max);
+                    .fold(0.0, f64::max)};
                 if prior <= 0.0 {
                     return Err(format!(
                         "pattern_input_invalid: symbol={}, date={}, reason=zero_reference_volume",
@@ -382,6 +581,44 @@ pub fn evaluate(
                     spec.v("shrink_ratio"),
                 );
             }
+            if spec.template=="mean_shrink_breakout" {check(&mut result.checks,"当前为阳线",c,">",o);}
+        }
+        "breakout_retest" => {
+            let mut anchors=Vec::new();let mut eligible=Vec::new();
+            for i in len-1-spec.n("retest_lookback")..len-1 {
+                let level=prices[i-spec.n("high_window")..i].iter().map(|b|b.1).fold(f64::NEG_INFINITY,f64::max);
+                if prices[i].3<=level {continue;}
+                let retraced=prices[i+1..].iter().any(|b| b.2 <= level*(1.0+spec.v("price_tolerance")));
+                anchors.push((i,level,retraced));
+                if retraced&&c>=level&&c>=prices[len-2].3&&prices[i].4>0.0&&v<=prices[i].4*spec.v("shrink_ratio") {eligible.push((i,level,retraced));}
+            }
+            check(&mut result.checks,"观察窗存在先前突破",anchors.len() as f64,">",0.0);
+            if let Some(&(i,level,retraced))=eligible.last().or_else(||anchors.last()) {
+                result.values["breakout_date"]=json!(days[i]);result.values["breakout_level"]=json!(level);result.values["days_since_breakout"]=json!(len-1-i);
+                check(&mut result.checks,"突破后曾回踩",if retraced{1.0}else{0.0},">",0.0);
+                check(&mut result.checks,"收盘重新站回突破位",c,">=",level);
+                check(&mut result.checks,"收盘不低于昨日",c,">=",prices[len-2].3);
+                if prices[i].4<=0.0{return Err("突破锚日成交量为零，不能计算缩量比例".into());}
+                check(&mut result.checks,"相对突破日缩量",v/prices[i].4,"<=",spec.v("shrink_ratio"));
+                score=Some(c/level-1.0);
+            }
+        }
+        "limit_consolidation" => {
+            let i=len-1-spec.n("anchor_lag");let anchor=by_day[&days[i]];
+            let is_limit=if anchor.no_limit==Some(true){false}else{
+                let upper=number(anchor.upper_limit,&series.symbol,days[i],"upper_limit")?;
+                if upper<=0.0||upper>=99999.0{return Err("涨停事件缺少有效源涨停价或无涨跌幅限制证据，禁止按比例推算".into());}
+                (anchor.close.unwrap()/upper-1.0).abs()<=1e-8
+            };
+            if prices[i].4<=0.0{return Err("涨停锚日成交量为零".into());}
+            let price_gap=prices[i+1..].iter().map(|b|(b.3/prices[i].3-1.0).abs()).fold(0.0,f64::max);
+            let volume_gap=prices[i+1..].iter().map(|b|(b.4/prices[i].4-1.0).abs()).fold(0.0,f64::max);
+            let avg=mean(prices[len-spec.n("ma_window")..].iter().map(|b|b.3))?;
+            result.values["limit_date"]=json!(days[i]);result.values["price_deviation"]=json!(price_gap);result.values["volume_deviation"]=json!(volume_gap);
+            check(&mut result.checks,"锚日真实涨停收盘",if is_limit{1.0}else{0.0},">",0.0);
+            check(&mut result.checks,"后续收盘最大偏离",price_gap,"<=",spec.v("price_band"));
+            check(&mut result.checks,"后续成交量最大偏离",volume_gap,"<=",spec.v("volume_band"));
+            check(&mut result.checks,"收盘低于日线均线",c,"<",avg);score=Some(avg/c-1.0);
         }
         _ => unreachable!(),
     }
@@ -399,35 +636,38 @@ pub fn evaluate_dataset(
     date: NaiveDate,
     symbol: &str,
 ) -> Result<PatternResult, String> {
+    let context = crate::pattern_context::build_dataset_context(spec, data, date)?;
+    evaluate_dataset_context(spec, data, date, symbol, &context)
+}
+
+pub fn dataset_series(data: &DataSet, days: &[NaiveDate], symbol: &str) -> PatternSeries {
+    let bars = days.iter().filter_map(|&d| data.market(d, symbol).map(|b| PatternBar {
+        date:d, open:Some(b.open), high:Some(b.high), low:Some(b.low), close:Some(b.close),
+        volume:Some(b.volume as f64), prev_close:Some(b.prev_close),
+        amount:data.factor_numeric_value(d,symbol,"amount"),upper_limit:Some(b.upper_limit),
+        no_limit:data.factor_numeric_value(d,symbol,"no_limit").map(|v|v==1.0),
+        adjustment_factor_backward1:data.factor(d,symbol).and_then(|f|f.adjustment_factor_backward1),
+        paused:Some(b.paused), source_path:None,
+    })).collect();
+    PatternSeries{symbol:symbol.into(),name:data.instrument(symbol).map(|i|i.name.clone()),
+        listed_at:data.instrument(symbol).and_then(|i|i.listed_at),bars}
+}
+
+pub fn evaluate_dataset_context(
+    spec: &PatternSpec, data: &DataSet, date: NaiveDate, symbol: &str, context: &ResearchContext,
+) -> Result<PatternResult,String> {
     let days = data.calendar().trailing_days(date, spec.history_len());
-    let bars = days
+    let mut fields = context.common.clone();
-        .iter()
+    fields.extend(context.by_symbol.get(symbol).cloned().unwrap_or_default());
-        .filter_map(|&d| {
+    let outside = spec.execution_context.as_ref().is_some_and(|c| c.rank_expression.is_some() && !c.rank_universe.iter().any(|s|s==symbol));
-            data.market(d, symbol).map(|b| PatternBar {
+    if outside {
-                date: d,
+        for name in ["scope_rank","scope_percentile"] {fields.insert(name.into(),vec![None;days.len()]);}
-                open: Some(b.open),
+        fields.insert("scope_size".into(),vec![Some(spec.execution_context.as_ref().unwrap().rank_universe.len() as f64);days.len()]);
-                high: Some(b.high),
+    }
-                low: Some(b.low),
+    let mut result = evaluate_with_context(spec,&days,&dataset_series(data,&days,symbol),&fields,false)?;
-                close: Some(b.close),
+    if outside && result.score.is_none() { result.exclusion=Some(json!({"reason":"outside_frozen_rank_universe","symbol":symbol,"signal_date":date})); }
-                volume: Some(b.volume as f64),
+    result.values["execution_context_latest"]=json!(fields.iter().map(|(k,v)|(k,v.last().copied().flatten())).collect::<BTreeMap<_,_>>());
-                adjustment_factor_backward1: data
+    Ok(result)
-                    .factor(d, symbol)
-                    .and_then(|f| f.adjustment_factor_backward1),
-                paused: Some(b.paused),
-                source_path: None,
-            })
-        })
-        .collect();
-    evaluate(
-        spec,
-        &days,
-        &PatternSeries {
-            symbol: symbol.into(),
-            name: None,
-            listed_at: data.instrument(symbol).and_then(|i| i.listed_at),
-            bars,
-        },
-    )
 }
 
 pub fn evaluate_batch(
@@ -456,6 +696,60 @@ pub fn evaluate_batch(
     )
 }
 
+/// Values are supplied only by the verified research transport or dataset context builder.
+#[derive(Debug, Clone, Default, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct ResearchContext {
+    #[serde(default)]
+    pub common: BTreeMap<String, Vec<Option<f64>>>,
+    #[serde(default)]
+    pub by_symbol: BTreeMap<String, BTreeMap<String, Vec<Option<f64>>>>,
+}
+
+pub fn evaluate_research_batch(
+    spec: PatternSpec, days: &[NaiveDate], series: &[PatternSeries],
+    context: &ResearchContext, numeric_output: bool,
+) -> Result<Value, String> {
+    let common_fields = ["index_open", "index_high", "index_low", "index_close"];
+    let symbol_fields = ["scope_rank", "scope_percentile", "scope_size"];
+    if spec.template != "expression" || series.is_empty() || series.len() > 200
+        || series.iter().map(|s| &s.symbol).collect::<BTreeSet<_>>().len() != series.len()
+        || context.common.keys().any(|k| !common_fields.contains(&k.as_str()))
+        || context.by_symbol.iter().any(|(s, fields)| !series.iter().any(|row| &row.symbol == s)
+            || fields.keys().any(|k| !symbol_fields.contains(&k.as_str()))) {
+        return Err("research_context_scope_or_fields_invalid".into());
+    }
+    for (name, values) in &context.common {
+        if values.len() != days.len() || values.iter().any(|v| !v.is_some_and(|x| x.is_finite() && x > 0.0)) {
+            return Err(format!("research_index_window_incomplete: {name}"));
+        }
+    }
+    let allowed = common_fields.into_iter().chain(symbol_fields).collect::<Vec<_>>();
+    let spec = spec.validate_with_context(&allowed)?;
+    let dependencies = crate::factor_events::field_dependencies(spec.expression.as_ref().unwrap());
+    let mut rows = Vec::with_capacity(series.len());
+    for item in series {
+        let mut fields = context.common.clone();
+        fields.extend(context.by_symbol.get(&item.symbol).cloned().unwrap_or_default());
+        if allowed.iter().any(|f| dependencies.contains(*f) && !fields.contains_key(*f)) {
+            return Err(format!("research_context_missing: {}", item.symbol));
+        }
+        for (name, values) in &fields {
+            if values.len() != days.len() || values.iter().flatten().any(|v| !v.is_finite()
+                || (name == "scope_percentile" && !(0.0..=1.0).contains(v))
+                || (matches!(name.as_str(), "scope_rank" | "scope_size") && *v < 1.0)) {
+                return Err(format!("research_context_invalid: {} {name}", item.symbol));
+            }
+        }
+        let mut result = evaluate_with_context(&spec, days, item, &fields, numeric_output)?;
+        result.values["research_context_latest"] = json!(fields.iter().map(|(k,v)|(k,v.last().copied().flatten())).collect::<BTreeMap<_,_>>());
+        rows.push(result);
+    }
+    Ok(json!({"contract":CONTRACT,"context_contract":"fidc_research_event_context_v1","spec":spec,
+        "required_history":spec.history_len(),"rows":rows,"read_only":true,
+        "source_evidence_verified":false,"live_routing":false,"rule_backtest_supported":false}))
+}
+
 pub fn expression_specs(expression: &str) -> Result<Vec<PatternSpec>, String> {
     let mut specs = Vec::new();
     for helper in ["pattern_signal", "pattern_score"] {
@@ -491,10 +785,110 @@ pub fn expression_specs(expression: &str) -> Result<Vec<PatternSpec>, String> {
 #[cfg(test)]
 mod tests {
     use super::*;
+    #[test]
+    fn research_index_and_ranking_context_never_unlock_strategy_mapping() {
+        let days=["2026-09-04","2026-09-07","2026-09-08"].map(|s|s.parse::<NaiveDate>().unwrap());
+        let spec:PatternSpec=serde_json::from_value(json!({"template":"expression","parameters":{"history_window":3},
+            "expression":{"kind":"operator","name":"CROSS_ABOVE","args":[{"kind":"field","name":"close"},{"kind":"field","name":"index_close"}]}})).unwrap();
+        assert!(spec.clone().validate().unwrap_err().contains("mapping_required"));
+        let series:PatternSeries=serde_json::from_value(json!({"symbol":"TEST","bars":days.iter().zip([9.0,10.0,11.0]).map(|(d,c)|json!({"date":d,"open":c,"high":c,"low":c,"close":c,"volume":100.0,"adjustment_factor_backward1":1.0,"paused":false})).collect::<Vec<_>>()})).unwrap();
+        let mut context=ResearchContext{common:BTreeMap::from([("index_close".into(),vec![Some(10.0);3])]),..Default::default()};
+        let result=evaluate_research_batch(spec.clone(),&days,&[series.clone()],&context,false).unwrap();
+        assert_eq!(result["rows"][0]["matched"],true);
+        assert_eq!(result["source_evidence_verified"],false);
+        assert_eq!(result["rule_backtest_supported"],false);
+        context.common.get_mut("index_close").unwrap()[1]=None;
+        assert!(evaluate_research_batch(spec.clone(),&days,&[series.clone()],&context,false).unwrap_err().contains("index_window_incomplete"));
+        context.common=BTreeMap::from([("close".into(),vec![Some(10.0);3])]);
+        assert!(evaluate_research_batch(spec,&days,&[series],&context,false).is_err());
+    }
+
+    #[test]
+    fn research_numeric_output_keeps_warmup_unknown_without_a_false_signal() {
+        let days=["2026-09-04","2026-09-07","2026-09-08"].map(|s|s.parse::<NaiveDate>().unwrap());
+        let spec:PatternSpec=serde_json::from_value(json!({"template":"expression","parameters":{"history_window":3},
+            "expression":{"kind":"operator","name":"PCT_CHANGE","window":2,"args":[{"kind":"field","name":"close"}]}})).unwrap();
+        let series:PatternSeries=serde_json::from_value(json!({"symbol":"TEST","bars":days.iter().zip([10.0,10.5,11.0]).map(|(d,c)|json!({"date":d,"open":c,"high":c,"low":c,"close":c,"volume":100.0,"adjustment_factor_backward1":1.0,"paused":false})).collect::<Vec<_>>()})).unwrap();
+        assert!(evaluate_batch(spec.clone(),&days,&[series.clone()]).is_err());
+        let result=evaluate_research_batch(spec,&days,&[series],&ResearchContext::default(),true).unwrap();
+        let values=&result["rows"][0]["values"]["expression"]["values"];
+        assert!(values[0].is_null() && values[1].is_null());
+        assert!((values[2].as_f64().unwrap()-0.1).abs()<1e-12);
+        assert_eq!(result["rows"][0]["matched"],false);
+    }
+    #[test]
+    fn expression_condition_preserves_native_types_and_rejects_numeric_as_signal() {
+        let make = |expression: Value| {
+            serde_json::from_value::<PatternSpec>(json!({"template":"expression","parameters":{"history_window":3},"expression":expression})).unwrap().validate().unwrap()
+        };
+        let spec = make(
+            json!({"kind":"operator","name":"GT","args":[{"kind":"field","name":"close"},{"kind":"indicator","name":"SMA","inputs":[{"kind":"field","name":"close"}],"parameters":{"optInTimePeriod":2}}]}),
+        );
+        let days = ["2026-09-04", "2026-09-07", "2026-09-08"]
+            .map(|d| NaiveDate::parse_from_str(d, "%Y-%m-%d").unwrap());
+        let series = PatternSeries {
+            symbol: "TEST".into(),
+            name: None,
+            listed_at: None,
+            bars: days
+                .iter()
+                .enumerate()
+                .map(|(i, &date)| {
+                    let p = 10.0 + i as f64;
+                    PatternBar {
+                        date,
+                        open: Some(p),
+                        high: Some(p),
+                        low: Some(p),
+                        close: Some(p),
+                        volume: Some(100.0),
+                        prev_close: Some(p - 1.0),
+                        amount: Some(p * 100.0),
+                        upper_limit: None,
+                        no_limit: None,
+                        adjustment_factor_backward1: Some(1.0),
+                        paused: Some(false),
+                        source_path: None,
+                    }
+                })
+                .collect(),
+        };
+        let result = evaluate(&spec, &days, &series).unwrap();
+        assert!(result.matched);
+        assert_eq!(result.score, Some(1.0));
+        let vwap_spec = make(
+            json!({"kind":"operator","name":"GT","args":[{"kind":"operator","name":"DIV","args":[{"kind":"field","name":"amount"},{"kind":"field","name":"volume"}]},{"kind":"field","name":"prev_close"}]}),
+        );
+        assert!(evaluate(&vwap_spec, &days, &series).unwrap().matched);
+        let mut missing_amount = series.clone();
+        missing_amount.bars[1].amount = None;
+        assert!(
+            evaluate(&vwap_spec, &days, &missing_amount)
+                .unwrap_err()
+                .contains("amount")
+        );
+        let mut missing_previous=series.clone();missing_previous.bars[1].prev_close=None;
+        assert!(evaluate(&vwap_spec,&days,&missing_previous).unwrap_err().contains("prev_close"));
+        assert!(
+            evaluate(
+                &make(json!({"kind":"field","name":"close"})),
+                &days,
+                &series
+            )
+            .unwrap_err()
+            .contains("requires_boolean")
+        );
+        let mut missing = series.clone();
+        missing.bars[1].close = None;
+        assert!(evaluate(&spec, &days, &missing).is_err());
+    }
     fn fixture(template: &str) -> (PatternSpec, Vec<NaiveDate>, PatternSeries) {
         let spec = PatternSpec {
             template: template.into(),
             parameters: BTreeMap::new(),
+            expression: None,
+            execution_context: None,
+            session_event: None,
         }
         .validate()
         .unwrap();
@@ -515,6 +909,10 @@ mod tests {
                     low: Some(c),
                     close: Some(c),
                     volume: Some(1000.0),
+                    prev_close: Some(c - 1.0),
+                    amount: Some(c * 1000.0),
+                    upper_limit: None,
+                    no_limit: None,
                     adjustment_factor_backward1: Some(1.0),
                     paused: Some(false),
                     source_path: Some("fixture.parquet".into()),
@@ -565,6 +963,51 @@ mod tests {
         assert_eq!(a.checks, b.checks);
     }
 
+    #[test]
+    fn mean_volume_is_not_prior_max_and_excludes_current_bar() {
+        let (spec,days,mut series)=fixture("mean_volume_spike");
+        for (bar,volume) in series.bars.iter_mut().zip([10.,10.,10.,10.,100.,100.]) {bar.volume=Some(volume);}
+        assert!(evaluate(&spec,&days,&series).unwrap().matched);
+        let mut old=spec.clone();old.template="volume_spike".into();
+        assert!(!evaluate(&old,&days,&series).unwrap().matched);
+        assert_eq!(evaluate(&spec,&days,&series).unwrap().values["volume_ratio"],json!(100./28.));
+    }
+
+    #[test]
+    fn mean_volume_followup_requires_bullish_breakout_and_shrink() {
+        let (spec,days,mut series)=fixture("mean_shrink_breakout");
+        series.bars[6].volume=Some(4000.);
+        let last=series.bars.last_mut().unwrap();last.open=Some(19.);last.low=Some(19.);
+        assert!(evaluate(&spec,&days,&series).unwrap().matched);
+        series.bars.last_mut().unwrap().volume=Some(3000.);
+        assert!(!evaluate(&spec,&days,&series).unwrap().matched);
+    }
+
+    #[test]
+    fn breakout_retest_needs_a_later_retest_not_the_breakout_candle_itself() {
+        let (spec,days,mut series)=fixture("breakout_retest");
+        for b in &mut series.bars {b.open=Some(10.);b.high=Some(10.);b.low=Some(10.);b.close=Some(10.);}
+        let anchor=series.bars.len()-11;
+        let b=&mut series.bars[anchor];b.open=Some(11.);b.high=Some(12.1);b.low=Some(9.9);b.close=Some(12.);b.volume=Some(2000.);
+        for b in &mut series.bars[anchor+1..] {b.open=Some(10.3);b.high=Some(10.4);b.low=Some(10.3);b.close=Some(10.4);}
+        assert!(!evaluate(&spec,&days,&series).unwrap().matched);
+        series.bars[anchor+1].low=Some(9.95);
+        assert!(evaluate(&spec,&days,&series).unwrap().matched);
+    }
+
+    #[test]
+    fn limit_consolidation_requires_real_limit_and_never_infers_ten_percent() {
+        let (spec,days,mut series)=fixture("limit_consolidation");
+        for (b,c) in series.bars.iter_mut().zip([10.,10.1,10.2,10.1,9.9]) {b.open=Some(c);b.high=Some(c);b.low=Some(c);b.close=Some(c);}
+        assert!(evaluate(&spec,&days,&series).unwrap_err().contains("upper_limit"));
+        series.bars[0].upper_limit=Some(10.);
+        assert!(evaluate(&spec,&days,&series).unwrap().matched);
+        series.bars[0].no_limit=Some(true);
+        assert!(!evaluate(&spec,&days,&series).unwrap().matched);
+        series.bars[0].no_limit=Some(false);series.bars[0].upper_limit=Some(0.);
+        assert!(evaluate(&spec,&days,&series).is_err());
+    }
+
     #[test]
     fn daily_patterns_flat_decimal_prices_do_not_create_a_sell_signal() {
         let (mut spec, _, mut series) = fixture("strength");

crates/fidc-core/src/data.rs

@@ -491,6 +491,7 @@ pub struct DataSetSnapshotComponents {
     pub benchmarks: Vec<BenchmarkSnapshot>,
     pub corporate_actions: Vec<CorporateAction>,
     pub execution_quotes: Vec<IntradayExecutionQuote>,
+    pub completed_minute_bars: Vec<crate::session_events::MinuteBar>,
 }
 
 #[derive(Debug, Clone, Serialize)]
@@ -1418,6 +1419,7 @@ pub struct DataSet {
     eligible_universe_by_date: Arc<OnceLock<BTreeMap<NaiveDate, Vec<EligibleUniverseSnapshot>>>>,
     benchmark_code: String,
     futures_params_by_symbol: Arc<HashMap<String, Vec<FuturesTradingParameter>>>,
+    completed_minute_bars: Arc<BTreeMap<(NaiveDate,String),Vec<crate::session_events::MinuteBar>>>,
 }
 
 struct DailySymbolRows<'a, T> {
@@ -1954,6 +1956,7 @@ impl DataSet {
             eligible_universe_by_date: Arc::new(OnceLock::new()),
             benchmark_code,
             futures_params_by_symbol: Arc::new(futures_params_by_symbol),
+            completed_minute_bars: Arc::new(BTreeMap::new()),
         })
     }
 
@@ -2627,9 +2630,21 @@ impl DataSet {
             benchmarks,
             corporate_actions,
             execution_quotes,
+            completed_minute_bars:self.completed_minute_bars.values().flatten().cloned().collect(),
         }
     }
 
+    pub fn with_completed_minute_bars(mut self,bars:Vec<crate::session_events::MinuteBar>)->Result<Self,String> {
+        self.completed_minute_bars=crate::session_events::bar_store(bars)?;Ok(self)
+    }
+
+    pub fn with_shared_completed_minute_bars(mut self,bars:crate::session_events::BarStore)->Self {self.completed_minute_bars=bars;self}
+    pub fn completed_minute_bar_count(&self)->usize {self.completed_minute_bars.values().map(Vec::len).sum()}
+
+    pub fn completed_minute_bars_on(&self,date:NaiveDate,symbol:&str)->&[crate::session_events::MinuteBar] {
+        self.completed_minute_bars.get(&(date,symbol.into())).map(Vec::as_slice).unwrap_or(&[])
+    }
+
     pub fn benchmark_series(&self) -> Vec<BenchmarkSnapshot> {
         self.benchmark_by_date.values().cloned().collect()
     }

crates/fidc-core/src/factor_cross_section.rs

@@ -0,0 +1,234 @@
+//! Cross-sectional operators require an explicit complete universe, never a UI page.
+use serde::{Deserialize, Serialize};
+use std::collections::{BTreeMap, BTreeSet};
+
+pub const OPERATORS: &[&str] = &[
+    "RANK",
+    "PERCENTILE",
+    "TOP",
+    "BOTTOM",
+    "TOP_PERCENT",
+    "BOTTOM_PERCENT",
+    "WINSORIZE",
+    "INDUSTRY_NEUTRALIZE",
+    "SIZE_NEUTRALIZE",
+];
+
+#[derive(Clone, Debug, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct Observation {
+    pub symbol: String,
+    pub value: f64,
+    pub industry: Option<String>,
+    pub market_cap: Option<f64>,
+}
+#[derive(Debug, Serialize)]
+pub struct Output {
+    pub symbol: String,
+    pub value: f64,
+}
+
+/// Every date ranks the same frozen research universe; unknown inputs invalidate the whole date.
+pub fn rank_history(
+    dates: &[chrono::NaiveDate], universe: &[String], values: &BTreeMap<String, Vec<Option<f64>>>,
+) -> Result<serde_json::Value, String> {
+    use serde_json::json;
+    if dates.is_empty() || dates.windows(2).any(|w| w[0] >= w[1]) || universe.len() < 2
+        || universe.len() > 20_000 || dates.len().saturating_mul(universe.len()) > 2_000_000
+        || universe.iter().collect::<BTreeSet<_>>().len() != universe.len()
+        || values.keys().collect::<BTreeSet<_>>() != universe.iter().collect::<BTreeSet<_>>()
+        || values.values().any(|v| v.len() != dates.len() || v.iter().flatten().any(|v| !v.is_finite())) {
+        return Err("research_rank_history_incomplete_or_invalid_universe".into());
+    }
+    let mut rank = universe.iter().map(|s|(s.clone(),vec![None;dates.len()])).collect::<BTreeMap<_,_>>();
+    let mut percentile = rank.clone();
+    let mut unknown_dates = Vec::new();
+    for (i, date) in dates.iter().enumerate() {
+        let missing = universe.iter().filter(|s|values[*s][i].is_none()).collect::<Vec<_>>();
+        if !missing.is_empty() {
+            unknown_dates.push(json!({"date":date,"missing_count":missing.len(),"missing_symbol_sample":missing.iter().take(20).collect::<Vec<_>>(),"sample_limit":20}));
+            continue;
+        }
+        let observations = universe.iter().map(|s|Observation{symbol:s.clone(),value:values[s][i].unwrap(),industry:None,market_cap:None}).collect::<Vec<_>>();
+        for item in evaluate("RANK", universe, &observations, 0.0)? {rank.get_mut(&item.symbol).unwrap()[i]=Some(item.value);}
+        for item in evaluate("PERCENTILE", universe, &observations, 0.0)? {percentile.get_mut(&item.symbol).unwrap()[i]=Some(item.value);}
+    }
+    Ok(json!({"rank":rank,"percentile":percentile,"unknown_dates":unknown_dates,
+        "universe":universe,"dates":dates,"tie_policy":"average_rank_descending",
+        "membership_policy":"fixed_research_scope_not_historical_index_membership"}))
+}
+
+fn mean(values: &[f64]) -> f64 {
+    let base = values[0];
+    base + values
+        .iter()
+        .skip(1)
+        .map(|v| (v - base) / values.len() as f64)
+        .sum::<f64>()
+}
+fn quantile(sorted: &[f64], p: f64) -> f64 {
+    let x = p * (sorted.len() - 1) as f64;
+    let l = x.floor() as usize;
+    let r = x.ceil() as usize;
+    sorted[l] + (sorted[r] - sorted[l]) * (x - l as f64)
+}
+
+pub fn evaluate(
+    name: &str,
+    universe: &[String],
+    rows: &[Observation],
+    threshold: f64,
+) -> Result<Vec<Output>, String> {
+    let expected = universe.iter().collect::<BTreeSet<_>>();
+    if rows.is_empty()
+        || rows.len() > 20_000
+        || expected.len() != universe.len()
+        || rows.len() != universe.len()
+        || rows.iter().map(|r| &r.symbol).collect::<BTreeSet<_>>() != expected
+        || rows.iter().any(|r| !r.value.is_finite())
+    {
+        return Err("cross_section_incomplete_or_invalid_universe".into());
+    }
+    if !OPERATORS.contains(&name) || !threshold.is_finite() {
+        return Err("cross_section_operator_invalid".into());
+    }
+    if matches!(name, "TOP" | "BOTTOM") && (threshold < 1.0 || threshold.fract() != 0.0)
+        || matches!(name, "TOP_PERCENT" | "BOTTOM_PERCENT") && !(0.0..=1.0).contains(&threshold)
+        || name == "WINSORIZE" && !(0.0..0.5).contains(&threshold)
+    {
+        return Err("cross_section_threshold_invalid".into());
+    }
+    let mut sorted = rows.iter().map(|r| r.value).collect::<Vec<_>>();
+    sorted.sort_by(f64::total_cmp);
+    let mut industry_values: BTreeMap<&str, Vec<f64>> = BTreeMap::new();
+    if name == "INDUSTRY_NEUTRALIZE" {
+        for row in rows {
+            let industry = row
+                .industry
+                .as_deref()
+                .filter(|v| !v.trim().is_empty())
+                .ok_or("cross_section_pit_industry_missing")?;
+            industry_values.entry(industry).or_default().push(row.value);
+        }
+    }
+    let size = if name == "SIZE_NEUTRALIZE" {
+        let x = rows
+            .iter()
+            .map(|r| {
+                r.market_cap
+                    .filter(|v| v.is_finite() && *v > 0.0)
+                    .map(f64::ln)
+                    .ok_or("cross_section_market_cap_missing")
+            })
+            .collect::<Result<Vec<_>, _>>()?;
+        let xm = mean(&x);
+        let ym = mean(&sorted);
+        let variance = x.iter().map(|v| (v - xm).powi(2)).sum::<f64>();
+        if variance == 0.0 || rows.len() < 3 {
+            return Err("cross_section_size_regression_unidentified".into());
+        }
+        let beta = x
+            .iter()
+            .zip(rows)
+            .map(|(x, y)| (x - xm) * (y.value - ym))
+            .sum::<f64>()
+            / variance;
+        Some((x, xm, ym, beta))
+    } else {
+        None
+    };
+    rows.iter()
+        .enumerate()
+        .map(|(index, row)| {
+            let low = sorted.partition_point(|v| *v < row.value);
+            let high = sorted.partition_point(|v| *v <= row.value);
+            let rank = (low + 1 + high) as f64 / 2.0;
+            let descending = (rows.len() + 1) as f64 - rank;
+            let percentile = if rows.len() == 1 {
+                0.5
+            } else {
+                (rank - 1.0) / (rows.len() - 1) as f64
+            };
+            let value = match name {
+                "RANK" => descending,
+                "PERCENTILE" => percentile,
+                "TOP" => f64::from(descending <= threshold),
+                "BOTTOM" => f64::from(rank <= threshold),
+                "TOP_PERCENT" => f64::from(descending <= threshold * rows.len() as f64),
+                "BOTTOM_PERCENT" => f64::from(rank <= threshold * rows.len() as f64),
+                "WINSORIZE" => row.value.clamp(
+                    quantile(&sorted, threshold),
+                    quantile(&sorted, 1.0 - threshold),
+                ),
+                "INDUSTRY_NEUTRALIZE" => {
+                    row.value - mean(&industry_values[row.industry.as_deref().unwrap()])
+                }
+                "SIZE_NEUTRALIZE" => {
+                    let (x, xm, ym, beta) = size.as_ref().unwrap();
+                    row.value - (ym + beta * (x[index] - xm))
+                }
+                _ => unreachable!(),
+            };
+            if !value.is_finite() {
+                return Err("cross_section_result_nonfinite".into());
+            }
+            Ok(Output {
+                symbol: row.symbol.clone(),
+                value,
+            })
+        })
+        .collect()
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    #[test]
+    fn historical_ranks_keep_ties_and_unknown_full_cross_sections() {
+        let dates=["2026-09-07","2026-09-08","2026-09-09"].map(|d|d.parse().unwrap());
+        let universe=vec!["A".into(),"B".into(),"C".into()];
+        let values=BTreeMap::from([("A".into(),vec![None,Some(10.0),Some(20.0)]),("B".into(),vec![Some(10.0),Some(10.0),Some(10.0)]),("C".into(),vec![Some(20.0),Some(5.0),Some(15.0)])]);
+        let out=rank_history(&dates,&universe,&values).unwrap();
+        assert_eq!(out["rank"]["A"],serde_json::json!([null,1.5,1.0]));
+        assert_eq!(out["rank"]["C"],serde_json::json!([null,3.0,2.0]));
+        assert_eq!(out["unknown_dates"][0]["missing_count"],1);
+        let earlier=values.iter().map(|(s,v)|(s.clone(),v[..2].to_vec())).collect();
+        let first=rank_history(&dates[..2],&universe,&earlier).unwrap();
+        assert_eq!(&out["rank"]["A"].as_array().unwrap()[..2],first["rank"]["A"].as_array().unwrap());
+        assert!(rank_history(&dates,&universe[..2],&values).is_err());
+    }
+    fn rows() -> Vec<Observation> {
+        [1.0, 3.0, 3.0, 4.0]
+            .iter()
+            .enumerate()
+            .map(|(i, &value)| Observation {
+                symbol: format!("S{i}"),
+                value,
+                industry: Some(if i < 2 { "A" } else { "B" }.into()),
+                market_cap: Some(10.0 + i as f64),
+            })
+            .collect()
+    }
+    #[test]
+    fn ties_keep_equal_rank_and_missing_universe_rejects() {
+        let r = rows();
+        let u = r.iter().map(|r| r.symbol.clone()).collect::<Vec<_>>();
+        let out = evaluate("RANK", &u, &r, 0.0).unwrap();
+        assert_eq!(
+            out.iter().map(|r| r.value).collect::<Vec<_>>(),
+            vec![4.0, 2.5, 2.5, 1.0]
+        );
+        assert!(evaluate("RANK", &u, &r[..3], 0.0).is_err());
+    }
+    #[test]
+    fn neutralization_preserves_input_order() {
+        let r = rows();
+        let u = r.iter().map(|r| r.symbol.clone()).collect::<Vec<_>>();
+        let out = evaluate("INDUSTRY_NEUTRALIZE", &u, &r, 0.0).unwrap();
+        assert_eq!(
+            out.iter().map(|r| r.value).collect::<Vec<_>>(),
+            vec![-1.0, 1.0, -0.5, 0.5]
+        );
+        assert!(evaluate("TOP_PERCENT", &u, &r, 20.0).is_err());
+    }
+}

crates/fidc-core/src/lib.rs

@@ -3,6 +3,10 @@ pub mod calendar;
 pub mod cost;
 pub mod data;
 pub mod daily_patterns;
+pub mod pattern_context;
+pub mod session_events;
+pub mod factor_events;
+pub mod factor_cross_section;
 pub mod engine;
 pub mod event_bus;
 pub mod events;

crates/fidc-core/src/pattern_context.rs

@@ -0,0 +1,427 @@
+//! Explicit reference identities and frozen rank universes shared by all daily runtimes.
+use crate::{
+    daily_patterns::{dataset_series, evaluate_with_context, PatternSpec, ResearchContext},
+    factor_events::{field_dependencies, Expr},
+    DataSet,
+};
+use chrono::NaiveDate;
+use serde::{Deserialize, Serialize};
+use serde_json::Value;
+use std::collections::{BTreeMap, BTreeSet};
+
+pub const CONTRACT: &str = "fidc_pattern_execution_context_v1";
+pub const CONTEXT_FIELDS: &[&str] = &[
+    "index_open",
+    "index_high",
+    "index_low",
+    "index_close",
+    "scope_rank",
+    "scope_percentile",
+    "scope_size",
+];
+const STOCK_FIELDS: &[&str] = &[
+    "open",
+    "high",
+    "low",
+    "close",
+    "volume",
+    "raw_open",
+    "raw_high",
+    "raw_low",
+    "raw_close",
+    "prev_close",
+    "amount",
+];
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct ExecutionContext {
+    pub contract: String,
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub benchmark: Option<String>,
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub rank_expression: Option<Expr>,
+    #[serde(default, skip_serializing_if = "Vec::is_empty")]
+    pub rank_universe: Vec<String>,
+}
+
+fn valid_symbol(s: &str) -> bool {
+    let Some((code, market)) = s.split_once('.') else {
+        return false;
+    };
+    code.len() == 6
+        && code.bytes().all(|c| c.is_ascii_digit())
+        && matches!(market, "SH" | "SZ" | "BJ" | "CSI")
+}
+
+impl ExecutionContext {
+    pub fn fields(&self, expression: &Expr) -> BTreeSet<String> {
+        let mut fields = field_dependencies(expression);
+        if let Some(rank) = &self.rank_expression {
+            fields.extend(field_dependencies(rank));
+        }
+        fields
+    }
+    pub fn validate(&self, expression: &Expr) -> Result<(), String> {
+        if self.contract != CONTRACT {
+            return Err("pattern_context_contract_invalid".into());
+        }
+        let needed = field_dependencies(expression);
+        let ranked = needed.iter().any(|f| f.starts_with("scope_"));
+        if ranked != self.rank_expression.is_some() || !ranked && !self.rank_universe.is_empty() {
+            return Err("pattern_rank_expression_and_universe_required".into());
+        }
+        if ranked
+            && (self.rank_universe.len() < 2
+                || self.rank_universe.len() > 20_000
+                || self.rank_universe.iter().any(|s| !valid_symbol(s))
+                || self.rank_universe.iter().collect::<BTreeSet<_>>().len()
+                    != self.rank_universe.len())
+        {
+            return Err("pattern_rank_universe_invalid".into());
+        }
+        if let Some(rank) = &self.rank_expression {
+            let fields = field_dependencies(rank);
+            if fields
+                .iter()
+                .any(|f| !STOCK_FIELDS.contains(&f.as_str()) && !f.starts_with("index_"))
+            {
+                return Err("pattern_rank_expression_invalid_or_recursive".into());
+            }
+        }
+        let fields = self.fields(expression);
+        if fields
+            .iter()
+            .any(|f| !STOCK_FIELDS.contains(&f.as_str()) && !CONTEXT_FIELDS.contains(&f.as_str()))
+        {
+            return Err("pattern_context_unmapped_field".into());
+        }
+        let index = fields.iter().any(|f| f.starts_with("index_"));
+        if index != self.benchmark.is_some()
+            || self
+                .benchmark
+                .as_ref()
+                .is_some_and(|s| !valid_symbol(s) || s.ends_with(".BJ"))
+        {
+            return Err("pattern_reference_index_required".into());
+        }
+        if !index && !ranked {
+            return Err("pattern_unused_context".into());
+        }
+        Ok(())
+    }
+}
+
+pub fn build_dataset_context(
+    spec: &PatternSpec,
+    data: &DataSet,
+    date: NaiveDate,
+) -> Result<ResearchContext, String> {
+    let Some(config) = &spec.execution_context else {
+        return Ok(ResearchContext::default());
+    };
+    config.validate(
+        spec.expression
+            .as_ref()
+            .ok_or("pattern_context_requires_expression")?,
+    )?;
+    let days = data.calendar().trailing_days(date, spec.history_len());
+    if days.len() != spec.history_len() || days.last() != Some(&date) {
+        return Err("pattern_context_calendar_incomplete".into());
+    }
+    let needed = config.fields(spec.expression.as_ref().unwrap());
+    let mut context = ResearchContext::default();
+    if let Some(symbol) = &config.benchmark {
+        for name in needed.iter().filter(|f| f.starts_with("index_")) {
+            let values = days
+                .iter()
+                .map(|d| {
+                    let value = if let Some(b) = data.market(*d, symbol) {
+                        match name.as_str() {
+                            "index_open" => Some(b.open),
+                            "index_high" => Some(b.high),
+                            "index_low" => Some(b.low),
+                            "index_close" => Some(b.close),
+                            _ => None,
+                        }
+                    } else if let Some(b) = data.benchmark(*d).filter(|b| &b.benchmark == symbol) {
+                        match name.as_str() {
+                            "index_open" => Some(b.open),
+                            "index_close" => Some(b.close),
+                            _ => None,
+                        }
+                    } else {
+                        None
+                    };
+                    value
+                        .filter(|v| v.is_finite() && *v > 0.0)
+                        .map(Some)
+                        .ok_or_else(|| format!("pattern_reference_missing: {symbol} {d} {name}"))
+                })
+                .collect::<Result<Vec<_>, _>>()?;
+            context.common.insert(name.clone(), values);
+        }
+    }
+    if let Some(expression) = &config.rank_expression {
+        let mut input = spec.clone();
+        input.execution_context = None;
+        input.expression = Some(expression.clone());
+        let mut values = BTreeMap::new();
+        for symbol in &config.rank_universe {
+            let row = evaluate_with_context(
+                &input,
+                &days,
+                &dataset_series(data, &days, symbol),
+                &context.common,
+                true,
+            )?;
+            if let Some(reason) = row.exclusion {
+                return Err(format!("pattern_rank_member_incomplete: {symbol} {reason}"));
+            }
+            values.insert(
+                symbol.clone(),
+                serde_json::from_value::<Vec<Option<f64>>>(
+                    row.values["expression"]["values"].clone(),
+                )
+                .map_err(|e| e.to_string())?,
+            );
+        }
+        let ranks =
+            crate::factor_cross_section::rank_history(&days, &config.rank_universe, &values)?;
+        for symbol in &config.rank_universe {
+            let decode = |value: &Value| {
+                serde_json::from_value::<Vec<Option<f64>>>(value.clone()).map_err(|e| e.to_string())
+            };
+            context.by_symbol.insert(
+                symbol.clone(),
+                BTreeMap::from([
+                    ("scope_rank".into(), decode(&ranks["rank"][symbol])?),
+                    (
+                        "scope_percentile".into(),
+                        decode(&ranks["percentile"][symbol])?,
+                    ),
+                    (
+                        "scope_size".into(),
+                        vec![Some(config.rank_universe.len() as f64); days.len()],
+                    ),
+                ]),
+            );
+        }
+    }
+    Ok(context)
+}
+
+pub fn specs_in_value(value: &Value) -> Result<Vec<PatternSpec>, String> {
+    let mut specs = Vec::new();
+    match value {
+        Value::String(text) => specs.extend(crate::daily_patterns::expression_specs(text)?),
+        Value::Array(items) => {
+            for v in items {
+                specs.extend(specs_in_value(v)?);
+            }
+        }
+        Value::Object(items) => {
+            for v in items.values() {
+                specs.extend(specs_in_value(v)?);
+            }
+        }
+        _ => {}
+    }
+    Ok(specs)
+}
+
+pub fn required_symbols(value: &Value) -> Result<(BTreeSet<String>, BTreeSet<String>), String> {
+    let (mut indices, mut stocks) = (BTreeSet::new(), BTreeSet::new());
+    for spec in specs_in_value(value)? {
+        if let Some(context) = spec.execution_context {
+            if let Some(index) = context.benchmark {
+                indices.insert(index);
+            }
+            stocks.extend(context.rank_universe);
+        }
+    }
+    Ok((indices, stocks))
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::{BenchmarkSnapshot, DailyFactorSnapshot, DailyMarketSnapshot, Instrument};
+    use serde_json::json;
+    #[test]
+    fn normalized_rule_does_not_turn_an_omitted_window_into_explicit_null() {
+        let expression:Expr=serde_json::from_value(json!({"kind":"operator","name":"GT","args":[{"kind":"field","name":"close"},{"kind":"number","value":1}]})).unwrap();
+        assert!(serde_json::to_value(expression).unwrap().get("window").is_none());
+    }
+    fn data(future: bool, reference: bool) -> DataSet {
+        let mut days = vec![
+            NaiveDate::from_ymd_opt(2026, 9, 4).unwrap(),
+            NaiveDate::from_ymd_opt(2026, 9, 7).unwrap(),
+            NaiveDate::from_ymd_opt(2026, 9, 8).unwrap(),
+        ];
+        if future {
+            days.push(NaiveDate::from_ymd_opt(2026, 9, 9).unwrap());
+        }
+        let symbols = vec!["000001.SZ", "000002.SZ", "000003.SZ"];
+        let mut instruments = symbols
+            .iter()
+            .map(|s| Instrument {
+                symbol: s.to_string(),
+                name: s.to_string(),
+                board: "SZ_MAIN".into(),
+                round_lot: 100,
+                listed_at: None,
+                delisted_at: None,
+                status: "active".into(),
+            })
+            .collect::<Vec<_>>();
+        if reference {
+            instruments.push(Instrument {
+                symbol: "399006.SZ".into(),
+                name: "reference".into(),
+                board: "INDEX".into(),
+                round_lot: 1,
+                listed_at: None,
+                delisted_at: None,
+                status: "active".into(),
+            });
+        }
+        let mut market = vec![];
+        let mut factors = vec![];
+        let mut benchmark = vec![];
+        for (i, d) in days.iter().enumerate() {
+            for (n, s) in symbols.iter().enumerate() {
+                let c = [
+                    [10., 12., 11., 1000.],
+                    [10., 11., 12., 1.],
+                    [10., 10., 13., 1.],
+                ][n][i];
+                market.push(DailyMarketSnapshot {
+                    date: *d,
+                    symbol: s.to_string(),
+                    timestamp: None,
+                    day_open: c,
+                    open: c,
+                    high: c,
+                    low: c,
+                    close: c,
+                    last_price: c,
+                    bid1: c,
+                    ask1: c,
+                    prev_close: 10.,
+                    volume: 100000,
+                    minute_volume: 0,
+                    bid1_volume: 10000,
+                    ask1_volume: 10000,
+                    trading_phase: None,
+                    paused: false,
+                    upper_limit: c * 2.,
+                    lower_limit: c / 2.,
+                    price_tick: 0.01,
+                });
+                factors.push(DailyFactorSnapshot {
+                    date: *d,
+                    symbol: s.to_string(),
+                    market_cap_bn: 1.,
+                    free_float_cap_bn: 1.,
+                    pe_ttm: 10.,
+                    turnover_ratio: None,
+                    effective_turnover_ratio: None,
+                    adjustment_factor_backward1: Some(1.),
+                    extra_factors: Default::default(),
+                });
+            }
+            if reference {
+                let mut row = market.last().unwrap().clone();
+                row.symbol = "399006.SZ".into();
+                row.open = 30.;
+                row.high = 30.;
+                row.low = 30.;
+                row.close = 30.;
+                market.push(row);
+            }
+            benchmark.push(BenchmarkSnapshot {
+                date: *d,
+                benchmark: "000300.SH".into(),
+                open: 4000.,
+                close: 4000.,
+                prev_close: 4000.,
+                volume: 1000,
+            });
+        }
+        DataSet::from_components(instruments, market, factors, vec![], benchmark).unwrap()
+    }
+    fn spec(rank: bool) -> PatternSpec {
+        let expression = if rank {
+            json!({"kind":"operator","name":"GT","args":[{"kind":"field","name":"scope_rank"},{"kind":"number","value":2}]})
+        } else {
+            json!({"kind":"operator","name":"LT","args":[{"kind":"field","name":"index_close"},{"kind":"number","value":100}]})
+        };
+        let context = if rank {
+            json!({"contract":CONTRACT,"rank_expression":{"kind":"operator","name":"PCT_CHANGE","window":1,"args":[{"kind":"field","name":"close"}]},"rank_universe":["000001.SZ","000002.SZ","000003.SZ"]})
+        } else {
+            json!({"contract":CONTRACT,"benchmark":"399006.SZ"})
+        };
+        serde_json::from_value::<PatternSpec>(json!({"template":"expression","parameters":{"history_window":3},"expression":expression,"execution_context":context})).unwrap().validate().unwrap()
+    }
+    #[test]
+    fn dataset_rank_is_full_scope_causal_and_equal_to_pure_cross_section() {
+        let spec = spec(true);
+        let date = NaiveDate::from_ymd_opt(2026, 9, 8).unwrap();
+        let original = build_dataset_context(&spec, &data(false, true), date).unwrap();
+        let future = build_dataset_context(&spec, &data(true, true), date).unwrap();
+        assert_eq!(original.by_symbol, future.by_symbol);
+        assert_eq!(original.by_symbol["000001.SZ"]["scope_rank"][2], Some(3.));
+        assert_eq!(original.by_symbol["000002.SZ"]["scope_rank"][2], Some(2.));
+        assert_eq!(original.by_symbol["000003.SZ"]["scope_rank"][2], Some(1.));
+        assert!(
+            crate::daily_patterns::evaluate_dataset(&spec, &data(false, true), date, "000001.SZ")
+                .unwrap()
+                .matched
+        );
+        let mut incomplete = data(false, true).snapshot_components();
+        incomplete.market.retain(|r| r.symbol != "000003.SZ");
+        let broken = DataSet::from_components(
+            incomplete.instruments,
+            incomplete.market,
+            incomplete.factors,
+            incomplete.candidates,
+            incomplete.benchmarks,
+        )
+        .unwrap();
+        assert!(build_dataset_context(&spec, &broken, date).is_err());
+    }
+    #[test]
+    fn reference_index_never_defaults_to_performance_benchmark() {
+        let spec = spec(false);
+        let date = NaiveDate::from_ymd_opt(2026, 9, 8).unwrap();
+        assert!(
+            crate::daily_patterns::evaluate_dataset(&spec, &data(false, true), date, "000001.SZ")
+                .unwrap()
+                .matched
+        );
+        assert!(build_dataset_context(&spec, &data(false, false), date)
+            .unwrap_err()
+            .contains("399006.SZ"));
+    }
+    #[test]
+    fn runtime_contract_rejects_missing_range_and_recursive_ranks() {
+        let mut missing = spec(true);
+        missing
+            .execution_context
+            .as_mut()
+            .unwrap()
+            .rank_universe
+            .clear();
+        assert!(missing.validate().is_err());
+        let mut recursive = spec(true);
+        recursive
+            .execution_context
+            .as_mut()
+            .unwrap()
+            .rank_expression = Some(Expr::Field {
+            name: "scope_rank".into(),
+        });
+        assert!(recursive.validate().is_err());
+    }
+}

crates/fidc-core/src/platform_expr_strategy.rs

@@ -14,7 +14,7 @@ use crate::data::EligibleUniverseSnapshot;
 use crate::data::{
     BACKWARD_ADJUSTMENT_FACTOR_FIELD, CandidateEligibility, DailyFactorSnapshot,
     DailyMarketSnapshot, DailySnapshotView, DataSet, PriceField, decision_free_float_cap_bn,
-    NumericFactorMap, decision_market_cap_bn,
+    decision_market_cap_bn,
 };
 use crate::engine::BacktestError;
 use crate::events::{OrderSide, ProcessEvent, ProcessEventKind};
@@ -672,6 +672,7 @@ pub struct PlatformExprStrategyConfig {
     pub completed_session_factor_fields: BTreeSet<String>,
     pub candidate_symbols_by_date: BTreeMap<NaiveDate, BTreeSet<String>>,
     pub intraday_execution_time: Option<NaiveTime>,
+    pub session_event_times: Vec<NaiveTime>,
     pub explicit_action_times: Vec<NaiveTime>,
     pub delayed_limit_open_exit_enabled: bool,
     pub delayed_limit_open_exit_time: Option<NaiveTime>,
@@ -753,6 +754,7 @@ impl PlatformExprStrategyConfig {
             completed_session_factor_fields: BTreeSet::new(),
             candidate_symbols_by_date: BTreeMap::new(),
             intraday_execution_time: None,
+            session_event_times: Vec::new(),
             explicit_action_times: Vec::new(),
             delayed_limit_open_exit_enabled: false,
             delayed_limit_open_exit_time: None,
@@ -974,7 +976,7 @@ struct StockExpressionState {
     stock_volume_ma60: f64,
     stock_volume_ma100: f64,
     current_series_end: Option<usize>,
-    extra_factors: NumericFactorMap,
+    extra_factors: BTreeMap<String, f64>,
     extra_text_factors: BTreeMap<String, String>,
 }
 
@@ -1287,7 +1289,7 @@ struct RuntimeHelperBinding {
 
 #[derive(Clone)]
 enum CompiledRuntimeHelperArgs {
-    DailyPattern { spec: crate::daily_patterns::PatternSpec },
+    DailyPattern { spec: crate::daily_patterns::PatternSpec, identity: String },
     RollingMean {
         field: String,
         lookback: usize,
@@ -1347,6 +1349,9 @@ enum RuntimeHelperResolution {
 pub struct PlatformExprStrategy {
     pattern_results_date: RefCell<Option<NaiveDate>>,
     pattern_results: RefCell<BTreeMap<(NaiveDate, String, String), crate::daily_patterns::PatternResult>>,
+    pattern_contexts: RefCell<BTreeMap<String,crate::daily_patterns::ResearchContext>>,
+    pattern_specs: RefCell<BTreeMap<String,String>>,
+    pattern_frame_at:RefCell<Option<NaiveDateTime>>,
     config: PlatformExprStrategyConfig,
     engine: Engine,
     rebalance_day_counter: usize,
@@ -1796,6 +1801,9 @@ impl PlatformExprStrategy {
             stock_extra_factor_map_required,
             stock_text_factors_required,
             pattern_results: RefCell::new(BTreeMap::new()),
+            pattern_contexts: RefCell::new(BTreeMap::new()),
+            pattern_specs: RefCell::new(BTreeMap::new()),
+            pattern_frame_at:RefCell::new(None),
             pattern_results_date: RefCell::new(None),
             stock_state_cache_date: RefCell::new(None),
             stock_state_cache_calendar_index: RefCell::new(None),
@@ -4806,7 +4814,7 @@ impl PlatformExprStrategy {
                     self.stock_extra_factor_map_required
                         || self.stock_extra_factor_identifiers.contains(field.as_ref())
                 })
-                .map(|(field, value)| (field.clone(), *value))
+                .map(|(field, value)| (field.to_string(), *value))
                 .collect()
         } else {
             BTreeMap::new()
@@ -4824,7 +4832,7 @@ impl PlatformExprStrategy {
                         .and_then(|row| row.extra_factors.get(field.as_str()))
                         .copied()
                         .unwrap_or(f64::NAN);
-                    extra_factors.insert(field.clone().into(), value);
+                    extra_factors.insert(field.clone(), value);
                 }
             }
         }
@@ -4835,10 +4843,7 @@ impl PlatformExprStrategy {
                     .contains(BACKWARD_ADJUSTMENT_FACTOR_FIELD))
             && let Some(value) = factor.adjustment_factor_backward1
         {
-            extra_factors.insert(
+            extra_factors.insert(BACKWARD_ADJUSTMENT_FACTOR_FIELD.to_string(), value);
-                std::borrow::Cow::Borrowed(BACKWARD_ADJUSTMENT_FACTOR_FIELD),
-                value,
-            );
         }
 
         let state = StockExpressionState {
@@ -5708,23 +5713,48 @@ impl PlatformExprStrategy {
         args: &CompiledRuntimeHelperArgs,
     ) -> Result<RuntimeHelperResolution, BacktestError> {
         match args {
-            CompiledRuntimeHelperArgs::DailyPattern { spec } => {
+            CompiledRuntimeHelperArgs::DailyPattern { spec, identity } => {
-                if self.config.matching_type != MatchingType::NextBarOpen {
+                if *self.pattern_results_date.borrow()!=Some(ctx.execution_date) {
+                    self.pattern_results.borrow_mut().clear();self.pattern_contexts.borrow_mut().clear();self.pattern_specs.borrow_mut().clear();
+                    *self.pattern_results_date.borrow_mut()=Some(ctx.execution_date);
+                }
+                if *self.pattern_frame_at.borrow()!=ctx.active_datetime {
+                    self.pattern_results.borrow_mut().clear();*self.pattern_frame_at.borrow_mut()=ctx.active_datetime;
+                }
+                if spec.template=="session_event" {
+                    if self.config.matching_type!=MatchingType::MinuteLast {return Err(BacktestError::Execution("session_event_requires_minute_last".into()));}
+                    let active=ctx.active_datetime.ok_or_else(||BacktestError::Execution("session_event_requires_explicit_clock".into()))?;
+                    let clock=active.time();
+                    if !((NaiveTime::from_hms_opt(9,31,0).unwrap()<=clock&&clock<=NaiveTime::from_hms_opt(11,30,0).unwrap())||(NaiveTime::from_hms_opt(13,1,0).unwrap()<=clock&&clock<=NaiveTime::from_hms_opt(15,0,0).unwrap())) {
+                        return Ok(if helper=="pattern_signal"{RuntimeHelperResolution::Boolean(false)}else{RuntimeHelperResolution::Number(0.)});
+                    }
+                    let stock=stock.ok_or_else(||BacktestError::Execution("session_event_requires_stock".into()))?;
+                    let key=(active.date(),stock.symbol.to_string(),identity.clone());
+                    if !self.pattern_results.borrow().contains_key(&key) {
+                        let result=crate::session_events::evaluate(spec,&stock.symbol,ctx.data.completed_minute_bars_on(active.date(),&stock.symbol),active).map_err(BacktestError::Execution)?;
+                        self.pattern_results.borrow_mut().insert(key.clone(),result);
+                        self.pattern_specs.borrow_mut().insert(identity.clone(),serde_json::to_string(spec).unwrap());
+                    }
+                    let rows=self.pattern_results.borrow();let result=&rows[&key];
+                    return if helper=="pattern_signal" {Ok(RuntimeHelperResolution::Boolean(result.matched))}else{result.score.map(RuntimeHelperResolution::Number).ok_or_else(||BacktestError::Execution("session_score_unknown".into()))};
+                }
+                if !matches!(self.config.matching_type,MatchingType::NextBarOpen|MatchingType::MinuteLast) {
                     return Err(BacktestError::Execution("daily_pattern_requires_next_bar_open: 完整日线形态只能在下一交易日执行".into()));
                 }
-                let date = day.date.min(ctx.decision_date);
+                let date = if self.config.matching_type==MatchingType::MinuteLast {ctx.data.previous_trading_date(ctx.execution_date,1).ok_or_else(||BacktestError::Execution("daily_pattern_previous_completed_date_missing".into()))?} else {day.date.min(ctx.decision_date)};
                 // Lagged replay retains the decision day's schedule label; execution is on a later session.
                 if !ctx.is_lagged_execution() && ctx.active_datetime.is_some_and(|t| t.date() == date && t.time() < NaiveTime::from_hms_opt(16, 0, 0).unwrap()) {
                     return Err(BacktestError::Execution(format!("daily_pattern_not_yet_visible: 不允许使用未完成的当日日线; decision_date={date}, execution_date={}, active_datetime={:?}",ctx.execution_date,ctx.active_datetime)));
                 }
                 let stock = stock.ok_or_else(|| BacktestError::Execution("pattern_signal requires stock context".into()))?;
-                let key = (date, stock.symbol.to_string(), serde_json::to_string(spec).unwrap());
+                let key = (date, stock.symbol.to_string(), identity.clone());
-                if *self.pattern_results_date.borrow() != Some(date) {
-                    self.pattern_results.borrow_mut().clear();
-                    *self.pattern_results_date.borrow_mut() = Some(date);
-                }
                 if !self.pattern_results.borrow().contains_key(&key) {
-                    let result = crate::daily_patterns::evaluate_dataset(spec,ctx.data,date,&stock.symbol).map_err(BacktestError::Execution)?;
+                    if !self.pattern_contexts.borrow().contains_key(&key.2) {
+                        let context=crate::pattern_context::build_dataset_context(spec,ctx.data,date).map_err(BacktestError::Execution)?;
+                        self.pattern_contexts.borrow_mut().insert(key.2.clone(),context);
+                        self.pattern_specs.borrow_mut().insert(key.2.clone(),serde_json::to_string(spec).unwrap());
+                    }
+                    let result = crate::daily_patterns::evaluate_dataset_context(spec,ctx.data,date,&stock.symbol,&self.pattern_contexts.borrow()[&key.2]).map_err(BacktestError::Execution)?;
                     self.pattern_results.borrow_mut().insert(key.clone(),result);
                 }
                 let results = self.pattern_results.borrow();
@@ -6986,7 +7016,10 @@ impl PlatformExprStrategy {
             "pattern_signal" | "pattern_score" if args.len() == 1 => {
                 let text: String = serde_json::from_str(&args[0]).ok()?;
                 let spec: crate::daily_patterns::PatternSpec = serde_json::from_str(&text).ok()?;
-                Some(CompiledRuntimeHelperArgs::DailyPattern { spec: spec.validate().ok()? })
+                let spec=spec.validate().ok()?;
+                use sha2::Digest;
+                let identity=format!("{:x}",sha2::Sha256::digest(serde_json::to_vec(&spec).ok()?));
+                Some(CompiledRuntimeHelperArgs::DailyPattern { spec, identity })
             }
             "rolling_mean" | "sma" | "ma" => {
                 let (field, lookback) = field_lookback()?;
@@ -12263,13 +12296,15 @@ impl Strategy for PlatformExprStrategy {
             .is_some()
             && self.config.rotation_enabled
         {
-            rules.push(
+            let schedule=self.config.rebalance_schedule.as_ref().expect("checked timed rebalance schedule");
-                self.config
+            if self.config.session_event_times.is_empty() {
-                    .rebalance_schedule
+                rules.push(schedule.as_schedule_rule(ScheduleStage::OnDay));
-                    .as_ref()
+            } else {
-                    .expect("checked timed rebalance schedule")
+                for time in &self.config.session_event_times {
-                    .as_schedule_rule(ScheduleStage::OnDay),
+                    let mut timed=schedule.clone();timed.time_rule=Some(ScheduleTimeRule::physical_time(time.hour(),time.minute()));
-            );
+                    rules.push(timed.as_schedule_rule(ScheduleStage::OnDay));
+                }
+            }
         }
         if self.config.explicit_actions.is_empty() {
             return rules;
@@ -12332,6 +12367,7 @@ impl Strategy for PlatformExprStrategy {
 
     fn decision_quote_times(&self) -> Vec<NaiveTime> {
         let mut times = BTreeSet::new();
+        times.extend(self.config.session_event_times.iter().copied());
         if self.uses_intraday_execution_quotes() {
             if self.config.explicit_action_times.is_empty() {
                 times.insert(self.intraday_execution_start_time());
@@ -12426,12 +12462,28 @@ impl PlatformExprStrategy {
     }
 
     fn append_pattern_diagnostics(&self, decision: &mut StrategyDecision) {
+        let mut contexts=BTreeMap::<String,serde_json::Value>::new();
         for ((date, symbol, spec), result) in self.pattern_results.borrow().iter() {
+            if result.values["session_contract"]==crate::session_events::CONTRACT {
+                let record=serde_json::json!({"event":"session_event_decision","date":date,"symbol":symbol,"spec_sha256":spec,"matched":result.matched,"signal_bar_end":result.values["signal_bar_end"],"decision_at":result.values["decision_at"],"exclusion":result.exclusion}).to_string();
+                if !decision.diagnostics.contains(&record){decision.diagnostics.push(record)}
+                continue;
+            }
+            if result.values["execution_context_latest"].as_object().is_some_and(|v|!v.is_empty()) {
+                let group=contexts.entry(spec.clone()).or_insert_with(||serde_json::json!({"event":"daily_pattern_context_decisions","date":date,"spec_sha256":spec,"evaluated":0,"matched":0,"excluded":0,"sample_limit":20,"samples":[]}));
+                group["evaluated"]=serde_json::json!(group["evaluated"].as_u64().unwrap()+1);
+                group["matched"]=serde_json::json!(group["matched"].as_u64().unwrap()+u64::from(result.matched));
+                group["excluded"]=serde_json::json!(group["excluded"].as_u64().unwrap()+u64::from(result.exclusion.is_some()));
+                let samples=group["samples"].as_array_mut().unwrap();
+                if samples.len()<20 {samples.push(serde_json::json!({"symbol":symbol,"matched":result.matched,"context":result.values["execution_context_latest"],"exclusion":result.exclusion}));}
+                continue;
+            }
             if let Some(evidence) = &result.exclusion {
-                let record = serde_json::json!({"event":"daily_pattern_excluded","date":date,"symbol":symbol,"spec":spec,"evidence":evidence}).to_string();
+                let record = serde_json::json!({"event":"daily_pattern_excluded","date":date,"symbol":symbol,"spec":self.pattern_specs.borrow().get(spec),"spec_sha256":spec,"evidence":evidence}).to_string();
                 if !decision.diagnostics.contains(&record) { decision.diagnostics.push(record); }
             }
         }
+        for value in contexts.values() {let record=value.to_string();if !decision.diagnostics.contains(&record){decision.diagnostics.push(record);}}
     }
 
     fn compute_day_decision(&mut self, ctx: &StrategyContext<'_>) -> Result<StrategyDecision, BacktestError> {
@@ -14302,6 +14354,28 @@ mod tests {
         assert_eq!(strategy.selection_quote_usage, StockFilterQuoteUsage::DailyOnly);
     }
 
+    #[test]
+    fn session_event_uses_previous_bar_and_recomputes_at_each_minute_without_becoming_a_quote() {
+        let date = d(2026,9,8); let symbol = "000001.SZ";
+        let bars = (0..=33).map(|i| {
+            let timestamp = date.and_hms_opt(9,30,0).unwrap() + chrono::Duration::minutes(i);
+            let close = if i==31 {11.} else {10.};
+            crate::session_events::MinuteBar {symbol:symbol.into(),timestamp,available_at:timestamp,open:close,high:close,low:close,close,volume:100.,amount:close*100.}
+        }).collect();
+        let data = single_symbol_platform_data(&[date],symbol).with_completed_minute_bars(bars).unwrap();
+        let portfolio=PortfolioState::new(100_000.); let subscriptions=BTreeSet::new();
+        let mut ctx=StrategyContext {execution_date:date,decision_date:date,decision_index:0,data:&data,portfolio:&portfolio,futures_account:None,open_orders:&[],dynamic_universe:None,subscriptions:&subscriptions,process_events:&[],active_process_event:None,active_datetime:None,order_events:&[],fills:&[]};
+        let mut config=PlatformExprStrategyConfig::generic();config.signal_symbol=symbol.into();config.matching_type=MatchingType::MinuteLast;
+        let strategy=PlatformExprStrategy::new(config);
+        let expression=r#"pattern_signal("{\"template\":\"session_event\",\"session_event\":\"OPENING_RANGE_BREAKOUT_UP\",\"parameters\":{}}")"#;
+        let day=strategy.day_state(&ctx,date).unwrap();let stock=strategy.stock_state(&ctx,date,symbol).unwrap();
+        for (minute,expected) in [(1,false),(2,true),(3,false)] {
+            ctx.active_datetime=date.and_hms_opt(10,minute,0);
+            assert_eq!(strategy.eval_bool(&ctx,expression,&day,Some(&stock),None).unwrap(),expected);
+        }
+        assert!(data.snapshot_components().execution_quotes.is_empty());
+    }
+
     #[test]
     fn buy_filter_uses_active_schedule_time_instead_of_first_configured_time() {
         let date = d(2025, 1, 2);

crates/fidc-core/src/platform_strategy_spec.rs

@@ -2538,6 +2538,10 @@ pub fn platform_expr_config_from_spec(
         cfg.benchmark_symbol = normalize_symbol(&cfg.benchmark_symbol, None);
     }
     let trade_times = spec_trade_times(spec);
+    if crate::pattern_context::specs_in_value(&serde_json::to_value(spec).map_err(|e|e.to_string())?)?.iter().any(|p|p.template=="session_event") {
+        if trade_times.is_empty() {return Err("session_event_requires_explicit_trade_times".into());}
+        cfg.session_event_times=trade_times.clone();
+    }
     let explicit_trading_schedule = spec
         .runtime_expressions
         .as_ref()
@@ -4458,6 +4462,20 @@ mod tests {
         assert_eq!(cfg.delayed_limit_open_exit_time, None);
     }
 
+    #[test]
+    fn session_rotation_keeps_every_declared_clock_not_only_the_last_one() {
+        use crate::Strategy;
+        let literal=serde_json::to_string(&serde_json::json!({"template":"session_event","session_event":"INTRADAY_VOLUME_SPIKE","parameters":{}}).to_string()).unwrap();
+        let mut spec=serde_json::json!({"rebalance":{"tradeTimes":["09:35","10:40","14:59"]},"runtimeExpressions":{"schedule":{"frequency":"daily","time":"14:59"},"trading":{"rotationEnabled":true,"buyFilterExpr":format!("pattern_signal({literal})")}},"execution":{"matchingType":"minute_last"}});
+        let config=platform_expr_config_from_value("session","000300.SH",&spec).unwrap();
+        assert_eq!(config.session_event_times.len(),3);
+        let strategy=crate::PlatformExprStrategy::new(config);
+        assert_eq!(strategy.schedule_rules().len(),3);
+        assert_eq!(strategy.decision_quote_times().len(),3);
+        spec["rebalance"]["tradeTimes"]=serde_json::json!([]);
+        assert!(platform_expr_config_from_value("session","000300.SH",&spec).unwrap_err().to_string().contains("explicit_trade_times"));
+    }
+
     #[test]
     fn explicit_trading_schedule_overrides_rebalance_trade_times() {
         let spec = serde_json::json!({

crates/fidc-core/src/session_events.rs

@@ -0,0 +1,398 @@
+//! Completed, same-session minute events. These bars never become execution quotes.
+use crate::{
+    daily_patterns::{PatternResult, PatternSpec},
+    factor_events::{Expr, Frame},
+};
+use chrono::{FixedOffset, NaiveDateTime, NaiveTime, TimeZone, Timelike};
+use serde::{Deserialize, Serialize};
+use serde_json::{json, Value};
+use std::collections::BTreeMap;
+use std::sync::Arc;
+
+pub const CONTRACT: &str = "fidc_completed_session_events_v1";
+pub const EVENTS: &[&str] = &[
+    "PRICE_CROSS_VWAP_UP",
+    "PRICE_CROSS_VWAP_DOWN",
+    "INTRADAY_HIGH_BREAKOUT",
+    "INTRADAY_LOW_BREAKDOWN",
+    "OPENING_RANGE_BREAKOUT_UP",
+    "OPENING_RANGE_BREAKOUT_DOWN",
+    "INTRADAY_VOLUME_SPIKE",
+    "MORNING_HIGH_BREAKOUT",
+    "MORNING_LOW_BREAKDOWN",
+    "AFTERNOON_MOMENTUM_UP",
+    "AFTERNOON_MOMENTUM_DOWN",
+    "LATE_SESSION_STRENGTH",
+    "LATE_SESSION_WEAKNESS",
+];
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct MinuteBar {
+    pub symbol: String,
+    pub timestamp: NaiveDateTime,
+    pub available_at: NaiveDateTime,
+    pub open: f64,
+    pub high: f64,
+    pub low: f64,
+    pub close: f64,
+    pub volume: f64,
+    pub amount: f64,
+}
+pub type BarStore = Arc<BTreeMap<(chrono::NaiveDate, String), Vec<MinuteBar>>>;
+pub fn bar_store(bars: Vec<MinuteBar>) -> Result<BarStore, String> {
+    let mut groups = BTreeMap::<(chrono::NaiveDate, String), Vec<MinuteBar>>::new();
+    for bar in bars {
+        groups
+            .entry((bar.timestamp.date(), bar.symbol.clone()))
+            .or_default()
+            .push(bar);
+    }
+    for rows in groups.values_mut() {
+        rows.sort_by_key(|r| r.timestamp);
+        if rows
+            .windows(2)
+            .any(|pair| pair[0].timestamp == pair[1].timestamp)
+        {
+            return Err("duplicate_completed_minute_bar".into());
+        }
+    }
+    Ok(Arc::new(groups))
+}
+fn f(name: &str) -> Expr {
+    Expr::Field { name: name.into() }
+}
+fn n(value: f64) -> Expr {
+    Expr::Number { value }
+}
+fn op(name: &str, args: Vec<Expr>, window: Option<usize>) -> Expr {
+    Expr::Operator {
+        name: name.into(),
+        args,
+        window,
+    }
+}
+fn time(minutes: u32) -> NaiveTime {
+    NaiveTime::from_hms_opt(minutes / 60, minutes % 60, 0).unwrap()
+}
+
+pub fn is_regular_label(t: NaiveTime) -> bool {
+    t.second() == 0 && (time(570) <= t && t <= time(690) || time(780) < t && t <= time(900))
+}
+
+pub fn expression(event: &str, p: &BTreeMap<String, Value>) -> Result<Expr, String> {
+    let cross = |up: bool, a: Expr, b: Expr| {
+        op(
+            if up { "CROSS_ABOVE" } else { "CROSS_BELOW" },
+            vec![a, b],
+            None,
+        )
+    };
+    Ok(match event {
+        "PRICE_CROSS_VWAP_UP" => cross(true, f("close"), f("session_vwap")),
+        "PRICE_CROSS_VWAP_DOWN" => cross(false, f("close"), f("session_vwap")),
+        "INTRADAY_HIGH_BREAKOUT" => op(
+            "GT",
+            vec![
+                f("close"),
+                op("LAG", vec![op("CUMMAX", vec![f("high")], None)], Some(1)),
+            ],
+            None,
+        ),
+        "INTRADAY_LOW_BREAKDOWN" => op(
+            "LT",
+            vec![
+                f("close"),
+                op("LAG", vec![op("CUMMIN", vec![f("low")], None)], Some(1)),
+            ],
+            None,
+        ),
+        "OPENING_RANGE_BREAKOUT_UP" => cross(true, f("close"), f("opening_high")),
+        "OPENING_RANGE_BREAKOUT_DOWN" => cross(false, f("close"), f("opening_low")),
+        "MORNING_HIGH_BREAKOUT" => cross(true, f("close"), f("morning_high")),
+        "MORNING_LOW_BREAKDOWN" => cross(false, f("close"), f("morning_low")),
+        "AFTERNOON_MOMENTUM_UP" => cross(true, f("afternoon_return"), n(0.)),
+        "AFTERNOON_MOMENTUM_DOWN" => cross(false, f("afternoon_return"), n(0.)),
+        "LATE_SESSION_STRENGTH" => cross(true, f("late_return"), n(0.)),
+        "LATE_SESSION_WEAKNESS" => cross(false, f("late_return"), n(0.)),
+        "INTRADAY_VOLUME_SPIKE" => op(
+            "GTE",
+            vec![
+                f("volume"),
+                op(
+                    "MUL",
+                    vec![
+                        op(
+                            "LAG",
+                            vec![op(
+                                "ROLLING_MEAN",
+                                vec![f("volume")],
+                                Some(p["volume_window"].as_u64().unwrap() as usize),
+                            )],
+                            Some(1),
+                        ),
+                        n(p["volume_multiple"].as_f64().unwrap()),
+                    ],
+                    None,
+                ),
+            ],
+            None,
+        ),
+        _ => return Err("session_event_not_registered".into()),
+    })
+}
+
+pub fn evaluate(
+    spec: &PatternSpec,
+    symbol: &str,
+    bars: &[MinuteBar],
+    decision: NaiveDateTime,
+) -> Result<PatternResult, String> {
+    let mut result = PatternResult {
+        symbol: symbol.into(),
+        name: None,
+        matched: false,
+        score: None,
+        checks: vec![],
+        values: json!({}),
+        anchor: Value::Null,
+        exclusion: None,
+    };
+    if bars.is_empty() {
+        return Err(format!(
+            "session_source_missing: {symbol} {}",
+            decision.date()
+        ));
+    }
+    let visible = bars
+        .iter()
+        .filter(|b| {
+            b.timestamp.date() == decision.date()
+                && b.timestamp < decision
+                && b.available_at <= decision
+        })
+        .collect::<Vec<_>>();
+    if visible.is_empty() {
+        result.exclusion = Some(json!({"reason":"session_before_first_completed_bar"}));
+        return Ok(result);
+    }
+    let last = visible.last().unwrap().timestamp;
+    let expected = (570..=690)
+        .chain(781..=900)
+        .map(|m| decision.date().and_time(time(m)))
+        .filter(|t| *t < decision)
+        .last();
+    if expected != Some(last) {
+        return Err(format!(
+            "session_latest_bar_missing: {symbol} expected={expected:?} actual={last}"
+        ));
+    }
+    let mut indexed = BTreeMap::new();
+    for b in &visible {
+        if b.symbol != symbol
+            || !is_regular_label(b.timestamp.time())
+            || b.available_at < b.timestamp
+            || [b.open, b.high, b.low, b.close, b.volume, b.amount]
+                .iter()
+                .any(|v| !v.is_finite())
+            || b.low <= 0.
+            || b.open <= 0.
+            || b.close <= 0.
+            || b.high < b.open.max(b.close)
+            || b.low > b.open.min(b.close)
+            || b.volume < 0.
+            || b.amount < 0.
+            || indexed.insert(b.timestamp, b).is_some()
+        {
+            return Err(format!("session_bar_invalid: {symbol} {}", b.timestamp));
+        }
+    }
+    for minute in (571..=690).chain(781..=900) {
+        let stamp = decision.date().and_time(time(minute));
+        if stamp <= last && !indexed.contains_key(&stamp) {
+            return Err(format!(
+                "session_bar_gap: {symbol} {stamp}; no filling or calendar compression"
+            ));
+        }
+    }
+    let opening_end = time(570 + spec.n("opening_minutes") as u32);
+    let (mut volume, mut amount) = (0., 0.);
+    let (mut opening_high, mut opening_low) = (f64::NEG_INFINITY, f64::INFINITY);
+    let (mut morning_high, mut morning_low) = (f64::NEG_INFINITY, f64::INFINITY);
+    let (mut morning_close, mut late_close) = (None, None);
+    let mut fields: BTreeMap<String, Vec<Option<f64>>> = [
+        "open",
+        "high",
+        "low",
+        "close",
+        "volume",
+        "amount",
+        "session_vwap",
+        "opening_high",
+        "opening_low",
+        "morning_high",
+        "morning_low",
+        "afternoon_return",
+        "late_return",
+    ]
+    .into_iter()
+    .map(|s| (s.into(), vec![]))
+    .collect();
+    let mut timestamps = vec![];
+    let mut available_at = vec![];
+    let zone = FixedOffset::east_opt(8 * 3600).unwrap();
+    for b in indexed.values() {
+        let t = b.timestamp.time();
+        volume += b.volume;
+        amount += b.amount;
+        if t <= opening_end {
+            opening_high = opening_high.max(b.high);
+            opening_low = opening_low.min(b.low);
+        }
+        if t <= time(690) {
+            morning_high = morning_high.max(b.high);
+            morning_low = morning_low.min(b.low);
+        }
+        if t == time(690) {
+            morning_close = Some(b.close);
+        }
+        if t == time(870) {
+            late_close = Some(b.close);
+        }
+        for (name, value) in [
+            ("open", Some(b.open)),
+            ("high", Some(b.high)),
+            ("low", Some(b.low)),
+            ("close", Some(b.close)),
+            ("volume", Some(b.volume)),
+            ("amount", Some(b.amount)),
+            ("session_vwap", (volume > 0.).then_some(amount / volume)),
+            ("opening_high", (t >= opening_end).then_some(opening_high)),
+            ("opening_low", (t >= opening_end).then_some(opening_low)),
+            ("morning_high", (t >= time(690)).then_some(morning_high)),
+            ("morning_low", (t >= time(690)).then_some(morning_low)),
+            ("afternoon_return", morning_close.map(|v| b.close / v - 1.)),
+            ("late_return", late_close.map(|v| b.close / v - 1.)),
+        ] {
+            fields.get_mut(name).unwrap().push(value);
+        }
+        timestamps.push(zone.from_local_datetime(&b.timestamp).single().unwrap());
+        available_at.push(zone.from_local_datetime(&b.available_at).single().unwrap());
+    }
+    let frame = Frame {
+        symbol: symbol.into(),
+        frequency: "1m".into(),
+        decision_at: zone.from_local_datetime(&decision).single().unwrap(),
+        timestamps,
+        available_at,
+        fields,
+    };
+    let event = spec
+        .session_event
+        .as_deref()
+        .ok_or("session_event_id_required")?;
+    let values = crate::factor_events::evaluate(&expression(event, &spec.parameters)?, &frame)?;
+    let latest = values.values.last().copied().flatten();
+    result.score = latest;
+    result.matched = latest == Some(1.);
+    result.values = json!({"session_event":event,"session_contract":CONTRACT,"expression":values,"signal_bar_end":last,"decision_at":decision,"bars":visible.len(),"bar_times":frame.timestamps.iter().map(|t|t.format("%Y-%m-%dT%H:%M:%S").to_string()).collect::<Vec<_>>(),"close":visible.last().unwrap().close,"session_return":visible.last().unwrap().close/visible.first().unwrap().open-1.,"price_policy":"same_session_raw_ohlcv"});
+    if latest.is_none() {
+        result.exclusion = Some(json!({"reason":"session_warmup_or_undefined"}));
+    } else {
+        result.checks.push(json!({"label":"分钟事件","actual":latest,"operator":"==","threshold":1,"passed":result.matched}));
+    }
+    Ok(result)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    fn spec(event: &str) -> PatternSpec {
+        serde_json::from_value::<PatternSpec>(
+            json!({"template":"session_event","session_event":event,"parameters":{}}),
+        )
+        .unwrap()
+        .validate()
+        .unwrap()
+    }
+    fn bars() -> Vec<MinuteBar> {
+        let date = chrono::NaiveDate::from_ymd_opt(2026, 9, 8).unwrap();
+        (570..=690)
+            .chain(781..=900)
+            .enumerate()
+            .map(|(i, m)| {
+                let timestamp = date.and_time(time(m));
+                let price = 100. + (i % 17) as f64 / 10.;
+                let volume = if i % 39 == 0 { 1000. } else { 100. };
+                MinuteBar {
+                    symbol: "300395.SZ".into(),
+                    timestamp,
+                    available_at: timestamp,
+                    open: price,
+                    high: price + 0.1,
+                    low: price - 0.1,
+                    close: price,
+                    volume,
+                    amount: volume * price,
+                }
+            })
+            .collect()
+    }
+    #[test]
+    fn all_thirteen_events_return_native_boolean_series() {
+        let bars = bars();
+        let decision = "2026-09-08T15:00:01".parse().unwrap();
+        for event in EVENTS {
+            let value = evaluate(&spec(event), "300395.SZ", &bars, decision).unwrap();
+            assert!(value.score.is_some(), "{event}");
+            assert_eq!(value.values["expression"]["value_type"], "boolean");
+        }
+    }
+    #[test]
+    fn decision_uses_the_previous_completed_label_and_future_prices_do_not_rewrite() {
+        let mut bars = bars();
+        let decision = "2026-09-08T10:02:00".parse().unwrap();
+        for event in EVENTS {
+            let before = evaluate(&spec(event), "300395.SZ", &bars, decision).unwrap();
+            for bar in &mut bars {
+                if bar.timestamp >= decision {
+                    bar.open = 1000.;
+                    bar.close = 1000.;
+                    bar.high = 1001.;
+                    bar.low = 999.;
+                }
+            }
+            let after = evaluate(&spec(event), "300395.SZ", &bars, decision).unwrap();
+            assert_eq!(before.values, after.values);
+            assert_eq!(after.values["signal_bar_end"], "2026-09-08T10:01:00");
+        }
+    }
+    #[test]
+    fn gaps_and_stale_last_bars_do_not_become_false_or_repeated_signals() {
+        let mut values = bars();
+        let decision = "2026-09-08T10:02:00".parse().unwrap();
+        values.retain(|r| r.timestamp.time() != time(600));
+        assert!(evaluate(&spec(EVENTS[0]), "300395.SZ", &values, decision)
+            .unwrap_err()
+            .contains("session_bar_gap"));
+        let stale = bars()
+            .into_iter()
+            .filter(|r| r.timestamp.time() < time(601))
+            .collect::<Vec<_>>();
+        assert!(evaluate(&spec(EVENTS[0]), "300395.SZ", &stale, decision)
+            .unwrap_err()
+            .contains("latest_bar_missing"));
+    }
+    #[test]
+    fn opening_range_is_unavailable_before_the_range_has_completed() {
+        let value = evaluate(
+            &spec("OPENING_RANGE_BREAKOUT_UP"),
+            "300395.SZ",
+            &bars(),
+            "2026-09-08T09:59:01".parse().unwrap(),
+        )
+        .unwrap();
+        assert_eq!(value.score, None);
+        assert!(!value.matched);
+    }
+}