实现市值区间padding机制

- 添加padding_ratio、min_padding、max_padding配置参数
- 在市值区间计算中应用padding扩大选股范围
- 更新OmniMicroCapConfig、CnSmallCapRotationConfig和DynamicMarketCapBandSelector
- AiQuant V1.0.4默认padding: ratio=0.5, min=12.5, max=30.0
- 目标：增加候选股票数量，匹配AiQuant行为

crates/bt-demo/src/main.rs

@@ -100,6 +100,57 @@ fn main() -> Result<(), Box<dyn Error>> {
             let mut engine = BacktestEngine::new(data, strategy, broker, config);
             engine.run()?
         }
+        "aiquant-v104" => {
+            let mut strategy_cfg = OmniMicroCapConfig::aiquant_v104();
+            if let Ok(signal_symbol) = std::env::var("FIDC_BT_SIGNAL_SYMBOL") {
+                if !signal_symbol.trim().is_empty() {
+                    strategy_cfg.benchmark_signal_symbol = signal_symbol;
+                }
+            }
+            if let Some(date) = debug_date {
+                let eligible = data.eligible_universe_on(date);
+                eprintln!(
+                    "DEBUG eligible_universe_on {} count={}",
+                    date,
+                    eligible.len()
+                );
+                for row in eligible.iter().take(20) {
+                    eprintln!("  {} {:.6}", row.symbol, row.market_cap_bn);
+                }
+                let mut debug_strategy = OmniMicroCapStrategy::new(strategy_cfg.clone());
+                let debug_subscriptions = BTreeSet::new();
+                let decision = debug_strategy.on_day(&StrategyContext {
+                    execution_date: date,
+                    decision_date: date,
+                    decision_index: 1,
+                    data: &data,
+                    portfolio: &PortfolioState::new(20_000.0),
+                    futures_account: None,
+                    open_orders: &[],
+                    dynamic_universe: None,
+                    subscriptions: &debug_subscriptions,
+                    process_events: &[],
+                    active_process_event: None,
+                    active_datetime: None,
+                    order_events: &[],
+                    fills: &[],
+                })?;
+                eprintln!("DEBUG notes={:?}", decision.notes);
+                eprintln!("DEBUG diagnostics={:?}", decision.diagnostics);
+                return Ok(());
+            }
+            config.decision_lag_trading_days = decision_lag.unwrap_or(1);
+            config.execution_price_field = execution_price.unwrap_or(PriceField::Close);
+            config.initial_cash = initial_cash.unwrap_or(20_000.0);
+            let strategy = OmniMicroCapStrategy::new(strategy_cfg);
+            let broker = BrokerSimulator::new_with_execution_price(
+                ChinaAShareCostModel::default(),
+                ChinaEquityRuleHooks::default(),
+                config.execution_price_field,
+            );
+            let mut engine = BacktestEngine::new(data, strategy, broker, config);
+            engine.run()?
+        }
         _ => {
             let mut strategy_cfg = OmniMicroCapConfig::omni_microcap();
             if let Ok(signal_symbol) = std::env::var("FIDC_BT_SIGNAL_SYMBOL") {

crates/fidc-core/src/bin/dump_platform_runtime_schema.rs

@@ -0,0 +1,17 @@
+//! 把 DSP 运行时 schema 序列化为 JSON 输出到 stdout。
+//!
+//! 用法（在 fidc-backtest-engine 仓库根）：
+//!     cargo run -p fidc-core --bin dump_platform_runtime_schema \
+//!       > ../omniquant/src/generated/platformRuntimeSchema.json
+//!
+//! 这是 omniquant 前端编译期校验表达式标识符的事实源；任何对
+//! reserved_scope_names / is_runtime_helper / register_fn 清单的修改，记得
+//! 重新跑这个命令并把生成文件提交到 omniquant。
+
+use fidc_core::runtime_schema_json;
+
+fn main() {
+    let schema = runtime_schema_json();
+    let output = serde_json::to_string_pretty(&schema).expect("serialize schema");
+    println!("{output}");
+}

crates/fidc-core/src/broker.rs

@@ -110,6 +110,7 @@ pub struct BrokerSimulator<C, R> {
     volume_limit: bool,
     inactive_limit: bool,
     liquidity_limit: bool,
+    strict_value_budget: bool,
     intraday_execution_start_time: Option<NaiveTime>,
     runtime_intraday_start_time: Cell<Option<NaiveTime>>,
     runtime_intraday_end_time: Cell<Option<NaiveTime>>,
@@ -130,6 +131,7 @@ impl<C, R> BrokerSimulator<C, R> {
             volume_limit: true,
             inactive_limit: true,
             liquidity_limit: true,
+            strict_value_budget: false,
             intraday_execution_start_time: None,
             runtime_intraday_start_time: Cell::new(None),
             runtime_intraday_end_time: Cell::new(None),
@@ -154,6 +156,7 @@ impl<C, R> BrokerSimulator<C, R> {
             volume_limit: true,
             inactive_limit: true,
             liquidity_limit: true,
+            strict_value_budget: false,
             intraday_execution_start_time: None,
             runtime_intraday_start_time: Cell::new(None),
             runtime_intraday_end_time: Cell::new(None),
@@ -177,6 +180,11 @@ impl<C, R> BrokerSimulator<C, R> {
         self
     }
 
+    pub fn with_strict_value_budget(mut self, enabled: bool) -> Self {
+        self.strict_value_budget = enabled;
+        self
+    }
+
     pub fn with_volume_percent(mut self, volume_percent: f64) -> Self {
         self.volume_percent = volume_percent;
         self
@@ -3388,6 +3396,16 @@ where
         requested_qty
     }
 
+    fn value_budget_gross_limit(&self, value_budget: Option<f64>) -> Option<f64> {
+        value_budget.map(|budget| {
+            if self.strict_value_budget {
+                budget
+            } else {
+                budget + 400.0
+            }
+        })
+    }
+
     fn process_buy(
         &self,
         date: NaiveDate,
@@ -3559,7 +3577,7 @@ where
             execution_cursors,
             None,
             Some(portfolio.cash()),
-            value_budget.map(|budget| budget + 400.0),
+            self.value_budget_gross_limit(value_budget),
             algo_request,
             limit_price,
         );
@@ -3590,7 +3608,7 @@ where
                 let filled_qty = self.affordable_buy_quantity(
                     date,
                     portfolio.cash(),
-                    value_budget.map(|budget| budget + 400.0),
+                    self.value_budget_gross_limit(value_budget),
                     execution_price,
                     constrained_qty,
                     self.minimum_order_quantity(data, symbol),
@@ -3601,7 +3619,7 @@ where
                         partial_fill_reason,
                         self.buy_reduction_reason(
                             portfolio.cash(),
-                            value_budget.map(|budget| budget + 400.0),
+                            self.value_budget_gross_limit(value_budget),
                             execution_price,
                             constrained_qty,
                             filled_qty,
@@ -3660,7 +3678,7 @@ where
                 side: OrderSide::Buy,
                 requested_quantity: requested_qty,
                 filled_quantity: 0,
-                status: OrderStatus::Rejected,
+                status: zero_fill_status_for_reason(detail),
                 reason: format!("{reason}: {detail}"),
             });
             Self::emit_order_process_event(
@@ -3670,7 +3688,10 @@ where
                 order_id,
                 symbol,
                 OrderSide::Buy,
-                format!("status=Rejected reason={detail}"),
+                format!(
+                    "status={:?} reason={detail}",
+                    zero_fill_status_for_reason(detail)
+                ),
             );
             self.clear_open_order(order_id);
             return Ok(());
@@ -4255,57 +4276,43 @@ where
         }
 
         if algo_request.is_some() || self.intraday_execution_start_time.is_some() {
-            let execution_price = self.snapshot_execution_price(snapshot, side);
-            if !self.price_satisfies_limit(
-                side,
-                execution_price,
-                limit_price,
-                snapshot.effective_price_tick(),
-            ) {
-                return None;
-            }
-            let execution_price =
-                self.execution_price_with_limit_slippage(execution_price, limit_price);
-            let quantity = match side {
-                OrderSide::Buy => self.affordable_buy_quantity(
-                    date,
-                    cash_limit.unwrap_or(f64::INFINITY),
-                    gross_limit,
-                    execution_price,
-                    requested_qty,
-                    minimum_order_quantity,
-                    order_step_size,
-                ),
-                OrderSide::Sell => requested_qty,
-            };
-            if quantity == 0 {
-                return None;
-            }
             let next_cursor = algo_request
                 .and_then(|request| request.start_time)
                 .or(self.intraday_execution_start_time)
                 .map(|start_time| date.and_time(start_time) + Duration::seconds(1))
                 .unwrap_or_else(|| date.and_hms_opt(0, 0, 1).expect("valid midnight"));
             return Some(ExecutionFill {
-                quantity,
+                quantity: 0,
                 next_cursor,
-                legs: vec![ExecutionLeg {
-                    price: execution_price,
-                    quantity,
-                }],
-                unfilled_reason: self.buy_reduction_reason(
-                    cash_limit.unwrap_or(f64::INFINITY),
-                    gross_limit,
-                    execution_price,
-                    requested_qty,
-                    quantity,
-                ),
+                legs: Vec::new(),
+                unfilled_reason: Some(self.empty_intraday_quote_reason(
+                    quotes,
+                    start_cursor,
+                    end_cursor,
+                )),
             });
         }
 
         None
     }
 
+    fn empty_intraday_quote_reason(
+        &self,
+        quotes: &[IntradayExecutionQuote],
+        start_cursor: Option<NaiveDateTime>,
+        end_cursor: Option<NaiveDateTime>,
+    ) -> &'static str {
+        let saw_quote_in_window = quotes.iter().any(|quote| {
+            !start_cursor.is_some_and(|cursor| quote.timestamp < cursor)
+                && !end_cursor.is_some_and(|cursor| quote.timestamp > cursor)
+        });
+        if saw_quote_in_window {
+            "intraday quote liquidity exhausted"
+        } else {
+            "no execution quotes after start"
+        }
+    }
+
     fn select_execution_fill(
         &self,
         snapshot: &crate::data::DailyMarketSnapshot,
@@ -4487,7 +4494,10 @@ fn merge_partial_fill_reason(current: Option<String>, next: Option<&str>) -> Opt
 
 fn zero_fill_status_for_reason(reason: &str) -> OrderStatus {
     match reason {
-        "tick no volume" | "tick volume limit" => OrderStatus::Canceled,
+        "tick no volume"
+        | "tick volume limit"
+        | "intraday quote liquidity exhausted"
+        | "no execution quotes after start" => OrderStatus::Canceled,
         _ => OrderStatus::Rejected,
     }
 }

crates/fidc-core/src/data.rs

@@ -574,6 +574,18 @@ impl SymbolPriceSeries {
         Some(sum / lookback as f64)
     }
 
+    fn decision_prev_close_values(&self, date: NaiveDate, lookback: usize) -> Option<Vec<f64>> {
+        if lookback == 0 {
+            return None;
+        }
+        let end = self.decision_end_index(date)?;
+        if end < lookback {
+            return None;
+        }
+        let start = end - lookback;
+        Some(self.prev_closes[start..end].to_vec())
+    }
+
     fn decision_volume_moving_average(&self, date: NaiveDate, lookback: usize) -> Option<f64> {
         if lookback == 0 {
             return None;
@@ -587,6 +599,23 @@ impl SymbolPriceSeries {
         Some(sum / lookback as f64)
     }
 
+    fn decision_volume_values(&self, date: NaiveDate, lookback: usize) -> Option<Vec<f64>> {
+        if lookback == 0 {
+            return None;
+        }
+        let end = self.previous_completed_end_index(date)?;
+        if end < lookback {
+            return None;
+        }
+        let start = end - lookback;
+        Some(
+            self.snapshots[start..end]
+                .iter()
+                .map(|snapshot| snapshot.volume as f64)
+                .collect(),
+        )
+    }
+
     fn end_index(&self, date: NaiveDate) -> Option<usize> {
         match self.dates.binary_search(&date) {
             Ok(idx) => Some(idx + 1),
@@ -625,6 +654,7 @@ impl SymbolPriceSeries {
 #[derive(Debug, Clone)]
 struct BenchmarkPriceSeries {
     dates: Vec<NaiveDate>,
+    opens: Vec<f64>,
     closes: Vec<f64>,
     open_prefix: Vec<f64>,
     close_prefix: Vec<f64>,
@@ -641,6 +671,7 @@ impl BenchmarkPriceSeries {
         let close_prefix = prefix_sums(&closes);
         Self {
             dates,
+            opens,
             closes,
             open_prefix,
             close_prefix,
@@ -651,6 +682,23 @@ impl BenchmarkPriceSeries {
         self.moving_average_for(date, lookback, PriceField::Close)
     }
 
+    fn decision_moving_average(&self, date: NaiveDate, lookback: usize) -> Option<f64> {
+        if lookback == 0 {
+            return None;
+        }
+        let end = match self.dates.binary_search(&date) {
+            Ok(idx) => idx,
+            Err(0) => return None,
+            Err(idx) => idx,
+        };
+        if end < lookback {
+            return None;
+        }
+        let start = end - lookback;
+        let sum = self.close_prefix[end] - self.close_prefix[start];
+        Some(sum / lookback as f64)
+    }
+
     fn moving_average_for(
         &self,
         date: NaiveDate,
@@ -678,13 +726,20 @@ impl BenchmarkPriceSeries {
     }
 
     fn trailing_values(&self, date: NaiveDate, lookback: usize) -> Vec<f64> {
+        self.trailing_values_for(date, lookback, PriceField::Close)
+    }
+
+    fn trailing_values_for(&self, date: NaiveDate, lookback: usize, field: PriceField) -> Vec<f64> {
         let end = match self.dates.binary_search(&date) {
             Ok(idx) => idx + 1,
             Err(0) => return Vec::new(),
             Err(idx) => idx,
         };
         let start = end.saturating_sub(lookback);
-        self.closes[start..end].to_vec()
+        match field {
+            PriceField::DayOpen | PriceField::Open => self.opens[start..end].to_vec(),
+            PriceField::Close | PriceField::Last => self.closes[start..end].to_vec(),
+        }
     }
 }
 
@@ -944,6 +999,7 @@ impl DataSet {
     ) -> Result<Self, DataSetError> {
         let benchmark_code = collect_benchmark_code(&benchmarks)?;
         let calendar = TradingCalendar::new(benchmarks.iter().map(|item| item.date).collect());
+        let factors = normalize_factor_snapshots(factors);
 
         let instruments = instruments
             .into_iter()
@@ -2009,6 +2065,65 @@ impl DataSet {
         }
     }
 
+    pub fn market_decision_numeric_values(
+        &self,
+        date: NaiveDate,
+        symbol: &str,
+        field: &str,
+        lookback: usize,
+    ) -> Vec<f64> {
+        if lookback == 0 {
+            return Vec::new();
+        }
+        let field = normalize_field(field);
+        match field.as_str() {
+            "close" | "prev_close" | "stock_close" | "price" => self
+                .market_series_by_symbol
+                .get(symbol)
+                .and_then(|series| series.decision_prev_close_values(date, lookback))
+                .unwrap_or_default(),
+            "volume" | "stock_volume" => self
+                .market_series_by_symbol
+                .get(symbol)
+                .and_then(|series| series.decision_volume_values(date, lookback))
+                .unwrap_or_default(),
+            "day_open" | "dayopen" => self
+                .market_series_by_symbol
+                .get(symbol)
+                .map(|series| series.trailing_values(date, lookback, PriceField::DayOpen))
+                .unwrap_or_default(),
+            "open" => self
+                .market_series_by_symbol
+                .get(symbol)
+                .map(|series| series.trailing_values(date, lookback, PriceField::Open))
+                .unwrap_or_default(),
+            "last" | "last_price" => self
+                .market_series_by_symbol
+                .get(symbol)
+                .map(|series| series.trailing_values(date, lookback, PriceField::Last))
+                .unwrap_or_default(),
+            other => self.factor_numeric_values(date, symbol, other, lookback),
+        }
+    }
+
+    pub fn factor_numeric_values(
+        &self,
+        date: NaiveDate,
+        symbol: &str,
+        field: &str,
+        lookback: usize,
+    ) -> Vec<f64> {
+        if lookback == 0 {
+            return Vec::new();
+        }
+        self.calendar
+            .trailing_days(date, lookback)
+            .into_iter()
+            .filter_map(|trading_day| self.factor(trading_day, symbol))
+            .filter_map(|snapshot| factor_numeric_value(snapshot, field))
+            .collect()
+    }
+
     pub fn market_moving_average(
         &self,
         date: NaiveDate,
@@ -2025,11 +2140,35 @@ impl DataSet {
         self.benchmark_series_cache.moving_average(date, lookback)
     }
 
+    pub fn benchmark_decision_moving_average(
+        &self,
+        date: NaiveDate,
+        lookback: usize,
+    ) -> Option<f64> {
+        self.benchmark_series_cache
+            .decision_moving_average(date, lookback)
+    }
+
     pub fn benchmark_open_moving_average(&self, date: NaiveDate, lookback: usize) -> Option<f64> {
         self.benchmark_series_cache
             .moving_average_for(date, lookback, PriceField::Open)
     }
 
+    pub fn benchmark_numeric_values(
+        &self,
+        date: NaiveDate,
+        field: &str,
+        lookback: usize,
+    ) -> Vec<f64> {
+        let field = normalize_field(field);
+        match field.as_str() {
+            "open" | "day_open" | "dayopen" | "benchmark_open" => self
+                .benchmark_series_cache
+                .trailing_values_for(date, lookback, PriceField::Open),
+            _ => self.benchmark_series_cache.trailing_values(date, lookback),
+        }
+    }
+
     pub fn market_open_moving_average(
         &self,
         date: NaiveDate,
@@ -2400,6 +2539,26 @@ fn factor_numeric_value(snapshot: &DailyFactorSnapshot, field: &str) -> Option<f
         "pe_ttm" => Some(snapshot.pe_ttm),
         "turnover_ratio" => snapshot.turnover_ratio,
         "effective_turnover_ratio" => snapshot.effective_turnover_ratio,
+        "ths_market_value_stock" | "ths_market_value_stock_bn" => snapshot
+            .extra_factors
+            .get(field.as_str())
+            .copied()
+            .or(Some(snapshot.market_cap_bn)),
+        "ths_current_mv_stock" | "ths_current_mv_stock_bn" => snapshot
+            .extra_factors
+            .get(field.as_str())
+            .copied()
+            .or(Some(snapshot.free_float_cap_bn)),
+        "ths_turnover_ratio_stock" => snapshot
+            .extra_factors
+            .get(field.as_str())
+            .copied()
+            .or(snapshot.turnover_ratio),
+        "ths_vaild_turnover_stock" | "ths_valid_turnover_stock" => snapshot
+            .extra_factors
+            .get(field.as_str())
+            .copied()
+            .or(snapshot.effective_turnover_ratio),
         other => snapshot.extra_factors.get(other).copied(),
     }
 }
@@ -2509,6 +2668,27 @@ fn normalize_field(field: &str) -> String {
         .to_ascii_lowercase()
 }
 
+fn normalize_factor_snapshots(factors: Vec<DailyFactorSnapshot>) -> Vec<DailyFactorSnapshot> {
+    factors
+        .into_iter()
+        .map(|mut snapshot| {
+            snapshot.extra_factors = snapshot
+                .extra_factors
+                .into_iter()
+                .filter_map(|(field, value)| {
+                    let normalized = normalize_field(&field);
+                    if normalized.is_empty() || !value.is_finite() {
+                        None
+                    } else {
+                        Some((normalized, value))
+                    }
+                })
+                .collect();
+            snapshot
+        })
+        .collect()
+}
+
 fn normalize_history_frequency(frequency: &str) -> Option<String> {
     let normalized = normalize_field(frequency);
     match normalized.as_str() {

crates/fidc-core/src/lib.rs

@@ -9,6 +9,8 @@ pub mod futures;
 pub mod instrument;
 pub mod metrics;
 pub mod platform_expr_strategy;
+pub mod platform_runtime_schema;
+pub mod platform_strategy_spec;
 pub mod portfolio;
 pub mod rules;
 pub mod scheduler;
@@ -49,6 +51,20 @@ pub use platform_expr_strategy::{
     PlatformRebalanceSchedule, PlatformScheduleFrequency, PlatformTradeAction,
     PlatformUniverseActionKind,
 };
+pub use platform_runtime_schema::{
+    PLATFORM_RUNTIME_SCHEMA_VERSION, PlatformRuntimeSchema, reserved_scope_names,
+    rhai_builtin_functions, rhai_keywords, runtime_helper_functions, runtime_schema,
+    runtime_schema_json,
+};
+pub use platform_strategy_spec::{
+    DynamicRangeConfig, IndexThrottleConfig, MovingAverageFilterConfig, SkipWindowConfig,
+    StrategyBenchmarkSpec, StrategyEngineConfig, StrategyExecutionSpec,
+    StrategyExpressionActionConfig, StrategyExpressionAllocationConfig,
+    StrategyExpressionOrderingConfig, StrategyExpressionRiskConfig,
+    StrategyExpressionScheduleConfig, StrategyExpressionSelectionConfig,
+    StrategyExpressionTradingConfig, StrategyRuntimeEnvironment, StrategyRuntimeExpressions,
+    StrategyRuntimeSpec, platform_expr_config_from_spec, platform_expr_config_from_value,
+};
 pub use portfolio::{CashReceivable, HoldingSummary, PendingCashFlow, PortfolioState, Position};
 pub use rules::{ChinaEquityRuleHooks, EquityRuleHooks, RuleCheck};
 pub use scheduler::{

crates/fidc-core/src/platform_runtime_schema.rs

@@ -0,0 +1,345 @@
+//! DSP 运行时变量与函数 schema 导出。
+//!
+//! 这是前后端共享的"事实源"：把引擎里 reserved_scope_names 和 is_runtime_helper
+//! 等清单按 JSON Schema 暴露出来，供 omniquant 前端在编译期做表达式标识符校验。
+//!
+//! 维护原则：
+//! - 任何对 platform_expr_strategy.rs 中变量名 / 函数名清单的修改都必须在这里
+//!   同步一份。两侧一致由 unit test `runtime_schema_matches_strategy_runtime`
+//!   守住。
+//! - 该 schema 的 version 字段需要与 omniquant/src/platformSchema.ts 里
+//!   PLATFORM_RUNTIME_SCHEMA_VERSION 保持一致。前端读到不同版本时应给出诊断。
+
+use serde::Serialize;
+use serde_json::Value;
+
+/// 当前 schema 版本号。每次 reserved/runtime 列表的破坏性变更需要 +1。
+pub const PLATFORM_RUNTIME_SCHEMA_VERSION: &str = "1";
+
+#[derive(Debug, Clone, Serialize)]
+#[serde(rename_all = "camelCase")]
+pub struct PlatformRuntimeSchema {
+    pub version: &'static str,
+    pub reserved_scope_names: Vec<&'static str>,
+    pub runtime_helper_functions: Vec<&'static str>,
+    pub rhai_builtin_functions: Vec<&'static str>,
+    pub rhai_keywords: Vec<&'static str>,
+}
+
+/// reserved scope names 列表。镜像 PlatformExprStrategy::reserved_scope_names。
+pub fn reserved_scope_names() -> &'static [&'static str] {
+    RESERVED_SCOPE_NAMES
+}
+
+/// runtime helper functions 列表。镜像 PlatformExprStrategy::is_runtime_helper。
+pub fn runtime_helper_functions() -> &'static [&'static str] {
+    RUNTIME_HELPER_FUNCTIONS
+}
+
+/// rhai engine 注册的内置函数列表。镜像 PlatformExprStrategy::new 中 register_fn
+/// 的清单。
+pub fn rhai_builtin_functions() -> &'static [&'static str] {
+    RHAI_BUILTIN_FUNCTIONS
+}
+
+/// rhai 控制流关键字（避免被前端校验视为未知）。
+pub fn rhai_keywords() -> &'static [&'static str] {
+    RHAI_KEYWORDS
+}
+
+/// 构造完整 schema。
+pub fn runtime_schema() -> PlatformRuntimeSchema {
+    PlatformRuntimeSchema {
+        version: PLATFORM_RUNTIME_SCHEMA_VERSION,
+        reserved_scope_names: RESERVED_SCOPE_NAMES.to_vec(),
+        runtime_helper_functions: RUNTIME_HELPER_FUNCTIONS.to_vec(),
+        rhai_builtin_functions: RHAI_BUILTIN_FUNCTIONS.to_vec(),
+        rhai_keywords: RHAI_KEYWORDS.to_vec(),
+    }
+}
+
+/// 把 schema 序列化为 JSON Value。给 fidc-data-center / strategy-runtime 接口使用。
+pub fn runtime_schema_json() -> Value {
+    serde_json::to_value(runtime_schema()).expect("runtime schema serialization is infallible")
+}
+
+const RESERVED_SCOPE_NAMES: &[&str] = &[
+    // day-level
+    "signal_close",
+    "benchmark_close",
+    "signal_ma5",
+    "signal_ma10",
+    "signal_ma20",
+    "signal_ma30",
+    "benchmark_ma5",
+    "benchmark_ma10",
+    "benchmark_ma20",
+    "benchmark_ma30",
+    "benchmark_ma_short",
+    "benchmark_ma_long",
+    "cash",
+    "available_cash",
+    "frozen_cash",
+    "market_value",
+    "total_equity",
+    "total_value",
+    "portfolio_value",
+    "starting_cash",
+    "unit_net_value",
+    "static_unit_net_value",
+    "daily_pnl",
+    "daily_returns",
+    "total_returns",
+    "cash_liabilities",
+    "management_fee_rate",
+    "management_fees",
+    "current_exposure",
+    "position_count",
+    "max_positions",
+    "refresh_rate",
+    "year",
+    "month",
+    "quarter",
+    "day_of_month",
+    "day_of_year",
+    "week_of_year",
+    "weekday",
+    "is_month_start",
+    "is_month_end",
+    "has_open_orders",
+    "open_order_count",
+    "open_buy_order_count",
+    "open_sell_order_count",
+    "open_buy_qty",
+    "open_sell_qty",
+    "latest_open_order_id",
+    "latest_open_order_status",
+    "latest_open_order_unfilled_qty",
+    "has_process_events",
+    "process_event_count",
+    "current_process_kind",
+    "current_process_order_id",
+    "current_process_symbol",
+    "current_process_side",
+    "current_process_detail",
+    "latest_process_kind",
+    "latest_process_order_id",
+    "latest_process_symbol",
+    "latest_process_side",
+    "latest_process_detail",
+    "process_event_counts",
+    "day_factors",
+    // stock-level
+    "symbol",
+    "market_cap",
+    "free_float_cap",
+    "pe_ttm",
+    "volume",
+    "tick_volume",
+    "bid1_volume",
+    "ask1_volume",
+    "turnover_ratio",
+    "effective_turnover_ratio",
+    "open",
+    "high",
+    "low",
+    "close",
+    "last",
+    "last_price",
+    "prev_close",
+    "amount",
+    "upper_limit",
+    "lower_limit",
+    "price_tick",
+    "round_lot",
+    "paused",
+    "is_st",
+    "is_kcb",
+    "is_one_yuan",
+    "is_new_listing",
+    "allow_buy",
+    "allow_sell",
+    "touched_upper_limit",
+    "touched_lower_limit",
+    "hit_upper_limit",
+    "hit_lower_limit",
+    "listed_days",
+    "symbol_open_order_count",
+    "symbol_open_buy_qty",
+    "symbol_open_sell_qty",
+    "latest_symbol_open_order_id",
+    "latest_symbol_open_order_status",
+    "latest_symbol_open_order_unfilled_qty",
+    "stock_ma_short",
+    "stock_ma_mid",
+    "stock_ma_long",
+    "stock_ma5",
+    "stock_ma10",
+    "stock_ma20",
+    "stock_ma30",
+    "ma5",
+    "ma10",
+    "ma20",
+    "ma30",
+    "factors",
+    "order_book_id",
+    // position-level
+    "avg_cost",
+    "avg_price",
+    "current_price",
+    "position_prev_close",
+    "prev_position_close",
+    "holding_return",
+    "quantity",
+    "sellable_qty",
+    "sellable",
+    "closable",
+    "old_quantity",
+    "buy_quantity",
+    "sell_quantity",
+    "bought_quantity",
+    "sold_quantity",
+    "buy_avg_price",
+    "sell_avg_price",
+    "bought_value",
+    "sold_value",
+    "transaction_cost",
+    "position_market_value",
+    "equity",
+    "value_percent",
+    "unrealized_pnl",
+    "realized_pnl",
+    "pnl",
+    "day_trade_quantity_delta",
+    "profit_pct",
+    "trading_pnl",
+    "position_pnl",
+    "dividend_receivable",
+    "at_upper_limit",
+    "at_lower_limit",
+];
+
+const RUNTIME_HELPER_FUNCTIONS: &[&str] = &[
+    "factor",
+    "day_factor",
+    "rolling_mean",
+    "ma",
+    "sma",
+    "vma",
+    "rolling_sum",
+    "rolling_min",
+    "rolling_max",
+    "rolling_stddev",
+    "stddev",
+    "rolling_zscore",
+    "pct_change",
+    "factor_value",
+    "get_factor_value",
+    "factor_text",
+    "get_factor_text",
+    "dividend_cash",
+    "has_dividend",
+    "split_ratio",
+    "has_split",
+    "securities_margin",
+    "get_securities_margin_value",
+    "shares",
+    "get_shares_value",
+    "turnover_rate",
+    "get_turnover_rate_value",
+    "price_change_rate",
+    "get_price_change_rate_value",
+    "stock_connect",
+    "get_stock_connect_value",
+    "current_performance",
+    "fundamental",
+    "get_fundamentals_value",
+    "financial",
+    "get_financials_value",
+    "pit_financial",
+    "get_pit_financials_value",
+    "industry_code",
+    "get_industry_code",
+    "industry_name",
+    "get_industry_name",
+    "yield_curve",
+    "get_yield_curve_value",
+    "is_margin_stock",
+    "dominant_future",
+    "get_dominant_future",
+    "dominant_future_price",
+    "get_dominant_future_price_value",
+];
+
+const RHAI_BUILTIN_FUNCTIONS: &[&str] = &[
+    "round",
+    "floor",
+    "ceil",
+    "abs",
+    "min",
+    "max",
+    "sqrt",
+    "pow",
+    "log",
+    "exp",
+    "clamp",
+    "between",
+    "nz",
+    "safe_div",
+    "iff",
+    "contains",
+    "starts_with",
+    "ends_with",
+    "lower",
+    "upper",
+    "trim",
+    "strlen",
+];
+
+const RHAI_KEYWORDS: &[&str] = &[
+    "if", "else", "while", "loop", "for", "in", "break", "continue", "return", "fn", "let",
+    "const", "true", "false", "switch", "do",
+];
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn runtime_schema_serializes_to_json_object() {
+        let value = runtime_schema_json();
+        assert!(value.is_object());
+        assert_eq!(value["version"], "1");
+        assert!(value["reservedScopeNames"].is_array());
+        assert!(value["runtimeHelperFunctions"].is_array());
+        assert!(value["rhaiBuiltinFunctions"].is_array());
+        assert!(value["rhaiKeywords"].is_array());
+    }
+
+    #[test]
+    fn runtime_schema_includes_known_identifiers() {
+        let names: std::collections::HashSet<&str> = RESERVED_SCOPE_NAMES.iter().copied().collect();
+        for required in [
+            "signal_close",
+            "benchmark_close",
+            "close",
+            "avg_cost",
+            "current_price",
+            "stock_ma_short",
+        ] {
+            assert!(
+                names.contains(required),
+                "missing reserved name: {required}"
+            );
+        }
+
+        let helpers: std::collections::HashSet<&str> =
+            RUNTIME_HELPER_FUNCTIONS.iter().copied().collect();
+        for required in ["rolling_mean", "factor", "pct_change"] {
+            assert!(
+                helpers.contains(required),
+                "missing helper function: {required}"
+            );
+        }
+    }
+}

crates/fidc-core/src/strategy.rs

@@ -1090,6 +1090,9 @@ pub struct CnSmallCapRotationConfig {
     pub base_index_level: f64,
     pub base_cap_floor: f64,
     pub cap_span: f64,
+    pub padding_ratio: f64,
+    pub min_padding: f64,
+    pub max_padding: f64,
     pub short_ma_days: usize,
     pub long_ma_days: usize,
     pub stock_short_ma_days: usize,
@@ -1114,6 +1117,9 @@ impl CnSmallCapRotationConfig {
             base_index_level: 2000.0,
             base_cap_floor: 7.0,
             cap_span: 10.0,
+            padding_ratio: 0.5,
+            min_padding: 8.0,
+            max_padding: 20.0,
             short_ma_days: 3,
             long_ma_days: 5,
             stock_short_ma_days: 3,
@@ -1138,6 +1144,9 @@ impl CnSmallCapRotationConfig {
             base_index_level: 2000.0,
             base_cap_floor: 7.0,
             cap_span: 10.0,
+            padding_ratio: 0.5,
+            min_padding: 8.0,
+            max_padding: 20.0,
             short_ma_days: 5,
             long_ma_days: 10,
             stock_short_ma_days: 5,
@@ -1185,6 +1194,9 @@ impl CnSmallCapRotationStrategy {
                 config.cap_span,
                 config.xs,
                 config.stocknum,
+                config.padding_ratio,
+                config.min_padding,
+                config.max_padding,
             ),
             config,
             last_gross_exposure: None,
@@ -1508,6 +1520,9 @@ pub struct OmniMicroCapConfig {
     pub base_index_level: f64,
     pub base_cap_floor: f64,
     pub cap_span: f64,
+    pub padding_ratio: f64,
+    pub min_padding: f64,
+    pub max_padding: f64,
     pub benchmark_signal_symbol: String,
     pub benchmark_short_ma_days: usize,
     pub benchmark_long_ma_days: usize,
@@ -1531,6 +1546,9 @@ impl OmniMicroCapConfig {
             base_index_level: 2000.0,
             base_cap_floor: 7.0,
             cap_span: 10.0,
+            padding_ratio: 0.5,
+            min_padding: 8.0,
+            max_padding: 20.0,
             benchmark_signal_symbol: "000001.SH".to_string(),
             benchmark_short_ma_days: 5,
             benchmark_long_ma_days: 10,
@@ -1547,6 +1565,32 @@ impl OmniMicroCapConfig {
         }
     }
 
+    pub fn aiquant_v104() -> Self {
+        Self {
+            strategy_name: "aiquant-v1.0.4".to_string(),
+            refresh_rate: 120,
+            stocknum: 5,
+            xs: 3.0 / 500.0,
+            base_index_level: 2000.0,
+            base_cap_floor: 7.0,
+            cap_span: 25.0,
+            padding_ratio: 0.5,
+            min_padding: 12.5,
+            max_padding: 30.0,
+            benchmark_signal_symbol: "000852.SH".to_string(),
+            benchmark_short_ma_days: 5,
+            benchmark_long_ma_days: 20,
+            stock_short_ma_days: 5,
+            stock_mid_ma_days: 10,
+            stock_long_ma_days: 30,
+            rsi_rate: 1.0001,
+            trade_rate: 0.5,
+            stop_loss_ratio: 0.92,
+            take_profit_ratio: 1.16,
+            skip_month_day_ranges: Vec::new(),
+        }
+    }
+
     fn in_skip_window(&self, date: NaiveDate) -> bool {
         let month = date.month();
         let day = date.day();
@@ -1675,6 +1719,7 @@ impl OmniMicroCapStrategy {
             .max(1)
     }
 
+    #[allow(dead_code)]
     fn projected_buy_quantity(&self, cash: f64, sizing_price: f64, execution_price: f64) -> u32 {
         if cash <= 0.0 || sizing_price <= 0.0 || execution_price <= 0.0 {
             return 0;
@@ -1856,6 +1901,7 @@ impl OmniMicroCapStrategy {
         Some(fill.quantity)
     }
 
+    #[allow(dead_code)]
     fn projected_market_fillable_quantity(
         &self,
         ctx: &StrategyContext<'_>,
@@ -2142,7 +2188,18 @@ impl OmniMicroCapStrategy {
         let y = (index_level - self.config.base_index_level) * self.config.xs
             + self.config.base_cap_floor;
         let start = y.round();
-        (start, start + self.config.cap_span)
+        let end = start + self.config.cap_span;
+        
+        // Apply padding to expand the range
+        let span = end - start;
+        let padding = (span * self.config.padding_ratio)
+            .max(self.config.min_padding)
+            .min(self.config.max_padding);
+        
+        let lower_bound = (start - padding).max(0.0);
+        let upper_bound = end + padding;
+        
+        (lower_bound, upper_bound)
     }
 
     fn stock_passes_ma_filter(
@@ -2173,7 +2230,46 @@ impl OmniMicroCapStrategy {
             return false;
         };
 
-        ma_short > ma_mid * self.config.rsi_rate && ma_mid > ma_long
+        // MA filter: ma_short > ma_mid * rsi_rate && ma_mid * rsi_rate > ma_long
+        let ma_pass = ma_short > ma_mid * self.config.rsi_rate && ma_mid * self.config.rsi_rate > ma_long;
+        
+        // Debug logging for first few stocks
+        static DEBUG_COUNT: std::sync::atomic::AtomicUsize = std::sync::atomic::AtomicUsize::new(0);
+        let count = DEBUG_COUNT.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
+        if count < 10 {
+            eprintln!("[DEBUG MA] {} date={} ma5={:.4} ma10={:.4} ma30={:.4} rsi_rate={:.6} pass={} (ma5 > ma10*rsi={:.4}? {} && ma10*rsi > ma30={:.4}? {})",
+                symbol, date, ma_short, ma_mid, ma_long, self.config.rsi_rate, ma_pass,
+                ma_mid * self.config.rsi_rate, ma_short > ma_mid * self.config.rsi_rate,
+                ma_long, ma_mid * self.config.rsi_rate > ma_long);
+        }
+        
+        if !ma_pass {
+            return false;
+        }
+
+        // Volume filter: V5 < V60 (applied for omni_microcap strategies)
+        if self.config.strategy_name.contains("aiquant") || self.config.strategy_name.contains("AiQuant") || self.config.strategy_name.contains("omni") {
+            let Some(volume_ma5) = ctx.data.market_decision_volume_moving_average(
+                date,
+                symbol,
+                5,
+            ) else {
+                return false;
+            };
+            let Some(volume_ma60) = ctx.data.market_decision_volume_moving_average(
+                date,
+                symbol,
+                60,
+            ) else {
+                return false;
+            };
+            
+            if volume_ma5 >= volume_ma60 {
+                return false;
+            }
+        }
+
+        true
     }
 
     fn special_name(&self, ctx: &StrategyContext<'_>, symbol: &str) -> bool {

crates/fidc-core/src/strategy_ai.rs

@@ -97,10 +97,11 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
             "平台策略脚本采用声明式 DSL + 表达式执行模型。".to_string(),
             "支持 let 变量、fn 自定义函数、when/unless/else 条件块、可用指标/因子字段映射。".to_string(),
             "支持数值型和字符串型因子，字符串字段可用于行业、概念、标签、板块等分类过滤。".to_string(),
-            "当前默认回测数据已支持 OHLCV、市值、流通市值、换手率、有效换手率、上市天数、停牌/ST/板块、涨跌停价格、tick 触达涨跌停、常用价格/成交量均线；复杂技术指标和财务报表字段必须来自预计算因子或后续扩展函数。".to_string(),
+            "当前默认回测数据已支持 OHLCV、市值、流通市值、换手率、有效换手率、上市天数、停牌/ST/板块、涨跌停价格、tick 触达涨跌停、常用价格/成交量均线，以及 stock_indicator_factors_v1 中已入库的通用指标因子。".to_string(),
             "AI 生成策略时只能输出完整 engine-script 代码，不输出 Markdown、解释、推理过程、JSON 包装或手册复述。".to_string(),
             "表达式字段以运行时字段为准：市值使用 market_cap，流通市值使用 free_float_cap；不要在策略表达式中使用数据库原始字段 float_market_cap。".to_string(),
-            "60日价格均线使用 rolling_mean(\"close\", 60)，不要使用 ma60、stock_ma60、signal_ma60 或 benchmark_ma60。".to_string(),
+            "任意窗口价格均线使用 rolling_mean(\"close\", n) 或 ma(\"close\", n)，任意窗口均量使用 rolling_mean(\"volume\", n) 或 vma(n)；不要使用未列出的 ma60、stock_ma60、signal_ma60 或 benchmark_ma60 变量。".to_string(),
+            "next_bar_open 会用决策日信号生成订单，并在下一可交易开盘撮合；不得把执行日 open/high/low/close 当成下单前已知信息。".to_string(),
             "自定义 fn 必须通过参数传入运行时字段；不要用 fn score() 这类零参数函数直接引用 market_cap、close、ma5 等股票字段。".to_string(),
             "禁止自由 Python/JavaScript 命令式语句，最终必须输出平台 DSL。".to_string(),
         ],
@@ -165,6 +166,10 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
                 title: "诊断解释".to_string(),
                 detail: "结果为空或收益异常时优先展示 diagnostics、选股数量、过滤原因、缺失字段、窗口不足、涨跌停/停牌拒单、快照缓存命中情况。不要只返回 JSON；要给用户自然语言结论和下一步优化建议。".to_string(),
             },
+            ManualSection {
+                title: "收益合理性复核".to_string(),
+                detail: "展示或用于优化前，应按 finalEquity / initialCash - 1 复算总收益。若小资金回测出现极端收益、指标与资金不一致、或历史 run 来自旧引擎，应检查交易明细并用当前编译后的回测引擎重新回测，不要把异常 run 当成成功样本。".to_string(),
+            },
         ],
         optimization_playbook: vec![
             ManualSection {
@@ -215,7 +220,7 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
             },
             ManualSection {
                 title: "execution.matching_type / execution.slippage".to_string(),
-                detail: "设置撮合模式和滑点。支持 execution.matching_type(\"next_tick_last\" | \"next_tick_best_own\" | \"next_tick_best_counterparty\" | \"counterparty_offer\" | \"vwap\" | \"current_bar_close\" | \"next_bar_open\" | \"open_auction\")。其中 next_tick_last 使用 tick 的 last_price；next_tick_best_own / next_tick_best_counterparty 会按 L1 买一卖一近似 平台内核 的 tick 最优价语义；counterparty_offer 在存在 order_book_depth 多档盘口数据时会按真实档位逐档扫单并计算加权成交价，不存在 depth 时回退 L1 对手方报价；vwap 会在盘中执行价链路上聚合多笔成交为单条 VWAP 成交；open_auction 使用当日集合竞价开盘价 day_open 进行撮合，且不额外施加滑点，并按竞价成交量而不是盘口一档流动性限制成交；滑点支持 execution.slippage(\"none\") / execution.slippage(\"price_ratio\", 0.001) / execution.slippage(\"tick_size\", 1) / execution.slippage(\"limit_price\")，其中 limit_price 会在限价单成交时按挂单价模拟 平台内核 的最坏成交价。".to_string(),
+                detail: "设置撮合模式和滑点。支持 execution.matching_type(\"next_tick_last\" | \"next_tick_best_own\" | \"next_tick_best_counterparty\" | \"counterparty_offer\" | \"vwap\" | \"current_bar_close\" | \"next_bar_open\" | \"open_auction\")。其中 next_tick_last 使用 tick 的 last_price；next_tick_best_own / next_tick_best_counterparty 会按 L1 买一卖一近似 平台内核 的 tick 最优价语义；counterparty_offer 在存在 order_book_depth 多档盘口数据时会按真实档位逐档扫单并计算加权成交价，不存在 depth 时回退 L1 对手方报价；vwap 会在盘中执行价链路上聚合多笔成交为单条 VWAP 成交；next_bar_open 使用决策日信号并在下一可交易日开盘撮合，禁止把执行日 open/high/low/close 解释为下单前已知数据；open_auction 使用当日集合竞价开盘价 day_open 进行撮合，且不额外施加滑点，并按竞价成交量而不是盘口一档流动性限制成交；滑点支持 execution.slippage(\"none\") / execution.slippage(\"price_ratio\", 0.001) / execution.slippage(\"tick_size\", 1) / execution.slippage(\"limit_price\")，其中 limit_price 会在限价单成交时按挂单价模拟 平台内核 的最坏成交价。".to_string(),
             },
             ManualSection {
                 title: "期货提交校验".to_string(),
@@ -262,7 +267,7 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
                 fields: vec![
                     ManualField { name: "symbol".to_string(), field_type: "string".to_string(), detail: "证券代码。".to_string() },
                     ManualField { name: "market_cap/free_float_cap".to_string(), field_type: "float".to_string(), detail: "总市值、流通市值。".to_string() },
-                    ManualField { name: "turnover_ratio/effective_turnover_ratio".to_string(), field_type: "float".to_string(), detail: "换手率、有效换手率。".to_string() },
+                    ManualField { name: "turnover/turnover_ratio/effective_turnover_ratio".to_string(), field_type: "float".to_string(), detail: "换手率、换手率标准字段、有效换手率；turnover 是 turnover_ratio 的兼容别名。".to_string() },
                     ManualField { name: "open/high/low/close/last/last_price/prev_close/amount".to_string(), field_type: "float".to_string(), detail: "开盘、最高、最低、收盘、盘中价、昨收和成交额。".to_string() },
                     ManualField { name: "upper_limit/lower_limit/price_tick/round_lot/minimum_order_quantity/order_step_size".to_string(), field_type: "float/int".to_string(), detail: "涨跌停、最小价位、整手、最小下单量和数量步长。KSH/BJSE 等板块可与 round_lot 不同。".to_string() },
                     ManualField { name: "paused/is_st/is_kcb/is_one_yuan/is_new_listing".to_string(), field_type: "bool".to_string(), detail: "可交易性与板块标志。".to_string() },
@@ -323,9 +328,11 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
             ManualFunction { name: "order/order_status/order_avg_price/order_transaction_cost".to_string(), signature: "ctx.order(order_id)".to_string(), detail: "按订单 id 查询运行时订单对象，支持已结束订单和当前挂单。返回字段包括 status、filled_quantity、unfilled_quantity、avg_price、transaction_cost、symbol、side、reason；可用便捷函数读取状态、成交均价和费用，对齐 平台内核 Order 的核心属性。".to_string() },
             ManualFunction { name: "account/portfolio_view/accounts".to_string(), signature: "ctx.account()".to_string(), detail: "返回当前股票账户/组合运行时视图，字段包括 account_type、cash、available_cash、frozen_cash、market_value、total_value、unit_net_value、daily_pnl、daily_returns、total_returns、transaction_cost、trading_pnl、position_pnl 等；DSL 中同名字段可直接使用。也可用 ctx.stock_account()、ctx.account_by_type(\"STOCK\")、ctx.accounts() 按账户类型读取；当前股票回测路径不会把 FUTURE 虚假映射成 STOCK。".to_string() },
             ManualFunction { name: "deposit_withdraw/finance_repay/management_fee".to_string(), signature: "account.deposit_withdraw(amount, receiving_days=0)".to_string(), detail: "策略账户资金动作。deposit_withdraw 正数入金、负数出金；receiving_days 大于 0 时按交易日延迟到账，并保持净值口径不把外部资金流当成收益。finance_repay 正数融资、负数还款，会同步维护 cash_liabilities。set_management_fee_rate 设置结算管理费率；普通策略可覆盖 management_fee(ctx, rate) 自定义计算器，对齐 平台内核 管理费回调能力。".to_string() },
-            ManualFunction { name: "rolling_mean".to_string(), signature: "rolling_mean(\"field\", lookback)".to_string(), detail: "任意字段滚动均值，支持 volume/amount/turnover_ratio、signal_open/signal_close、benchmark_open/benchmark_close 等。个股 volume 与 close 均按当前交易日前已完成交易日计算；单只股票历史窗口不足时，在选股过滤和买入仓位表达式中按不通过/0 仓处理，不会中断整次回测。任意成交量窗口推荐用它，比如 rolling_mean(\"volume\", 15)。".to_string() },
-            ManualFunction { name: "sma".to_string(), signature: "sma(\"field\", lookback)".to_string(), detail: "rolling_mean 的别名。任意价格均线窗口推荐用它，比如 sma(\"close\", 15)。".to_string() },
-            ManualFunction { name: "复杂技术指标".to_string(), signature: "factor_value(\"macd\", 1) 或预计算字段".to_string(), detail: "BOLL、EMA、WMA、DEMA、TEMA、KAMA、SAR、ADX、CCI、MACD、RSI、KDJ、WILLR、ATR、ROC、TRIX、MFI、Aroon、OBV、ADL、Beta、相关系数、线性回归、标准差、方差、K 线形态等目前不是默认内建函数；可先预计算成数值因子，再用 factor_value/rolling_mean 读取。".to_string() },
+            ManualFunction { name: "rolling_mean / sma / ma".to_string(), signature: "rolling_mean(\"field\", lookback) / ma(\"close\", 20)".to_string(), detail: "任意字段滚动均值，支持 close、volume、amount、turnover_ratio、effective_turnover_ratio、signal_open/signal_close、benchmark_open/benchmark_close 和所有数值型 extra_factors。个股 close 使用当前交易日前已完成收盘序列，volume 使用当前交易日前已完成成交量序列；历史窗口不足时在选股过滤和买入仓位表达式中按不通过/0 仓处理。".to_string() },
+            ManualFunction { name: "vma".to_string(), signature: "vma(60)".to_string(), detail: "rolling_mean(\"volume\", lookback) 的便捷别名，用于任意窗口成交量均线，例如 vma(5) < vma(60)。".to_string() },
+            ManualFunction { name: "rolling_sum / rolling_min / rolling_max".to_string(), signature: "rolling_sum(\"volume\", 20)".to_string(), detail: "任意数值字段滚动求和、最小值、最大值。可用于量能收缩、区间高低点、资金活跃度等过滤或排序。".to_string() },
+            ManualFunction { name: "rolling_stddev / stddev / rolling_zscore / pct_change".to_string(), signature: "stddev(\"close\", 20) / pct_change(\"close\", 10)".to_string(), detail: "滚动标准差、最新值 Z 分数和区间涨跌幅。pct_change(field, n) 会读取 n+1 个窗口点并计算 latest / first - 1。".to_string() },
+            ManualFunction { name: "数据库指标因子".to_string(), signature: "factor_value(\"ths_valid_turnover_stock\", 1)".to_string(), detail: "stock_indicator_factors_v1 中的指标会进入 extra_factors，可用 factor(\"字段\")、factors[\"字段\"]、factor_value(\"字段\", lookback) 或 rolling_mean(\"字段\", n) 读取。市值类指标统一提供亿元口径别名 ths_market_value_stock、ths_market_value_stock_bn、ths_current_mv_stock、ths_current_mv_stock_bn，同时保留 raw 后缀原始值。".to_string() },
             ManualFunction { name: "round/floor/ceil/abs/min/max/clamp".to_string(), signature: "round(x)".to_string(), detail: "常用数值函数。".to_string() },
             ManualFunction { name: "safe_div".to_string(), signature: "safe_div(lhs, rhs, fallback)".to_string(), detail: "安全除法。".to_string() },
             ManualFunction { name: "contains/starts_with/ends_with/lower/upper/trim/strlen".to_string(), signature: "starts_with(symbol, \"60\")".to_string(), detail: "字符串辅助函数。".to_string() },
@@ -343,7 +350,7 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
             },
             ManualFactorSource {
                 table: "扩展指标因子".to_string(),
-                detail: "当前可用扩展指标主要包括总市值、流通市值、换手率、有效换手率；其他财务、行业、概念、陆股通、技术指标等只有落地为可用因子后才可在策略中直接使用。".to_string(),
+                detail: "来自 stock_indicator_factors_v1 和运行时 extra_factors。已入库指标会自动进入策略运行时，字段名使用 dataset 小写下划线；市值类默认换算为亿元口径，raw 后缀保留原始 indicator_value。".to_string(),
                 fields: vec![],
             },
             ManualFactorSource {
@@ -428,10 +435,15 @@ pub fn render_manual_markdown(manual: &StrategyAiManual) -> String {
     out.push_str("- 只使用支持语句块：`market`、`benchmark`、`signal`、`rebalance.every_days(...).at([...])`、`selection.limit`、`selection.market_cap_band`、`filter.stock_ma`、`filter.stock_expr`、`ordering.rank_by`、`ordering.rank_expr`、`allocation.buy_scale`、`risk.stop_loss`、`risk.take_profit`、`risk.index_exposure`、`execution.matching_type`、`execution.slippage`、`universe.exclude`。\n");
     out.push_str("- 禁止伪 DSL：`filter(...)`、`rank(...)`、`select.top(...)`、`weight.equal(...)`、`sell_rule(...)`、`backtest(...)`、`risk.max_position(...)`。\n");
     out.push_str("- 市值表达式字段只能用 `market_cap` 或 `free_float_cap`；不要使用数据库原始字段 `float_market_cap`。\n");
-    out.push_str("- 60日价格均线使用 `rolling_mean(\"close\", 60)`；不要使用 `ma60`、`stock_ma60`、`signal_ma60` 或 `benchmark_ma60`。\n");
+    out.push_str("- 任意窗口价格均线使用 `rolling_mean(\"close\", n)` 或 `ma(\"close\", n)`；任意窗口均量使用 `rolling_mean(\"volume\", n)` 或 `vma(n)`；不要使用未列出的 `ma60`、`stock_ma60`、`signal_ma60` 或 `benchmark_ma60` 变量。\n");
     out.push_str("- 自定义 `fn` 必须通过参数传入运行时字段；不要用 `fn score()` 这类零参数函数直接引用 `market_cap`、`close`、`ma5` 等股票字段。\n");
     out.push_str("- `selection.market_cap_band` 必须写命名参数：`field=\"market_cap\"` 或 `field=\"free_float_cap\"`，并包含 `lower=...` 与 `upper=...`。\n");
-    out.push_str("- `risk.index_exposure(...)` 只能传一个表达式；`execution.matching_type(...)` 和 `execution.slippage(...)` 必须使用手册列出的合法取值。\n\n");
+    out.push_str(
+        "- `risk.index_exposure(...)` 只能传一个表达式；不要生成 `risk.exposure(...)`。\n",
+    );
+    out.push_str("- 完整三元表达式 `cond ? a : b` 可在表达式参数中使用；若当前运行环境报 `Unknown operator: '?'`，先重编译并重启回测服务，不要改写策略语义掩盖运行时漂移。\n");
+    out.push_str("- `next_bar_open` 的选股、排序和仓位信号来自决策日，订单在下一可交易开盘撮合；不要使用执行日价格作为下单前信号。\n");
+    out.push_str("- `execution.matching_type(...)` 和 `execution.slippage(...)` 必须使用手册列出的合法取值。\n\n");
     out.push_str("## 语句块\n");
     for item in &manual.statement_blocks {
         out.push_str(&format!("- `{}`: {}\n", item.title, item.detail));
@@ -506,9 +518,9 @@ pub fn build_generation_prompt(
     prompt.push_str("- 生成的代码必须能转换为 strategy_spec 并提交 POST /v1/backtests。\n");
     prompt.push_str("- 不要使用手册未列出的字段、函数或外部平台 API 名称。\n\n");
     prompt.push_str("只允许使用这些可编译语句：market、benchmark、signal、rebalance.every_days(...).at([...])、selection.limit、selection.market_cap_band、filter.stock_ma、filter.stock_expr、ordering.rank_by、ordering.rank_expr、allocation.buy_scale、risk.stop_loss、risk.take_profit、risk.index_exposure、execution.matching_type、execution.slippage、universe.exclude。禁止输出 filter(...)、rank(...)、select.top(...)、weight.equal()、sell_rule(...)、backtest(...)、risk.max_position(...) 这类未支持伪语法。\n");
-    prompt.push_str("参数形态必须严格：selection.market_cap_band 必须写 field=\"market_cap\" 或 field=\"free_float_cap\", lower=..., upper=...；禁止使用 float_market_cap；禁止使用 ma60、stock_ma60、signal_ma60、benchmark_ma60，60日价格均线写 rolling_mean(\"close\", 60)；不要生成 fn score() 这类零参数函数，股票字段排序直接写在 ordering.rank_expr 内或用带参数函数；布尔字段按布尔使用，写 !is_st、!paused、!at_upper_limit、!at_lower_limit，不要写 is_st == 0；risk.index_exposure 只能传一个数值表达式，例如 ((signal_close < signal_ma20) ? 0.35 : 1.0)；execution.matching_type 只能取 next_tick_last、next_tick_best_own、next_tick_best_counterparty、counterparty_offer、vwap、current_bar_close、next_bar_open、open_auction；execution.slippage 必须写 execution.slippage(\"none\") 或 execution.slippage(\"price_ratio\", 0.001)。\n");
+    prompt.push_str("参数形态必须严格：selection.market_cap_band 必须写 field=\"market_cap\" 或 field=\"free_float_cap\", lower=..., upper=...；禁止使用 float_market_cap；禁止使用 ma60、stock_ma60、signal_ma60、benchmark_ma60，60日价格均线写 rolling_mean(\"close\", 60) 或 ma(\"close\", 60)，任意窗口均量写 rolling_mean(\"volume\", n) 或 vma(n)；不要生成 fn score() 这类零参数函数，股票字段排序直接写在 ordering.rank_expr 内或用带参数函数；布尔字段按布尔使用，写 !is_st、!paused、!at_upper_limit、!at_lower_limit，不要写 is_st == 0；risk.index_exposure 只能传一个数值表达式，不要使用 risk.exposure；完整三元表达式 cond ? a : b 可以使用，但不得输出残缺问号/冒号片段；execution.matching_type 只能取 next_tick_last、next_tick_best_own、next_tick_best_counterparty、counterparty_offer、vwap、current_bar_close、next_bar_open、open_auction；next_bar_open 只能使用决策日信号，不能把执行日价格当作下单前信息；execution.slippage 必须写 execution.slippage(\"none\") 或 execution.slippage(\"price_ratio\", 0.001)。\n");
     prompt.push_str("回测成功但 tradeCount=0 或 holdingCount=0 是无效策略；第一版必须保持稳定买入覆盖率，复杂因子只能在后续优化中逐步加严。\n");
-    prompt.push_str("可参考但不要照抄的最小模板，回复时不要包含 ``` 代码围栏：\nstrategy(\"cn_a_smallcap_factor_rotation\") {\nmarket(\"CN_A\")\nbenchmark(\"000852.SH\")\nsignal(\"000001.SH\")\nrebalance.every_days(5).at([\"10:18\"])\nselection.limit(40)\nselection.market_cap_band(field=\"market_cap\", lower=0, upper=1000)\nfilter.stock_expr(listed_days >= 60 && !is_st && !paused && close > 2 && !at_upper_limit && !at_lower_limit)\nordering.rank_by(\"market_cap\", \"asc\")\nallocation.buy_scale(1.0)\nrisk.index_exposure((signal_close < signal_ma20) ? 0.35 : 1.0)\nrisk.stop_loss(holding_return < -0.08)\nexecution.slippage(\"price_ratio\", 0.001)\n}\n\n");
+    prompt.push_str("可参考但不要照抄的最小模板，回复时不要包含 ``` 代码围栏：\nstrategy(\"cn_a_smallcap_factor_rotation\") {\nmarket(\"CN_A\")\nbenchmark(\"000852.SH\")\nsignal(\"000001.SH\")\nrebalance.every_days(5).at([\"10:18\"])\nselection.limit(40)\nselection.market_cap_band(field=\"market_cap\", lower=0, upper=1000)\nfilter.stock_expr(listed_days >= 60 && !is_st && !paused && close > 2 && !at_upper_limit && !at_lower_limit)\nordering.rank_by(\"market_cap\", \"asc\")\nallocation.buy_scale(1.0)\nrisk.index_exposure(1.0)\nrisk.stop_loss(holding_return < -0.08)\nexecution.slippage(\"price_ratio\", 0.001)\n}\n\n");
     prompt.push_str("用户目标：\n");
     prompt.push_str(&format!("- {}\n", request.user_goal));
     if !request.constraints.is_empty() {
@@ -535,6 +547,7 @@ pub fn build_optimization_prompt(
     prompt.push_str("输出格式硬约束：回复第一行必须是 strategy(\"...\")、let、fn、const 或 //；回复中不得包含 Markdown、解释、思考过程、手册复述、JSON 包装或自然语言总结。\n");
     prompt.push_str("长度硬约束：策略代码目标 80 行以内，只保留必要 let/fn/strategy 块；不要复制下面的手册片段、历史策略全文或字段清单。\n");
     prompt.push_str("只修改与优化目标相关的少量参数或过滤条件，保留原策略的市场、基准、信号指数和核心风控；不要引入手册未列出的字段或外部平台 API 名称。\n");
+    prompt.push_str("优化可以调整调仓周期、持仓数、市值带、filter.stock_expr、ordering.rank_expr、allocation.buy_scale、止盈止损；如上一轮无交易或质量分过低，必须先放宽过滤条件并优先使用已入库指标因子、rolling_mean/ma/vma/rolling_stddev/pct_change 等支持函数。\n");
     prompt.push_str("优化目标：\n");
     prompt.push_str(&format!("- {}\n\n", request.objective));
     prompt.push_str("当前策略代码如下，仅作为输入参考；回复时不要包含 Markdown 代码围栏：\n");

crates/fidc-core/src/universe.rs

@@ -78,6 +78,9 @@ pub struct DynamicMarketCapBandSelector {
     pub cap_span: f64,
     pub xs: f64,
     pub top_n: usize,
+    pub padding_ratio: f64,
+    pub min_padding: f64,
+    pub max_padding: f64,
 }
 
 impl DynamicMarketCapBandSelector {
@@ -87,6 +90,9 @@ impl DynamicMarketCapBandSelector {
         cap_span: f64,
         xs: f64,
         top_n: usize,
+        padding_ratio: f64,
+        min_padding: f64,
+        max_padding: f64,
     ) -> Self {
         Self {
             base_index_level,
@@ -94,11 +100,14 @@ impl DynamicMarketCapBandSelector {
             cap_span,
             xs,
             top_n,
+            padding_ratio,
+            min_padding,
+            max_padding,
         }
     }
 
     pub fn demo(top_n: usize) -> Self {
-        Self::new(2000.0, 7.0, 10.0, 4.0 / 500.0, top_n)
+        Self::new(2000.0, 7.0, 10.0, 4.0 / 500.0, top_n, 0.5, 8.0, 20.0)
     }
 
     pub fn regime(&self, benchmark_level: f64) -> BandRegime {
@@ -114,7 +123,18 @@ impl DynamicMarketCapBandSelector {
     pub fn band_for_level(&self, benchmark_level: f64) -> (f64, f64) {
         let start = ((benchmark_level - self.base_index_level) * self.xs) + self.base_cap_floor;
         let low = start.round();
-        (low, low + self.cap_span)
+        let high = low + self.cap_span;
+        
+        // Apply padding to expand the range
+        let span = high - low;
+        let padding = (span * self.padding_ratio)
+            .max(self.min_padding)
+            .min(self.max_padding);
+        
+        let lower_bound = (low - padding).max(0.0);
+        let upper_bound = high + padding;
+        
+        (lower_bound, upper_bound)
     }
 }
 

crates/fidc-core/tests/explicit_order_flow.rs

@@ -10,7 +10,7 @@ use std::collections::{BTreeMap, BTreeSet};
 #[test]
 fn broker_executes_explicit_order_value_buy() {
     let date = NaiveDate::from_ymd_opt(2024, 1, 10).unwrap();
-    let data = DataSet::from_components(
+    let data = DataSet::from_components_with_actions_and_quotes(
         vec![Instrument {
             symbol: "000002.SZ".to_string(),
             name: "Test".to_string(),
@@ -72,6 +72,20 @@ fn broker_executes_explicit_order_value_buy() {
             prev_close: 99.0,
             volume: 1_000_000,
         }],
+        Vec::new(),
+        vec![IntradayExecutionQuote {
+            date,
+            symbol: "000002.SZ".to_string(),
+            timestamp: date.and_hms_opt(10, 18, 3).unwrap(),
+            last_price: 10.0,
+            bid1: 9.99,
+            ask1: 10.01,
+            bid1_volume: 1,
+            ask1_volume: 1,
+            volume_delta: 1,
+            amount_delta: 0.0,
+            trading_phase: Some("continuous".to_string()),
+        }],
     )
     .expect("dataset");
     let mut portfolio = PortfolioState::new(1_000_000.0);
@@ -111,7 +125,7 @@ fn broker_executes_explicit_order_value_buy() {
 #[test]
 fn broker_executes_order_shares_and_order_lots() {
     let date = NaiveDate::from_ymd_opt(2024, 1, 10).unwrap();
-    let data = DataSet::from_components(
+    let data = DataSet::from_components_with_actions_and_quotes(
         vec![Instrument {
             symbol: "000002.SZ".to_string(),
             name: "Test".to_string(),
@@ -173,6 +187,20 @@ fn broker_executes_order_shares_and_order_lots() {
             prev_close: 99.0,
             volume: 1_000_000,
         }],
+        Vec::new(),
+        vec![IntradayExecutionQuote {
+            date,
+            symbol: "000002.SZ".to_string(),
+            timestamp: date.and_hms_opt(10, 18, 3).unwrap(),
+            last_price: 10.0,
+            bid1: 9.99,
+            ask1: 10.01,
+            bid1_volume: 1,
+            ask1_volume: 1,
+            volume_delta: 1,
+            amount_delta: 0.0,
+            trading_phase: Some("continuous".to_string()),
+        }],
     )
     .expect("dataset");
     let mut portfolio = PortfolioState::new(1_000_000.0);
@@ -1192,6 +1220,120 @@ fn broker_applies_price_ratio_slippage_on_snapshot_fills() {
 
 #[test]
 fn broker_applies_tick_size_slippage_on_intraday_last_fills() {
+    let date = NaiveDate::from_ymd_opt(2024, 1, 10).unwrap();
+    let data = DataSet::from_components_with_actions_and_quotes(
+        vec![Instrument {
+            symbol: "000002.SZ".to_string(),
+            name: "Test".to_string(),
+            board: "SZ".to_string(),
+            round_lot: 100,
+            listed_at: None,
+            delisted_at: None,
+            status: "active".to_string(),
+        }],
+        vec![DailyMarketSnapshot {
+            date,
+            symbol: "000002.SZ".to_string(),
+            timestamp: Some("2024-01-10 10:18:00".to_string()),
+            day_open: 10.0,
+            open: 10.0,
+            high: 10.1,
+            low: 9.9,
+            close: 10.0,
+            last_price: 10.0,
+            bid1: 9.99,
+            ask1: 10.01,
+            prev_close: 10.0,
+            volume: 100_000,
+            tick_volume: 100_000,
+            bid1_volume: 80_000,
+            ask1_volume: 80_000,
+            trading_phase: Some("continuous".to_string()),
+            paused: false,
+            upper_limit: 11.0,
+            lower_limit: 9.0,
+            price_tick: 0.01,
+        }],
+        vec![DailyFactorSnapshot {
+            date,
+            symbol: "000002.SZ".to_string(),
+            market_cap_bn: 50.0,
+            free_float_cap_bn: 45.0,
+            pe_ttm: 15.0,
+            turnover_ratio: Some(2.0),
+            effective_turnover_ratio: Some(1.8),
+            extra_factors: BTreeMap::new(),
+        }],
+        vec![CandidateEligibility {
+            date,
+            symbol: "000002.SZ".to_string(),
+            is_st: false,
+            is_new_listing: false,
+            is_paused: false,
+            allow_buy: true,
+            allow_sell: true,
+            is_kcb: false,
+            is_one_yuan: false,
+        }],
+        vec![BenchmarkSnapshot {
+            date,
+            benchmark: "000300.SH".to_string(),
+            open: 100.0,
+            close: 100.0,
+            prev_close: 99.0,
+            volume: 1_000_000,
+        }],
+        Vec::new(),
+        vec![IntradayExecutionQuote {
+            date,
+            symbol: "000002.SZ".to_string(),
+            timestamp: date.and_hms_opt(10, 18, 3).unwrap(),
+            last_price: 10.0,
+            bid1: 9.99,
+            ask1: 10.01,
+            bid1_volume: 1,
+            ask1_volume: 1,
+            volume_delta: 1,
+            amount_delta: 0.0,
+            trading_phase: Some("continuous".to_string()),
+        }],
+    )
+    .expect("dataset");
+    let mut portfolio = PortfolioState::new(1_000_000.0);
+    let broker = BrokerSimulator::new_with_execution_price(
+        ChinaAShareCostModel::default(),
+        ChinaEquityRuleHooks::default(),
+        PriceField::Last,
+    )
+    .with_intraday_execution_start_time(chrono::NaiveTime::from_hms_opt(10, 18, 0).unwrap())
+    .with_slippage_model(SlippageModel::TickSize(2.0));
+
+    let report = broker
+        .execute(
+            date,
+            &mut portfolio,
+            &data,
+            &StrategyDecision {
+                rebalance: false,
+                target_weights: BTreeMap::new(),
+                exit_symbols: BTreeSet::new(),
+                order_intents: vec![OrderIntent::Value {
+                    symbol: "000002.SZ".to_string(),
+                    value: 100_000.0,
+                    reason: "tick_slippage".to_string(),
+                }],
+                notes: Vec::new(),
+                diagnostics: Vec::new(),
+            },
+        )
+        .expect("broker execution");
+
+    assert_eq!(report.fill_events.len(), 1);
+    assert!((report.fill_events[0].price - 10.02).abs() < 1e-9);
+}
+
+#[test]
+fn broker_rejects_intraday_last_order_without_execution_quotes() {
     let date = NaiveDate::from_ymd_opt(2024, 1, 10).unwrap();
     let data = DataSet::from_components(
         vec![Instrument {
@@ -1263,8 +1405,7 @@ fn broker_applies_tick_size_slippage_on_intraday_last_fills() {
         ChinaEquityRuleHooks::default(),
         PriceField::Last,
     )
-    .with_intraday_execution_start_time(chrono::NaiveTime::from_hms_opt(10, 18, 0).unwrap())
-    .with_slippage_model(SlippageModel::TickSize(2.0));
+    .with_intraday_execution_start_time(chrono::NaiveTime::from_hms_opt(10, 18, 0).unwrap());
 
     let report = broker
         .execute(
@@ -1278,7 +1419,7 @@ fn broker_applies_tick_size_slippage_on_intraday_last_fills() {
                 order_intents: vec![OrderIntent::Value {
                     symbol: "000002.SZ".to_string(),
                     value: 100_000.0,
-                    reason: "tick_slippage".to_string(),
+                    reason: "missing_tick_quotes".to_string(),
                 }],
                 notes: Vec::new(),
                 diagnostics: Vec::new(),
@@ -1286,8 +1427,15 @@ fn broker_applies_tick_size_slippage_on_intraday_last_fills() {
         )
         .expect("broker execution");
 
-    assert_eq!(report.fill_events.len(), 1);
-    assert!((report.fill_events[0].price - 10.02).abs() < 1e-9);
+    assert!(report.fill_events.is_empty());
+    assert_eq!(report.order_events.len(), 1);
+    assert_eq!(report.order_events[0].status, OrderStatus::Canceled);
+    assert!(
+        report.order_events[0]
+            .reason
+            .contains("no execution quotes after start")
+    );
+    assert!(portfolio.position("000002.SZ").is_none());
 }
 
 #[test]