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修正平台策略滚动因子优先级

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This commit is contained in:
boris
2026-06-16 14:49:41 +08:00
parent 0628dd528a
commit 716149c06c
1 changed files with 190 additions and 72 deletions
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crates/fidc-core/src/platform_expr_strategy.rs
+190 -72
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@@ -218,6 +218,7 @@ pub struct PlatformExprStrategyConfig {
pub matching_type: MatchingType,
pub quote_quantity_limit: bool,
pub current_day_precomputed_factors: bool,
pub prefer_precomputed_rolling_factors: bool,
pub intraday_execution_time: Option<NaiveTime>,
pub delayed_limit_open_exit_enabled: bool,
pub delayed_limit_open_exit_time: Option<NaiveTime>,
@@ -286,6 +287,7 @@ fn band_low(index_close) {
matching_type: MatchingType::NextTickLast,
quote_quantity_limit: true,
current_day_precomputed_factors: false,
prefer_precomputed_rolling_factors: false,
intraday_execution_time: None,
delayed_limit_open_exit_enabled: false,
delayed_limit_open_exit_time: None,
@@ -2090,6 +2092,26 @@ impl PlatformExprStrategy {
self.stock_state_with_factor_date_and_time(ctx, date, factor_date, symbol, None)
}
fn stock_decision_rolling_mean(
&self,
ctx: &StrategyContext<'_>,
date: NaiveDate,
symbol: &str,
extra_factors: &BTreeMap<String, f64>,
field: &str,
lookback: usize,
) -> Option<f64> {
let precomputed = precomputed_stock_rolling_mean(extra_factors, field, lookback);
let computed = ctx
.data
.market_decision_numeric_moving_average(date, symbol, field, lookback);
if self.config.prefer_precomputed_rolling_factors {
precomputed.or(computed)
} else {
computed.or(precomputed)
}
}
fn stock_state_at_time(
&self,
ctx: &StrategyContext<'_>,
@@ -2116,78 +2138,59 @@ impl PlatformExprStrategy {
let factor = ctx.data.require_factor(factor_date, symbol)?;
let candidate = ctx.data.require_candidate(date, symbol)?;
let instrument = ctx.data.instrument(symbol);
let stock_ma_short = ctx
.data
.market_decision_close_moving_average(date, symbol, self.config.stock_short_ma_days)
.or_else(|| {
precomputed_stock_rolling_mean(
&factor.extra_factors,
"close",
self.config.stock_short_ma_days,
)
})
let stock_ma_short = self
.stock_decision_rolling_mean(
ctx,
date,
symbol,
&factor.extra_factors,
"close",
self.config.stock_short_ma_days,
)
.unwrap_or(f64::NAN);
let stock_ma_mid = ctx
.data
.market_decision_close_moving_average(date, symbol, self.config.stock_mid_ma_days)
.or_else(|| {
precomputed_stock_rolling_mean(
&factor.extra_factors,
"close",
self.config.stock_mid_ma_days,
)
})
let stock_ma_mid = self
.stock_decision_rolling_mean(
ctx,
date,
symbol,
&factor.extra_factors,
"close",
self.config.stock_mid_ma_days,
)
.unwrap_or(f64::NAN);
let stock_ma_long = ctx
.data
.market_decision_close_moving_average(date, symbol, self.config.stock_long_ma_days)
.or_else(|| {
precomputed_stock_rolling_mean(
&factor.extra_factors,
"close",
self.config.stock_long_ma_days,
)
})
let stock_ma_long = self
.stock_decision_rolling_mean(
ctx,
date,
symbol,
&factor.extra_factors,
"close",
self.config.stock_long_ma_days,
)
.unwrap_or(f64::NAN);
let stock_ma5 = ctx
.data
.market_decision_close_moving_average(date, symbol, 5)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "close", 5))
let stock_ma5 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "close", 5)
.unwrap_or(f64::NAN);
let stock_ma10 = ctx
.data
.market_decision_close_moving_average(date, symbol, 10)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "close", 10))
let stock_ma10 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "close", 10)
.unwrap_or(f64::NAN);
let stock_ma20 = ctx
.data
.market_decision_close_moving_average(date, symbol, 20)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "close", 20))
let stock_ma20 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "close", 20)
.unwrap_or(f64::NAN);
let stock_ma30 = ctx
.data
.market_decision_close_moving_average(date, symbol, 30)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "close", 30))
let stock_ma30 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "close", 30)
.unwrap_or(f64::NAN);
let stock_volume_ma5 = ctx
.data
.market_decision_volume_moving_average(date, symbol, 5)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "volume", 5))
let stock_volume_ma5 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "volume", 5)
.unwrap_or(f64::NAN);
let stock_volume_ma10 = ctx
.data
.market_decision_volume_moving_average(date, symbol, 10)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "volume", 10))
let stock_volume_ma10 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "volume", 10)
.unwrap_or(f64::NAN);
let stock_volume_ma20 = ctx
.data
.market_decision_volume_moving_average(date, symbol, 20)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "volume", 20))
let stock_volume_ma20 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "volume", 20)
.unwrap_or(f64::NAN);
let stock_volume_ma60 = ctx
.data
.market_decision_volume_moving_average(date, symbol, 60)
.or_else(|| precomputed_stock_rolling_mean(&factor.extra_factors, "volume", 60))
let stock_volume_ma60 = self
.stock_decision_rolling_mean(ctx, date, symbol, &factor.extra_factors, "volume", 60)
.unwrap_or(f64::NAN);
let touched_upper_limit = !market.paused
&& (market.is_at_upper_limit_price(market.close)
@@ -4023,16 +4026,14 @@ impl PlatformExprStrategy {
"rolling_mean(\"{other}\", {lookback}) requires stock context"
))
})?;
ctx.data
.market_decision_numeric_moving_average(
day.date,
&stock.symbol,
other,
lookback,
)
.or_else(|| {
precomputed_stock_rolling_mean(&stock.extra_factors, other, lookback)
})
self.stock_decision_rolling_mean(
ctx,
day.date,
&stock.symbol,
&stock.extra_factors,
other,
lookback,
)
}
};
value.ok_or_else(|| {
@@ -14697,6 +14698,123 @@ mod tests {
));
}
#[test]
fn platform_stock_state_can_prefer_precomputed_rolling_factors() {
let dates = [
d(2025, 1, 2),
d(2025, 1, 3),
d(2025, 1, 6),
d(2025, 1, 7),
d(2025, 1, 8),
d(2025, 1, 9),
];
let date = dates[5];
let symbol = "300001.SZ";
let mut extra_factors = BTreeMap::new();
extra_factors.insert("ma5_prev_close".to_string(), 99.0);
extra_factors.insert("avg_volume5".to_string(), 88.0);
let data = DataSet::from_components(
vec![Instrument {
symbol: symbol.to_string(),
name: symbol.to_string(),
board: "SZ".to_string(),
round_lot: 100,
listed_at: Some(d(2020, 1, 1)),
delisted_at: None,
status: "active".to_string(),
}],
dates
.into_iter()
.map(|trade_date| DailyMarketSnapshot {
date: trade_date,
symbol: symbol.to_string(),
timestamp: None,
day_open: 10.0,
open: 10.0,
high: 10.2,
low: 9.8,
close: 10.0,
last_price: 10.0,
bid1: 9.99,
ask1: 10.01,
prev_close: 10.0,
volume: 1_000,
tick_volume: 1_000,
bid1_volume: 1_000,
ask1_volume: 1_000,
trading_phase: None,
paused: false,
upper_limit: 11.0,
lower_limit: 9.0,
price_tick: 0.01,
})
.collect(),
vec![DailyFactorSnapshot {
date,
symbol: symbol.to_string(),
market_cap_bn: 20.0,
free_float_cap_bn: 20.0,
pe_ttm: 0.0,
turnover_ratio: None,
effective_turnover_ratio: None,
extra_factors,
}],
vec![CandidateEligibility {
date,
symbol: symbol.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: "000852.SH".to_string(),
open: 1000.0,
close: 1002.0,
prev_close: 998.0,
volume: 1_000_000,
}],
)
.expect("dataset");
let portfolio = PortfolioState::new(100_000.0);
let subscriptions = BTreeSet::new();
let ctx = StrategyContext {
execution_date: date,
decision_date: date,
decision_index: 5,
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 cfg = PlatformExprStrategyConfig::microcap_rotation();
cfg.prefer_precomputed_rolling_factors = true;
let strategy = PlatformExprStrategy::new(cfg);
let stock = strategy
.stock_state_with_factor_date(&ctx, date, date, symbol)
.expect("stock state");
assert_eq!(stock.stock_ma5, 99.0);
assert_eq!(stock.stock_volume_ma5, 88.0);
let strategy = PlatformExprStrategy::new(PlatformExprStrategyConfig::microcap_rotation());
let stock = strategy
.stock_state_with_factor_date(&ctx, date, date, symbol)
.expect("stock state");
assert_eq!(stock.stock_ma5, 10.0);
assert_eq!(stock.stock_volume_ma5, 1_000.0);
}
#[test]
fn platform_strategy_emits_target_shares_explicit_action() {
let date = d(2025, 2, 3);