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修正平台策略选股和弱市调仓口径

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This commit is contained in:
boris
2026-06-17 07:40:27 +08:00
parent bc39df0ee5
commit ed4658ccd0
1 changed files with 393 additions and 18 deletions
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crates/fidc-core/src/platform_expr_strategy.rs
+393 -18
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@@ -470,22 +470,14 @@ fn precomputed_stock_rolling_mean(
lookback: usize,
) -> Option<f64> {
let keys: &[&str] = match (field.trim().to_ascii_lowercase().as_str(), lookback) {
("close" | "prev_close" | "stock_close" | "price", 5) => {
&["ma5_prev_close", "sf_jq_v104_ma5", "ma5"]
}
("close" | "prev_close" | "stock_close" | "price", 10) => {
&["ma10_prev_close", "sf_jq_v104_ma10", "ma10"]
}
("close" | "prev_close" | "stock_close" | "price", 20) => {
&["ma20_prev_close", "sf_jq_v104_ma20", "ma20"]
}
("close" | "prev_close" | "stock_close" | "price", 30) => {
&["ma30_prev_close", "sf_jq_v104_ma30", "ma30"]
}
("volume" | "stock_volume", 5) => &["avg_volume5", "sf_jq_v104_v5", "vma5"],
("volume" | "stock_volume", 20) => &["avg_volume20", "sf_jq_v104_v20", "vma20"],
("volume" | "stock_volume", 60) => &["avg_volume60", "sf_jq_v104_v60", "vma60"],
("volume" | "stock_volume", 100) => &["avg_volume100", "sf_jq_v104_v100", "vma100"],
("close" | "prev_close" | "stock_close" | "price", 5) => &["ma5_prev_close", "ma5"],
("close" | "prev_close" | "stock_close" | "price", 10) => &["ma10_prev_close", "ma10"],
("close" | "prev_close" | "stock_close" | "price", 20) => &["ma20_prev_close", "ma20"],
("close" | "prev_close" | "stock_close" | "price", 30) => &["ma30_prev_close", "ma30"],
("volume" | "stock_volume", 5) => &["avg_volume5", "vma5"],
("volume" | "stock_volume", 20) => &["avg_volume20", "vma20"],
("volume" | "stock_volume", 60) => &["avg_volume60", "vma60"],
("volume" | "stock_volume", 100) => &["avg_volume100", "vma100"],
_ => return None,
};
keys.iter()
@@ -498,6 +490,7 @@ pub struct PlatformExprStrategy {
engine: Engine,
rebalance_day_counter: usize,
last_rebalance_date: Option<NaiveDate>,
last_trading_ratio: Option<f64>,
pending_highlimit_holdings: BTreeSet<String>,
/// 已编译表达式 AST 缓存。
/// Key 是经过 normalize/expand_runtime_helpers 之后的完整 script 文本，
@@ -591,6 +584,7 @@ impl PlatformExprStrategy {
engine,
rebalance_day_counter: 0,
last_rebalance_date: None,
last_trading_ratio: None,
pending_highlimit_holdings: BTreeSet::new(),
compiled_cache: RefCell::new(HashMap::new()),
cache_hits: RefCell::new(0),
@@ -5792,8 +5786,24 @@ impl PlatformExprStrategy {
Err(error) => Err(error),
};
}
let rank_by = self.config.rank_by.as_str();
match rank_by {
"market_cap" => {
return Ok(Self::market_cap_storage_to_strategy_unit(
candidate.market_cap_bn,
));
}
"market_cap_bn" => return Ok(candidate.market_cap_bn),
"free_float_cap" | "free_float_market_cap" => {
return Ok(Self::market_cap_storage_to_strategy_unit(
candidate.free_float_cap_bn,
));
}
"free_float_cap_bn" => return Ok(candidate.free_float_cap_bn),
_ => {}
}
Ok(self
.stock_numeric_field_value(candidate, stock, self.config.rank_by.as_str())
.stock_numeric_field_value(candidate, stock, rank_by)
.unwrap_or_else(|| self.field_value(candidate)))
}
@@ -6349,6 +6359,9 @@ impl Strategy for PlatformExprStrategy {
} else {
0.0
};
let previous_trading_ratio = self.last_trading_ratio.unwrap_or(1.0);
let weak_market_shrink_due =
trading_ratio.is_finite() && trading_ratio < previous_trading_ratio - 1e-9;
let marked_total_value = self.marked_total_value(ctx, execution_date);
let aiquant_total_value = if marked_total_value.is_finite() && marked_total_value > 0.0 {
marked_total_value
@@ -6563,6 +6576,7 @@ impl Strategy for PlatformExprStrategy {
&& self.config.rotation_enabled
&& trading_ratio > 0.0
&& trading_ratio < 1.0
&& weak_market_shrink_due
&& selection_limit > 0
&& !ctx.portfolio.positions().is_empty()
{
@@ -7021,6 +7035,9 @@ impl Strategy for PlatformExprStrategy {
self.rebalance_day_counter = self.rebalance_day_counter.saturating_add(1);
}
}
if self.config.rotation_enabled && trading_ratio.is_finite() {
self.last_trading_ratio = Some(trading_ratio);
}
if !explicit_action_intents.is_empty() {
order_intents.extend(explicit_action_intents);
}
@@ -7133,7 +7150,7 @@ mod tests {
PlatformAccountActionKind, PlatformExplicitActionStage, PlatformExplicitCancelKind,
PlatformExplicitOrderKind, PlatformExprStrategy, PlatformExprStrategyConfig,
PlatformRebalanceSchedule, PlatformScheduleFrequency, PlatformTradeAction,
PlatformUniverseActionKind,
PlatformUniverseActionKind, precomputed_stock_rolling_mean,
};
use crate::{
AlgoOrderStyle, BenchmarkSnapshot, CandidateEligibility, CorporateAction,
@@ -9304,6 +9321,161 @@ mod tests {
)));
}
#[test]
fn platform_aiquant_weak_market_does_not_retarget_same_ratio_every_day() {
let first_date = d(2023, 5, 4);
let second_date = d(2023, 5, 5);
let symbol = "300621.SZ";
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(),
}],
[first_date, second_date]
.iter()
.map(|date| DailyMarketSnapshot {
date: *date,
symbol: symbol.to_string(),
timestamp: Some(format!("{date} 10:40:00")),
day_open: 10.0,
open: 10.0,
high: 11.0,
low: 9.8,
close: 10.8,
last_price: 10.8,
bid1: 10.79,
ask1: 10.81,
prev_close: 10.5,
volume: 200_000,
tick_volume: 1_000,
bid1_volume: 2_000,
ask1_volume: 2_000,
trading_phase: Some("continuous".to_string()),
paused: false,
upper_limit: 11.55,
lower_limit: 9.45,
price_tick: 0.01,
})
.collect(),
[first_date, second_date]
.iter()
.map(|date| DailyFactorSnapshot {
date: *date,
symbol: symbol.to_string(),
market_cap_bn: 20.0,
free_float_cap_bn: 20.0,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
})
.collect(),
[first_date, second_date]
.iter()
.map(|date| CandidateEligibility {
date: *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,
})
.collect(),
[first_date, second_date]
.iter()
.map(|date| BenchmarkSnapshot {
date: *date,
benchmark: "000852.SH".to_string(),
open: 1000.0,
close: 1000.0,
prev_close: 999.0,
volume: 1_000_000,
})
.collect(),
)
.expect("dataset");
let subscriptions = BTreeSet::new();
let empty_portfolio = PortfolioState::new(1_000_000.0);
let first_ctx = StrategyContext {
execution_date: first_date,
decision_date: first_date,
decision_index: 1,
data: &data,
portfolio: &empty_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 held_portfolio = PortfolioState::new(1_000_000.0);
held_portfolio
.position_mut(symbol)
.buy(first_date, 4_000, 10.52);
let second_ctx = StrategyContext {
execution_date: second_date,
decision_date: second_date,
decision_index: 2,
data: &data,
portfolio: &held_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.aiquant_transaction_cost = true;
cfg.signal_symbol = symbol.to_string();
cfg.exposure_expr = "0.5".to_string();
cfg.selection_limit_expr = "40".to_string();
cfg.stock_filter_expr = "false".to_string();
cfg.stop_loss_expr.clear();
cfg.take_profit_expr.clear();
let mut strategy = PlatformExprStrategy::new(cfg);
let first_decision = strategy
.on_day(&first_ctx)
.expect("first platform decision");
assert!(
!first_decision.order_intents.iter().any(|intent| matches!(
intent,
OrderIntent::Shares { reason, .. } if reason == "daily_position_target_adjust"
)),
"{:?}",
first_decision.order_intents
);
let second_decision = strategy
.on_day(&second_ctx)
.expect("second platform decision");
assert!(
!second_decision.order_intents.iter().any(|intent| matches!(
intent,
OrderIntent::Shares { reason, .. } if reason == "daily_position_target_adjust"
)),
"{:?}",
second_decision.order_intents
);
}
#[test]
fn platform_aiquant_skips_positive_target_adjust_when_position_will_close() {
let prev_date = d(2023, 5, 11);
@@ -14700,6 +14872,181 @@ mod tests {
));
}
#[test]
fn platform_selection_ranks_by_candidate_market_cap_with_current_precomputed_factors() {
let prev = d(2025, 1, 2);
let curr = d(2025, 1, 3);
let symbols = ["300001.SZ", "300002.SZ", "000001.SZ"];
let data = DataSet::from_components(
symbols
.iter()
.map(|symbol| 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(),
})
.collect(),
[prev, curr]
.into_iter()
.flat_map(|date| {
symbols.iter().map(move |symbol| DailyMarketSnapshot {
date,
symbol: (*symbol).to_string(),
timestamp: Some("2025-01-03 09:33:00".to_string()),
day_open: 10.0,
open: 10.0,
high: 10.5,
low: 9.8,
close: 10.0,
last_price: 10.0,
bid1: 9.99,
ask1: 10.01,
prev_close: 9.9,
volume: 1_000_000,
tick_volume: 10_000,
bid1_volume: 2_000,
ask1_volume: 2_000,
trading_phase: Some("continuous".to_string()),
paused: false,
upper_limit: 11.0,
lower_limit: 9.0,
price_tick: 0.01,
})
})
.collect(),
vec![
DailyFactorSnapshot {
date: prev,
symbol: "300001.SZ".to_string(),
market_cap_bn: 30.0,
free_float_cap_bn: 30.0,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
},
DailyFactorSnapshot {
date: prev,
symbol: "300002.SZ".to_string(),
market_cap_bn: 10.0,
free_float_cap_bn: 10.0,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
},
DailyFactorSnapshot {
date: curr,
symbol: "300001.SZ".to_string(),
market_cap_bn: 10.0,
free_float_cap_bn: 10.0,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
},
DailyFactorSnapshot {
date: curr,
symbol: "300002.SZ".to_string(),
market_cap_bn: 30.0,
free_float_cap_bn: 30.0,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
},
],
[prev, curr]
.into_iter()
.flat_map(|date| {
["300001.SZ", "300002.SZ"]
.into_iter()
.map(move |symbol| 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,
})
})
.collect(),
[prev, curr]
.into_iter()
.map(|date| BenchmarkSnapshot {
date,
benchmark: "000852.SH".to_string(),
open: 1000.0,
close: 1002.0,
prev_close: 998.0,
volume: 1_000_000,
})
.collect(),
)
.expect("dataset");
let portfolio = PortfolioState::new(30_000.0);
let subscriptions = BTreeSet::new();
let ctx = StrategyContext {
execution_date: curr,
decision_date: curr,
decision_index: 1,
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.signal_symbol = "000001.SZ".to_string();
cfg.refresh_rate = 99;
cfg.max_positions = 1;
cfg.benchmark_short_ma_days = 1;
cfg.benchmark_long_ma_days = 1;
cfg.market_cap_lower_expr = "0".to_string();
cfg.market_cap_upper_expr = "100".to_string();
cfg.selection_limit_expr = "1".to_string();
cfg.stock_filter_expr = "close > 0".to_string();
cfg.current_day_precomputed_factors = true;
cfg.retry_empty_rebalance = true;
let mut strategy = PlatformExprStrategy::new(cfg);
let decision = strategy.on_day(&ctx).expect("platform decision");
assert!(
decision
.diagnostics
.iter()
.any(|item| item.contains("selection_universe_factor_date=2025-01-02")),
"{:?}",
decision.diagnostics
);
assert!(
decision
.diagnostics
.iter()
.any(|item| item.contains("selection_factor_date=2025-01-03")),
"{:?}",
decision.diagnostics
);
assert!(matches!(
decision.order_intents.first(),
Some(crate::strategy::OrderIntent::Value { symbol, .. }) if symbol == "300002.SZ"
));
}
#[test]
fn platform_stock_state_can_prefer_precomputed_rolling_factors() {
let dates = [
@@ -14817,6 +15164,34 @@ mod tests {
assert_eq!(stock.stock_volume_ma5, 1_000.0);
}
#[test]
fn precomputed_rolling_mean_ignores_strategy_specific_v104_labels() {
let mut extra_factors = BTreeMap::new();
extra_factors.insert("sf_jq_v104_ma5".to_string(), 99.0);
extra_factors.insert("sf_jq_v104_v100".to_string(), 88.0);
assert_eq!(
precomputed_stock_rolling_mean(&extra_factors, "close", 5),
None
);
assert_eq!(
precomputed_stock_rolling_mean(&extra_factors, "volume", 100),
None
);
extra_factors.insert("ma5_prev_close".to_string(), 10.5);
extra_factors.insert("avg_volume100".to_string(), 120_000.0);
assert_eq!(
precomputed_stock_rolling_mean(&extra_factors, "close", 5),
Some(10.5)
);
assert_eq!(
precomputed_stock_rolling_mean(&extra_factors, "volume", 100),
Some(120_000.0)
);
}
#[test]
fn platform_strategy_emits_target_shares_explicit_action() {
let date = d(2025, 2, 3);