5 Commits

Author SHA1 Message Date
boris
2165831708 使用前一交易日指数价格计算市值区间,模拟实盘场景
- 修改trading_ratio()返回5个值,包含prev_level
- 使用prev_level计算市值区间,符合实盘决策逻辑
- 调整默认参数对齐AiQuant实际运行版本(xs=0.008, cap_span=10)
- 增强MA过滤调试日志,输出首个决策日所有股票的过滤详情
- 添加市值区间计算调试日志
2026-05-12 18:03:56 +08:00
boris
1a402f2048 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
2026-05-11 20:38:12 +08:00
boris
bbe60537ff 修复MA过滤器逻辑错误和成交量过滤器策略名称匹配
- 修复MA过滤器:第二个比较添加 * rsi_rate (ma10 * rsi_rate > ma30)
- 修复成交量过滤器:使用contains匹配策略名称而非精确匹配
- 添加调试日志用于诊断MA过滤问题
- 同时修复strategy.rs和platform_strategy_spec.rs中的逻辑
2026-05-11 20:13:52 +08:00
boris
3b033fd294 修复 core 执行层默认添加 new_listing 的问题
问题:
- platform expr 选股从 eligible_universe_on 开始
- eligible_universe_on 无条件过滤新股
- 导致即使 strategy_spec.universe.exclude 不含 new_listing,仍会过滤新股

修复:
- StrategyRuntimeSpec 补 universe_exclude 字段
- platform expr 选股从 factor/candidate/market 合并开始
- 按 strategy_spec.universe.exclude 自己决定是否排除 new_listing
- 补回归测试

相关:
- 保持旧策略默认排除不变
- 新策略可以显式不排除新股
2026-05-09 02:08:36 -07:00
boris
d9de9715ef chore: 更新 fidc-backtest-engine - 2026-05-08 2026-05-08 19:57:49 -07:00
5 changed files with 580 additions and 17 deletions

View File

@@ -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") {

View File

@@ -4190,6 +4190,77 @@ impl PlatformExprStrategy {
}
}
fn selectable_universe_on(
&self,
ctx: &StrategyContext<'_>,
date: NaiveDate,
) -> Vec<EligibleUniverseSnapshot> {
let mut rows = Vec::new();
for factor in ctx.data.factor_snapshots_on(date) {
if factor.market_cap_bn <= 0.0 || !factor.market_cap_bn.is_finite() {
continue;
}
if ctx.has_dynamic_universe() && !ctx.dynamic_universe_contains(&factor.symbol) {
continue;
}
let Some(candidate) = ctx.data.candidate(date, &factor.symbol) else {
continue;
};
let Some(market) = ctx.data.market(date, &factor.symbol) else {
continue;
};
if market.paused {
continue;
}
if !self.stock_passes_universe_exclude(
candidate,
market,
self.special_name(ctx, &factor.symbol),
) {
continue;
}
rows.push(EligibleUniverseSnapshot {
symbol: factor.symbol.clone(),
market_cap_bn: factor.market_cap_bn,
free_float_cap_bn: factor.free_float_cap_bn,
});
}
rows.sort_by(|left, right| {
left.market_cap_bn
.partial_cmp(&right.market_cap_bn)
.unwrap_or(std::cmp::Ordering::Equal)
.then_with(|| left.symbol.cmp(&right.symbol))
});
rows
}
fn stock_passes_universe_exclude(
&self,
candidate: &crate::data::CandidateEligibility,
market: &DailyMarketSnapshot,
has_special_name: bool,
) -> bool {
let excludes = &self.config.universe_exclude;
if excludes.iter().any(|item| item == "paused") && (market.paused || candidate.is_paused) {
return false;
}
if excludes.iter().any(|item| item == "st") && (candidate.is_st || has_special_name) {
return false;
}
if excludes.iter().any(|item| item == "kcb") && candidate.is_kcb {
return false;
}
if excludes.iter().any(|item| item == "new_listing") && candidate.is_new_listing {
return false;
}
if excludes.iter().any(|item| item == "one_yuan")
&& (candidate.is_one_yuan || market.day_open <= 1.0)
{
return false;
}
candidate.allow_buy && candidate.allow_sell
}
fn stock_numeric_field_value(
&self,
candidate: &EligibleUniverseSnapshot,
@@ -4353,7 +4424,7 @@ impl PlatformExprStrategy {
band_high: f64,
limit: usize,
) -> Result<(Vec<String>, Vec<String>), BacktestError> {
let universe = ctx.eligible_universe_on(date);
let universe = self.selectable_universe_on(ctx, date);
let mut diagnostics = Vec::new();
let mut candidates = Vec::new();
for candidate in universe {
@@ -4612,18 +4683,13 @@ impl Strategy for PlatformExprStrategy {
0
};
let stock_list = if self.config.rotation_enabled {
let selection_scan_limit = if self.config.daily_top_up_enabled {
selection_limit.saturating_add(80).max(120)
} else {
selection_limit
};
let (stock_list, notes) = self.select_symbols(
ctx,
decision_date,
&day,
band_low,
band_high,
selection_scan_limit,
selection_limit,
)?;
selection_notes = notes;
stock_list
@@ -5850,6 +5916,152 @@ mod tests {
);
}
#[test]
fn platform_strategy_honors_configured_universe_excludes_for_new_listings() {
let date = d(2025, 2, 3);
let symbols = ["301001.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(2025, 1, 1)),
delisted_at: None,
status: "active".to_string(),
})
.collect(),
symbols
.iter()
.map(|symbol| DailyMarketSnapshot {
date,
symbol: (*symbol).to_string(),
timestamp: Some("2025-02-03 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,
symbol: "301001.SZ".to_string(),
market_cap_bn: 8.0,
free_float_cap_bn: 7.0,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
},
DailyFactorSnapshot {
date,
symbol: "000001.SZ".to_string(),
market_cap_bn: 12.0,
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(),
},
],
vec![
CandidateEligibility {
date,
symbol: "301001.SZ".to_string(),
is_st: false,
is_new_listing: true,
is_paused: false,
allow_buy: true,
allow_sell: true,
is_kcb: false,
is_one_yuan: false,
},
CandidateEligibility {
date,
symbol: "000001.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: "000852.SH".to_string(),
open: 1000.0,
close: 1002.0,
prev_close: 998.0,
volume: 1_000_000,
}],
)
.expect("dataset");
let portfolio = PortfolioState::new(1_000_000.0);
let subscriptions = BTreeSet::new();
let 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 cfg = PlatformExprStrategyConfig::microcap_rotation();
cfg.signal_symbol = "000001.SZ".to_string();
cfg.refresh_rate = 1;
cfg.max_positions = 1;
cfg.benchmark_short_ma_days = 1;
cfg.benchmark_long_ma_days = 1;
cfg.stock_short_ma_days = 1;
cfg.stock_mid_ma_days = 1;
cfg.stock_long_ma_days = 1;
cfg.universe_exclude = vec![
"paused".to_string(),
"st".to_string(),
"kcb".to_string(),
"one_yuan".to_string(),
];
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 = "true".to_string();
let mut strategy = PlatformExprStrategy::new(cfg);
let decision = strategy.on_day(&ctx).expect("platform decision");
assert!(decision.order_intents.iter().any(|intent| matches!(
intent,
crate::strategy::OrderIntent::Value { symbol, .. } if symbol == "301001.SZ"
)));
}
#[test]
fn platform_helpers_support_generic_rolling_stats_and_normalized_factors() {
let dates = [d(2025, 1, 2), d(2025, 1, 3), d(2025, 1, 6)];
@@ -6121,6 +6333,139 @@ mod tests {
assert_eq!(decision.order_intents.len(), 1);
}
#[test]
fn platform_daily_top_up_keeps_selection_limited_to_target_count() {
let date = d(2025, 2, 3);
let symbols = ["000001.SZ", "000002.SZ", "000003.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(),
symbols
.iter()
.map(|symbol| DailyMarketSnapshot {
date,
symbol: (*symbol).to_string(),
timestamp: Some("2025-02-03 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(),
symbols
.iter()
.enumerate()
.map(|(index, symbol)| DailyFactorSnapshot {
date,
symbol: (*symbol).to_string(),
market_cap_bn: 10.0 + index as f64,
free_float_cap_bn: 10.0 + index as f64,
pe_ttm: 8.0,
turnover_ratio: Some(1.0),
effective_turnover_ratio: Some(1.0),
extra_factors: BTreeMap::new(),
})
.collect(),
symbols
.iter()
.map(|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(),
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(30_000.0);
let subscriptions = BTreeSet::new();
let ctx = StrategyContext {
execution_date: date,
decision_date: date,
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 = 2;
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 = "2".to_string();
cfg.stock_filter_expr = "close > 0".to_string();
cfg.daily_top_up_enabled = 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("selected=2")),
"{:?}",
decision.diagnostics
);
assert!(
!decision
.diagnostics
.iter()
.any(|item| item.contains("selected=3")),
"{:?}",
decision.diagnostics
);
}
#[test]
fn platform_strategy_emits_target_shares_explicit_action() {
let date = d(2025, 2, 3);

View File

@@ -20,6 +20,8 @@ pub struct StrategyRuntimeSpec {
#[serde(default)]
pub benchmark: Option<StrategyBenchmarkSpec>,
#[serde(default)]
pub universe: Option<StrategyUniverseSpec>,
#[serde(default)]
pub signal_symbol: Option<String>,
#[serde(default)]
pub execution: Option<StrategyExecutionSpec>,
@@ -40,6 +42,13 @@ pub struct StrategyBenchmarkSpec {
pub fallback_instrument_id: Option<String>,
}
#[derive(Debug, Clone, Default, Deserialize, Serialize)]
#[serde(rename_all = "camelCase")]
pub struct StrategyUniverseSpec {
#[serde(default)]
pub exclude: Vec<String>,
}
#[derive(Debug, Clone, Default, Deserialize, Serialize)]
#[serde(rename_all = "camelCase")]
pub struct StrategyExecutionSpec {
@@ -105,6 +114,15 @@ pub struct DynamicRangeConfig {
pub cap_span: Option<f64>,
#[serde(default)]
pub xs: Option<f64>,
/// Padding ratio to expand the market cap range (e.g., 0.5 means 50% of span)
#[serde(default)]
pub padding_ratio: Option<f64>,
/// Minimum padding in billion yuan
#[serde(default)]
pub min_padding: Option<f64>,
/// Maximum padding in billion yuan
#[serde(default)]
pub max_padding: Option<f64>,
}
#[derive(Debug, Clone, Default, Deserialize, Serialize)]
@@ -424,6 +442,14 @@ pub fn platform_expr_config_from_spec(
cfg.signal_symbol = spec_signal_symbol.clone();
}
}
if let Some(universe) = spec.universe.as_ref() {
cfg.universe_exclude = universe
.exclude
.iter()
.map(|item| item.trim().to_ascii_lowercase())
.filter(|item| !item.is_empty())
.collect();
}
let mut prelude_parts = Vec::new();
if let Some(runtime_expr) = spec.runtime_expressions.as_ref()
@@ -619,8 +645,8 @@ pub fn platform_expr_config_from_spec(
if let Some(stock_ma_filter) = engine.stock_ma_filter.as_ref() {
let ratio = stock_ma_filter.rsi_rate.unwrap_or(1.0001);
cfg.stock_filter_expr = format!(
"stock_ma_short > stock_ma_mid * {} && stock_ma_mid > stock_ma_long",
ratio
"stock_ma_short > stock_ma_mid * {} && stock_ma_mid * {} > stock_ma_long",
ratio, ratio
);
}
if let Some(index_throttle) = engine.index_throttle.as_ref() {
@@ -1024,6 +1050,7 @@ mod tests {
"strategyId": "runtime_spec_test",
"signalSymbol": "000852.SH",
"benchmark": { "instrumentId": "000852.SH" },
"universe": { "exclude": ["paused", "st", "kcb", "one_yuan"] },
"runtimeExpressions": {
"prelude": "let stocknum = 8;",
"selection": {
@@ -1054,6 +1081,7 @@ mod tests {
assert_eq!(cfg.strategy_name, "runtime_spec_test");
assert_eq!(cfg.signal_symbol, "000852.SH");
assert_eq!(cfg.selection_limit_expr, "stocknum");
assert_eq!(cfg.universe_exclude, ["paused", "st", "kcb", "one_yuan"]);
assert!(!cfg.rotation_enabled);
assert!(cfg.daily_top_up_enabled);
assert!(cfg.retry_empty_rebalance);

View File

@@ -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: 4.0 / 500.0,
base_index_level: 2000.0,
base_cap_floor: 7.0,
cap_span: 10.0,
padding_ratio: 1.2,
min_padding: 29.5,
max_padding: 50.0,
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();
@@ -2097,7 +2141,8 @@ impl OmniMicroCapStrategy {
&self,
ctx: &StrategyContext<'_>,
date: NaiveDate,
) -> Result<(f64, f64, f64, f64), BacktestError> {
) -> Result<(f64, f64, f64, f64, f64), BacktestError> {
// 当前交易日的指数价格用于MA计算和仓位控制
let current_level = ctx
.data
.market_decision_close(date, &self.config.benchmark_signal_symbol)
@@ -2106,6 +2151,16 @@ impl OmniMicroCapStrategy {
symbol: self.config.benchmark_signal_symbol.clone(),
field: "decision_close",
})?;
// 前一交易日的指数价格(用于市值区间计算,模拟实盘场景)
let prev_level = if let Some(prev_date) = ctx.data.previous_trading_date(date, 1) {
ctx.data
.market_decision_close(prev_date, &self.config.benchmark_signal_symbol)
.unwrap_or(current_level)
} else {
current_level
};
let ma_short = ctx
.data
.market_decision_close_moving_average(
@@ -2137,14 +2192,25 @@ impl OmniMicroCapStrategy {
} else {
1.0
};
Ok((current_level, ma_short, ma_long, trading_ratio))
Ok((current_level, prev_level, ma_short, ma_long, trading_ratio))
}
fn market_cap_band(&self, index_level: f64) -> (f64, f64) {
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(
@@ -2175,7 +2241,57 @@ 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 ALL stocks on first decision date
static DEBUG_DATE: std::sync::Mutex<Option<NaiveDate>> = std::sync::Mutex::new(None);
let mut debug_date = DEBUG_DATE.lock().unwrap();
let should_debug = if let Some(d) = *debug_date {
d == date
} else {
*debug_date = Some(date);
true
};
if should_debug {
eprintln!("[MA_FILTER] {} cap={:.2} ma5={:.4} ma10={:.4} ma30={:.4} ma10*rsi={:.4} pass={} ({}>{:.4}? {} && {:.4}>{}? {})",
symbol,
ctx.data.market_decision_close(date, symbol).unwrap_or(0.0),
ma_short, ma_mid, ma_long,
ma_mid * self.config.rsi_rate,
ma_pass,
ma_short, ma_mid * self.config.rsi_rate, ma_short > ma_mid * self.config.rsi_rate,
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 {
@@ -2546,7 +2662,7 @@ impl Strategy for OmniMicroCapStrategy {
});
}
let (index_level, ma_short, ma_long, trading_ratio) = match self.trading_ratio(ctx, date) {
let (index_level, prev_index_level, ma_short, ma_long, trading_ratio) = match self.trading_ratio(ctx, date) {
Ok(value) => value,
Err(BacktestError::Execution(message))
if message.contains("insufficient benchmark") =>
@@ -2564,7 +2680,10 @@ impl Strategy for OmniMicroCapStrategy {
}
Err(err) => return Err(err),
};
let (band_low, band_high) = self.market_cap_band(index_level);
// 使用前一交易日的指数价格计算市值区间(模拟实盘场景)
let (band_low, band_high) = self.market_cap_band(prev_index_level);
eprintln!("[DEBUG] date={} current_index={:.2} prev_index={:.2} band=[{:.0}, {:.0}]",
date, index_level, prev_index_level, band_low, band_high);
let (stock_list, selection_notes) = self.select_symbols(ctx, date, band_low, band_high)?;
let periodic_rebalance = ctx.decision_index % self.config.refresh_rate == 0;
let mut projected = ctx.portfolio.clone();

View File

@@ -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)
}
}