Low Volatility Stocks
取引規則
VolWindowDays + 1 個の確定日足終値から VolWindowDays 区間の単純日次収益率 r[d] = P[d] / P[d−1] − 1 を計算します。変動率は標本標準偏差 sqrt(Σ(r−mean(r))² / (VolWindowDays−1)) です。毎月、変動率下位 Deciles 区分を買い、上位区分を売り、各側 floor(有効数 / Deciles) 銘柄とします。両側の米ドル予算は等しく、ベンチマーク差、トレンド判定、日中閾値は使いません。
時刻が一致する確定足だけを評価します。統計は異なる UTC 日付を数え、同じ日の後続足が日次価格を更新します。毎月最初の条件を満たす同期確定足で一度リバランスします。データ不足時は延期し、同点は Security.Id 順に並べます。
全観測値はシグナル足の終値時刻までに公表されている必要があります。日中足では当日 UTC 日付より前の日足価格だけを使い、確定日足では自身の日付を使えます。将来の CSV 日付で判断を先取りしません。
入力データ
PriceHistoryFile は正の日次終値の任意 CSV です:SecurityId,Date,Close。日付は yyyy-MM-dd。現在・将来の日付で判断を先取りせず、実際の確定足で該当 UTC 日の価格を上書きします。重複日付は禁止です。短い約定履歴で長い期間を準備するために使えます。
パラメーター
| パラメーター | 初期値 |
|---|---|
Universe |
必須 |
Capital |
100000 |
Leverage |
1 |
MinTradeUsd |
200 |
CandleType |
TimeSpan.FromDays(1).TimeFrame() |
PriceHistoryFile |
任意 — 未指定 |
VolWindowDays |
60 |
Deciles |
10 |
約定と保有数量
Universe を明示的に設定します。価格と Capital は取引単位当たりの USD です。Capital は固定予算、Leverage は総エクスポージャーを指定します。損切りや利食い注文は追加しません。
買い・売りの各バスケットに Capital × Leverage の半分を均等配分します。信号終値で数量に換算し、VolumeStep 単位でゼロ方向へ丸めます。実際の約定残高を使い、未完了注文を待ち、MinVolume/MaxVolume を守って大口調整を後続足へ分割します。MinTradeUsd は小口調整を除外しますが、全決済には適用しません。
検証
両言語を同梱 BTC/TON 約定データと明示的な金利・財務・評価・文章・事前履歴データで検証します。カレンダー検証はアーカイブの OHLC・出来高の日付を移し、決まった約定気配を与えたもので、複数年の市場履歴ではありません。独立計算、注文方向・数量、実約定、残高、禁止判断日を確認します。2区分、K=1、AssetDecile=1 は明示的な機構検証設定であり、全本番銘柄群の証明ではありません。収益を保証しません。
namespace StockSharp.Samples.Strategies;
using System;
using System.Collections.Generic;
using System.Globalization;
using System.IO;
using System.Linq;
using Ecng.Common;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
/// <summary>Low Volatility Stocks with point-in-time inputs and execution-based portfolio accounting.</summary>
public class LowVolatilityStocksStrategy : Strategy
{
private readonly StrategyParam<IEnumerable<Security>> _universe;
private readonly StrategyParam<decimal> _capital;
private readonly StrategyParam<decimal> _leverage;
private readonly StrategyParam<decimal> _minTradeUsd;
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<string> _priceHistoryFile;
private readonly StrategyParam<int> _volWindowDays;
private readonly StrategyParam<int> _deciles;
private Security[] _securities = [];
private readonly Dictionary<Security, (DateTime time, decimal price)> _latest = [];
private readonly Dictionary<Security, SortedDictionary<DateTime, decimal>> _history = [];
private readonly Dictionary<Security, decimal> _targets = [];
private readonly List<Order> _pending = [];
private int _lastRebalance;
private DateTime? _lastBar;
/// <summary>Explicit execution securities with valid native volume metadata.</summary>
public IEnumerable<Security> Universe { get => _universe.Value; set => _universe.Value = value; }
/// <summary>Fixed capital budget in USD.</summary>
public decimal Capital { get => _capital.Value; set => _capital.Value = value; }
/// <summary>Gross target exposure divided by the capital budget.</summary>
public decimal Leverage { get => _leverage.Value; set => _leverage.Value = value; }
/// <summary>Minimum USD adjustment; complete liquidation bypasses this filter.</summary>
public decimal MinTradeUsd { get => _minTradeUsd.Value; set => _minTradeUsd.Value = value; }
/// <summary>Finished execution candle type.</summary>
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
/// <summary>Optional daily close CSV; future dates cannot prefill a decision.</summary>
public string PriceHistoryFile { get => _priceHistoryFile.Value; set => _priceHistoryFile.Value = value; }
/// <summary>Completed daily returns in the sample standard deviation.</summary>
public int VolWindowDays { get => _volWindowDays.Value; set => _volWindowDays.Value = value; }
/// <summary>Number of volatility buckets.</summary>
public int Deciles { get => _deciles.Value; set => _deciles.Value = value; }
/// <summary>Initialize the strategy parameters.</summary>
public LowVolatilityStocksStrategy()
{
_universe = Param<IEnumerable<Security>>(nameof(Universe)).SetRequired()
.SetDisplay("Universe", "Explicit execution securities with valid native volume metadata", "Parameters");
_capital = Param(nameof(Capital), 100000m).SetGreaterThanZero()
.SetDisplay("Capital", "Fixed capital budget in USD", "Parameters");
_leverage = Param(nameof(Leverage), 1m).SetGreaterThanZero()
.SetDisplay("Leverage", "Gross target exposure divided by the capital budget", "Parameters");
_minTradeUsd = Param(nameof(MinTradeUsd), 200m).SetRange(0m, decimal.MaxValue)
.SetDisplay("MinTradeUsd", "Minimum USD adjustment; complete liquidation bypasses this filter", "Parameters");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1440).TimeFrame())
.SetDisplay("CandleType", "Finished execution candle type", "Parameters");
_priceHistoryFile = Param<string>(nameof(PriceHistoryFile))
.SetDisplay("PriceHistoryFile", "Optional daily close CSV; future dates cannot prefill a decision", "Parameters");
_volWindowDays = Param(nameof(VolWindowDays), 60).SetRange(2, int.MaxValue)
.SetDisplay("VolWindowDays", "Completed daily returns in the sample standard deviation", "Parameters");
_deciles = Param(nameof(Deciles), 10).SetRange(2, int.MaxValue)
.SetDisplay("Deciles", "Number of volatility buckets", "Parameters");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> (Universe ?? []).Where(s => s is not null).DistinctBy(s => s.Id, StringComparer.OrdinalIgnoreCase).Select(s => (s, CandleType));
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_securities = [];
_latest.Clear();
_history.Clear();
_targets.Clear();
_pending.Clear();
_lastRebalance = 0;
_lastBar = null;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
_securities = (Universe ?? []).ToArray();
if (_securities.Length == 0 || _securities.Any(s => s is null || string.IsNullOrWhiteSpace(s.Id))
|| _securities.Select(s => s.Id).Distinct(StringComparer.OrdinalIgnoreCase).Count() != _securities.Length)
throw new InvalidOperationException("Universe must contain distinct execution securities.");
foreach (var security in _securities)
{
if (security.VolumeStep is not > 0m || security.MinVolume is not > 0m || security.MaxVolume is not > 0m)
throw new InvalidOperationException("Every security needs positive VolumeStep, MinVolume and MaxVolume.");
_history[security] = [];
}
LoadPriceHistory();
base.OnStarted2(time);
foreach (var security in _securities)
SubscribeCandles(CandleType, security: security).Bind(candle => ProcessCandle(security, candle)).Start();
}
private void ProcessCandle(Security security, ICandleMessage candle)
{
if (candle.State != CandleStates.Finished || candle.ClosePrice <= 0m) return;
_latest[security] = (candle.OpenTime, candle.ClosePrice);
_history[security][candle.OpenTime.Date] = candle.ClosePrice;
if (_latest.Count != _securities.Length || _latest.Values.Any(v => v.time != candle.OpenTime)
|| _lastBar == candle.OpenTime || !IsFormedAndOnlineAndAllowTrading()) return;
_lastBar = candle.OpenTime;
var month = candle.OpenTime.Year * 100 + candle.OpenTime.Month;
if (_lastRebalance != month && SelectTargets(candle.OpenTime))
_lastRebalance = month;
ReconcileTargets();
}
private decimal Budget => Capital * Leverage;
private DateTime AsOf(DateTime time)
=> CandleType.Arg is TimeSpan frame ? time.Add(frame).AddTicks(-1) : time;
private decimal UnitPrice(Security security) => _latest[security].price;
private decimal Units(Security security, decimal notional)
=> Math.Floor(notional / UnitPrice(security) / security.VolumeStep.Value) * security.VolumeStep.Value;
private void ReconcileTargets()
{
if (_pending.Any(o => o.State is not (OrderStates.Done or OrderStates.Failed))) return;
_pending.Clear();
foreach (var security in _securities)
{
if (!_targets.TryGetValue(security, out var target)) continue;
var delta = target - GetPositionValue(security, Portfolio).GetValueOrDefault();
if (delta == 0m || (target != 0m && Math.Abs(delta) * UnitPrice(security) < MinTradeUsd)) continue;
var step = security.VolumeStep.Value;
var quantity = Math.Floor(Math.Min(Math.Abs(delta), security.MaxVolume.Value) / step) * step;
if (quantity < security.MinVolume.Value) continue;
var order = new Order
{
Security = security, Portfolio = Portfolio, Type = OrderTypes.Market,
Side = delta > 0m ? Sides.Buy : Sides.Sell, Volume = quantity, Comment = "0377Rebalance",
};
_pending.Add(order);
RegisterOrder(order);
}
}
private static DateTime ParseUtc(string value)
=> DateTime.ParseExact(value.Trim(), "yyyy-MM-dd'T'HH:mm:ss'Z'", CultureInfo.InvariantCulture, DateTimeStyles.AssumeUniversal | DateTimeStyles.AdjustToUniversal);
private static IEnumerable<string[]> ReadRows(string path, string header, int fields)
{
using var lines = File.ReadLines(path).GetEnumerator();
if (!lines.MoveNext() || lines.Current.Trim() != header)
throw new InvalidOperationException("Invalid CSV header: expected " + header + ".");
while (lines.MoveNext())
{
if (string.IsNullOrWhiteSpace(lines.Current)) continue;
var row = lines.Current.Split(',');
if (row.Length != fields) throw new InvalidOperationException("Invalid CSV field count.");
yield return row;
}
}
private DateTime LastClosedDate(DateTime time)
=> CandleType.Arg is TimeSpan frame && frame == TimeSpan.FromDays(1) ? time.Date : time.Date.AddDays(-1);
private decimal[] Daily(Security security, DateTime time, int count, DateTime cutoff)
=> _history[security].Where(x => x.Key <= LastClosedDate(time) && x.Key < cutoff).Select(x => x.Value).TakeLast(count).ToArray();
private void LoadPriceHistory()
{
if (string.IsNullOrWhiteSpace(PriceHistoryFile)) return;
foreach (var row in ReadRows(PriceHistoryFile, "SecurityId,Date,Close", 3))
{
var security = _securities.SingleOrDefault(s => string.Equals(s.Id, row[0].Trim(), StringComparison.OrdinalIgnoreCase));
if (security is null) continue;
var date = DateTime.ParseExact(row[1].Trim(), "yyyy-MM-dd", CultureInfo.InvariantCulture);
var price = decimal.Parse(row[2], CultureInfo.InvariantCulture);
if (price <= 0m || !_history[security].TryAdd(date, price))
throw new InvalidOperationException("Daily prices must be positive and unique per security and UTC date.");
}
}
private bool SelectTargets(DateTime time)
{
var scores = new List<(Security security, double score)>();
foreach (var security in _securities)
{
var prices = Daily(security, time, VolWindowDays + 1, DateTime.MaxValue);
if (prices.Length != VolWindowDays + 1) continue;
var returns = prices.Skip(1).Select((p, i) => (double)(p / prices[i] - 1m)).ToArray();
var mean = returns.Average();
var deviation = Math.Sqrt(returns.Sum(r => (r - mean) * (r - mean)) / (VolWindowDays - 1));
scores.Add((security, deviation));
}
if (scores.Count < Deciles) return false;
var ranked = scores.OrderBy(x => x.score).ThenBy(x => x.security.Id, StringComparer.Ordinal).Select(x => x.security).ToArray();
var count = ranked.Length / Deciles;
SetBasketTargets(ranked.Take(count), ranked.TakeLast(count), Budget);
return true;
}
private void SetBasketTargets(IEnumerable<Security> longBasket, IEnumerable<Security> shortBasket, decimal grossCapital)
{
var longs = longBasket.ToArray();
var shorts = shortBasket.ToArray();
foreach (var security in _securities) _targets[security] = 0m;
foreach (var security in longs) _targets[security] = Units(security, grossCapital / (2m * longs.Length));
foreach (var security in shorts) _targets[security] = -Units(security, grossCapital / (2m * shorts.Length));
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.BusinessEntities")
clr.AddReference("StockSharp.Algo.Strategies")
from System import Boolean, DateTime, Decimal, Int32, Math, TimeSpan, InvalidOperationException
from System.Collections.Generic import IEnumerable
from System.Globalization import CultureInfo, DateTimeStyles
from System.IO import File, Path
from StockSharp.Algo.Strategies import Strategy
from StockSharp.BusinessEntities import Order, Security
from StockSharp.Messages import CandleStates, DataType, OrderStates, OrderTypes, Sides
class low_volatility_stocks_strategy(Strategy):
"""Low Volatility Stocks with point-in-time inputs and execution-based portfolio accounting."""
def __init__(self):
super(low_volatility_stocks_strategy, self).__init__()
self._universe = self.Param[IEnumerable[Security]]("Universe", None).SetRequired() \
.SetDisplay("Universe", "Explicit execution securities with valid native volume metadata", "Parameters")
self._capital = self.Param("Capital", Decimal(100000)).SetGreaterThanZero() \
.SetDisplay("Capital", "Fixed capital budget in USD", "Parameters")
self._leverage = self.Param("Leverage", Decimal(1)).SetGreaterThanZero() \
.SetDisplay("Leverage", "Gross target exposure divided by the capital budget", "Parameters")
self._min_trade_usd = self.Param("MinTradeUsd", Decimal(200)).SetRange(Decimal(0), Decimal.MaxValue) \
.SetDisplay("MinTradeUsd", "Minimum USD adjustment; complete liquidation bypasses this filter", "Parameters")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(1440))) \
.SetDisplay("CandleType", "Finished execution candle type", "Parameters")
self._price_history_file = self.Param[str]("PriceHistoryFile", None) \
.SetDisplay("PriceHistoryFile", "Optional daily close CSV; future dates cannot prefill a decision", "Parameters")
self._vol_window_days = self.Param("VolWindowDays", 60).SetRange(2, 2147483647) \
.SetDisplay("VolWindowDays", "Completed daily returns in the sample standard deviation", "Parameters")
self._deciles = self.Param("Deciles", 10).SetRange(2, 2147483647) \
.SetDisplay("Deciles", "Number of volatility buckets", "Parameters")
self._clear_state()
def _clear_state(self):
self._securities = []
self._latest = {}
self._history = {}
self._targets = {}
self._pending = []
self._last_rebalance = 0
self._last_bar = None
@property
def Universe(self):
return self._universe.Value
@Universe.setter
def Universe(self, value):
self._universe.Value = value
@property
def Capital(self):
return self._capital.Value
@Capital.setter
def Capital(self, value):
self._capital.Value = value
@property
def Leverage(self):
return self._leverage.Value
@Leverage.setter
def Leverage(self, value):
self._leverage.Value = value
@property
def MinTradeUsd(self):
return self._min_trade_usd.Value
@MinTradeUsd.setter
def MinTradeUsd(self, value):
self._min_trade_usd.Value = value
@property
def CandleType(self):
return self._candle_type.Value
@CandleType.setter
def CandleType(self, value):
self._candle_type.Value = value
@property
def PriceHistoryFile(self):
return self._price_history_file.Value
@PriceHistoryFile.setter
def PriceHistoryFile(self, value):
self._price_history_file.Value = value
@property
def VolWindowDays(self):
return self._vol_window_days.Value
@VolWindowDays.setter
def VolWindowDays(self, value):
self._vol_window_days.Value = value
@property
def Deciles(self):
return self._deciles.Value
@Deciles.setter
def Deciles(self, value):
self._deciles.Value = value
def GetWorkingSecurities(self):
return [(s, self.CandleType) for s in self.Universe] if self.Universe is not None else []
def OnReseted(self):
super(low_volatility_stocks_strategy, self).OnReseted()
self._clear_state()
def OnStarted2(self, time):
self._securities = list(self.Universe) if self.Universe is not None else []
if not self._securities or any(s is None or not s.Id for s in self._securities) or len(set(s.Id.upper() for s in self._securities)) != len(self._securities):
raise InvalidOperationException("Universe must contain distinct execution securities.")
for security in self._securities:
if security.VolumeStep is None or security.MinVolume is None or security.MaxVolume is None or security.VolumeStep <= 0 or security.MinVolume <= 0 or security.MaxVolume <= 0:
raise InvalidOperationException("Every security needs positive VolumeStep, MinVolume and MaxVolume.")
self._history[security] = {}
self._load_price_history()
super(low_volatility_stocks_strategy, self).OnStarted2(time)
for security in self._securities:
self.SubscribeCandles(self.CandleType, True, security).Bind(lambda candle, s=security: self._process_candle(s, candle)).Start()
def _process_candle(self, security, candle):
if candle.State != CandleStates.Finished or candle.ClosePrice <= 0:
return
self._latest[security] = (candle.OpenTime, candle.ClosePrice)
self._history[security][candle.OpenTime.Date] = candle.ClosePrice
if len(self._latest) != len(self._securities) or any(t != candle.OpenTime for t, p in self._latest.values()) or self._last_bar == candle.OpenTime or not self.IsFormedAndOnlineAndAllowTrading():
return
self._last_bar = candle.OpenTime
month = candle.OpenTime.Year * 100 + candle.OpenTime.Month
if self._last_rebalance != month and self._select_targets(candle.OpenTime):
self._last_rebalance = month
self._reconcile_targets()
def _budget(self):
return self.Capital * self.Leverage
def _as_of(self, time):
return time.Add(self.CandleType.Arg).AddTicks(-1)
def _unit_price(self, security):
return self._latest[security][1]
def _units(self, security, notional):
return Math.Floor(notional / self._unit_price(security) / security.VolumeStep) * security.VolumeStep
def _reconcile_targets(self):
if any(o.State != OrderStates.Done and o.State != OrderStates.Failed for o in self._pending):
return
self._pending = []
for security in self._securities:
if security not in self._targets:
continue
target = self._targets[security]
position = self.GetPositionValue(security, self.Portfolio)
delta = target - (position if position is not None else Decimal(0))
if delta == 0 or (target != 0 and abs(delta) * self._unit_price(security) < self.MinTradeUsd):
continue
quantity = Math.Floor(min(abs(delta), security.MaxVolume) / security.VolumeStep) * security.VolumeStep
if quantity < security.MinVolume:
continue
order = Order()
order.Security = security
order.Portfolio = self.Portfolio
order.Type = OrderTypes.Market
order.Side = Sides.Buy if delta > 0 else Sides.Sell
order.Volume = quantity
order.Comment = "0377Rebalance"
self._pending.append(order)
self.RegisterOrder(order)
@staticmethod
def _parse_utc(value):
return DateTime.ParseExact(value.strip(), "yyyy-MM-dd'T'HH:mm:ss'Z'", CultureInfo.InvariantCulture, DateTimeStyles.AssumeUniversal | DateTimeStyles.AdjustToUniversal)
@staticmethod
def _read_rows(path, header, fields):
lines = list(File.ReadLines(path))
if not lines or lines[0].strip() != header:
raise InvalidOperationException("Invalid CSV header: expected " + header + ".")
for line in lines[1:]:
if not line.strip():
continue
row = line.split(",")
if len(row) != fields:
raise InvalidOperationException("Invalid CSV field count.")
yield row
def _last_closed_date(self, time):
return time.Date if self.CandleType.Arg == TimeSpan.FromDays(1) else time.Date.AddDays(-1)
def _daily(self, security, time, count, cutoff):
dates = [d for d in sorted(self._history[security]) if d <= self._last_closed_date(time) and d < cutoff]
return [self._history[security][d] for d in dates[-count:]]
def _load_price_history(self):
if not self.PriceHistoryFile:
return
for row in self._read_rows(self.PriceHistoryFile, "SecurityId,Date,Close", 3):
security = next((s for s in self._securities if s.Id.upper() == row[0].strip().upper()), None)
if security is None:
continue
date = DateTime.ParseExact(row[1].strip(), "yyyy-MM-dd", CultureInfo.InvariantCulture)
price = Decimal.Parse(row[2], CultureInfo.InvariantCulture)
if price <= 0 or date in self._history[security]:
raise InvalidOperationException("Daily prices must be positive and unique per security and UTC date.")
self._history[security][date] = price
def _select_targets(self, time):
scores = []
for security in self._securities:
prices = self._daily(security, time, self.VolWindowDays + 1, DateTime.MaxValue)
if len(prices) != self.VolWindowDays + 1:
continue
returns = [float(prices[i] / prices[i - 1] - Decimal(1)) for i in range(1, len(prices))]
mean = sum(returns) / len(returns)
deviation = Math.Sqrt(sum((r - mean) ** 2 for r in returns) / (self.VolWindowDays - 1))
scores.append((security, deviation))
if len(scores) < self.Deciles:
return False
ranked = [s for s, score in sorted(scores, key=lambda x: (x[1], x[0].Id))]
count = len(ranked) // self.Deciles
self._set_basket_targets(ranked[:count], ranked[-count:], self._budget())
return True
def _set_basket_targets(self, longs, shorts, gross):
self._targets = {s: Decimal(0) for s in self._securities}
for security in longs:
self._targets[security] = self._units(security, gross / Decimal(2 * len(longs)))
for security in shorts:
self._targets[security] = -self._units(security, gross / Decimal(2 * len(shorts)))
def CreateClone(self):
return low_volatility_stocks_strategy()