| Overall Statistics |
|
Total Orders 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Start Equity 100000 End Equity 100000 Net Profit 0% Sharpe Ratio 0 Sortino Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -4.038 Tracking Error 0.07 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset Portfolio Turnover 0% Drawdown Recovery 0 |
# MWN (Micro Ultra U.S. Treasury Bond, CBOT) live-data probe.
# The chain has no universe files in the cloud store, so contracts are added
# one by one from their expiry ticker.
from AlgorithmImports import *
class MwnLiveDataCheck(QCAlgorithm):
TICKERS = ["MWNZ26", "MWNH27", "MWNM27"]
def initialize(self):
self.set_start_date(2026, 8, 20)
self.set_cash(100000)
self.counts = {}
for ticker in self.TICKERS:
symbol = SymbolRepresentation.parse_future_symbol(ticker)
self.add_future_contract(symbol, Resolution.MINUTE, extended_market_hours=True)
self.counts[symbol] = 0
self.log(f"INIT: {ticker} -> {symbol.value} expiry={symbol.id.date:%Y-%m-%d %H:%M}")
self.schedule.on(self.date_rules.every_day(), self.time_rules.every(timedelta(minutes=30)),
self.report)
def on_data(self, slice):
for symbol in self.counts:
bar = slice.bars.get(symbol) or slice.quote_bars.get(symbol)
if bar is None:
continue
if self.counts[symbol] == 0:
self.log(f"FIRST DATA {symbol.value} @ {self.time} close={bar.close}")
self.counts[symbol] += 1
def report(self):
counts = {symbol.value: count for symbol, count in self.counts.items()}
self.set_runtime_statistic("MWN bars", str(sum(counts.values())))
self.set_runtime_statistic("Counts", str(counts))
self.log(f"MWN bars={sum(counts.values())} {counts}")