Векторные сигналы

from ziplime.finance.execution import MarketOrder

FAST, SLOW = 20, 60
WARMUP = SLOW                    # сколько баров истории нужно самому длинному индикатору


async def initialize(context):
    context.universe = {
        "SBER": await context.symbol("SBER", mic="MISX"),
        "GAZP": await context.symbol("GAZP", mic="MISX"),
    }


def compute_signals(context, prices):           # один раз, по всей истории
    close = prices.close
    return {
        "fast": close.rolling(FAST).mean(),
        "slow": close.rolling(SLOW).mean(),
    }


async def handle_data(context, data):           # по барам, как обычно
    signals = context.signals
    if not (signals.is_ready("fast") and signals.is_ready("slow")):
        return

    for name, listing in context.universe.items():
        target = 0.5 if float(signals["fast"][name]) > float(signals["slow"][name]) else 0.0
        await context.order_target_percent(listing, target, style=MarketOrder())

Signal 'momentum' looks ahead. At bar 240 (2024-03-15) the whole-history computation
gives 1.0, but computing from the first 240 bars alone -- all that was known then --
gives 2.0.