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Support clearing ticks ('last' & 'trade') fills 

Previously we only simulated paper engine fills when the data feed
provide L1 queue-levels matched an execution. This patch add further
support for clear-level matches when there are real live clears on the
data feed that are faster/not synced with the L1 (aka usually during
periods of HFT).

The solution was to simply iterate the interleaved paper book entries on
both sides for said tick types and instead yield side-specific predicate
per entry.
size_in_shm_token
Tyler Goodlet 2022-08-25 15:27:05 -04:00
parent fe3d0c6fdd
commit 4cedfedc21
1 changed files with 57 additions and 34 deletions
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91
piker/clearing/_paper_engine.py
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@ -22,6 +22,7 @@ from collections import defaultdict
from contextlib import asynccontextmanager
from datetime import datetime
from operator import itemgetter
import itertools
import time
from typing import (
Any,
@ -324,6 +325,26 @@ async def simulate_fills(
# dark order price filter(s)
types=('ask', 'bid', 'trade', 'last')
):
tick_price = tick['price']
buys: bidict[str, tuple] = client._buys[sym]
iter_buys = reversed(sorted(
buys.values(),
key=itemgetter(0),
))
def sell_on_bid(our_price):
return tick_price <= our_price
sells: bidict[str, tuple] = client._sells[sym]
iter_sells = sorted(
sells.values(),
key=itemgetter(0)
)
def buy_on_ask(our_price):
return tick_price >= our_price
match tick:
case {
'price': tick_price,
@ -335,13 +356,10 @@ async def simulate_fills(
tick.get('size', client.last_ask[1]),
)
# orders = client._buys.get(sym, {})
orders = client._buys[sym]
book_sequence = reversed(
sorted(orders.values(), key=itemgetter(0)))
def pred(our_price):
return tick_price <= our_price
iter_entries = zip(
iter_buys,
itertools.repeat(sell_on_bid)
)
case {
'price': tick_price,
@ -352,40 +370,48 @@ async def simulate_fills(
tick_price,
tick.get('size', client.last_bid[1]),
)
# orders = client._sells.get(sym, {})
orders = client._sells[sym]
book_sequence = sorted(
orders.values(),
key=itemgetter(0)
)
def pred(our_price):
return tick_price >= our_price
iter_entries = zip(
iter_sells,
itertools.repeat(buy_on_ask)
)
case {
'price': tick_price,
'type': ('trade' | 'last'),
}:
# TODO: simulate actual book queues and our
# orders place in it, might require full L2
# data?
continue
# in the clearing price / last price case we
# want to iterate both sides of our book for
# clears since we don't know which direction the
# price is going to move (especially with HFT)
# and thus we simply interleave both sides (buys
# and sells) until one side clears and then
# break until the next tick?
def interleave():
for pair in zip(
iter_buys,
iter_sells,
):
for order_info, pred in zip(
pair,
itertools.cycle([sell_on_bid, buy_on_ask]),
):
yield order_info, pred
# iterate book prices descending
# for oid, our_price in book_sequence:
# print(tick)
# print((
# sym,
# list(book_sequence),
# client._buys,
# client._sells,
# ))
for order_info in book_sequence:
iter_entries = interleave()
# iterate all potentially clearable book prices
# in FIFO order per side.
for order_info, pred in iter_entries:
(our_price, size, reqid, action) = order_info
clearable = pred(our_price)
if clearable:
# retreive order info
oid = orders.inverse.pop(order_info)
# pop and retreive order info
oid = {
'buy': buys,
'sell': sells
}[action].inverse.pop(order_info)
# clearing price would have filled entirely
await client.fake_fill(
@ -397,9 +423,6 @@ async def simulate_fills(
reqid=reqid,
oid=oid,
)
else:
# prices are iterated in sorted order so we're done
break
async def handle_order_requests(