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Add transaction costs to "fills" 

This makes a few major changes but mostly is centered around including
transaction (aka trade-clear) costs in the avg breakeven price
calculation.

TL;DR:
- rename `TradeRecord` -> `Transaction`.
- make `Position.fills` a `dict[str, float]` which holds each clear's
  cost value.
- change `Transaction.symkey` -> `.bsuid` for "backend symbol unique id".
- drop `brokername: str` arg to `update_pps()`
- rename `._split_active()` -> `dump_active()` and use input keys
  verbatim in output map.
- in `update_pps_conf()` always incrementally update from trade records
  even when no `pps.toml` exists yet since it may be both the case that
  the ledger needs loading **and** the caller is handing new records not
  yet in the ledger.
lifo_pps_ib
Tyler Goodlet 2022-06-14 14:58:21 -04:00
parent c1b63f4757
commit 412138a75b
1 changed files with 72 additions and 56 deletions
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128
piker/pp.py
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@ -15,9 +15,9 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Personal/Private position parsing, calculmating, summarizing in a way
Personal/Private position parsing, calculating, summarizing in a way
that doesn't try to cuk most humans who prefer to not lose their moneys..
(looking at you `ib` and shitzy friends)
(looking at you `ib` and dirt-bird friends)
'''
from contextlib import contextmanager as cm
@ -86,9 +86,9 @@ def open_trade_ledger(
return toml.dump(ledger, cf)
class TradeRecord(Struct):
class Transaction(Struct):
fqsn: str # normally fqsn
tid: Union[str, int]
tid: Union[str, int] # unique transaction id
size: float
price: float
cost: float # commisions or other additional costs
@ -98,7 +98,7 @@ class TradeRecord(Struct):
# optional key normally derived from the broker
# backend which ensures the instrument-symbol this record
# is for is truly unique.
symkey: Optional[Union[str, int]] = None
bsuid: Optional[Union[str, int]] = None
class Position(Struct):
@ -113,9 +113,14 @@ class Position(Struct):
# last size and avg entry price
size: float
avg_price: float # TODO: contextual pricing
bsuid: str
# ordered record of known constituent trade messages
fills: list[Union[str, int, Status]] = []
fills: dict[
Union[str, int, Status], # trade id
float, # cost
] = {}
def to_dict(self):
return {
@ -160,6 +165,7 @@ class Position(Struct):
self,
size: float,
price: float,
cost: float = 0,
# TODO: idea: "real LIFO" dynamic positioning.
# - when a trade takes place where the pnl for
@ -198,6 +204,8 @@ class Position(Struct):
self.avg_price = (
abs(size) * price # weight of current exec
+
cost # transaction cost
+
self.avg_price * abs(self.size) # weight of previous pp
) / abs(new_size)
@ -207,9 +215,7 @@ class Position(Struct):
def update_pps(
brokername: str,
records: dict[str, TradeRecord],
records: dict[str, Transaction],
pps: Optional[dict[str, Position]] = None
) -> dict[str, Position]:
@ -223,7 +229,7 @@ def update_pps(
for r in records:
pp = pps.setdefault(
r.fqsn or r.symkey,
r.fqsn or r.bsuid,
# if no existing pp, allocate fresh one.
Position(
@ -233,27 +239,39 @@ def update_pps(
),
size=0.0,
avg_price=0.0,
bsuid=r.bsuid,
)
)
# don't do updates for ledger records we already have
# included in the current pps state.
if r.tid in pp.fills:
# NOTE: likely you'll see repeats of the same
# ``TradeRecord`` passed in here if/when you are restarting
# ``Transaction`` passed in here if/when you are restarting
# a ``brokerd.ib`` where the API will re-report trades from
# the current session, so we need to make sure we don't
# "double count" these in pp calculations.
continue
# lifo style average price calc
pp.lifo_update(r.size, r.price)
pp.fills.append(r.tid)
# lifo style "breakeven" price calc
pp.lifo_update(
r.size,
r.price,
# include transaction cost in breakeven price
# and presume the worst case of the same cost
# to exit this transaction (even though in reality
# it will be dynamic based on exit stratetgy).
cost=2*r.cost,
)
# track clearing costs
pp.fills[r.tid] = r.cost
assert len(set(pp.fills)) == len(pp.fills)
return pps
def _split_active(
def dump_active(
pps: dict[str, Position],
) -> tuple[
@ -277,9 +295,9 @@ def _split_active(
fqsn = pp.symbol.front_fqsn()
asdict = pp.to_dict()
if pp.size == 0:
closed[fqsn] = asdict
closed[k] = asdict
else:
active[fqsn] = asdict
active[k] = asdict
return active, closed
@ -292,7 +310,7 @@ def load_pps_from_ledger(
) -> tuple[dict, dict]:
'''
Open a ledger file by broker name and account and read in and
process any trade records into our normalized ``TradeRecord``
process any trade records into our normalized ``Transaction``
form and then pass these into the position processing routine
and deliver the two dict-sets of the active and closed pps.
@ -305,9 +323,8 @@ def load_pps_from_ledger(
brokermod = get_brokermod(brokername)
records = brokermod.norm_trade_records(ledger)
pps = update_pps(brokername, records)
return _split_active(pps)
pps = update_pps(records)
return dump_active(pps)
def get_pps(
@ -326,57 +343,55 @@ def get_pps(
def update_pps_conf(
brokername: str,
acctid: str,
trade_records: Optional[list[TradeRecord]] = None,
trade_records: Optional[list[Transaction]] = None,
) -> dict[str, Position]:
conf, path = config.load('pps')
brokersection = conf.setdefault(brokername, {})
entries = brokersection.setdefault(acctid, {})
if not entries:
accountsection = pps = brokersection.setdefault(acctid, {})
if not pps:
# no pps entry yet for this broker/account so parse
# any available ledgers to build a pps state.
active, closed = load_pps_from_ledger(
pps, closed = load_pps_from_ledger(
brokername,
acctid,
)
elif trade_records:
# table for map-back to object form
pps = {}
# load ``pps.toml`` config entries back into object form.
for fqsn, entry in entries.items():
pps[f'{fqsn}.{brokername}'] = Position(
Symbol.from_fqsn(fqsn, info={}),
size=entry['size'],
avg_price=entry['avg_price'],
# XXX: super critical, we need to be sure to include
# all pps.toml fills to avoid reusing fills that were
# already included in the current incremental update
# state, since today's records may have already been
# processed!
fills=entry['fills'],
if not pps:
log.warning(
f'No trade history could be loaded for {brokername}:{acctid}'
)
pps = update_pps(
brokername,
trade_records,
pps=pps,
# unmarshal/load ``pps.toml`` config entries into object form.
pp_objs = {}
for fqsn, entry in pps.items():
pp_objs[fqsn] = Position(
Symbol.from_fqsn(fqsn, info={}),
size=entry['size'],
avg_price=entry['avg_price'],
bsuid=entry['bsuid'],
# XXX: super critical, we need to be sure to include
# all pps.toml fills to avoid reusing fills that were
# already included in the current incremental update
# state, since today's records may have already been
# processed!
fills=entry['fills'],
)
active, closed = _split_active(pps)
else:
raise ValueError('wut wut')
# update all pp objects from any (new) trade records which
# were passed in (aka incremental update case).
if trade_records:
pp_objs = update_pps(
trade_records,
pps=pp_objs,
)
for fqsn in closed:
print(f'removing closed pp: {fqsn}')
entries.pop(fqsn, None)
active, closed = dump_active(pp_objs)
# dict-serialize all active pps
pp_entries = {}
for fqsn, pp_dict in active.items():
print(f'Updating active pp: {fqsn}')
@ -386,8 +401,9 @@ def update_pps_conf(
# XXX: ugh, it's cuz we push the section under
# the broker name.. maybe we need to rethink this?
brokerless_key = fqsn.rstrip(f'.{brokername}')
entries[brokerless_key] = pp_dict
pp_entries[brokerless_key] = pp_dict
conf[brokername][acctid] = pp_entries
config.write(
conf,
'pps',