research/pairs_trading
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This commit is contained in:
Oleg Sheynin 2026-01-23 20:15:24 +00:00
parent e6ae62ebb6
commit 8f7f82549e
5 changed files with 22 additions and 15 deletions
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4
.vscode/launch.json vendored
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@ -31,8 +31,8 @@
"PYTHONPATH": "${workspaceFolder}/..",
"CONFIG_SERVICE": "cloud16.cvtt.vpn:6789",
"MODEL_CONFIG": "vecm",
"CVTT_URL": "http://cvtt-tester-01.cvtt.vpn:23456",
// "CVTT_URL": "http://dev-server-02.cvtt.vpn:23456",
// "CVTT_URL": "http://cvtt-tester-01.cvtt.vpn:23456",
"CVTT_URL": "http://dev-server-02.cvtt.vpn:23456",
},
"args": [
// "--config=${workspaceFolder}/configuration/pair_trader.cfg",

2
LIBRARIES
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@ -1,2 +0,0 @@
cvttpy_tools: 1.3.4
cvttpy_trading: 2.4.1

2
VERSION
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@ -1 +1 @@
0.0.3
0.0.4

3
lib/live/mkt_data_client.py
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@ -196,8 +196,9 @@ class MdSummaryCollector(NamedObject):
Log.info(f"{self.fname()} Timer for {self.exch_inst_.details_short()} is set to run in {start_in} sec")
def next_load_time(self) -> NanosT:
ALLOW_LAG_SEC = 1
curr_sec = int(current_seconds())
return (curr_sec - curr_sec % self.interval_sec_) + self.interval_sec_ + 5
return (curr_sec - curr_sec % self.interval_sec_) + self.interval_sec_ + ALLOW_LAG_SEC
async def _load_new(self) -> None:

26
lib/pt_strategy/live/live_strategy.py
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@ -42,14 +42,14 @@ class PtLiveStrategy(NamedObject):
# for presentation: history of prediction values and trading signals
predictions_df_: pd.DataFrame
trading_signals_df_: pd.DataFrame
allowed_md_lag_sec_: int
def __init__(
self,
config: Config,
pairs_trader: PairTrader,
):
# import copy
# self.config_ = Config(json_src=copy.deepcopy(config.data()))
self.config_ = config
self.pairs_trader_ = pairs_trader
@ -83,6 +83,8 @@ class PtLiveStrategy(NamedObject):
)
assert self.history_depth_sec_ > 0, "history_depth_hours cannot be 0"
self.allowed_md_lag_sec_ = self.config_.get_value("allowed_md_lag_sec", 3)
await self.pairs_trader_.subscribe_md()
self.open_threshold_ = self.config_.get_value(
@ -136,23 +138,29 @@ class PtLiveStrategy(NamedObject):
Log.warning(f"{self.fname()} list of aggregates IS EMPTY")
return False
ALLOWED_LAG_SEC = 5.0
curr_ns = current_nanoseconds()
LAG_THRESHOLD = NanosT((self.interval_sec() + ALLOWED_LAG_SEC) * NanoPerSec)
# MAYBE check market data length
lag_ns = curr_ns - hist_aggr[-1].aggr_time_ns_
if lag_ns > LAG_THRESHOLD:
# at 18:05:01 we should see data for 18:04:00
lag_sec = (curr_ns - hist_aggr[-1].aggr_time_ns_) / NanoPerSec - self.interval_sec()
if lag_sec > self.allowed_md_lag_sec_:
Log.warning(
f"{self.fname()} {hist_aggr[-1].exch_inst_.details_short()}"
f" Lagging {int(lag_ns/NanoPerSec)} seconds:"
f" Lagging {int(lag_sec)} > {self.allowed_md_lag_sec_} seconds:"
f"\n{len(hist_aggr)} records"
f"\n{hist_aggr[-1].exch_inst_.base_asset_id_}: {hist_aggr[-1].tstamp()}"
f"\n{hist_aggr[-2].exch_inst_.base_asset_id_}: {hist_aggr[-2].tstamp()}"
# f" {hist_aggr[-1].exch_inst_.base_asset_id_}: {format_nanos_utc(hist_aggr[-1].aggr_time_ns_)}"
# f" {hist_aggr[-2].exch_inst_.base_asset_id_}: {format_nanos_utc(hist_aggr[-2].aggr_time_ns_)}"
)
return False
else:
Log.info(
f"{self.fname()} {hist_aggr[-1].exch_inst_.details_short()}"
f" Lag {int(lag_sec)} <= {self.allowed_md_lag_sec_} seconds"
f"\n{len(hist_aggr)} records"
f"\n{hist_aggr[-1].exch_inst_.base_asset_id_}: {hist_aggr[-1].tstamp()}"
f"\n{hist_aggr[-2].exch_inst_.base_asset_id_}: {hist_aggr[-2].tstamp()}"
)
return True
def _create_md_df(self, hist_aggr: List[MdTradesAggregate]) -> pd.DataFrame: