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[Feature] Add Deribit Provider Extension For Crypto Options Data (#6985)

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* add deribit provider and make some small changes to the standard model to allow for fractional volume and size

* linter

* typehint

* more lint

* more touchup

* update test

* remove line in test

* maybe we need that after all..?
This commit is contained in:
Danglewood
2024-12-30 15:57:57 -08:00
committed by GitHub
parent 8fd46ed450
commit efd09ce75b
20 changed files with 2831 additions and 106 deletions
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19
openbb_platform/core/openbb_core/provider/standard_models/options_chains.py
View File

@@ -150,10 +150,13 @@ class OptionsChainsData(OptionsChainsProperties):
json_schema_extra={"x-unit_measurement": "currency"},
)
option_type: List[str] = Field(description="Call or Put.")
open_interest: List[Union[int, None]] = Field(
contract_size: List[Union[int, float, None]] = Field(
default_factory=list, description="Number of underlying units per contract."
)
open_interest: List[Union[int, float, None]] = Field(
default_factory=list, description="Open interest on the contract."
)
volume: List[Union[int, None]] = Field(
volume: List[Union[int, float, None]] = Field(
default_factory=list, description=DATA_DESCRIPTIONS.get("volume", "")
)
theoretical_price: List[Union[float, None]] = Field(
@@ -166,7 +169,7 @@ class OptionsChainsData(OptionsChainsProperties):
description="Last trade price of the option.",
json_schema_extra={"x-unit_measurement": "currency"},
)
last_trade_size: List[Union[int, None]] = Field(
last_trade_size: List[Union[int, float, None]] = Field(
default_factory=list, description="Last trade size of the option."
)
last_trade_time: List[Union[datetime, None]] = Field(
@@ -182,7 +185,7 @@ class OptionsChainsData(OptionsChainsProperties):
description="Current bid price for the option.",
json_schema_extra={"x-unit_measurement": "currency"},
)
bid_size: List[Union[int, None]] = Field(
bid_size: List[Union[int, float, None]] = Field(
default_factory=list, description="Bid size for the option."
)
bid_time: List[Union[datetime, None]] = Field(
@@ -197,7 +200,7 @@ class OptionsChainsData(OptionsChainsProperties):
description="Current ask price for the option.",
json_schema_extra={"x-unit_measurement": "currency"},
)
ask_size: List[Union[int, None]] = Field(
ask_size: List[Union[int, float, None]] = Field(
default_factory=list, description="Ask size for the option."
)
ask_time: List[Union[datetime, None]] = Field(
@@ -262,7 +265,7 @@ class OptionsChainsData(OptionsChainsProperties):
description=DATA_DESCRIPTIONS.get("close", ""),
json_schema_extra={"x-unit_measurement": "currency"},
)
close_size: List[Union[int, None]] = Field(
close_size: List[Union[int, float, None]] = Field(
default_factory=list,
description="The closing trade size for the option that day.",
)
@@ -275,7 +278,7 @@ class OptionsChainsData(OptionsChainsProperties):
description="The closing bid price for the option that day.",
json_schema_extra={"x-unit_measurement": "currency"},
)
close_bid_size: List[Union[int, None]] = Field(
close_bid_size: List[Union[int, float, None]] = Field(
default_factory=list,
description="The closing bid size for the option that day.",
)
@@ -287,7 +290,7 @@ class OptionsChainsData(OptionsChainsProperties):
default_factory=list,
description="The closing ask price for the option that day.",
)
close_ask_size: List[Union[int, None]] = Field(
close_ask_size: List[Union[int, float, None]] = Field(
default_factory=list,
description="The closing ask size for the option that day.",
)

205
openbb_platform/core/openbb_core/provider/utils/options_chains_properties.py
View File

@@ -3,6 +3,7 @@
# pylint: disable=too-many-lines, too-many-arguments, too-many-locals, too-many-statements, too-many-positional-arguments
from datetime import datetime
from functools import cached_property
from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Union
from openbb_core.app.model.abstract.error import OpenBBError
@@ -41,7 +42,7 @@ class OptionsChainsProperties(Data):
if hasattr(self, "_last_price"):
del self._last_price
@property
@cached_property
def dataframe(self) -> "DataFrame":
"""Return all data as a Pandas DataFrame,
with additional computed columns (Breakeven, GEX, DEX) if available.
@@ -72,13 +73,13 @@ class OptionsChainsProperties(Data):
raise OpenBBError("Error: No validated data was found.")
if "dte" not in chains_data.columns and "eod_date" in chains_data.columns:
_date = to_datetime(chains_data["eod_date"])
_date = to_datetime(chains_data.eod_date)
temp = DatetimeIndex(chains_data.expiration)
temp_ = temp - _date # type: ignore
chains_data.loc[:, "dte"] = [Timedelta(_temp_).days for _temp_ in temp_]
if "dte" in chains_data.columns:
chains_data = DataFrame(chains_data[chains_data["dte"] >= 0])
chains_data = DataFrame(chains_data[chains_data.dte >= 0])
if "dte" not in chains_data.columns and "eod_date" not in chains_data.columns:
today = datetime.today().date()
@@ -86,51 +87,75 @@ class OptionsChainsProperties(Data):
# Add the breakeven price for each option, and the DEX and GEX for each option, if available.
try:
last_price = chains_data.underlying_price.iloc[0]
_calls = DataFrame(chains_data[chains_data["option_type"] == "call"])
_puts = DataFrame(chains_data[chains_data["option_type"] == "put"])
_ask = self._identify_price_col(
_calls = DataFrame(chains_data[chains_data.option_type == "call"])
_puts = DataFrame(chains_data[chains_data.option_type == "put"])
_ask = self._identify_price_col( # pylint: disable=W0212
chains_data, "call", "ask"
) # pylint: disable=W0212
_calls.loc[:, ("Breakeven")] = (
_calls.loc[:, ("strike")] + _calls.loc[:, (_ask)]
)
_puts.loc[:, ("Breakeven")] = (
_puts.loc[:, ("strike")] - _puts.loc[:, (_ask)]
)
_calls.loc[:, ("Breakeven")] = _calls.strike + _calls.loc[:, (_ask)]
_puts.loc[:, ("Breakeven")] = _puts.strike - _puts.loc[:, (_ask)]
if "delta" in _calls.columns:
_calls.loc[:, ("DEX")] = (
(_calls.loc[:, ("delta")] * 100)
* (_calls.loc[:, ("open_interest")])
* last_price
(
_calls.delta
* (
_calls.contract_size
if hasattr(_calls, "contract_size")
else 100
)
* _calls.open_interest
* _calls.underlying_price
)
.replace({nan: 0})
.astype("int64")
)
_calls["DEX"] = _calls["DEX"].replace({nan: 0}).astype("int64")
_puts.loc[:, ("DEX")] = (
(_puts.loc[:, ("delta")] * 100)
* (_puts.loc[:, ("open_interest")])
* last_price
(
_puts.delta
* (
_puts.contract_size
if hasattr(_puts, "contract_size")
else 100
)
* _puts.open_interest
* _puts.underlying_price
)
.replace({nan: 0})
.astype("int64")
)
_puts["DEX"] = _puts["DEX"].replace({nan: 0}).astype("int64")
if "gamma" in _calls.columns:
_calls.loc[:, ("GEX")] = (
_calls.loc[:, ("gamma")]
* 100
* _calls.loc[:, ("open_interest")]
* (last_price * last_price)
* 0.01
(
_calls.gamma
* (
_calls.contract_size
if hasattr(_calls, "contract_size")
else 100
)
* _calls.open_interest
* (_calls.underlying_price * _calls.underlying_price)
* 0.01
)
.replace({nan: 0})
.astype("int64")
)
_calls["GEX"] = _calls["GEX"].replace({nan: 0}).astype("int64")
_puts.loc[:, ("GEX")] = (
_puts.loc[:, ("gamma")]
* 100
* _puts.loc[:, ("open_interest")]
* (last_price * last_price)
* 0.01
* (-1)
(
_puts.gamma
* (
_puts.contract_size
if hasattr(_puts, "contract_size")
else 100
)
* _puts.open_interest
* (_puts.underlying_price * _puts.underlying_price)
* 0.01
* (-1)
)
.replace({nan: 0})
.astype("int64")
)
_puts["GEX"] = _puts["GEX"].replace({nan: 0}).astype("int64")
_calls.set_index(keys=["expiration", "strike", "option_type"], inplace=True)
_puts.set_index(keys=["expiration", "strike", "option_type"], inplace=True)
@@ -371,17 +396,7 @@ class OptionsChainsProperties(Data):
from numpy import inf, nan
from pandas import DataFrame, concat
df = DataFrame()
if metric in ["volume", "open_interest"]:
df = DataFrame(
self.model_dump(
exclude_unset=True,
exclude_none=True,
)
)
else:
df = self.dataframe
df = self.dataframe
if metric in ["DEX", "GEX"]:
if not self.has_greeks:
@@ -395,7 +410,7 @@ class OptionsChainsProperties(Data):
"Calls": total_calls,
"Puts": total_puts,
"Total": total_metric,
"PCR": round(total_puts / total_calls, 4),
"PCR": round(total_puts / total_calls, 4) if total_calls != 0 else 0,
}
df = DataFrame(df[df[metric].notnull()]) # type: ignore
@@ -542,6 +557,11 @@ class OptionsChainsProperties(Data):
"Error: underlying_price must be provided if underlying_price is not available"
)
if date is not None:
date = self._get_nearest_expiration(date)
df = df[df.expiration.astype(str) == date]
strikes = Series(df.strike.unique().tolist())
last_price = (
underlying_price
if underlying_price is not None
@@ -549,11 +569,6 @@ class OptionsChainsProperties(Data):
)
strikes = Series(self.strikes)
if date is not None:
date = self._get_nearest_expiration(date)
df = df[df.expiration.astype(str) == date]
strikes = Series(df.strike.unique().tolist())
upper = last_price * (1 + moneyness) # type: ignore
lower = last_price * (1 - moneyness) # type: ignore
nearest_call = (upper - strikes).abs().idxmin()
@@ -606,15 +621,14 @@ class OptionsChainsProperties(Data):
if days is None:
days = 30
if strike is None:
strike = chains.underlying_price.iloc[0]
dte_estimate = self._get_nearest_expiration(days)
df = (
chains[chains.expiration.astype(str) == dte_estimate]
.query("`option_type` == @option_type")
.copy()
)
if strike is None:
strike = df.underlying_price.iloc[0]
if price_col is not None:
df = df[df[price_col].notnull()] # type: ignore
@@ -676,16 +690,6 @@ class OptionsChainsProperties(Data):
chains = self.dataframe
if not hasattr(chains, "underlying_price") and underlying_price is None:
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
underlying_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if days is None:
days = 30
@@ -696,6 +700,16 @@ class OptionsChainsProperties(Data):
chains = chains[chains.expiration.astype(str) == dte_estimate]
if not hasattr(chains, "underlying_price") and underlying_price is None:
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
underlying_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
force_otm = True
if strike is None and not hasattr(chains, "underlying_price"):
@@ -843,6 +857,12 @@ class OptionsChainsProperties(Data):
"Error: underlying_price must be provided if underlying_price is not available"
)
underlying_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
strikes = self._get_nearest_otm_strikes(
dte_estimate, underlying_price, moneyness
)
@@ -968,11 +988,6 @@ class OptionsChainsProperties(Data):
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if days is None:
days = 30
@@ -986,6 +1001,12 @@ class OptionsChainsProperties(Data):
"`option_type` == 'call'"
)
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if bought is None:
bought = last_price * 1.0250
@@ -1103,11 +1124,6 @@ class OptionsChainsProperties(Data):
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if days is None:
days = 30
@@ -1121,6 +1137,12 @@ class OptionsChainsProperties(Data):
"`option_type` == 'put'"
)
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if bought is None:
bought = last_price * 0.9750
@@ -1226,11 +1248,6 @@ class OptionsChainsProperties(Data):
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if days is None:
days = 30
@@ -1240,6 +1257,11 @@ class OptionsChainsProperties(Data):
dte_estimate = self._get_nearest_expiration(days)
chains = DataFrame(chains[chains["expiration"].astype(str) == dte_estimate])
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
bid = self._identify_price_col(chains, "put", "bid")
ask = self._identify_price_col(chains, "call", "ask")
strike_price = last_price if strike == 0 else strike
@@ -1329,11 +1351,6 @@ class OptionsChainsProperties(Data):
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
if days is None:
days = 30
@@ -1343,6 +1360,11 @@ class OptionsChainsProperties(Data):
dte_estimate = self._get_nearest_expiration(days)
chains = DataFrame(chains[chains["expiration"].astype(str) == dte_estimate])
last_price = (
underlying_price
if underlying_price is not None
else chains.underlying_price.iloc[0]
)
bid = self._identify_price_col(chains, "call", "bid")
ask = self._identify_price_col(chains, "put", "ask")
strike_price = last_price if strike == 0 else strike
@@ -1667,11 +1689,6 @@ class OptionsChainsProperties(Data):
raise OpenBBError(
"Error: underlying_price must be provided if underlying_price is not available"
)
last_price = (
underlying_price
if underlying_price is not None
else data.underlying_price.iloc[0]
)
if moneyness is not None and date is None:
date = -1
@@ -1703,13 +1720,12 @@ class OptionsChainsProperties(Data):
if moneyness is not None:
atm_call_iv = DataFrame()
atm_put_iv = DataFrame()
for day in days:
strikes = self._get_nearest_otm_strikes(
date=day, moneyness=moneyness, underlying_price=underlying_price
)
atm_call_strike = self._get_nearest_strike( # noqa:F841
"call", day, last_price, call_price_col, False
"call", day, underlying_price, call_price_col, False
)
call_strike = self._get_nearest_strike( # noqa:F841
"call", day, strikes["call"], call_price_col, False
@@ -1719,6 +1735,11 @@ class OptionsChainsProperties(Data):
.query("`option_type` == 'call'") # type: ignore
.copy()
)
last_price = (
underlying_price
if underlying_price is not None
else _calls.underlying_price.iloc[0]
)
if len(_calls) > 0:
call_iv = _calls[_calls.strike == call_strike][
["expiration", "strike", "implied_volatility"]