Add fiscal data (#28)

Author: lsbardel

notebooks/_config.yml

@@ -2,8 +2,8 @@
 # Learn more at https://jupyterbook.org/customize/config.html
 
 title: Quantflow library
-author: Quantmind Team
-copyright: "2024"
+author: <a href="https://quantmind.com">quantmind</a>
+copyright: "2014-2025"
 logo: assets/quantflow-light.svg
 
 # Force re-execution of notebooks on each build.

notebooks/data/fiscal_data.md

@@ -0,0 +1,31 @@
+---
+jupytext:
+  text_representation:
+    extension: .md
+    format_name: myst
+    format_version: 0.13
+    jupytext_version: 1.16.6
+kernelspec:
+  display_name: Python 3 (ipykernel)
+  language: python
+  name: python3
+---
+
+# Fiscal Data
+
+```{code-cell} ipython3
+from quantflow.data.fiscal_data import FiscalData
+```
+
+```{code-cell} ipython3
+fd = FiscalData()
+```
+
+```{code-cell} ipython3
+data = await fd.securities()
+data
+```
+
+```{code-cell} ipython3
+
+```

notebooks/data/fmp.md

@@ -18,10 +18,25 @@ The library provides a python client for the [Financial Modelling Prep API](http
 
 ```{code-cell} ipython3
 from quantflow.data.fmp import FMP
+import pandas as pd
 cli = FMP()
 cli.url
 ```
 
+## Get path
+
+```{code-cell} ipython3
+d = await cli.get_path("stock-list")
+pd.DataFrame(d)
+```
+
+## Search
+
+```{code-cell} ipython3
+d = await cli.search("electric")
+pd.DataFrame(d)
+```
+
 ```{code-cell} ipython3
 stock = "KNOS.L"
 ```
@@ -41,7 +56,7 @@ c
 ## Executive trading
 
 ```{code-cell} ipython3
-stock = "KNOS.L"
+stock = "AAPL"
 ```
 
 ```{code-cell} ipython3
@@ -58,3 +73,8 @@ await cli.insider_trading(stock)
 c = await cli.news(stock)
 c
 ```
+
+```{code-cell} ipython3
+p = await cli.market_risk_premium()
+pd.DataFrame(p)
+```

poetry.lock

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "quantflow"
-version = "0.3.2"
+version = "0.3.3"
 description = "quantitative analysis"
 authors = ["Luca <luca@quantmind.com>"]
 license = "BSD-3-Clause"
@@ -17,21 +17,21 @@ scipy = "^1.14.1"
 pydantic = "^2.0.2"
 ccy = { version = "^1.7.1" }
 python-dotenv = "^1.0.1"
-polars = {version = "^1.11.0", extras=["pandas", "pyarrow"]}
+polars = { version = "^1.11.0", extras = ["pandas", "pyarrow"] }
 asciichartpy = { version = "^1.5.25", optional = true }
 prompt-toolkit = { version = "^3.0.43", optional = true }
-aio-fluid = {version = "^1.2.1", extras=["http"], optional = true}
-rich = {version = "^13.9.4", optional = true}
-click = {version = "^8.1.7", optional = true}
-holidays = {version = "^0.63", optional = true}
-async-cache = {version = "^1.1.1", optional = true}
+aio-fluid = { version = "^1.2.1", extras = ["http"], optional = true }
+rich = { version = "^13.9.4", optional = true }
+click = { version = "^8.1.7", optional = true }
+holidays = { version = "^0.63", optional = true }
+async-cache = { version = "^1.1.1", optional = true }
 
 [tool.poetry.group.dev.dependencies]
 black = "^25.1.0"
 pytest-cov = "^6.0.0"
 mypy = "^1.14.1"
 ghp-import = "^2.0.2"
-ruff = "^0.11.2"
+ruff = "^0.11.12"
 pytest-asyncio = "^0.26.0"
 isort = "^6.0.1"
 
@@ -44,7 +44,7 @@ cli = [
     "prompt-toolkit",
     "rich",
     "click",
-    "holidays"
+    "holidays",
 ]
 
 [tool.poetry.group.book]
@@ -74,9 +74,7 @@ formats = "ipynb,myst"
 
 [tool.pytest.ini_options]
 asyncio_mode = "auto"
-testpaths = [
-    "quantflow_tests"
-]
+testpaths = ["quantflow_tests"]
 
 [tool.isort]
 profile = "black"
@@ -102,7 +100,7 @@ module = [
     "IPython.*",
     "pandas.*",
     "plotly.*",
-    "scipy.*"
+    "scipy.*",
 ]
 ignore_missing_imports = true
 disallow_untyped_defs = false

pyproject.toml

@@ -1,3 +1,3 @@
 """Quantitative analysis and pricing"""
 
-__version__ = "0.3.2"
+__version__ = "0.3.3"

quantflow/__init__.py

@@ -8,7 +8,7 @@
 from cache import AsyncTTL
 from ccy.cli.console import df_to_rich
 
-from quantflow.data.deribit import Deribit
+from quantflow.data.deribit import Deribit, InstrumentKind
 from quantflow.options.surface import VolSurface
 from quantflow.utils.numbers import round_to_step
 
@@ -24,13 +24,34 @@ def crypto() -> None:
         ctx.set_as_section()
 
 
+@crypto.command()
+@click.argument("currency")
+@click.option(
+    "-k",
+    "--kind",
+    type=click.Choice(list(InstrumentKind)),
+    default=InstrumentKind.spot.value,
+)
+def instruments(currency: str, kind: str) -> None:
+    """Provides information about instruments
+
+    Instruments for given cryptocurrency from Deribit API"""
+    ctx = QuantContext.current()
+    data = asyncio.run(get_instruments(ctx, currency, kind))
+    df = pd.DataFrame(data)
+    ctx.qf.print(df_to_rich(df))
+
+
 @crypto.command()
 @click.argument("currency")
 @options.length
 @options.height
 @options.chart
 def volatility(currency: str, length: int, height: int, chart: bool) -> None:
-    """Provides information about historical volatility for given cryptocurrency"""
+    """Provides information about historical volatility
+
+    Historical volatility for given cryptocurrency from Deribit API
+    """
     ctx = QuantContext.current()
     df = asyncio.run(get_volatility(ctx, currency))
     df["volatility"] = df["volatility"].map(lambda p: round_to_step(p, "0.01"))
@@ -109,9 +130,16 @@ def prices(symbol: str, height: int, length: int, chart: bool, frequency: str) -
         )
 
 
+async def get_instruments(ctx: QuantContext, currency: str, kind: str) -> list[dict]:
+    async with Deribit() as client:
+        return await client.get_instruments(
+            currency=currency, kind=InstrumentKind(kind)
+        )
+
+
 async def get_volatility(ctx: QuantContext, currency: str) -> pd.DataFrame:
     async with Deribit() as client:
-        return await client.get_volatility(params=dict(currency=currency))
+        return await client.get_volatility(currency)
 
 
 @AsyncTTL(time_to_live=10)

quantflow/cli/commands/crypto.py

@@ -24,6 +24,15 @@ def stocks() -> None:
         ctx.set_as_section()
 
 
+@stocks.command()
+def indices() -> None:
+    """Search companies"""
+    ctx = QuantContext.current()
+    data = asyncio.run(get_indices(ctx))
+    df = pd.DataFrame(data)
+    ctx.qf.print(df_to_rich(df))
+
+
 @stocks.command()
 @click.argument("symbol")
 def profile(symbol: str) -> None:
@@ -78,6 +87,11 @@ def sectors(period: str) -> None:
     ctx.qf.print(df_to_rich(df))
 
 
+async def get_indices(ctx: QuantContext) -> list[dict]:
+    async with ctx.fmp() as cli:
+        return await cli.indices()
+
+
 async def get_prices(ctx: QuantContext, symbol: str, frequency: str) -> pd.DataFrame:
     async with ctx.fmp() as cli:
         return await cli.prices(symbol, frequency)

quantflow/cli/commands/stocks.py

@@ -1,9 +1,12 @@
+import enum
+from dataclasses import dataclass
 from datetime import datetime, timezone
 from decimal import Decimal
 from typing import Any, cast
 
 import pandas as pd
 from dateutil.parser import parse
+from fluid.utils.data import compact_dict
 from fluid.utils.http_client import AioHttpClient, HttpResponse, HttpResponseError
 
 from quantflow.options.surface import VolSecurityType, VolSurfaceLoader
@@ -14,47 +17,79 @@ def parse_maturity(v: str) -> datetime:
     return parse(v).replace(tzinfo=timezone.utc, hour=8)
 
 
+class InstrumentKind(enum.StrEnum):
+    """Instrument kind for Deribit API."""
+
+    future = enum.auto()
+    option = enum.auto()
+    spot = enum.auto()
+    future_combo = enum.auto()
+    option_combo = enum.auto()
+
+
+@dataclass
 class Deribit(AioHttpClient):
     """Deribit API client
 
-    Fetch market and static data from `Deribit`_.
+    Fetch market and static data from `Deribit`_ API.
 
     .. _Deribit: https://docs.deribit.com/
     """
 
-    url = "https://www.deribit.com/api/v2"
+    url: str = "https://www.deribit.com/api/v2"
 
-    async def get_book_summary_by_instrument(self, **kw: Any) -> list[dict]:
-        kw.update(callback=self.to_result)
+    async def get_book_summary_by_instrument(
+        self,
+        instrument_name: str,
+        **kw: Any,
+    ) -> list[dict]:
+        """Get the book summary for a given instrument."""
+        kw.update(params=dict(instrument_name=instrument_name), callback=self.to_result)
         return cast(
             list[dict],
             await self.get_path("public/get_book_summary_by_instrument", **kw),
         )
 
-    async def get_book_summary_by_currency(self, **kw: Any) -> list[dict]:
-        kw.update(callback=self.to_result)
+    async def get_book_summary_by_currency(
+        self, currency: str, kind: InstrumentKind | None = None, **kw: Any
+    ) -> list[dict]:
+        """Get the book summary for a given currency."""
+        kw.update(
+            params=compact_dict(currency=currency, kind=kind), callback=self.to_result
+        )
         return cast(
             list[dict], await self.get_path("public/get_book_summary_by_currency", **kw)
         )
 
-    async def get_instruments(self, **kw: Any) -> list[dict]:
-        kw.update(callback=self.to_result)
+    async def get_instruments(
+        self,
+        currency: str,
+        kind: InstrumentKind | None = None,
+        expired: bool | None = None,
+        **kw: Any,
+    ) -> list[dict]:
+        """Get the list of instruments for a given currency."""
+        kw.update(
+            params=compact_dict(currency=currency, kind=kind, expired=expired),
+            callback=self.to_result,
+        )
         return cast(list[dict], await self.get_path("public/get_instruments", **kw))
 
-    async def get_volatility(self, **kw: Any) -> pd.DataFrame:
-        kw.update(callback=self.to_df)
+    async def get_volatility(self, currency: str, **kw: Any) -> pd.DataFrame:
+        """Provides information about historical volatility for given cryptocurrency"""
+        kw.update(params=dict(currency=currency), callback=self.to_df)
         return await self.get_path("public/get_historical_volatility", **kw)
 
     async def volatility_surface_loader(self, currency: str) -> VolSurfaceLoader:
         """Create a :class:`.VolSurfaceLoader` for a given crypto-currency"""
         loader = VolSurfaceLoader()
         futures = await self.get_book_summary_by_currency(
-            params=dict(currency=currency, kind="future")
+            currency=currency, kind=InstrumentKind.future
         )
         options = await self.get_book_summary_by_currency(
-            params=dict(currency=currency, kind="option")
+            currency=currency, kind=InstrumentKind.option
         )
-        instruments = await self.get_instruments(params=dict(currency=currency))
+        instruments = await self.get_instruments(currency=currency)
         instrument_map = {i["instrument_name"]: i for i in instruments}
         min_tick_size = Decimal("inf")
         for future in futures:

quantflow/data/deribit.py

@@ -6,12 +6,7 @@
 import pandas as pd
 from fluid.utils.http_client import AioHttpClient
 
-URL = (
-    "https://www.federalreserve.gov/datadownload/Output.aspx?"
-    "rel=H15&series=bf17364827e38702b42a58cf8eaa3f78&lastobs=&"
-)
-
-maturities = [
+MATURITIES = (
     "month_1",
     "month_3",
     "month_6",
@@ -23,7 +18,7 @@
     "year_10",
     "year_20",
     "year_30",
-]
+)
 
 
 @dataclass
@@ -52,7 +47,7 @@ async def yield_curves(self, **params: Any) -> pd.DataFrame:
         params.update(series="bf17364827e38702b42a58cf8eaa3f78", rel="H15")
         data = await self._get_text(params)
         df = pd.read_csv(data, header=5, index_col=None, parse_dates=True)
-        df.columns = ["date"] + maturities  # type: ignore
+        df.columns = list(("date",) + MATURITIES)  # type: ignore
         df = df.set_index("date").replace("ND", np.nan)
         return df.dropna(axis=0, how="all").reset_index()