tessl/pypi-openbb
Investment research for everyone, anywhere.
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Pending
regulatory.mddocs/
Regulatory and Research Data
Regulatory filings, academic research factors, and econometric analysis tools. This module provides access to regulatory data, academic research, and econometric modeling capabilities.
Capabilities
Regulatory Data
SEC filings and regulatory compliance data.
def obb.regulators.rss_litigation(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get RSS litigation data.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with litigation data
"""
def obb.regulators.cik_map(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get CIK mapping data.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with CIK mappings
"""
def obb.regulators.symbol_map(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get symbol mapping data.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with symbol mappings
"""
def obb.regulators.sic_search(
query: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Search SIC codes.
Parameters:
- query: Search term
- provider: Data provider to use
Returns:
ResponseObject with SIC search results
"""
def obb.regulators.htm_file(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get HTM file data.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with HTM file data
"""
def obb.regulators.schema_files(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get schema files.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with schema files
"""
def obb.regulators.institutions_search(
query: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Search institutions.
Parameters:
- query: Search term
- provider: Data provider to use
Returns:
ResponseObject with institution search results
"""
def obb.regulators.filing_headers(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get filing headers.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with filing headers
"""Academic Research Factors
Fama-French research factors and academic finance data.
def obb.famafrench.international_index_returns(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get international index returns.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with international index returns
"""
def obb.famafrench.regional_portfolio_returns(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get regional portfolio returns.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with regional portfolio returns
"""
def obb.famafrench.country_portfolio_returns(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get country portfolio returns.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with country portfolio returns
"""
def obb.famafrench.us_portfolio_returns(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get US portfolio returns.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with US portfolio returns
"""
def obb.famafrench.factors(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get Fama-French factors.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with Fama-French factors
"""
def obb.famafrench.breakpoints(
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Get Fama-French breakpoints.
Parameters:
- provider: Data provider to use
Returns:
ResponseObject with breakpoints data
"""Econometric Analysis
Econometric modeling and statistical analysis tools.
def obb.econometrics.panel_random_effects(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Perform panel random effects analysis.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with random effects results
"""
def obb.econometrics.panel_first_difference(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Perform panel first difference analysis.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with first difference results
"""
def obb.econometrics.panel_pooled(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Perform panel pooled analysis.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with pooled analysis results
"""
def obb.econometrics.correlation_matrix(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Calculate correlation matrix.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with correlation matrix
"""
def obb.econometrics.cointegration(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Perform cointegration analysis.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with cointegration results
"""
def obb.econometrics.variance_inflation_factor(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Calculate variance inflation factor.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with VIF results
"""
def obb.econometrics.panel_fixed(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Perform panel fixed effects analysis.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with fixed effects results
"""
def obb.econometrics.causality(
data: str,
provider: str = None,
**kwargs
) -> ResponseObject:
"""
Perform causality analysis.
Parameters:
- data: Input data
- provider: Data provider to use
Returns:
ResponseObject with causality test results
"""Usage Examples
Regulatory Data Analysis
from openbb import obb
# Search institutions
institutions = obb.regulators.institutions_search(query="Bank")
inst_df = institutions.to_dataframe()
# Get CIK mapping
cik_data = obb.regulators.cik_map()
cik_df = cik_data.to_dataframe()Academic Research Factors
# Access Fama-French factors
# Get Fama-French factors
factors_data = obb.famafrench.factors()
factors_df = factors_data.to_dataframe()
# Get US portfolio returns
us_returns = obb.famafrench.us_portfolio_returns()
us_df = us_returns.to_dataframe()Econometric Modeling
# Access econometric analysis tools
# Calculate correlation matrix
corr_data = obb.econometrics.correlation_matrix(data="panel_data")
corr_df = corr_data.to_dataframe()
# Perform cointegration analysis
coint_data = obb.econometrics.cointegration(data="time_series")
coint_df = coint_data.to_dataframe()Research Workflow
# Retrieve regulatory filings for compliance analysis
# Use academic factors for portfolio attribution
# Perform econometric analysis on financial time seriesInstall with Tessl CLI
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