Proxy Statements (DEF 14A): Parse Executive Compensation and Governance Data

Form DEF 14A is a definitive proxy statement filed by public companies before annual shareholder meetings. It contains critical information about executive compensation, board composition, shareholder voting matters, and corporate governance. This guide details all data available from the ProxyStatement class for building views.

Overview

Property	Type	Description
Class Name	`ProxyStatement`
Forms Handled	`DEF 14A`, `DEFA14A`, `DEFM14A`, `DEF 14A/A`
Module	`edgar.proxy`
Source Data	XBRL (primary) + HTML (secondary)

Form Type Descriptions

Form	Description
`DEF 14A`	Definitive Proxy Statement - standard proxy filing
`DEFA14A`	Definitive Additional Proxy Soliciting Materials
`DEFM14A`	Definitive Proxy Statement relating to Merger or Acquisition
`DEF 14A/A`	Amendment to Definitive Proxy Statement

Data Source Reliability

Source	Reliability	Description
XBRL	High	Executive compensation, pay vs performance - standardized across all companies
HTML	Medium	Beneficial ownership, board info, proposals - requires parsing

Basic Metadata

Property	Type	Description	Example
`form`	`str`	Form type	`"DEF 14A"`
`filing_date`	`str`	Date filed with SEC	`"2025-01-10"`
`fiscal_year_end`	`str`	Fiscal year end date	`"2024-09-28"`
`company_name`	`str`	Company legal name	`"Apple Inc."`
`cik`	`str`	Central Index Key	`"0000320193"`
`accession_number`	`str`	SEC accession number	`"0001308179-25-000008"`

Executive Compensation (XBRL - High Reliability)

Executive compensation data is extracted from XBRL using the SEC's Executive Compensation Disclosure (ECD) taxonomy. This data is highly standardized and available for all companies.

PEO (Principal Executive Officer / CEO)

Property	Type	XBRL Concept	Description	Example
`peo_name`	`str`	`ecd:PeoName`	CEO name	`"Mr. Cook"`
`peo_total_comp`	`Decimal`	`ecd:PeoTotalCompAmt`	Total compensation from Summary Compensation Table	`74,609,802`
`peo_actually_paid_comp`	`Decimal`	`ecd:PeoActuallyPaidCompAmt`	Compensation Actually Paid (CAP)	`168,980,568`

Non-PEO Named Executive Officers (NEOs)

Property	Type	XBRL Concept	Description	Example
`neo_avg_total_comp`	`Decimal`	`ecd:NonPeoNeoAvgTotalCompAmt`	Average NEO total compensation	`27,178,896`
`neo_avg_actually_paid_comp`	`Decimal`	`ecd:NonPeoNeoAvgCompActuallyPaidAmt`	Average NEO compensation actually paid	`58,633,525`

Compensation Time Series (5 Years)

The executive_compensation property returns a DataFrame with 5 years of compensation data:

proxy = filing.obj()
comp_df = proxy.executive_compensation  # pd.DataFrame

Column	Type	Description
`fiscal_year_end`	`date`	End of fiscal year
`peo_total_comp`	`Decimal`	PEO total from SCT
`peo_actually_paid_comp`	`Decimal`	PEO compensation actually paid
`neo_avg_total_comp`	`Decimal`	Non-PEO NEO average total
`neo_avg_actually_paid_comp`	`Decimal`	Non-PEO NEO average CAP

Example Output

# Apple Inc. Executive Compensation (5 years)
fiscal_year_end  peo_total_comp  peo_actually_paid_comp  neo_avg_total_comp  neo_avg_actually_paid
2024-09-28       74,609,802      168,980,568             27,178,896          58,633,525
2023-09-30       63,209,845      106,643,588             26,938,240          48,892,163
2022-09-24       99,420,097      128,833,021             26,929,095          35,842,114
2021-09-25       98,734,394      311,845,801             26,989,456          89,764,231
2020-09-26       14,769,259       4,567,123              23,976,158          12,589,743

Named Executives (Dimensional Data)

Some companies tag individual executive data using dimensional XBRL. When available:

# Check if individual executive data is available
if proxy.has_individual_executive_data:
    executives = proxy.named_executives  # list of executive dicts
    for exec in executives:
        print(f"{exec['name']}: ${exec['actually_paid_comp']:,}")

Property	Type	Description
`has_individual_executive_data`	`bool`	Whether individual executive dimensions are available
`named_executives`	`list[dict]`	Individual executive compensation details (when available)

Note: Only ~60% of companies use dimensional tagging (AAPL, JPM, JNJ). Others aggregate to PEO vs Non-PEO NEO averages (MSFT, XOM).

Pay vs Performance (XBRL - High Reliability)

Pay vs Performance disclosures correlate executive compensation with company performance metrics.

Primary Metrics

Property	Type	XBRL Concept	Description	Example
`total_shareholder_return`	`Decimal`	`ecd:TotalShareholderRtnAmt`	Company TSR (cumulative %)	`207.6`
`peer_group_tsr`	`Decimal`	`ecd:PeerGroupTotalShareholderRtnAmt`	Peer group TSR	`189.3`
`net_income`	`Decimal`	`us-gaap:NetIncomeLoss`	Net income (USD)	`93,736,000,000`

Company-Selected Performance Measure

Property	Type	XBRL Concept	Description	Example
`company_selected_measure`	`str`	`ecd:CoSelectedMeasureName`	Company's chosen KPI name	`"Operating Cash Flow"`
`company_selected_measure_value`	`Decimal`	`ecd:CoSelectedMeasureAmt`	KPI value	`118,254,000,000`

Most Important Performance Measures

Property	Type	XBRL Concept	Description
`performance_measures`	`list[str]`	`ecd:MeasureName`	List of performance measures used

Example values: ["Revenue", "Operating Income", "Free Cash Flow", "Total Shareholder Return"]

Pay vs Performance DataFrame

pvp_df = proxy.pay_vs_performance  # pd.DataFrame

Column	Type	Description
`fiscal_year_end`	`date`	End of fiscal year
`peo_actually_paid_comp`	`Decimal`	CEO compensation actually paid
`neo_avg_actually_paid_comp`	`Decimal`	NEO average CAP
`total_shareholder_return`	`Decimal`	Company TSR
`peer_group_tsr`	`Decimal`	Peer group TSR
`net_income`	`Decimal`	Net income
`company_selected_measure_value`	`Decimal`	Company KPI value

Governance Indicators (XBRL)

Property	Type	XBRL Concept	Description	Example
`insider_trading_policy_adopted`	`bool`	`ecd:InsiderTrdPoliciesProcAdoptedFlag`	Has adopted insider trading policy	`True`

XBRL Concept Reference

Universal Concepts (Present in ALL Companies)

These 25 concepts are available across all sampled DEF 14A filings (100% coverage):

Executive Compensation

Concept	Description
`ecd:PeoTotalCompAmt`	PEO total compensation from Summary Compensation Table
`ecd:PeoActuallyPaidCompAmt`	PEO compensation actually paid
`ecd:NonPeoNeoAvgTotalCompAmt`	Non-PEO NEO average total compensation
`ecd:NonPeoNeoAvgCompActuallyPaidAmt`	Non-PEO NEO average compensation actually paid
`ecd:AdjToCompAmt`	Adjustments to compensation (reconciliation)
`ecd:PeoName`	Name of Principal Executive Officer

Performance Metrics

Concept	Description
`ecd:TotalShareholderRtnAmt`	Company total shareholder return
`ecd:PeerGroupTotalShareholderRtnAmt`	Peer group total shareholder return
`us-gaap:NetIncomeLoss`	Net income (GAAP)
`ecd:CoSelectedMeasureAmt`	Company-selected performance measure value
`ecd:CoSelectedMeasureName`	Company-selected performance measure name
`ecd:MeasureName`	Names of most important performance measures

Text Blocks and Footnotes

Concept	Description
`ecd:PvpTableTextBlock`	Pay vs Performance table text block
`ecd:TabularListTableTextBlock`	Tabular list of performance measures
`ecd:NamedExecutiveOfficersFnTextBlock`	Named executives footnote
`ecd:PeerGroupIssuersFnTextBlock`	Peer group issuers footnote
`ecd:AdjToPeoCompFnTextBlock`	PEO compensation adjustment footnote
`ecd:AdjToNonPeoNeoCompFnTextBlock`	Non-PEO NEO adjustment footnote
`ecd:CompActuallyPaidVsTotalShareholderRtnTextBlock`	CAP vs TSR discussion
`ecd:CompActuallyPaidVsNetIncomeTextBlock`	CAP vs Net Income discussion
`ecd:CompActuallyPaidVsCoSelectedMeasureTextBlock`	CAP vs company measure discussion

Governance

Concept	Description
`ecd:InsiderTrdPoliciesProcAdoptedFlag`	Insider trading policy adoption flag

Code Examples

Example 1: Extract Executive Compensation

from edgar import Company

# Get company and filing
company = Company("AAPL")
filing = company.get_filings(form="DEF 14A").latest()

# Get proxy statement object
proxy = filing.obj()

# Access executive compensation
print(f"CEO: {proxy.peo_name}")
print(f"CEO Total Compensation: ${proxy.peo_total_comp:,}")
print(f"CEO Compensation Actually Paid: ${proxy.peo_actually_paid_comp:,}")
print(f"NEO Average Compensation: ${proxy.neo_avg_actually_paid_comp:,}")

Example 2: Pay vs Performance Analysis

from edgar import Company

company = Company("MSFT")
filing = company.get_filings(form="DEF 14A").latest()
proxy = filing.obj()

# Get pay vs performance DataFrame
pvp = proxy.pay_vs_performance

# Calculate pay-for-performance correlation
correlation = pvp['peo_actually_paid_comp'].corr(pvp['total_shareholder_return'])
print(f"CEO Pay vs TSR Correlation: {correlation:.2f}")

# Compare to peer group
print(f"Company TSR: {proxy.total_shareholder_return}%")
print(f"Peer Group TSR: {proxy.peer_group_tsr}%")
print(f"Outperformance: {proxy.total_shareholder_return - proxy.peer_group_tsr:.1f}%")

Example 3: Governance Check

from edgar import Company

company = Company("JPM")
filing = company.get_filings(form="DEF 14A").latest()
proxy = filing.obj()

# Check governance indicators
if proxy.insider_trading_policy_adopted:
    print("Insider Trading Policy: Adopted")
else:
    print("Insider Trading Policy: Not Adopted (flag for review)")

# List performance measures used
print("Performance Measures:")
for measure in proxy.performance_measures:
    print(f"  - {measure}")

Example 4: Multi-Company Comparison

from edgar import Company
import pandas as pd

tickers = ["AAPL", "MSFT", "GOOGL", "META", "AMZN"]
data = []

for ticker in tickers:
    company = Company(ticker)
    filing = company.get_filings(form="DEF 14A").latest()
    proxy = filing.obj()

    data.append({
        'company': company.name,
        'ceo': proxy.peo_name,
        'ceo_total_comp': proxy.peo_total_comp,
        'ceo_actually_paid': proxy.peo_actually_paid_comp,
        'tsr': proxy.total_shareholder_return,
        'peer_tsr': proxy.peer_group_tsr
    })

comparison_df = pd.DataFrame(data)
print(comparison_df.to_string())

Example 5: Access Board and Director Information

The ProxyStatement class focuses on XBRL-based executive compensation data. Board composition, director details, and shareholder proposals live in the HTML body of the filing and are not yet extracted into structured properties. However, you can access this information today using the Filing object's built-in search and HTML capabilities.

from edgar import Company

# Get a DEF 14A filing
company = Company("AAPL")
filing = company.get_filings(form="DEF 14A").latest()

# Search the filing HTML for board-related sections
results = filing.search("board of directors")
for section in results[:3]:
    print(section[:200])  # Preview matching sections

# Search for specific governance topics
director_sections = filing.search("director nominees")
ownership_sections = filing.search("beneficial ownership")
proposal_sections = filing.search("proposal")
audit_sections = filing.search("audit fees")

# Get the full HTML for manual inspection or custom parsing
html_content = filing.html()

# Or access the filing document directly
doc = filing.document()

Note: Board composition, director bios, beneficial ownership tables, and shareholder proposals are available in the filing HTML but require custom parsing. Structured Director and Proposal objects are planned for a future release. See the HTML-Based Data section below for details on what data is available and extraction patterns.

View Design Recommendations

Primary View Components

Header Section
Company name (prominent)
Form type with amendment indicator
Filing date and fiscal year end
Annual meeting date (if available)
Compensation Dashboard
CEO compensation card (Total SCT vs Actually Paid)
NEO average compensation card
5-year trend sparkline or chart
Year-over-year change indicators
Pay vs Performance Panel
TSR comparison chart (company vs peer group)
Compensation vs TSR correlation visualization
Net income trend overlay
Company-selected performance measure
Governance Indicators
Insider trading policy status badge
Performance measures list
Key Metrics Cards
Total Shareholder Return
Peer Group TSR
Net Income
Company KPI with label

Data Priority for Display

Priority	Data	Reason
High	CEO compensation (both SCT and CAP)	Primary user interest
High	Total Shareholder Return	Key performance metric
High	Peer group comparison	Benchmark context
Medium	NEO average compensation	Executive team context
Medium	Net income	Financial performance
Medium	Company-selected measure	Company's chosen KPI
Medium	5-year compensation trends	Historical context
Low	Adjustment details	Technical reconciliation
Low	Footnote text blocks	Reference material

Value Formatting

Data Type	Format	Example
Compensation	Currency with commas	`$168,980,568`
Large values (>$1B)	Abbreviated	`$93.7B`
TSR	Percentage with 1 decimal	`207.6%`
Year-over-year change	Signed percentage	`+12.5%` or `-8.3%`

Visual Indicators (Suggested)

Condition	Visual Treatment
Amendment (`/A`)	Yellow "Amendment" badge
TSR > Peer TSR	Green upward arrow
TSR < Peer TSR	Red downward arrow
Insider policy adopted	Green checkmark
Insider policy not adopted	Red warning icon
Compensation increase >25% YoY	Orange highlight
Compensation decrease	Blue highlight

Compensation Card Layout

+----------------------------------+
|  CEO Compensation                |
|  Mr. Tim Cook                    |
+----------------------------------+
|  Summary Comp Table              |
|  $74,609,802                     |
|  +18.0% vs prior year            |
+----------------------------------+
|  Compensation Actually Paid      |
|  $168,980,568                    |
|  +58.4% vs prior year            |
+----------------------------------+

Example Data Structure

{
    # Metadata
    "form": "DEF 14A",
    "filing_date": "2025-01-10",
    "fiscal_year_end": "2024-09-28",
    "company_name": "Apple Inc.",
    "cik": "0000320193",
    "accession_number": "0001308179-25-000008",

    # Executive Compensation
    "peo_name": "Mr. Cook",
    "peo_total_comp": 74609802,
    "peo_actually_paid_comp": 168980568,
    "neo_avg_total_comp": 27178896,
    "neo_avg_actually_paid_comp": 58633525,

    # Pay vs Performance
    "total_shareholder_return": 207.6,
    "peer_group_tsr": 189.3,
    "net_income": 93736000000,
    "company_selected_measure": "Operating Cash Flow",
    "company_selected_measure_value": 118254000000,

    # Performance Measures
    "performance_measures": [
        "Net Sales",
        "Operating Income",
        "Total Shareholder Return",
        "Operating Cash Flow"
    ],

    # Governance
    "insider_trading_policy_adopted": True,

    # Named Executives (when dimensional data available)
    "has_individual_executive_data": True,
    "named_executives": [
        {
            "id": "aapl:CookMember",
            "name": "Mr. Cook",
            "role": "PEO",
            "total_comp": 74609802,
            "actually_paid_comp": 168980568
        },
        {
            "id": "aapl:MaestriMember",
            "name": "Luca Maestri",
            "role": "NEO",
            "total_comp": 27178896,
            "actually_paid_comp": 58633525
        }
    ],

    # Time Series (5 years)
    "executive_compensation": [
        {
            "fiscal_year_end": "2024-09-28",
            "peo_total_comp": 74609802,
            "peo_actually_paid_comp": 168980568,
            "neo_avg_total_comp": 27178896,
            "neo_avg_actually_paid_comp": 58633525
        },
        {
            "fiscal_year_end": "2023-09-30",
            "peo_total_comp": 63209845,
            "peo_actually_paid_comp": 106643588,
            "neo_avg_total_comp": 26938240,
            "neo_avg_actually_paid_comp": 48892163
        }
        # ... 3 more years
    ],

    # Pay vs Performance Series
    "pay_vs_performance": [
        {
            "fiscal_year_end": "2024-09-28",
            "peo_actually_paid_comp": 168980568,
            "neo_avg_actually_paid_comp": 58633525,
            "total_shareholder_return": 207.6,
            "peer_group_tsr": 189.3,
            "net_income": 93736000000
        }
        # ... more years
    ]
}

HTML-Based Data (Future Features)

The following data is available in DEF 14A HTML sections but not yet extracted into structured properties. You can access these sections today using filing.search() to find relevant content.

Beneficial Ownership

Section	Description
Principal Shareholders	Shareholders owning >5% of shares
Director/Executive Ownership	Shares owned by insiders

How to access today:

results = filing.search("beneficial ownership")
# or
results = filing.search("security ownership")

Board of Directors

Data	Description
Director Names	Full list of board members
Director Ages	Ages of directors
Director Tenure	Years on board
Independence Status	Independent vs non-independent
Committee Memberships	Audit, Compensation, Governance

How to access today:

results = filing.search("board of directors")
# or
results = filing.search("director nominees")

Director Compensation

Data	Description
Director Fees	Annual retainer and meeting fees
Stock Awards	Equity compensation
Total Compensation	Sum of all compensation

How to access today:

results = filing.search("director compensation")

Voting Proposals

Proposal Type	Description
Election of Directors	Board member elections
Ratification of Auditors	Audit firm approval
Say-on-Pay	Executive compensation advisory vote
Shareholder Proposals	Proposals submitted by shareholders
Equity Plan Amendments	Stock compensation plan changes

How to access today:

results = filing.search("proposal")

Audit Information

Data	Description
Auditor Name	Independent auditor firm
Audit Fees	Fees for audit services
Tax Fees	Fees for tax services
Other Fees	Other professional fees

How to access today:

results = filing.search("audit fees")

Notes for Implementation

XBRL Namespace: The primary namespace for proxy data is ecd: (Executive Compensation Disclosure), introduced by SEC in 2022 for fiscal years ending on or after December 16, 2022.
Dimensional Tagging Variation:
~60% of companies tag individual executive data using dim_ecd_IndividualAxis
~40% only provide aggregate data (PEO and Non-PEO NEO averages)
Always check has_individual_executive_data before accessing individual executives
Time Series Data: Pay vs Performance tables include 5 years of historical data per SEC requirements. This enables robust trend analysis.
Compensation Actually Paid (CAP): This SEC-mandated metric differs from Summary Compensation Table totals due to adjustments for:
Change in pension value
Stock/option awards fair value changes
Vesting date fair values
Company-Selected Measure: Each company chooses one performance measure they consider most important. Common choices include:
Revenue or Net Sales
Operating Income
Free Cash Flow
Adjusted EBITDA
Return on Invested Capital
Peer Group: Companies define their own peer groups for TSR comparison. The peer group composition is disclosed in the filing but not structured in XBRL.
Amendment Handling: DEF 14A/A filings contain corrections or updates. Always use the most recent filing for a given fiscal year.
Form Variants:
DEF 14A: Standard proxy statement
DEFA14A: Additional soliciting materials (may have limited data)
DEFM14A: Merger-related proxy (may have different structure)
Fiscal Year Alignment: Match compensation periods with company fiscal year ends, which vary by company (e.g., Apple uses September, Microsoft uses June).
Large Cap Coverage: XBRL data is highly reliable for S&P 500 companies. Smaller companies may have less complete tagging.