ExitCompute Specification

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ExitCompute

Macro Signals and Risk Models – Combined for Your Exit Plan.

Mission

ExitCompute is an open-source AI platform designed to help investors make structured decisions about exiting the stock market.

The system is designed around the principle that successful investing is not only about entering an investment or accumulating returns. It is also about determining when accumulated capital and gains should be protected.

ExitCompute analyzes the relationship between personal financial requirements, portfolio exposure, market conditions, macroeconomic signals, risk factors, taxation, and potential future scenarios.

The platform does not attempt to guarantee that users will identify a market top. Instead, it evaluates the tradeoffs between remaining invested and reducing exposure under different market and personal financial conditions.

The system must prioritize capital preservation, transparency, explainability, scenario comparison, tax awareness, and user control.

Core Design Principles

ExitCompute must follow these principles:

Open-source development
Modular architecture
Transparent calculations
Explainable AI
Reproducible analysis
User-controlled assumptions
Human-in-the-loop decision making
Separation of analysis from trade execution
Scenario-based decision support
Tax-aware planning
Macro-aware risk analysis
Portfolio-level analysis
Clear uncertainty communication
No guaranteed financial outcomes
No false precision
No dependence on a single data provider
Replaceable AI models
Replaceable financial data sources
Extensible plugin architecture
Privacy-conscious handling of financial information
RIA-style analytical and disclosure practices

System Architecture

ExitCompute shall operate as a web service consisting of modular analytical services connected through a common application interface.

The platform shall separate:

User financial inputs
Portfolio analysis
Market data
Macroeconomic analysis
Risk calculations
Scenario simulations
Tax analysis
AI interpretation
Compliance and disclosure
Reporting
Notifications
Optional integrations

Core analytical calculations should not depend on the AI language model.

The AI layer should interpret, explain, compare, and communicate outputs generated by deterministic and statistical engines.

Financial calculations should remain independently testable without requiring an AI model.

Core Modules

Personal Financial Planning Module

The Personal Financial Planning Module shall collect and model the user’s financial objectives and constraints.

The module shall support:

Financial goals
Investment objectives
Time horizon
Income information
Cash flow requirements
Emergency cash requirements
Planned expenditures
Retirement timelines
Liquidity requirements
Risk tolerance
Maximum acceptable loss
Minimum desired capital preservation
Minimum desired profit preservation
Desired cash-out amount
Desired exit date
Exit urgency
Partial-exit objectives
Full-exit objectives
User-defined financial priorities

The module shall distinguish between financial information supplied by the user and values calculated by ExitCompute.

The module shall identify missing information that could materially affect an analysis.

Portfolio Analysis Module

The Portfolio Analysis Module shall evaluate the user’s current investment exposure.

The module shall support:

Securities
Shares or units
Current market value
Purchase price
Cost basis
Acquisition date
Unrealized gains
Unrealized losses
Realized gains
Realized losses
Position concentration
Sector concentration
Asset allocation
Portfolio beta
Historical volatility
Correlation
Drawdown
Liquidity
Principal at risk
Profit at risk
Market exposure

The module shall calculate position-level and portfolio-level risk.

The module shall identify concentrations that could materially affect an exit strategy.

Market Data Module

The Market Data Module shall ingest and normalize market information required by the analytical engines.

Supported information may include:

Security prices
Historical prices
Trading volume
Market capitalization
Earnings information
Valuation metrics
Dividend information
Volatility data
Index data
Sector data
Market breadth
Interest rates
Treasury yields
Credit spreads

The module shall record:

Data source
Retrieval timestamp
Data period
Data quality
Data version
Missing values
Data transformations

The system shall avoid creating analytical conclusions from stale or incomplete data without clearly identifying the limitation.

Macro Signal Module

The Macro Signal Module shall evaluate macroeconomic conditions that may influence portfolio risk and market behavior.

The module shall support analysis of:

Interest rates
Federal funds rate
Treasury yields
Yield curve
Yield curve inversions
Inflation
Consumer Price Index
Producer Price Index
Employment
Unemployment
Payroll trends
GDP
Consumer confidence
Manufacturing activity
Services activity
Purchasing Managers’ Index
Credit spreads
Corporate credit conditions
Banking-sector stress
Liquidity conditions
Money supply
Financial conditions
Volatility regimes
Earnings trends

The module shall classify macroeconomic conditions into configurable regimes.

Possible regimes include:

Expansion
Late expansion
Slowdown
Recession
Recovery
Inflationary stress
Deflationary stress
Liquidity stress
Credit stress
High-volatility environment

The module shall calculate a configurable Macro Risk Score.

The score shall expose the underlying signals and weights rather than functioning as an unexplained black box.

Market Valuation Module

The Market Valuation Module shall evaluate whether securities, sectors, or broader markets appear historically expensive, inexpensive, or within normal valuation ranges.

The module shall support:

Price-to-earnings analysis
Forward price-to-earnings analysis
Price-to-sales analysis
Price-to-book analysis
Earnings yield
Historical valuation percentiles
Sector-relative valuation
Market concentration
Valuation expansion
Valuation contraction
Momentum versus valuation
Fundamental versus price divergence

The module shall identify valuation conditions as risk indicators rather than treating valuation alone as a market-timing mechanism.

Risk Analysis Module

The Risk Analysis Module shall quantify portfolio risk under current and hypothetical conditions.

The module shall support:

Historical volatility
Portfolio volatility
Beta
Drawdown
Maximum drawdown
Value at Risk
Conditional Value at Risk
Expected Shortfall
Downside deviation
Sharpe ratio
Sortino ratio
Correlation risk
Concentration risk
Liquidity risk
Tail risk
Position-level risk contribution
Portfolio-level risk contribution
Volatility clustering
Risk regime analysis

The module shall calculate a Portfolio Risk Score.

All material risk calculations shall expose their methodology and assumptions.

Tail Risk Module

The Tail Risk Module shall evaluate the potential consequences of unusually severe market events.

The module shall support:

Extreme-loss estimation
Fat-tail analysis
Conditional Value at Risk
Expected Shortfall
Gap-down analysis
Correlation convergence
Liquidity deterioration
Multi-factor stress
Cascading-risk scenarios
Extreme volatility scenarios
Black-swan sensitivity analysis

Tail-risk outputs shall communicate that extreme-event models contain substantial uncertainty.

Scenario Engine Module

The Scenario Engine shall be a central component of ExitCompute.

It shall allow users to compare multiple exit strategies using common assumptions and standardized outputs.

The engine shall support:

Immediate Exit
Gradual Exit
Dollar-Based Exit
Percentage-Based Exit
Profit-Only Exit
Principal Preservation Exit
Tax-Optimized Exit
Macro-Conditional Exit
Risk-Triggered Exit
Hybrid Exit
Custom Exit

Each scenario shall calculate, where applicable:

Gross proceeds
Estimated taxes
Estimated transaction costs
Net proceeds
Remaining exposure
Remaining principal at risk
Remaining profit at risk
Expected return
Downside risk
Maximum modeled drawdown
Probability distributions
Time to completion
Liquidity generated
Tax impact
Risk reduction

Immediate Exit Scenario

The Immediate Exit Scenario shall model liquidation of the selected portfolio positions at the current modeled price.

It shall calculate:

Gross liquidation value
Estimated tax liability
Estimated transaction costs
Net proceeds
Remaining exposure
Capital preserved
Profit preserved

The scenario shall establish a baseline for comparison against alternative exit strategies.

Gradual Exit Scenario

The Gradual Exit Scenario shall model staged reductions in market exposure.

Users shall be able to define:

Exit percentage
Exit amount
Frequency
Duration
Target completion date

The engine shall support:

Daily schedules
Weekly schedules
Monthly schedules
Custom schedules

The system shall compare gradual exits against immediate liquidation and other strategies.

Profit-Only Exit Scenario

The Profit-Only Exit Scenario shall model withdrawing accumulated gains while maintaining some or all of the original principal in the market.

The system shall calculate:

Realized profit
Remaining principal
Remaining market exposure
Tax consequences
Downside exposure
Potential future gains
Principal-at-risk

Principal Preservation Scenario

The Principal Preservation Scenario shall model exiting enough of a position or portfolio to recover the user’s original capital.

The system shall calculate:

Principal recovered
Remaining exposure
Remaining potential upside
Remaining downside
Estimated tax impact
Probability of losing recovered capital after the modeled exit

Tax-Optimized Exit Scenario

The Tax-Optimized Exit Scenario shall search for exit schedules that may reduce estimated tax consequences while satisfying user-defined constraints.

The module shall consider:

Holding periods
Short-term capital gains
Long-term capital gains
Tax brackets
Estimated taxable income
Tax-year boundaries
Tax-loss harvesting
Loss offsets
Wash-sale considerations
State taxation
Multi-year realization schedules

The system shall distinguish tax optimization from tax avoidance and shall only model legally recognized strategies.

Tax calculations shall be treated as estimates and shall identify assumptions and jurisdictional limitations.

Macro-Conditional Exit Scenario

The Macro-Conditional Exit Scenario shall model exit strategies triggered by changes in macroeconomic conditions.

Triggers may include:

Yield curve changes
Inflation thresholds
Employment deterioration
Credit-spread expansion
Volatility increases
Liquidity deterioration
Economic growth deterioration
Composite Macro Risk Score changes

Users shall be able to define thresholds and confirmation requirements.

The system shall support multiple simultaneous conditions.

Risk-Triggered Exit Scenario

The Risk-Triggered Exit Scenario shall model portfolio reductions when predefined risk thresholds are reached.

Triggers may include:

Portfolio drawdown
Position drawdown
Volatility
Value at Risk
Conditional Value at Risk
Tail-risk measures
Concentration risk
Liquidity risk
Correlation breakdown
Earnings deterioration

The system shall allow users to configure thresholds.

Hybrid Exit Scenario

The Hybrid Exit Scenario shall combine:

Personal financial requirements
Tax constraints
Macro signals
Portfolio risk
Market valuation
User-defined timing requirements

The engine shall rank potential exit paths based on the user’s stated priorities.

Monte Carlo Simulation Module

The Monte Carlo Simulation Module shall generate multiple modeled future portfolio paths.

The module shall support:

Return distributions
Volatility assumptions
Drift assumptions
Correlation structures
Randomized market paths
Portfolio-level simulations
Position-level simulations
Thousands of simulation paths
User-defined simulation periods

Outputs shall include:

Median outcome
Lower-percentile outcomes
Upper-percentile outcomes
Probability of loss
Probability of preserving principal
Probability of preserving gains
Probability of reaching a cash target
Probability of exceeding a loss threshold
Distribution of portfolio values
Distribution of net proceeds

Monte Carlo results shall never be presented as predictions or guarantees.

Historical Stress Testing Module

The Historical Stress Testing Module shall evaluate portfolio resilience under historical market environments.

The module shall support historical stress periods including:

Dot-com market decline
Global Financial Crisis
COVID-19 market crash
2022 monetary tightening cycle

The system shall also support configurable:

Equity drawdowns
Interest-rate shocks
Inflation shocks
Credit shocks
Liquidity shocks
Volatility shocks

The system shall calculate:

Portfolio decline
Peak drawdown
Time to recovery
Capital remaining
Profit remaining
Exit effectiveness

Historical scenarios shall clearly indicate that past market behavior does not establish future outcomes.

Exit Optimization Module

The Exit Optimization Module shall evaluate competing strategies using user-defined objectives.

Optimization criteria may include:

Capital preservation
Profit preservation
Tax minimization
Risk reduction
Liquidity
Exit duration
Financial deadlines

Users shall be able to assign relative priorities.

The system shall identify tradeoffs instead of presenting a single outcome as universally optimal.

Tax Analysis Module

The Tax Analysis Module shall estimate the tax implications of proposed exits.

It shall support:

Cost-basis analysis
Acquisition-date analysis
Holding-period analysis
Long-term gain analysis
Short-term gain analysis
Tax-bracket modeling
Tax-year modeling
Tax-loss harvesting
Wash-sale awareness
State-tax estimates
Multi-year tax projections
Tax-sensitive lot selection

The module shall maintain a clear separation between financial modeling and professional tax advice.

AI Analysis Module

The AI Analysis Module shall provide natural-language interpretation of analytical results.

The AI shall:

Explain scenario results
Explain risk scores
Explain macroeconomic signals
Compare exit strategies
Identify tradeoffs
Identify missing information
Identify conflicting assumptions
Summarize tax considerations
Explain uncertainty
Generate user-readable reports
Answer questions about model outputs

The AI shall not independently override deterministic calculations.

The AI shall reference the underlying model outputs when explaining conclusions.

The AI shall avoid:

Guaranteed returns
Claims of certainty
Claims that a market top has been identified
Unsupported predictions
Hidden assumptions
Fabricated financial data
Fabricated sources

Decision Support Module

The Decision Support Module shall translate analytical results into structured choices.

Outputs may include:

Lower-risk pathway
Higher-liquidity pathway
Tax-efficient pathway
Faster-exit pathway
Gradual-exit pathway
Capital-preservation pathway
Profit-preservation pathway

The system shall explain why a scenario ranks higher according to the user’s selected objectives.

The final decision shall remain with the user.

Compliance and Disclosure Module

The Compliance and Disclosure Module shall enforce RIA-style analytical practices.

The module shall provide:

Financial-analysis disclaimers
Risk disclosures
Model limitations
Data limitations
Tax disclaimers
Historical-data disclosures
Scenario uncertainty disclosures
AI limitations
Conflict-of-interest disclosures where applicable
Data-source disclosures
Methodology disclosures

The system shall clearly distinguish:

Financial education
Financial analysis
Scenario modeling
Decision support
Professional investment advice
Trade execution

ExitCompute shall not represent itself as a registered investment adviser unless operated through an appropriately registered entity and configured for that purpose.

Explainability Module

The Explainability Module shall provide visibility into how outputs are produced.

It shall expose:

Inputs
Assumptions
Data sources
Indicator values
Model versions
Calculation methods
Scenario parameters
Risk parameters
Tax assumptions
Simulation settings
Output scores

Users shall be able to understand the major factors contributing to a result.

Audit Module

The Audit Module shall record important analytical events.

Audit records may include:

User input changes
Portfolio changes
Scenario creation
Scenario modifications
Model versions
Data versions
Risk calculations
Tax calculations
AI-generated reports
Disclosure versions
User decisions
System alerts

Audit records shall support reproducibility and troubleshooting.

Alert Module

The Alert Module shall monitor user-defined and system-defined conditions.

Alerts may include:

Macro Risk Score changes
Portfolio Risk Score changes
Valuation changes
Volatility increases
Drawdown thresholds
Tax deadlines
Holding-period milestones
Wash-sale warnings
Concentration warnings
Liquidity warnings
Scenario deterioration
Exit-condition triggers

Users shall control alert preferences.

Dashboard Module

The Dashboard Module shall provide a centralized view of the user’s analysis.

It shall display:

Portfolio value
Market exposure
Unrealized gains and losses
Capital at risk
Profit at risk
Macro Risk Score
Portfolio Risk Score
Tax Exposure
Exit Readiness
Scenario comparisons
Monte Carlo results
Stress-test results
Tail-risk results
Exit timeline
Relevant alerts

The dashboard shall prioritize understandable decision-support information.

Scenario Comparison Module

The Scenario Comparison Module shall allow users to compare multiple exit strategies simultaneously.

Comparison fields shall include:

Gross proceeds
Net proceeds
Estimated taxes
Risk
Remaining exposure
Potential downside
Potential upside
Liquidity
Exit duration
Probability distributions
Capital preservation
Profit preservation

The system shall make assumptions consistent across scenarios unless explicitly changed by the user.

Exit Timeline Module

The Exit Timeline Module shall provide a visual representation of a proposed exit.

It shall display:

Planned sales
Exit percentages
Dollar amounts
Tax-year boundaries
Holding-period milestones
Macro checkpoints
Risk checkpoints
User deadlines
Actual versus planned progress

The timeline shall dynamically update when material assumptions change.

Reporting Module

The Reporting Module shall generate structured reports.

Supported reports shall include:

Personalized Exit Report
Portfolio Risk Report
Macro Environment Report
Tax Impact Report
Scenario Comparison Report
Monte Carlo Report
Historical Stress Report
Tail-Risk Report
Exit Timeline Report
Executive Summary
Detailed Analytical Report

Reports shall include assumptions, methodology, limitations, and applicable disclosures.

Data Provenance Module

The Data Provenance Module shall track the origin and transformation of analytical data.

Each significant data element shall support:

Source
Timestamp
Retrieval date
Data period
Transformation history
Validation status
Data version

The system shall identify stale, incomplete, or questionable data.

Security and Privacy Module

The Security and Privacy Module shall protect sensitive financial information.

It shall support:

Secure authentication
Authorization
Encrypted communications
Secure credential storage
Session security
Access controls
Audit logging
Data minimization
Configurable retention
Secure API access
Protection of portfolio information

Brokerage credentials shall not be stored unless required by an optional integration and protected using appropriate security controls.

API Module

The API Module shall expose controlled programmatic access to ExitCompute.

API capabilities may include:

User management
Portfolio management
Position management
Market data
Macro data
Risk analysis
Tax analysis
Scenario creation
Scenario execution
Simulation execution
Report generation
Alerts
Configuration
Audit information

The API shall use documented schemas and validation.

The API shall provide OpenAPI documentation.

Web Interface Module

The Web Interface Module shall provide the primary user experience.

The interface shall support:

Account management
Portfolio entry
Financial profile setup
Risk assessment
Scenario creation
Scenario comparison
Macro dashboard
Risk dashboard
Tax dashboard
Exit timeline
Reports
Alerts
Model explanations
Disclosure review

The interface shall be accessible to users without advanced financial knowledge while providing an advanced analysis mode for experienced investors.

Optional Plugin Modules

ExitCompute shall support optional modules that can be installed without changing the core analytical architecture.

Brokerage Integration Plugin

Potential capabilities:

Portfolio import
Position synchronization
Cost-basis synchronization
Transaction history
Account balance synchronization

The plugin shall not execute trades by default.

Any future trade-execution capability shall require explicit user authorization and additional compliance controls.

Additional Market Data Plugin

Supports alternative market-data providers.

The plugin architecture shall allow providers to be added or replaced without changing the core analytical modules.

News Analysis Plugin

Potential capabilities:

Financial news ingestion
Event detection
News classification
Sentiment analysis
Market-moving event identification
Source comparison

News sentiment shall be treated as supplementary information rather than definitive evidence.

Advanced Sentiment Plugin

Potential capabilities:

Social sentiment
News sentiment
Investor sentiment
Sentiment regime detection
Sentiment divergence
Sentiment volatility

The system shall clearly identify sentiment-derived signals as probabilistic.

Retirement Planning Plugin

Potential capabilities:

Retirement income modeling
Withdrawal schedules
Required liquidity
Social Security inputs
Retirement-account considerations
Sequence-of-returns analysis
Retirement-specific exit strategies

Cryptocurrency Exit Plugin

Potential capabilities:

Cryptocurrency portfolio analysis
Crypto volatility modeling
Crypto drawdown scenarios
Tax-aware crypto liquidation
Crypto-specific risk indicators

Fixed Income Plugin

Potential capabilities:

Bond portfolio analysis
Treasury analysis
Duration risk
Interest-rate sensitivity
Credit risk
Fixed-income replacement scenarios

International Markets Plugin

Potential capabilities:

International equities
Currency exposure
Country risk
International macroeconomic indicators
Foreign tax considerations

Alternative Assets Plugin

Potential capabilities:

Real estate
Commodities
Private investments
Alternative asset liquidity
Asset rotation scenarios

Professional Advisor Plugin

The Professional Advisor Plugin may provide controlled functionality for qualified financial professionals.

Potential capabilities:

Advisor review
Client scenario sharing
Report review
Commenting
Approval workflows
Compliance review
Client collaboration

Professional functionality shall require appropriate legal and regulatory review before deployment.

Custom Risk Model Plugin

The Custom Risk Model Plugin shall allow qualified developers or organizations to add alternative risk methodologies.

Custom models shall expose:

Methodology
Inputs
Assumptions
Version
Limitations
Output definitions

Custom Tax Jurisdiction Plugin

The Custom Tax Jurisdiction Plugin shall support additional tax jurisdictions.

Each jurisdiction implementation shall document:

Tax rules
Effective dates
Applicable thresholds
Calculation methods
Assumptions
Limitations

AI Model Requirements

The AI layer shall be replaceable.

ExitCompute shall not require a proprietary AI model.

Supported implementations may include:

Open-source language models
Locally hosted models
Self-hosted inference
API-based models
Specialized financial language models

The AI layer shall not be the authoritative source for numerical calculations.

Numerical outputs shall originate from validated analytical engines.

Model Governance

Every analytical model shall have:

Model name
Model version
Purpose
Inputs
Outputs
Methodology
Assumptions
Limitations
Validation procedures
Test coverage
Change history

Material model changes shall increment the model version.

Historical scenario results shall retain the model version used to generate them.

Data Governance

ExitCompute shall maintain data-quality controls.

The system shall detect:

Missing data
Duplicate data
Stale data
Outliers
Invalid values
Inconsistent timestamps
Source conflicts

Data-quality problems shall be surfaced to users when they could materially affect an analysis.

Testing Requirements

The project shall include automated tests for:

Portfolio calculations
Cost-basis calculations
Tax calculations
Risk calculations
Scenario calculations
Monte Carlo simulations
Historical stress tests
Macro scoring
API validation
Security controls
Disclosure generation

Financial calculations shall include deterministic test cases.

Scenario engines shall include regression tests to detect unintended changes.

Reproducibility Requirements

A scenario should be reproducible using:

Input data
Data version
Model version
Scenario parameters
Risk parameters
Tax parameters
Simulation seed where applicable
Calculation configuration

Users should be able to identify why two analyses produced different results.

User-Controlled Assumptions

Users shall be able to review and modify applicable assumptions.

Examples include:

Expected return
Volatility
Inflation
Tax rate
Exit duration
Exit percentage
Risk threshold
Macro threshold
Liquidity requirement
Maximum acceptable loss

The system shall clearly distinguish user-provided assumptions from system-derived values.

No Automated Trade Execution by Core

The core ExitCompute system shall provide analysis and decision support rather than automatically executing securities transactions.

Optional brokerage plugins may provide account information.

Any future automated execution capability shall be isolated from the core analytical system and require separate authorization, security, compliance, and risk controls.

Financial Safety Principles

ExitCompute shall never guarantee:

A market peak
A market bottom
A specific return
A specific sale price
A specific tax outcome
A specific future market condition

The system shall communicate uncertainty whenever an output depends on assumptions, forecasts, simulations, or incomplete information.

Open-Source Requirements

ExitCompute shall remain compatible with the principles of the AGPL-3.0+ license.

The project shall preserve:

Source availability
License notices
Attribution requirements
Contributor acknowledgments
Network-source requirements
Modification notices
Applicable legal notices

All derivative deployments shall preserve the required attribution to:

Roxanne Ardary

roxanneardary.com

Documentation Requirements

Documentation shall cover:

System architecture
Core modules
Plugin modules
APIs
Data sources
Models
Calculations
Scenario methodologies
Tax assumptions
Risk methodologies
AI behavior
Security
Privacy
Compliance
Deployment
Contribution procedures

Documentation shall be maintained as the system evolves.

Future Expansion

ExitCompute shall be designed to support future capabilities without requiring fundamental changes to the core architecture.

Potential future capabilities include:

Additional asset classes
Additional jurisdictions
Advanced portfolio optimization
More historical stress periods
Real-time macro monitoring
Advanced regime detection
Institutional risk models
Advisor collaboration
Personalized financial planning
Additional AI models
Federated data sources
Additional visualization systems

Project Outcome

ExitCompute is intended to provide investors with a structured way to evaluate the decision to remain invested, reduce exposure, or exit.

The platform focuses on the practical problem of protecting accumulated capital and gains rather than attempting to predict markets with certainty.

The central analytical question is:

Given an investor’s financial needs, portfolio, tax circumstances, risk tolerance, macroeconomic environment, and available exit strategies, which modeled path provides the most appropriate balance between capital preservation, profit preservation, liquidity, taxation, and remaining market exposure?

Specification Branding License (SBL)

Fully AGPL-3.0+ compliant system
Copyleft enforced for network deployments
Required attribution:
- Roxanne Ardary
- https://www.roxanneardary.com/

Optional:

Specification Branding License (SBL)
- Attribution-free commercial deployment
- Pricing based on scale, usage, and deployment scope
- https://roxanneardary.com/exitcompute/

License & Notice Requirements

ExitCompute is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

By contributing to this project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to:
Roxanne Ardary and roxanneardary.com.
ExitCompute specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments. Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – ExitCompute

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – March 27, 2026
Created the repository for ExitCompute. Designed the foundational concept for an open-source AI system that models macroeconomic signals, portfolio risk, and tax-aware scenarios to support structured stock market exit planning.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License – ExitCompute

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.