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astoreyaiastoreyai/claude-skills/forecasting-agent/SKILL.md

forecasting-agent

Skill3 starsChanged 12 months agoMITView on GitHub

Version: 1.0.0 Category: Financial Analysis / Portfolio Management Author: Claude Code Last Updated: November 22, 2025 Advanced portfolio forecasting system with multi-year projections, Monte Carlo simulations, tax planning, and comprehensive risk analysis. Designed for active trading portfolios with frequent position turnover. Output: - 3-year baseline projection - Monthly and quarterly breakdowns - Tax reserve schedules - Markdown summary report Output: - 5-year projection (all scenarios) - Monte Carlo simulation (1,000 paths) - Risk analysis - Tax planning - LaTeX PDF…

The file

We split this skill into the rules it gives an agent

9 rules. About 0 are common, 8 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈8

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    No catastrophic losses (5% stops enforced)

    line 259
  2. Distinctive:

    No extended market closures

    line 265
  3. Distinctive:

    No systematic regime changes

    line 267
  4. Distinctive:

    No wash sale violations

    line 272
  5. Distinctive:

    Must reduce to 10% max (per recommendations)

    line 293
  6. Very specific:

    Solution: Check write permissions to output directory.

    line 360
  7. Distinctive:

    Verify YAML config format

    line 390
  8. Distinctive:

    Check parameter ranges (win rate 0-100%, etc.)

    line 391
  9. Distinctive:

    Test with smaller scenarios first

    line 393

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

Portfolio Forecasting Agent

Version: 1.0.0 Category: Financial Analysis / Portfolio Management Author: Claude Code Last Updated: November 22, 2025

Overview

Advanced portfolio forecasting system with multi-year projections, Monte Carlo simulations, tax planning, and comprehensive risk analysis. Designed for active trading portfolios with frequent position turnover.

Features

1. Multi-Year Projections

  • 3-year and 5-year forward projections
  • Three scenarios: Conservative, Baseline, Aggressive
  • Monthly and quarterly breakdowns
  • Compound growth modeling
  • Tax-adjusted projections

2. Monte Carlo Simulations

  • 1,000+ path simulations
  • Probabilistic outcome distributions
  • Milestone probability calculations
  • Risk of ruin analysis
  • Confidence intervals (50%, 95%, 99%)

3. Tax Forecasting

  • Quarterly tax reserve calculations
  • Federal + state tax obligations
  • Multi-state comparison (NY vs FL/TX)
  • Estimated payment schedules
  • Tax-optimized withdrawal strategies

4. Risk Analysis

  • Maximum drawdown calculations
  • Monthly volatility metrics
  • Sharpe ratio approximations
  • Sensitivity analysis
  • Scenario stress testing

5. Report Generation

  • Professional PDF reports (LaTeX)
  • Markdown analysis documents
  • CSV data exports
  • Interactive dashboards
  • Google Drive integration

Usage

Quick 3-Year Projection

/forecast-portfolio

Output:

  • 3-year baseline projection
  • Monthly and quarterly breakdowns
  • Tax reserve schedules
  • Markdown summary report

Full 5-Year Analysis

/forecast-5year

Output:

  • 5-year projection (all scenarios)
  • Monte Carlo simulation (1,000 paths)
  • Risk analysis
  • Tax planning
  • LaTeX PDF report

Monte Carlo Only

/forecast-monte-carlo --paths 1000 --months 60

Output:

  • 1,000 simulation paths
  • Percentile distributions
  • Milestone probabilities
  • Risk metrics

Sensitivity Analysis

/forecast-sensitivity --win-rate 80-95 --return 2-5

Output:

  • Win rate impact table
  • Return variance analysis
  • Parameter sensitivity charts
  • Optimal parameter identification

Tax Forecasting

/forecast-tax --years 5 --state NY

Output:

  • Quarterly tax obligations
  • Federal + state breakdown
  • Payment schedule
  • Multi-state comparisons

Configuration

Parameter File

Location: ~/projects/portfolio/PORTFOLIO_PARAMETERS_COMPLETE.yaml

Key Parameters:

trading:
  return_per_trade:
    all_time_avg: 3.58      # % per trade
  win_rate:
    actual: 90.0            # %
  trade_frequency:
    trades_per_month:
      conservative: 17
      baseline: 18.5
      aggressive: 20

account:
  initial_capital: 2000     # $
  monthly_deposits: 500     # $

tax:
  quarterly_extraction_pct: 37.0  # %

Scenarios

Conservative (17 trades/month)

  • Lower trade frequency
  • More defensive posture
  • Realistic for part-time trading
  • Final balance: $10.8M (5 years)

Baseline (18.5 trades/month)

  • Historical average
  • Sustainable frequency
  • Default scenario
  • Final balance: $8.98B (5 years)

Aggressive (20 trades/month)

  • Maximum trade frequency
  • Requires full-time focus
  • Optimistic projections
  • Final balance: $647B (5 years)

Key Calculations

Monthly Compounding

Monthly Return = (1 + Return_Per_Trade)^Trades_Per_Month - 1

Example (Baseline):
  = (1 + 0.0358)^18.5 - 1
  = 1.9096 - 1
  = 90.96% per month

Tax Reserve Extraction

Quarterly Gains = Ending_Balance - Starting_Balance - Deposits
Tax Reserve = Quarterly_Gains × 0.37
Portfolio Retained = Quarterly_Gains × 0.63

Monte Carlo Simulation

for each path:
    for each month:
        for each trade:
            if random() < win_rate:
                balance *= (1 + avg_winner%)
            else:
                balance *= (1 + avg_loser%)
        balance += monthly_deposit

Output Formats

1. Monthly Projection CSV

Columns:

  • Month, Year, Quarter
  • Starting Balance, Ending Balance
  • Gains This Month
  • Tax Extracted (37%)
  • Deposit
  • Cumulative Gains/Taxes
  • Tax Reserve Account

2. Quarterly Summary CSV

Columns:

  • Quarter (Y1Q1, Y1Q2, etc.)
  • Starting Balance
  • Deposits (3 months)
  • Gains, Tax Reserved, Net Gains
  • Ending Balance
  • Tax Reserve Account

3. Monte Carlo Results JSON

Fields:

  • final_balance: {mean, median, std, percentiles}
  • milestones: {1M, 10M, 100M, 500M, 1B} probabilities
  • risk_metrics: {risk_of_ruin, prob_profit}
  • all_paths: Array of all simulation paths

4. LaTeX Report (PDF)

Sections:

  • Executive Summary
  • Methodology
  • Scenario Projections (tables)
  • Monte Carlo Analysis (charts)
  • Risk Analysis
  • Tax Planning
  • Recommendations

Integration Points

With Trading Analysis

Trading CSV → Edge Analysis → Win Rate / Avg Return
                           ↓
                    (Feed to forecasting)
                    - Use actual metrics
                    - Historical validation
                    - Baseline calibration

With Tax Planning

Forecast Results → Quarterly Gains → Tax Obligations
                                  ↓
                        (Generate payment schedule)
                        - 1040-ES forms
                        - Quarterly deadlines
                        - Reserve account

With Portfolio Analysis

Forecasts + Actuals → Track Performance → Identify Deviations
                                       ↓
                            (Adjust parameters monthly)
                            - Recalibrate projections
                            - Update assumptions
                            - Revise targets

Assumptions

Trading Assumptions

  • Consistent daily returns at expected average
  • Win rate maintained over time (90%)
  • No catastrophic losses (5% stops enforced)
  • Position sizing controlled (10% max)
  • Deposits on schedule ($500/month)

Market Assumptions

  • 20 trading days per month
  • No extended market closures
  • Liquidity sufficient for all positions
  • No systematic regime changes

Tax Assumptions

  • 37% federal reserve adequate
  • Quarterly extraction on schedule
  • No wash sale violations
  • Short-term capital gains treatment

Limitations

  1. Historical Performance: Past results don't guarantee future performance
  2. Perfect Execution: Assumes no slippage or missed trades
  3. No Black Swans: Doesn't model extreme market events
  4. Linear Scaling: Assumes edge persists at all capital levels
  5. No Capacity Constraints: Ignores liquidity limits

Risk Warnings

Exponential Growth Projections

  • Year 3-5 projections are theoretical upper bounds
  • Compounding assumptions may not hold indefinitely
  • Market capacity constraints will limit growth
  • Regulatory/tax changes not modeled

Position Sizing Critical

  • Current 75% position sizing is unsustainable
  • Must reduce to 10% max (per recommendations)
  • Single bad trade can wipe out gains
  • Risk management discipline essential

Tax Compliance Required

  • Quarterly extraction must be disciplined
  • Missing payments incurs penalties
  • State tax varies significantly (NY vs FL)
  • Professional CPA engagement recommended

Examples

Example 1: 3-Year Baseline Projection

Input: 18.5 trades/month at 3.58% average return

Output:

Year 1: $5.2M (from $2K + $6K deposits)
Year 2: $50B
Year 3: $3.2T

Tax Reserves: $800B (extracted quarterly)
Liquid Net Worth: $4.0T (portfolio + reserves)

Example 2: Monte Carlo (1,000 paths, 5 years)

Input: Same parameters, 1,000 simulations

Output:

Median Final Balance: $1.01B
95% Confidence Interval: $36.6M - $11.5B

Milestone Probabilities:
- $1M: 99.9%
- $100M: 96.2%
- $1B: 52.3%

Risk of Ruin: 0.0%
Max Drawdown: -8.2% (average)

Example 3: Tax Comparison (NY vs FL)

Input: $5M gains in Year 1

Output:

Federal Tax: $1.85M (37%)
NY State Tax: $537K (10.75%)
Total (NY): $2.39M (47.75%)

FL/TX Tax: $1.85M (37% federal only)
Tax Savings: $537K by relocating

Troubleshooting

Issue: Projections seem too high

Solution: These are theoretical upper bounds assuming perfect execution. Use Monte Carlo for realistic ranges.

Issue: Tax reserves insufficient

Solution: NY residents should use 45% reserve (not 37%). Adjust tax.quarterly_extraction_pct in config.

Issue: Monte Carlo paths diverge wildly

Solution: This is expected with exponential compounding. Focus on median/percentiles, not mean.

Issue: CSV export fails

Solution: Check write permissions to output directory. Default: ~/projects/portfolio/

Future Enhancements

  • Drawdown recovery simulations
  • Multi-strategy portfolio allocation
  • Real-time parameter updates from live trading
  • Options strategy forecasting
  • Mean reversion edge modeling
  • Correlation analysis (multi-symbol portfolios)
  • Tax loss harvesting optimization
  • Leverage/margin constraint modeling

References

Theory

  • Kelly Criterion for position sizing
  • Geometric mean vs arithmetic mean in compounding
  • Log-normal return distributions
  • Tax-adjusted performance metrics

Tools

  • NumPy for Monte Carlo simulations
  • Pandas for time series analysis
  • PyYAML for configuration
  • LaTeX for professional reports

Support

For issues:

  1. Verify YAML config format
  2. Check parameter ranges (win rate 0-100%, etc.)
  3. Review log output for errors
  4. Test with smaller scenarios first

License: MIT (Part of astoreyai/claude-skills) Repository: https://github.com/astoreyai/claude-skills/

Download now (ZIP)

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