InvestTool

Financial Goal Setting and Risk Analysis Framework

A C++ terminal application that implements standard financial equations for analyzing investment scenarios, quantifying risk, and evaluating investment efficiency.

⚠️ WARNING: This tool performs mathematically accurate calculations but does NOT predict the future. Past performance is not a guarantee of future results. Use for risk analysis and planning purposes only.

Features

Core Features

1. Future Value Calculations (Dollar-Cost Averaging)

• Formula 1: Calculate Future Value given regular payments
• Formula 2: Calculate required payment to reach a financial goal
• Formula 3: Calculate time needed to reach a goal
• Annual/Monthly interest rate conversions

2. Risk Measurement

• Formula 4: Variance (σ²) - Measure of return dispersion
• Formula 5: Volatility/Standard Deviation (σ) - Standard risk measure
• Formula 8: Correlation Coefficient (ρ) - Asset correlation analysis
• Formula 9: Portfolio Volatility - Two-asset portfolio risk calculation
• Daily/Monthly to Annual volatility conversions

3. Risk-Adjusted Performance

• Formula 6: Sharpe Ratio - Return per unit of risk
• Formula 7: Beta (β) - Correlation with market volatility
• Formula 10-11: Sortino Ratio - Downside risk-adjusted return
• Formula 12: Value at Risk (VaR) - Maximum expected loss quantification
• Covariance calculations for portfolio analysis

4. Asset Classification

• Classify assets by volatility into 5 risk levels:
  • Very Low Risk (0-2% annual volatility)
  • Low Risk (2-8%)
  • Medium Risk (8-20%)
  • High Risk (20-40%)
  • Very High Risk/Speculation (40%+)
• Detailed risk interpretations and asset examples

Premium Features

5. Portfolio Optimization (Efficient Frontier)

• Monte Carlo Simulation: Test 10,000+ random portfolio allocations
• Modern Portfolio Theory (MPT): Find optimal asset mix for maximum Sharpe Ratio
• Diversification Analysis: Account for asset correlations and covariance
• Risk-Return Tradeoff: Identify efficient portfolios on the frontier

Example Use:

EfficientFrontierResult result = PortfolioOptimizer::CalculateEfficientFrontier(
    {goldReturns, sp500Returns, btcReturns},
    {"Gold", "S&P 500", "Bitcoin"},
    10000,  // Number of simulations
    0.02    // Risk-free rate
);
// Returns optimal weights, expected return, risk, and Sharpe Ratio

6. Advanced Risk Metrics (Sortino Ratio & VaR)

• Sortino Ratio: Better than Sharpe - only penalizes downside volatility
• Downside Deviation: Measures only negative return volatility
• Value at Risk (VaR): Parametric and Historical methods
• Confidence Levels: 90%, 95%, and 99% VaR calculations

Example Use:

// Sortino Ratio (ignores upside volatility)
double sortino = RiskAnalyzer::CalculateSortinoRatio(returns, 0.02);

// Value at Risk
double var95 = RiskAnalyzer::CalculateHistoricalVaR(returns, 200000.0, 0.95);
// "95% confident won't lose more than $X"

7. Strategy Backtesting

• Dollar-Cost Averaging (DCA): Test fixed-amount periodic investments
• Buy and Hold: Simple buy-and-hold strategy
• Moving Average Crossover: Golden Cross / Death Cross signals
• Performance Metrics: Total return, annualized return, maximum drawdown

Example Use:

// Test DCA strategy
DCAConfig config = {500.0, 30};  // $500 every 30 days
BacktestResult result = StrategyBacktester::RunDCABacktest(
    historicalPrices, 10000.0, config
);
// Compare multiple strategies side-by-side

8. Ratio Analysis (Z-Score for Mean Reversion)

• Z-Score Calculation: Identify statistical anomalies
• Mean Reversion Signals: Detect when ratios are extreme
• Relative Value Analysis: Compare two assets (Gold/Silver, etc.)
• Statistical Thresholds: |Z| > 2 indicates extreme deviation

Example Use:

RatioAnalysisResult result = RatioAnalyzer::AnalyzeRatio(
    goldPrices, silverPrices, "Gold", "Silver"
);
// Get Z-score, signal, and interpretation
// Z > 2: Gold extremely expensive relative to silver
// Z < -2: Gold extremely cheap relative to silver

Educational Framework

• Comprehensive documentation of limitations
• Black Swan event awareness (Nassim Taleb)
• Source citations for all formulas
• Clear warnings about predictive validity
• Implementation pseudocode and mathematical foundations

Building the Project

This is a C++ terminal application. To build and run:

Prerequisites

• CMake 3.10 or higher
• C++ compiler with C++17 support (GCC, Clang, or MSVC)

Build Instructions

# Create build directory
mkdir build
cd build

# Configure with CMake
cmake ..

# Build the project
make

# Run the application
./investool

Project Structure

Core Components:

• FinancialCalculator.h/cpp - Future Value of Annuity calculations (Formulas 1-3)
• RiskAnalyzer.h/cpp - Risk measurement and risk-adjusted performance metrics (Formulas 4-13)
• AssetClassifier.h/cpp - Asset classification by volatility and risk interpretation
• main.cpp - Demonstration application with practical examples

Premium Features:

• PortfolioOptimizer.h/cpp - Efficient Frontier via Monte Carlo simulation (Formulas 8-9)
• StrategyBacktester.h/cpp - Investment strategy backtesting engine
• RatioAnalyzer.h/cpp - Z-Score ratio analysis for mean reversion (Formula 13)

Build Configuration:

• CMakeLists.txt - CMake build configuration

Documentation:

• DOCUMENTATION.md - Complete API reference for core features (Formulas 1-7)
• ADVANCED_FORMULAS.md - Detailed mathematical documentation for premium features (Formulas 8-13)
• README.md - This file

Build Artifacts:

• build/ - CMake build directory (generated, gitignored)

Quick Start Example

#include "FinancialCalculator.h"
#include "RiskAnalyzer.h"
#include "AssetClassifier.h"

// Calculate investment goal
double fv = FinancialCalculator::CalculateFutureValue(20000, 0.01, 7);

// Analyze risk
std::vector<double> returns = {0.15, -0.20, 0.30, -0.10, 0.25};
double volatility = RiskAnalyzer::CalculateVolatility(returns);
double annualVol = RiskAnalyzer::MonthlyToAnnualVolatility(volatility);

// Classify asset
AssetClass classification = AssetClassifier::ClassifyByVolatility(annualVol);
std::cout << classification.description << std::endl;

For complete API reference and detailed examples, see DOCUMENTATION.md.

Key Formulas

Core Formulas (Formulas 1-7)

Formula	Purpose	Implementation
Formula 1	Future Value (FV)	CalculateFutureValue(pmt, i, n)
Formula 2	Required Payment (PMT)	CalculateRequiredPayment(fv, i, n)
Formula 3	Required Periods (n)	CalculateRequiredPeriods(fv, pmt, i)
Formula 4	Variance (σ²)	CalculateVariance(returns)
Formula 5	Volatility (σ)	CalculateVolatility(returns)
Formula 6	Sharpe Ratio	CalculateSharpeRatio(returns, rf)
Formula 7	Beta (β)	CalculateBeta(assetReturns, marketReturns)

Premium Formulas (Formulas 8-13)

Formula	Purpose	Implementation
Formula 8	Correlation Coefficient (ρ)	CalculateCorrelation(returns1, returns2)
Formula 9	Portfolio Volatility (σ_p)	CalculatePortfolioVolatility(w1, σ1, w2, σ2, ρ)
Formula 10	Downside Deviation (σ_d)	CalculateDownsideDeviation(returns, MARR)
Formula 11	Sortino Ratio	CalculateSortinoRatio(returns, rf)
Formula 12	Value at Risk (VaR)	CalculateHistoricalVaR(returns, value, conf)
Formula 13	Z-Score	CalculateZScore(value, historicalData)

Sources

Core Features

• Future Value Formulas: Corporate Finance Institute (CFI), standard finance literature
• Risk Metrics: Modern Portfolio Theory (MPT), documented by Investopedia
• Sharpe Ratio: William F. Sharpe (Nobel Prize winner, 1990)
• Beta & CAPM: Capital Asset Pricing Model, standard finance theory

Premium Features

• Modern Portfolio Theory: Harry Markowitz, "Portfolio Selection" (1952), Nobel Prize winner (1990)
• Sortino Ratio: Frank A. Sortino and Robert van der Meer, "Downside Risk" (1991)
• Value at Risk: J.P. Morgan RiskMetrics (1996); Philippe Jorion, "Value at Risk" (2006)
• Z-Score & Statistical Methods: Standard statistical theory, quantitative finance literature

Risk Awareness

• Black Swan Theory: Nassim Nicholas Taleb
  • "The Black Swan: The Impact of the Highly Improbable" (2007)
  • "Antifragile: Things That Gain from Disorder" (2012)
  • "Fooled by Randomness" (2001)

License

This is an educational tool implementing standard financial formulas from public domain finance literature.