AI Portfolio Builder

Build sophisticated portfolios using plain English. The AI Portfolio Builder translates your investment ideas into mathematically optimized portfolios, combining the intuitive power of natural language with rigorous quantitative methods.

Instead of manually researching, selecting, and weighting hundreds of securities, simply describe your investment thesis in natural language. Our AI interprets your goals, applies institutional-grade optimization techniques, and generates allocation-ready portfolios with clear rationale.

The Science Behind AI Portfolio Construction

Bridging Human Intuition and Mathematical Optimization

Traditional portfolio construction requires extensive quantitative knowledge. You need to understand correlation matrices, covariance calculations, and optimization algorithms.

The AI Builder democratizes this process by translating natural language investment ideas into mathematical frameworks.

The Process:

1. Natural Language Processing: AI interprets your investment thesis, constraints, and objectives
2. SQL Matching & Validation: Natural language queries are matched to structured SQL queries to ensure reproducible, replicable output and mitigate hallucination
3. Universe Construction: Identifies relevant securities based on your validated criteria
4. Factor Analysis: Evaluates holdings across multiple risk factors using Fama-French based models updated for real-time data
5. Mathematical Optimization: Applies modern portfolio theory including Black-Litterman, Risk Parity, and other academic optimization methods
6. Constraint Integration: Respects your specified limits and preferences

Academic Foundations

Modern Portfolio Theory: Harry Markowitz's groundbreaking work on efficient portfolios—maximizing return for given risk levels.

Black-Litterman Model: Combines market equilibrium with investor views to generate more intuitive portfolio recommendations.

Factor Investing Framework: Eugene Fama and Kenneth French's research on systematic factors that drive returns.

Risk Parity Theory: Ray Dalio's approach to balancing risk contribution rather than dollar amounts.

Behavioral Finance Integration: Acknowledging human biases while maintaining mathematical rigor.

Understanding Natural Language Processing

How AI Interprets Investment Ideas

The AI Builder uses advanced natural language understanding to extract:

Investment Objectives: Growth, income, capital preservation, wealth building Risk Tolerance: Conservative, moderate, aggressive, or specific volatility targets Time Horizon: Short-term (under 2 years), medium-term (2-10 years), long-term (10+ years) Constraints: ESG requirements, sector preferences, geographic limits, size restrictions Factor Preferences: Value, growth, momentum, quality, defensive characteristics

The Translation Process

Example Input: "Create a $50,000 growth portfolio focused on technology and healthcare innovation with moderate risk tolerance for a 10-year time horizon, avoiding tobacco and fossil fuel companies."

AI Interpretation:

• Investment amount: $50,000
• Objective: Growth-focused returns
• Sector preference: Technology and healthcare
• Theme: Innovation/disruption
• Risk level: Moderate (target volatility 12-15%)
• Time horizon: Long-term (10 years)
• ESG constraint: Exclude tobacco and fossil fuels
• Optimization goal: Maximize risk-adjusted returns subject to constraints

Getting Started with Natural Language Prompts

Basic Prompt Structure

Effective prompts typically include:

1. Investment Amount: Specify portfolio size for proper allocation
2. Primary Objective: Growth, income, stability, or balanced
3. Risk Tolerance: Conservative, moderate, aggressive, or specific metrics
4. Time Horizon: Investment timeline affects asset selection
5. Preferences/Constraints: Sectors, themes, geography, ESG considerations

Starter Prompt Templates

Growth-Focused Portfolios

"Create a $100,000 aggressive growth portfolio targeting technology innovation and emerging markets, with high risk tolerance and a 15-year time horizon."

AI Focus: High-growth sectors, emerging market exposure, higher volatility tolerance, long-term oriented

"Build a growth portfolio emphasizing artificial intelligence, robotics, and clean energy companies for someone comfortable with substantial volatility."

AI Focus: Thematic exposure, disruptive technologies, higher risk/reward profile

Income-Oriented Portfolios

"Generate a $75,000 dividend-focused portfolio for retirement income, emphasizing stability and quarterly distributions with low to moderate risk."

AI Focus: Dividend-paying stocks, REITs, utilities, consumer staples, lower volatility

"Create a high-yield portfolio balancing dividend stocks and REITs, targeting 4-5% annual income with some potential for capital appreciation."

AI Focus: Yield optimization, income sustainability analysis, REIT/dividend stock balance

Balanced and Strategic Portfolios

"Build a $200,000 balanced portfolio for a 35-year-old professional saving for retirement, combining growth and stability with international diversification."

AI Focus: Age-appropriate allocation, domestic/international balance, growth/value mix

"Design a defensive portfolio that can weather economic uncertainty while providing modest growth, emphasizing quality companies and avoiding cyclical sectors."

AI Focus: Quality factors, defensive characteristics, low cyclicality, recession resilience

Factor-Based Portfolios

"Create a value-investing portfolio following Warren Buffett's principles, focusing on undervalued quality companies with strong competitive moats."

AI Focus: Value factors, quality metrics, competitive advantages, fundamental analysis

"Build a momentum portfolio capturing trending stocks and sectors while managing drawdown risk through diversification and position sizing."

AI Focus: Momentum factors, trend analysis, risk management, correlation considerations

Advanced Prompt Engineering

Multi-Objective Optimization

"Create a $150,000 portfolio with three goals: ESG compliance with high environmental scores, international diversification across developed and emerging markets, and factor balance between growth and value. Target moderate risk for a 20-year horizon."

Complex Constraints: Multiple objectives require sophisticated optimization balancing competing goals.

Constraint-Heavy Portfolios

"Build a portfolio excluding: all fossil fuel companies, tobacco, weapons manufacturers, and companies with poor labor practices. Focus on: renewable energy, sustainable agriculture, educational technology, and healthcare innovation. Target moderate growth with below-average volatility."

ESG Integration: Negative and positive screening combined with financial objectives.

Strategic Asset Allocation

"Design a portfolio implementing a 60/40 stocks/bonds allocation, but within equities, emphasize: 40% US large-cap, 20% US small/mid-cap, 25% international developed, 15% emerging markets. Within bonds: mix of treasuries, corporates, and international bonds."

Precise Allocation: Specific asset allocation targets with detailed sub-category requirements.

Understanding AI Responses

Response Structure

AI-generated portfolios typically include:

Executive Summary: Investment thesis and key characteristics Detailed Holdings: Individual securities with allocations and rationale Risk/Return Profile: Expected performance and volatility estimates Factor Analysis: Exposure to key investment factors Implementation Notes: Practical considerations for execution

Interpreting Allocations

Portfolio Weights: Understanding why certain allocations were chosen

• Large positions (over 5%): High-conviction ideas aligned with thesis
• Medium positions (2-5%): Diversification and factor balance
• Small positions (under 2%): Tactical exposures or constraints-driven

Sector Distribution: How sector weights support investment objectives Geographic Allocation: Domestic vs. international exposure rationale Market Cap Distribution: Large, mid, small-cap balance explanation

Factor Exposure Analysis

Understanding Your Portfolio's Factor Profile:

Generated Portfolio Factor Analysis:
Market Beta: 1.15 (15% more volatile than market)
Value Factor: -0.2 (slight growth tilt)
Size Factor: 0.3 (modest small-cap exposure)
Momentum Factor: 0.8 (strong momentum characteristics)
Quality Factor: 0.6 (above-average quality)
Defensive Factor: -0.1 (slightly aggressive positioning)

Interpretation: This portfolio emphasizes momentum and quality while maintaining growth characteristics—consistent with a growth-oriented investment thesis.

Refining and Iterating

Continuous Improvement Process

Portfolio construction is iterative. Use these techniques to refine AI suggestions:

Feedback and Adjustment

Initial: "Create a tech-focused growth portfolio"
Refinement: "The portfolio seems too concentrated in large-cap tech. Add some mid-cap innovation companies and reduce the Apple/Microsoft weighting."
Further refinement: "Good balance now, but can we add some international tech exposure to capture global innovation trends?"

Constraint Modification

Original: "Build a dividend portfolio targeting 4% yield"
Modification: "The yield target looks good, but I'm concerned about interest rate sensitivity. Can we reduce REIT exposure and add more dividend-paying industrial and technology companies?"

Risk Adjustment

Initial Portfolio: 18% expected volatility
Adjustment: "This seems too aggressive for my moderate risk tolerance. Can we reduce volatility to around 12-14% while maintaining the growth focus?"

Advanced Refinement Techniques

Factor Tilting

"The portfolio has good momentum exposure, but I'd like to add some value characteristics for better diversification. Can we include some undervalued companies that still fit the innovation theme?"

Timing Considerations

"Given current market conditions with rising interest rates, can we adjust the portfolio to be less sensitive to rate changes while maintaining the core strategy?"

Implementation Constraints

"I love the portfolio, but I can only invest in ETFs due to account restrictions. Can you recreate this exposure using low-cost ETFs instead of individual stocks?"

Integration with Investment Process

From Builder to Analyzer

Every AI-generated portfolio can be immediately analyzed:

1. Generate Portfolio: Use natural language to create allocation
2. Instant Analysis: Automatically analyze risk, return, and factor characteristics
3. Optimization Review: Understand strengths and potential improvements
4. Implementation Planning: Get specific trade recommendations

Connecting to Research

From Chat to Builder

Chat Insight: "Clean energy sector showing strong momentum with supportive policy environment"
Builder Prompt: "Create a clean energy portfolio capitalizing on current momentum while managing regulatory and technology risks"

From Screener to Builder

Screener Results: Found 25 high-quality dividend stocks in defensive sectors
Builder Prompt: "Build a portfolio using these screened stocks, optimized for income and stability with appropriate diversification"

Portfolio Versioning and Comparison

Track Evolution: Save multiple versions to see how strategies develop Performance Comparison: Backtest different approaches against each other Sensitivity Analysis: Understand how small changes affect outcomes

Advanced Use Cases

Dynamic Strategy Implementation

Market Condition Adaptation

Bull Market: "Adjust my conservative portfolio to capture more upside while maintaining downside protection"
Bear Market: "Make my growth portfolio more defensive without abandoning the long-term strategy"
Uncertain Market: "Create a barbell strategy combining high-conviction growth bets with stable defensive positions"

Tactical Allocation

"My core portfolio is balanced, but I want to create a satellite position emphasizing the sectors that look most attractive for the next 6-12 months based on current market dynamics."

Lifecycle Investing

Age-Based Strategies

Young Professional: "Create an aggressive growth portfolio for someone 25 years old with 40 years until retirement and high risk tolerance"
Mid-Career: "Design a balanced portfolio for a 45-year-old focusing on wealth accumulation with moderate risk management"
Pre-Retirement: "Build a capital preservation portfolio for someone 5 years from retirement, emphasizing income and stability"

Goal-Based Investing

Education Funding: "Create a portfolio to fund college expenses in 10 years, balancing growth potential with the certainty of having funds available when needed"
Home Purchase: "Design a conservative growth portfolio for a house down payment in 3-5 years, prioritizing capital preservation with modest appreciation"

Institutional-Style Strategies

Factor Investing Implementation

"Create a multi-factor portfolio systematically capturing value, momentum, and quality factors while maintaining broad diversification and managing turnover"

Risk Parity Approach

"Build a risk parity portfolio where each major asset class contributes equally to overall portfolio risk, not dollar allocation"

Best Practices and Common Pitfalls

Effective Prompt Writing

Be Specific About Constraints: Vague preferences lead to generic portfolios Include Context: Market views, personal situation, and investment experience matter Specify Success Metrics: How will you measure if the portfolio meets objectives? Consider Implementation: Include practical constraints like account types, tax implications

Avoiding Common Mistakes

Over-Complexity: Simple, well-executed strategies often outperform complex ones Chasing Performance: Don't build portfolios based solely on recent winners Ignoring Costs: Factor in transaction costs, expense ratios, and tax implications Perfect Portfolio Fallacy: No portfolio is perfect for all market conditions

Validation and Reality Checks

Sanity Check Allocations: Do the weights make intuitive sense? Stress Test Scenarios: How would the portfolio perform in different market conditions? Compare to Benchmarks: Is the complexity justified by expected outperformance? Implementation Feasibility: Can you actually execute and maintain this portfolio?

Troubleshooting and Optimization

Common Issues and Solutions

Generic Portfolios:

• Problem: AI generates broad, unfocused allocations
• Solution: Provide more specific constraints and preferences

Over-Concentration:

• Problem: Too much weight in single securities or sectors
• Solution: Add diversification constraints or risk limits

Misaligned Risk Level:

• Problem: Portfolio volatility doesn't match stated risk tolerance
• Solution: Specify numerical targets (e.g., "target 10-12% volatility")

Poor Factor Balance:

• Problem: Extreme factor exposures create unintended risks
• Solution: Request more balanced factor exposure or specific factor targets

Advanced Optimization Requests

"Optimize this portfolio for tax efficiency in a taxable account, considering dividend yields and potential capital gains"
"Adjust allocations to minimize tracking error while maintaining the core investment thesis"
"Create a more liquid version of this portfolio for someone who might need to access funds quickly"

Next Steps and Integration

Workflow Integration

Complete Investment Process:

1. Research: Use Chat to understand market conditions and opportunities
2. Screen: Identify potential securities using Screener
3. Build: Create optimized portfolios with AI Builder
4. Analyze: Deep-dive analysis with Portfolio Analyzer
5. Monitor: Track performance and rebalance using Watchlists

Continuous Learning

Track Performance: Monitor how AI-generated portfolios perform over time Refine Prompts: Learn what prompt styles generate better results Study Factors: Understand which factor exposures work in different market conditions Integration Mastery: Become fluent in moving between platform features

Advanced Features

• Portfolio Analyzer: Deep quantitative analysis and comprehensive analysis of AI-generated allocations
• Investment Methodology: Complete investment process workflows and systematic approaches

The AI Portfolio Builder becomes more powerful as you develop expertise in prompt engineering and integrate it with other platform features. Start with simple prompts and gradually build more sophisticated portfolio construction workflows.