Introduction to TradeDots Portfolio Manager
What is Portfolio Manager?
Portfolio Manager is TradeDots' quantitative portfolio management toolkit designed to bring institutional-grade portfolio optimization and risk management tools to retail traders. Built on Modern Portfolio Theory and quantitative finance principles, it empowers traders to make informed decisions through data, backtesting, and proven methodologies.
The Portfolio Management Challenge
What traders face:
Position sizing: How to calculate optimal allocation for each stock?
Rebalancing: When do quantitative signals indicate portfolio adjustments?
Risk management: How to measure and monitor total portfolio risk?
Correlation: How to quantify relationships between positions?
Performance tracking: Which strategies show statistical significance?
Systematic approach: How to remove emotion through rule-based frameworks?
Traditional retail approaches:
Manual spreadsheets (time-consuming, no quantitative framework)
Equal weighting (ignores risk-adjusted returns)
No systematic methodology (inconsistent decision-making)
"Gut feeling" for position sizing (no statistical foundation)
Institutional approaches (what professionals use):
Quantitative models: Kelly Criterion, Risk Parity, Mean-Variance Optimization
Portfolio analytics: Sharpe ratios, correlation matrices, Value-at-Risk
Backtesting frameworks: Historical validation of methodologies
Risk management systems: Real-time monitoring and alerts
The TradeDots Solution
Quantitative portfolio management tools that provide:
Position Sizing Calculators: Apply proven methodologies (Kelly Criterion, Risk Parity, volatility-adjusted models)
Backtesting Framework: Historical analysis showing how different approaches performed (2020-2024 data)
Portfolio Analytics Dashboard: Real-time risk metrics based on Modern Portfolio Theory
Correlation Analysis: Quantify relationships between positions to optimize diversification
Performance Attribution: Statistical analysis of what's working and why
Educational Resources: Learn institutional-grade portfolio management principles
Core Philosophy: We provide the tools, data, and knowledge. You make the informed decisions.
Key Features (Planned)
Feature 1: Position Sizing Calculator
What it provides:
Quantitative Models: Kelly Criterion, Risk Parity, Volatility-Adjusted Position Sizing
Backtesting Results: Historical performance of different position sizing methodologies (2020-2024)
Risk Calculators: Tools to determine position size based on personal risk tolerance and portfolio constraints
Correlation Adjustments: Quantify how correlated positions should influence allocation decisions
How it works:
Analyzes AI Score, technical setup quality, volatility, and correlations
Calculates position sizes using multiple quantitative models
Shows backtesting results for each methodology
Provides educational context on why each model works
Educational Example (Backtesting-Based Framework):
NVDA (AI Score 97, high conviction, low current correlation):
Kelly Criterion: Historical data shows 6-10% optimal range for similar setups
Risk Parity: Volatility-adjusted calculation indicates 7-9% allocation
Backtesting Result: Positions with these characteristics averaged +12.3% returns over 30-day holding period (2022-2024)
User Decision: Apply methodology based on personal risk tolerance
AMD (AI Score 95, correlated with NVDA 0.85):
Correlation Tool: Shows 0.85 correlation with existing NVDA position
Academic Research: Portfolios with >0.80 correlation experienced X% higher drawdowns
Adjusted Calculation: Tools show correlation-adjusted position size range
Educational Insight: Learn how correlation impacts portfolio risk
JPM (AI Score 85, different sector, correlation 0.15):
Diversification Benefit: Low correlation provides portfolio stabilization
Backtesting: Adding low-correlation positions historically reduced portfolio volatility by X%
Quantitative Framework: Calculator shows allocation range for diversification benefits
Outcome: Traders learn institutional methodologies and apply quantitative frameworks to their personal trading decisions.
Feature 2: Rebalancing Analysis Tool
What it provides:
Quantitative Signals: Identifies when positions deviate from optimal allocation ranges
Statistical Triggers: Shows thresholds based on historical performance data
Rebalancing Scenarios: Calculates potential outcomes of different rebalancing approaches
Educational Frameworks: Learn when and why to rebalance based on quantitative research
How it works:
Monitors all positions continuously against quantitative benchmarks
Identifies rebalancing triggers:
AI Score changes >15 points (historically correlated with X% performance degradation)
Technical indicator divergences (backtesting shows Y% probability of reversal)
Better opportunities emerge (comparative risk/reward analysis)
Provides quantitative analysis of different rebalancing options
Educational Example (Data-Driven Analysis):
Scenario 1: TSLA AI Score drops from 94 to 78
Historical Data: Stocks with >15-point score drops underperformed by 8.2% on average (2020-2024)
Momentum Analysis: Backtesting shows 68% probability of continued weakness
Rebalancing Framework: Tool calculates risk/reward of reducing vs holding position
Educational Value: Learn quantitative triggers for position management
Scenario 2: NVDA AI Score improves from 95 to 98 + breakout occurs
Statistical Analysis: Breakouts with improving AI scores showed +18.5% avg continuation (30-day)
Risk Analysis: Tool shows current allocation vs optimal range
Backtesting: Historical data on similar setups and rebalancing outcomes
Decision Framework: Quantitative basis for size adjustment considerations
Scenario 3: AAPL shows technical breakdown + score drops to 65
Exit Criteria: Backtesting shows scores <70 with technical breakdowns had -12% avg return
Statistical Significance: 73% of similar historical setups continued declining
Risk Management: Tool quantifies cost of exit vs potential further loss
Scenario 4: JPM enters top 5 rankings with strong technical setup
Entry Analysis: Backtesting of new entries with similar characteristics
Portfolio Impact: Tool calculates how addition affects total portfolio risk
Quantitative Framework: Shows optimal allocation ranges based on historical data
Outcome: Traders understand quantitative rebalancing triggers and make data-informed portfolio adjustments.
Feature 3: Portfolio Risk Analytics Dashboard
What it provides:
Modern Portfolio Theory Metrics: Sharpe ratio, Sortino ratio, maximum drawdown, Value-at-Risk
Risk Decomposition: Understand sources of portfolio risk (systematic vs idiosyncratic)
Correlation Matrix: Visual representation of position relationships
Scenario Analysis: "What-if" calculators for portfolio changes
Educational Resources: Learn how institutional investors measure and manage risk
Dashboard Metrics:
Total Portfolio Value: Real-time valuation
Position Count: Number of holdings
Portfolio Beta: Sensitivity to market movements
Volatility: Standard deviation of portfolio returns
Sharpe Ratio: Risk-adjusted return measurement
Maximum Drawdown: Largest peak-to-trough decline
Value-at-Risk (VaR): Statistical estimate of potential loss
Sector Exposure: Percentage allocation by sector with historical context
Correlation Heatmap: Visualize position interdependencies
Risk Analysis Tools:
Sector Concentration: Historical data shows portfolios >50% in single sector experienced X% higher volatility
Correlation Analysis: Tools identify when positions move together (reducing diversification benefits)
Stress Testing: Calculate portfolio impact under various market scenarios
Educational Alerts: "Your current tech exposure (65%) is Y% above optimal historical range"
Outcome: Traders gain institutional-level portfolio risk visibility and understand quantitative risk management principles.
Feature 4: Performance Attribution Analysis
What it analyzes:
Strategy Performance: Win rates, average returns, and risk-adjusted metrics by strategy type
Indicator Effectiveness: Statistical significance of different indicator combinations
Sector/Timeframe Analysis: Which sectors and holding periods produced best risk-adjusted returns
AI Score Correlation: Validate relationship between AI Scores and actual performance
Statistical Significance: Determine if performance differences are meaningful or random
Analytical Reports:
Weekly Performance: Returns, trades, win rate, Sharpe ratio
Monthly Strategy Review: Comparative analysis of different approaches
Yearly Performance: Long-term statistical validation
Quantitative Insights: Data-driven analysis of trading patterns
Educational Example (Statistical Analysis):
Finding: Swing trades in tech sector showed 72% win rate vs 52% day trades in finance
Statistical Validation: Sample size n=150, p-value <0.05 (statistically significant)
Risk-Adjusted Analysis: Tech swing trades: Sharpe ratio 1.8 vs Finance day trades: Sharpe ratio 0.6
Backtesting Context: Similar market conditions (2022-2024) showed consistent pattern
Educational Value: Learn to identify statistically significant trading edges
Decision Framework: Tools help focus on what's quantitatively proven to work
Quantitative Metrics Tracked:
Win rate by strategy, sector, timeframe
Average R:R (risk:reward) by setup type
Sharpe ratio by approach
Maximum drawdown by strategy
Profit factor (gross profit / gross loss)
Expectancy (average $ per trade)
Outcome: Traders understand their performance through institutional-grade statistical analysis and identify edges with quantitative evidence.
Feature 5: Integrated Workflow Tools
Seamless analytical workflow:
AI Rankings: Identifies highest-scoring stocks based on momentum, volume, technicals
TradeDots Indicators: Provides technical timing signals
Portfolio Tools: Calculates position sizing, risk impacts, correlation effects
AI Chat: Answers questions about portfolio analytics and methodologies
Educational Workflow Example: Morning Analysis:
AI App identifies: NVDA (#1, score 97), AMD (#2, score 95), TSLA (#3, score 94)
Portfolio Analysis:
Current Holdings: NVDA 8%, AMD 5% (total tech: 13%)
Correlation Analysis: Tool calculates adding TSLA would create 0.78 avg correlation with existing positions
Historical Context: Backtesting shows portfolios with >20% in highly correlated positions (r>0.75) experienced 15% higher drawdowns during market corrections
Risk Calculation: Tool shows adding TSLA at various sizes and total portfolio risk impact
Quantitative Framework:
Option A: Add TSLA 4% → Total tech 21%, avg correlation 0.78, portfolio volatility +8%
Option B: Add TSLA 2% + JPM 4% → Total tech 19%, reduced correlation 0.62, portfolio volatility +4%
Backtesting: Option B historically produced 1.4x better risk-adjusted returns in similar market conditions
Educational Insight: Learn diversification principles through quantitative comparison
Intraday Management:
NVDA hits technical target
Performance Tool: Calculates realized gain
Rebalancing Analysis: Shows current NVDA allocation vs optimal range
Historical Data: Taking partial profits at targets historically improved long-term performance by X%
Decision Framework: Quantitative basis for profit-taking and redeployment decisions
Outcome: Complete workflow where each tool provides data, analysis, and educational context for informed decision-making.
How Portfolio Manager Differs
vs Manual Spreadsheets
Feature
Manual Spreadsheet
Portfolio Manager
Position sizing
Manual calculation
Quantitative models with backtesting
Rebalancing
You decide when
Daily quantitative analysis tools
Risk monitoring
Manual tracking
Real-time analytics dashboard
Performance analysis
Limited metrics
Comprehensive statistical analysis
Integration
Separate tool
Seamless with AI Rankings + Indicators
Educational Value
None
Learn institutional methodologies
Time required
30-60 min/day
5-10 min/day (tools do calculations)
vs Traditional Portfolio Tools
Traditional portfolio tools (Personal Capital, Morningstar, etc.):
Designed for long-term buy-and-hold investors
Focus on asset allocation (stocks vs bonds)
No active trading support or technical analysis
No integration with momentum-based strategies
No quantitative models for position sizing
No backtesting frameworks
TradeDots Portfolio Manager:
Designed for active traders (day trading, swing trading)
Focus on tactical stock allocation (which stocks now)
Integrated with AI Rankings and technical indicators
Quantitative tools for position sizing and risk management
Historical backtesting of methodologies (2020-2024)
Educational framework teaching institutional approaches
Statistical performance attribution
Who It's For
Ideal Users
✅ Active traders holding 5-15 positions simultaneously ✅ Quantitatively-minded traders wanting data-driven decision frameworks ✅ Risk-conscious traders needing institutional-grade risk analytics ✅ Traders seeking education in portfolio management principles ✅ Systematic traders wanting to learn rules-based methodologies
Not Ideal For
❌ Long-term buy-and-hold investors (use traditional portfolio tools) ❌ Traders holding 1-2 positions only (insufficient complexity to require portfolio tools) ❌ Traders seeking financial advice (we provide tools and education, not recommendations) ❌ Fundamental analysts focused solely on valuation (our tools focus on technical momentum)
Development Status & Early Access
Current Status: In Development - Early Access Program
Development Roadmap
Phase 1 (Current): Core Development
Building position sizing calculators with multiple quantitative models
Developing backtesting framework using historical data (2020-2024)
Creating risk analytics dashboard with Modern Portfolio Theory metrics
Designing educational content and methodology documentation
Phase 2: Beta Testing Program
Limited release to select Pro Plan subscribers
Gather feedback on tools and educational content
Refine quantitative models based on real-world usage
Validate backtesting accuracy
Phase 3: General Release
Complete feature set available to all Pro Plan subscribers
Full educational resource library
Performance attribution and statistical analysis tools
Mobile app integration
Phase 4: Advanced Features
Multi-account portfolio aggregation
Tax optimization tools and calculators
Advanced strategy backtesting laboratory
Expanded educational courses on quantitative finance
Learning Portfolio Management Now
Educational Resources
While Portfolio Manager is being developed, focus on learning fundamentals:
Study Quantitative Finance Principles:
Modern Portfolio Theory (Harry Markowitz)
Capital Asset Pricing Model (CAPM)
Risk-adjusted returns (Sharpe ratio, Sortino ratio)
Kelly Criterion for position sizing
Correlation and diversification principles
Practice Manual Portfolio Management:
Track positions in spreadsheet (template provided below)
Calculate position sizes using simple models
Monitor sector concentration manually
Analyze your performance systematically
Educational Resources:
Books: "The Intelligent Investor" (Graham), "A Random Walk Down Wall Street" (Malkiel)
Papers: Academic research on portfolio optimization and position sizing
Courses: Quantitative finance basics, risk management principles
TradeDots Resources: Blog articles on portfolio management (coming soon)
Manual Portfolio Management Framework
Track Your Portfolio (Spreadsheet Template):
Stock
Entry Date
Entry Price
Shares
Position Value
% of Portfolio
Stop Loss
Target
Risk ($)
Risk (%)
Sector
NVDA
2025-01-15
$450.00
20
$9,000
9.0%
$430
$500
$400
4.4%
Tech
JPM
2025-01-16
$150.00
40
$6,000
6.0%
$145
$160
$200
3.3%
Finance
Daily Review Checklist:
Check AI Scores for all held positions (exit if score drops below 75-80)
Review technical indicators for exit signals
Calculate current portfolio risk (sum of all position risks)
Monitor sector concentration (keep below 40% in any sector)
Identify correlation between positions (avoid multiple highly correlated stocks)
Risk Management Guidelines (Quantitative Frameworks):
Position Size: No single position >10% of portfolio (standard institutional limit)
Total Risk: Total portfolio risk <15% (sum of all position risks)
Sector Concentration: Max 40% in any single sector (historical volatility increases above this threshold)
Correlation Limit: Avoid 3+ positions with correlation >0.75 (reduced diversification benefits)
Stop Losses: Always use technical-based stops (don't let emotions override)
Performance Tracking:
Weekly: Calculate win rate, average R:R, total return
Monthly: Analyze which strategies worked best
Quarterly: Review sector performance, adjust approach based on data
Important: Educational Tools, Not Financial Advice
What Portfolio Manager Provides
✅ Quantitative Finance Tools and Calculators
Position sizing calculators using proven methodologies
Risk analytics based on Modern Portfolio Theory
Correlation and diversification analysis tools
Performance attribution and statistical analysis
✅ Historical Backtesting and Research
Performance data from 2020-2024 market conditions
Statistical validation of different approaches
Academic research and proven methodologies
Quantitative frameworks used by institutions
✅ Educational Resources and Knowledge
Learn how institutional investors manage portfolios
Understand quantitative finance principles
Master risk management methodologies
Develop systematic decision-making frameworks
✅ Data and Analytics
Real-time portfolio metrics and visualizations
Statistical analysis of your trading performance
Historical context for decision-making
Comparative analysis of different strategies
What Portfolio Manager Does NOT Provide
❌ Financial Advice or Specific Recommendations
We do not tell you which stocks to buy or sell
We do not suggest specific position sizes for your situation
We do not provide suitability assessments
We do not offer personalized investment advice
❌ Guaranteed Results or Performance
Past performance does not predict future results
Backtesting results are historical only
No trading strategy guarantees profits
Markets are inherently uncertain
❌ Regulatory Advisory Services
We are not registered investment advisors (RIAs)
We do not manage assets or make investment decisions
We do not provide fiduciary advice
Consult licensed professionals for personalized guidance
Your Responsibilities
As a Trader Using Portfolio Manager Tools:
Understand the Tools: Learn how each calculator and framework works
Make Your Own Decisions: Apply tools to your personal risk tolerance and goals
Assess Your Situation: Determine your risk capacity and investment objectives
Seek Professional Advice: Consult licensed financial advisors for personalized guidance
Continuous Learning: Stay educated on portfolio management principles
Risk Management: Never risk more than you can afford to lose
Due Diligence: Verify all calculations and understand methodologies
Legal Disclaimer
For Educational and Informational Purposes Only
All tools, calculators, backtesting results, and educational content provided by TradeDots Portfolio Manager are for informational and educational purposes only. They do not constitute financial, investment, legal, or tax advice.
No Guarantees: Past performance, whether actual or backtested, does not guarantee future results. All investments involve risk of loss.
Do Your Own Research: You are solely responsible for your investment decisions. TradeDots provides tools and education, but you must evaluate your personal circumstances, risk tolerance, and investment objectives.
Professional Guidance: Consider consulting with licensed financial advisors, tax professionals, and legal counsel for personalized advice suited to your situation.
Accuracy: While we strive for accuracy in our tools and data, we cannot guarantee completeness or correctness. Always verify independently.
Key Takeaways
✅ Quantitative Tools: Portfolio Manager provides institutional-grade portfolio management tools based on proven methodologies
✅ Educational Platform: Learn how professional investors approach position sizing, risk management, and portfolio optimization
✅ Backtesting Framework: Access historical performance data (2020-2024) showing how different approaches performed
✅ Integrated Workflow: Seamless connection between AI Rankings → Indicators → Portfolio Tools for complete analysis
✅ Statistical Analysis: Understand your performance through data, not emotions - identify what's quantitatively working
✅ Risk Analytics: Institutional-level portfolio risk visibility based on Modern Portfolio Theory
✅ For Active Traders: Designed for day trading and swing trading with tactical momentum strategies, not long-term investing
✅ Pro Plan Included: Available to Pro Plan subscribers ($129/month) when released - no additional cost
✅ Your Decisions: Tools empower informed decision-making, but you remain responsible for your trades
Next Steps
Continue Learning: Complete Trading Workflows to understand end-to-end trading processes with current TradeDots tools.
Explore Application: Real-World Trading Scenarios for practical examples of AI Rankings + Indicators.
Stay Updated: Follow TradeDots blog and email updates for Portfolio Manager development announcements and quantitative finance education.
Join Early Access: Email [email protected] with "Portfolio Manager Early Access" to express interest in beta testing program.
Remember: While Portfolio Manager tools are being developed, you can achieve excellent results with AI Rankings + Indicators + manual portfolio management using the quantitative frameworks described above. The Portfolio Manager will provide automated calculators and analytics for what disciplined traders already do manually with spreadsheets. Focus now on mastering stock selection (AI Rankings), trade execution (indicators), and learning portfolio management principles - the tools will enhance your existing systematic approach.