DIONYSUS uses advanced algorithms to create optimized portfolios based on your risk preferences and financial goals.
Our system analyzes market data, identifies opportunities, and constructs portfolios that aim to maximize returns
while managing risk according to your specifications.
For Beginners
Start with the "Conservative" risk preset
Use Equal Weight allocation for simplicity
Keep max positions between 10-15
Review the automated allocations before investing
For Intermediate Investors
Experiment with Kelly Criterion for optimized position sizing
Consider Stage Weighted allocation to adapt to market cycles
Adjust max risk per trade based on your comfort level
Balance diversification with concentration in high-conviction positions
Learn More About Portfolio Optimization
Understanding Allocation Strategies
Kelly Criterion
Originally developed for gambling, the Kelly Criterion determines the optimal size of investments to maximize long-term growth. It uses probabilities of success and the ratio of potential gains to losses.
Best for: Experienced investors comfortable with mathematics and statistical concepts.
Equal Weight
Allocates the same percentage of capital to each position, creating a simple, diversified portfolio without bias toward any single investment.
Best for: Beginners or those preferring simplicity and diversification.
Confidence Weighted
Allocates more capital to positions with higher confidence signals, allowing stronger convictions to have more impact on returns.
Best for: Investors who want a balance between equal weight and more concentrated approaches.
Stage Weighted
Allocates based on the market cycle stage of each security, increasing exposure to those in optimal stages for growth.
Best for: Investors seeking to capitalize on market cycle timing.
Risk Management Fundamentals
Effective risk management is the foundation of successful investing. DIONYSUS provides several controls to help you manage portfolio risk:
Max Risk Per Trade
Limits the percentage of your portfolio that can be lost on any single position. Lower values (1-2%) are conservative, while higher values (10%+) are more aggressive.
Beginner recommendation: 1-3%
Intermediate recommendation: 3-7%
Max Portfolio Risk
Caps the total risk exposure across your entire portfolio, ensuring that even in worst-case scenarios, losses remain within your tolerance.
Beginner recommendation: 15-20%
Intermediate recommendation: 20-30%
Max Position Size
Prevents over-concentration by limiting how much of your portfolio can be allocated to any single position.
Beginner recommendation: 5-8%
Intermediate recommendation: 8-15%
Max Positions
Controls portfolio diversification by setting the maximum number of securities to hold. More positions increase diversification but may dilute returns.
Beginner recommendation: 10-15 positions
Intermediate recommendation: 15-30 positions
Understanding Market Cycles
DIONYSUS identifies different market cycle stages for securities, which helps inform allocation decisions:
Accumulation
Early stage where informed investors begin buying while prices are relatively low. Volatility decreases and a price floor forms.
Strategy: Begin building positions with moderate allocations.
Markup
Price rises consistently with higher highs and higher lows. Public participation increases and momentum builds.
Strategy: Maximize position sizing for strongest opportunities.
Distribution
Selling begins by informed investors while the public remains optimistic. Price range narrows and momentum slows.
Strategy: Begin reducing position sizes and taking profits.
Decline
Prices fall, often rapidly, with lower lows and lower highs. Sentiment turns negative.
Strategy: Minimize exposure or exit positions while monitoring for new accumulation signs.
Advanced Portfolio Optimization Techniques
These techniques are designed for investors with a strong understanding of market dynamics and portfolio theory.
Factor-Based Investing
DIONYSUS incorporates factor exposure analysis to optimize portfolios based on market anomalies like value, momentum, quality, and volatility that have historically generated excess returns.
Key benefit: Targeting specific return drivers while maintaining balanced risk exposure.
Dynamic Position Sizing
Rather than static allocation, this approach adjusts position sizes based on changing market conditions, volatility, and correlation structures between assets.
Implementation: Use Stage Weighted allocation with higher position limits during confirmed markup phases.
Drawdown Minimization
This strategy prioritizes minimizing the depth and duration of portfolio drawdowns over absolute returns, leading to smoother equity curves.
Settings: Lower Max Portfolio Risk (15-20%) with Confidence Weighted allocation to reduce volatility.
Volatility Targeting
Adjust overall portfolio exposure to maintain a constant level of volatility, increasing exposure during low-volatility periods and reducing it during high-volatility periods.
Required: Regular rebalancing with attention to the VIX and individual security volatility metrics.
Expert Portfolio Management Strategies
These sophisticated approaches require deep market knowledge and disciplined execution. They represent cutting-edge portfolio management techniques.
Hierarchical Risk Parity
This technique improves upon traditional risk parity by using machine learning clustering to identify and allocate across truly diversified market segments rather than asset classes.
DIONYSUS implementation: Use Equal Weight with a high number of positions (30+) across different sectors and apply sector-based constraints.
Adaptive Kelly Optimization
Instead of using fixed probabilities, this approach dynamically adjusts Kelly parameters based on regime detection algorithms and changing market conditions.
Setup: Use Kelly Criterion with moderate settings (Half-Kelly) and adjust Max Risk Per Trade based on market volatility.
Multi-timeframe Signal Aggregation
Combines signals from multiple timeframes to confirm entries and exits, reducing false signals and improving timing accuracy.
Implementation: Use Confidence Weighted allocation and focus on securities with matching signals across multiple timeframes.
Tail Risk Hedging
Systematically allocates a small portion of capital to instruments that are expected to perform well during market crashes and black swan events.
Strategy: Reserve 5-10% of portfolio for inverse ETFs or put options on index ETFs during late-stage markup and distribution phases.
DIONYSUS - TRINITY Optimized Portfolios
Making the Most of DIONYSUS Portfolio Optimization
DIONYSUS uses advanced portfolio optimization algorithms to help you build and manage a portfolio that maximizes returns
while respecting your risk constraints. Below are expert tips to help you get the most out of this powerful tool.
Getting Started
Choose a descriptive name for your portfolio that reflects its strategy or goal
Set realistic capital that matches what you actually plan to invest
Start conservative with risk settings until you understand how the system works
Use the risk presets as starting points and adjust based on your needs
Review allocations before finalizing to ensure they align with your expectations
Understanding Allocation Strategies
Kelly Criterion
Mathematically optimizes position sizes based on historical probabilities of success and the win/loss ratio. The system uses a modified Kelly formula to prevent over-concentration.
Best for: Experienced investors seeking mathematically optimized growth.
Equal Weight
Allocates the same percentage to each position, providing simple diversification without bias.
Best for: Beginners or those seeking simplicity and broad exposure.
Confidence Weighted
Allocates more capital to positions with higher algorithmic confidence scores.
Best for: Investors who want to leverage the system's predictive capabilities.
Stage Weighted
Allocates based on the market cycle stage of each security, increasing exposure to those in optimal stages for growth.
Best for: Technical traders focused on market cycle timing.
Fine-Tuning Risk Settings
Max Risk Per Trade: Determines the maximum downside for any single position. Conservative investors should stay below 2%, moderate between 2-5%, and aggressive above 5%.
Max Portfolio Risk: Caps your total portfolio exposure. This should generally be 5-10x your max risk per trade, depending on your diversification needs.
Max Position Size: Prevents over-concentration in any single security. A common rule of thumb is not to exceed 10-15% for any position.
Max Positions: Controls diversification. Too few positions (under 10) increases concentration risk, while too many (over 40) can dilute returns and increase complexity.
Expert Strategies
Half-Kelly Approach
Many professional investors use a "Half-Kelly" strategy (setting allocations to half of what the full Kelly formula suggests) to reduce volatility while maintaining strong growth. This approach sacrifices some theoretical return for more consistent performance.
Barbell Strategy
Combine very safe investments (80-90% of capital) with a small allocation to high-risk, high-reward opportunities. Set a higher Max Position Size but with a very low Max Risk Per Trade to implement this approach.
Adaptive Allocation
Periodically adjust your allocation strategy based on market conditions. Consider Stage Weighted during volatile markets and Confidence Weighted during trending markets.
Advanced & Expert Techniques
Position Correlation Management
DIONYSUS analyzes cross-asset correlations to minimize overall portfolio risk. Advanced users can exploit this by combining securities with negative or low correlation to achieve better risk-adjusted returns.
Expert tip: Combine securities from different sectors and market cap ranges to reduce correlation. Aim for at least 5-8 distinct clusters of securities.
Conditional Value at Risk (CVaR) Optimization
Unlike traditional models that focus on standard deviation, CVaR optimization focuses on minimizing the expected loss in the worst-case scenarios, providing better tail risk protection.
Expert setup: Set a lower Max Risk Per Trade (0.5-2%) with higher position counts (25+) and Equal Weight allocation when market volatility is elevated.
Multi-factor Allocation Weighting
This technique blends multiple weighting schemes (stage, confidence, Kelly, etc.) to create a more robust allocation model that isn't dependent on any single approach.
Implementation: Rotate between allocation strategies quarterly based on which has performed best in the current market regime.
Tactical Rebalance Timing
Rather than rebalancing at fixed intervals, this approach triggers rebalancing based on deviation thresholds, volatility changes, or signal strength shifts.
Expert workflow: Re-optimize portfolios when top positions exceed Max Position Size by 20% or when market volatility (VIX) changes by more than 20% from optimization date.
Regime-based Risk Management
This sophisticated approach uses market regime detection algorithms to dynamically adjust risk parameters based on identified market conditions.
Expert configuration: For accumulation phases, set Max Risk Per Trade to 1.5-2.5%; for markup phases 2.5-4%; for distribution phases 0.5-1.5%; for decline phases, minimize exposure (<0.5%).
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TRINITY Investor Academy
What's your investment experience level?
We'll personalize your learning journey based on your experience
Beginner
New to investing or just getting started with portfolio management
Intermediate
Familiar with investing concepts and have some portfolio experience
Advanced
Experienced investor looking to optimize strategies and performance
ATHENA analyzes stocks to identify which ones are trending up (good for buying) or down (best to avoid). Here's how to understand what you're seeing:
The Four Market Stages - Interactive Guide
Stage 1: Accumulation
Stock price moves sideways after a downtrend. This is when smart money begins buying quietly.
Stage 2: Uptrend (Markup)
Price rises steadily, making higher highs and higher lows. Best stage for buying!
Stage 3: Distribution
Price moves sideways after an uptrend. Smart money sells to eager public buyers.
Stage 4: Downtrend (Decline)
Price falls steadily, making lower lows and lower highs. Avoid buying in this stage!
What You Should Do:
Filter for Stage 2 stocks using the Stage filter above
Look for BUY signals in the Signal filter
Focus on High confidence signals
Add promising stocks to a watchlist to track them
Effective Technical Analysis Strategies
Now that you understand the basics, let's explore how ATHENA identifies high-probability trading opportunities.
Pattern Recognition - Interactive Guide
Cup with Handle Pattern
A bullish continuation pattern that resembles a cup with a handle. The cup forms after a downtrend as prices form a rounded bottom, followed by a slight pullback forming the handle.
Typically appears in Stage 1 to Stage 2 transition
Cup depth usually 15-33% from previous high
Handle should be at least 5 days but not too deep
Increased volume on breakout confirms pattern
Practical Application:
Filter for Stage 1-2 stocks to find patterns forming
Check volume confirmation on pattern breakouts
Look for high confidence signals alongside pattern completion
Set price targets based on pattern measurements
Advanced Pattern Analysis
ATHENA's algorithms go beyond basic pattern identification to assess quality, reliability, and context.
Multi-Timeframe Confirmation
Analyzing patterns across multiple timeframes increases signal reliability. When patterns align across timeframes, the probability of success increases significantly.
Signal Confluence Analysis
Daily timeframe: Cup with Handle forming
Weekly timeframe: Stage 2 uptrend confirmation
Monthly timeframe: Above major moving averages
Confidence score calculation includes multi-timeframe alignment, volume confirmation, and pattern quality metrics.
Sector Correlation and Relative Strength
ATHENA considers how stocks perform relative to their sectors and the broader market, helping identify true strength versus market-driven movements.
Algorithm Mechanics and Customization
For professional investors, understanding the algorithmic mechanics behind ATHENA's analysis allows for more sophisticated use and potential customization.
Stage Classification Algorithm
# Pseudocode for ATHENA's Stage Classification
def classify_stage(price_data, volume_data):
# Calculate key technical indicators
sma_20 = calculate_sma(price_data, period=20)
sma_50 = calculate_sma(price_data, period=50)
sma_200 = calculate_sma(price_data, period=200)
# Calculate moving average slopes
sma_20_slope = calculate_slope(sma_20, period=5)
sma_50_slope = calculate_slope(sma_50, period=10)
sma_200_slope = calculate_slope(sma_200, period=30)
# Check price in relation to moving averages
price_above_sma20 = price_data[-1] > sma_20[-1]
price_above_sma50 = price_data[-1] > sma_50[-1]
price_above_sma200 = price_data[-1] > sma_200[-1]
# Analyze price action patterns (higher highs/lows or lower highs/lows)
has_higher_highs = check_higher_highs(price_data, lookback=10)
has_higher_lows = check_higher_lows(price_data, lookback=10)
has_lower_highs = check_lower_highs(price_data, lookback=10)
has_lower_lows = check_lower_lows(price_data, lookback=10)
# Analyze volume trends
volume_trend = analyze_volume_trend(volume_data, price_data, period=20)
# Stage classification logic
if sma_20_slope < 0 and sma_50_slope < 0 and has_lower_highs and has_lower_lows:
return "STAGE 4" # Downtrend
elif sma_20_slope > 0 and sma_50_slope > 0 and has_higher_highs and has_higher_lows:
return "STAGE 2" # Uptrend
elif previous_stage == "STAGE 4" and price_action_sideways and volume_trend == "INCREASING":
return "STAGE 1" # Accumulation after downtrend
elif previous_stage == "STAGE 2" and price_action_sideways and volume_trend == "DISTRIBUTION":
return "STAGE 3" # Distribution after uptrend
# Additional logic for stage transitions...
Key Parameters:
SMA Periods: 20, 50, 200 days
Slope Calculation Periods: 5, 10, 30 days
Price Pattern Lookback: 10 days
Volume Analysis Period: 20 days
ATHENA combines these parameters with machine learning models trained on historical market data to calculate stage confidence scores and predict potential stage transitions.
API Integration Points
Access ATHENA's analysis programmatically via our REST API:
curl -X GET "https://api.trinity-tyche.com/v1/athena/analysis?symbol=AAPL&timeframe=daily" \
-H "Authorization: Bearer YOUR_API_KEY"
Response includes complete analysis data, confidence scores, and historical pattern detection that can be integrated into custom trading systems.
For Beginners
Focus on Stage 2 (Uptrend): Filter for "Stage 2" securities which are in established uptrends - the safest option for beginners
Look for "BUY" signals: Use the Signal filter to find stocks with a current buy recommendation
Prioritize High Confidence: Start with "High" confidence signals (>0.7) for the strongest opportunities
Check the Pattern Type: Cup with Handle and Ascending Triangle patterns tend to be more reliable and easier to identify
Use the Info Tooltips: Hover over any metric or data point in the analysis cards to see explanations
Pro Tip: Create a watchlist of Stage 1 stocks to monitor for potential breakouts into Stage 2.
For Intermediate Investors
Stage Transitions: Look for early Stage 1 to Stage 2 transitions for optimal entry points
Pattern Confirmation: Pay attention to volume confirmation on breakouts and pattern completions
Use Multiple Filters: Combine stage, signal, and confidence filters to find the best opportunities
Consider Relative Strength: Check if a stock is outperforming its sector or the market
Risk Assessment: Review the volatility metrics and price targets to determine position sizing
Pro Tip: Create separate watchlists for different stages to monitor market rotation opportunities.
For Advanced Investors
Multi-Timeframe Analysis: Use the full analysis page to examine pattern confirmation across multiple timeframes
Stage 4 Opportunities: For short positions or put options, filter for high-confidence Stage 4 (Downtrend) securities
Correlation Analysis: Build a diversified portfolio by selecting securities with low correlations to each other
Sector Rotation: Track which sectors are showing increasing Stage 2 patterns to identify emerging trends
Market Breadth Context: Interpret signals in the context of overall market health and breadth indicators
Pro Tip: Use Stage 3 distribution patterns to time exits or position reduction in existing holdings.
For Expert Investors
Algorithm Augmentation: Use ATHENA's signals as a screening tool, then apply your own proprietary analysis for final decisions
Intermarket Analysis: Correlate signals across different asset classes (equities, bonds, commodities) for macro-level insights
Custom Confidence Thresholds: Develop personal confidence thresholds based on historical performance in your strategy
Signal Divergence: Look for instances where ATHENA's signals diverge from traditional indicators - these can be high-alpha opportunities
API Integration: Use the API endpoints to integrate ATHENA's signals into your own trading systems or algorithms
Pro Tip: Track the historical hit rate of signals by confidence level to calibrate your position sizing algorithm.
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