In partnership with
Like Playing Moneyball with Your Stock Picks
The data that actually moves markets:
Congressional Trades: Pelosi up 178% on TEM options
Reddit Sentiment: 3,968% increase in DOOR mentions before 530% in gains
Insider Activity: UNH execs bought $31M before Buffett joined
While you analyze P/E ratios, professionals track Reddit mentions, Congressional filings, and insider purchases in real-time.
What if you had access to all of it?
Every week, our AI processes 50,000+ Reddit comments, every Congressional filing, and insider transactions from 500+ companies.
Then we send you the AltIndex Newsletter telling you which 5 stocks show the strongest signals across ALL categories for the week.
Or you can download our app to get access to those signals at all times (get a free 7-day trial when you subscribe to the newsletter).
The next big winner is already showing signals. Will you see them this time?
Past performance does not guarantee future results. Investing involves risk including possible loss of principal.
🚀 Your Investing Journey Just Got Better: Premium Subscriptions Are Here! 🚀
It’s been 4 months since we launched our premium subscription plans at GuruFinance Insights, and the results have been phenomenal! Now, we’re making it even better for you to take your investing game to the next level. Whether you’re just starting out or you’re a seasoned trader, our updated plans are designed to give you the tools, insights, and support you need to succeed.
Here’s what you’ll get as a premium member:
Exclusive Trading Strategies: Unlock proven methods to maximize your returns.
In-Depth Research Analysis: Stay ahead with insights from the latest market trends.
Ad-Free Experience: Focus on what matters most—your investments.
Monthly AMA Sessions: Get your questions answered by top industry experts.
Coding Tutorials: Learn how to automate your trading strategies like a pro.
Masterclasses & One-on-One Consultations: Elevate your skills with personalized guidance.
Our three tailored plans—Starter Investor, Pro Trader, and Elite Investor—are designed to fit your unique needs and goals. Whether you’re looking for foundational tools or advanced strategies, we’ve got you covered.
Don’t wait any longer to transform your investment strategy. The last 4 months have shown just how powerful these tools can be—now it’s your turn to experience the difference.
================================================================================
PERFORMANCE SUMMARY
================================================================================
Initial Capital......................... 10000.0000
Final Capital........................... 26712.5148
Total Return (%)........................ 167.13%
Annualized Return (%)................... 15.71%
Volatility (Annualized %)............... 19.54%
Sharpe Ratio............................ 0.8038
Max Drawdown (%)........................ -21.85%
Number of Trades........................ 38
Total Commissions ($)................... $ 842.64
Commission Impact (%)................... 8.43%
Outperformance vs SPY................... 44.98%
================================================================================A Quantitative Approach to Tactical Trading with 167% Returns Over 7 Years
Executive Summary
In quantitative trading, the challenge is not just finding a strategy that works on paper, but building one that performs in real market conditions with realistic constraints. This article presents a complete production-ready implementation of a mean reversion strategy combining Internal Bar Strength (IBS) with momentum indicators, achieving a 167% total return over a 7-year period while maintaining rigorous backtesting standards.
Key Performance Metrics (2018–2024):
Total Return: 167.13%
Annualized Return: 15.71%
Sharpe Ratio: 0.80
Maximum Drawdown: -21.85%
Outperformance vs SPY: 44.98%
Learn AI in 5 minutes a day
This is the easiest way for a busy person wanting to learn AI in as little time as possible:
Sign up for The Rundown AI newsletter
They send you 5-minute email updates on the latest AI news and how to use it
You learn how to become 2x more productive by leveraging AI
The Strategy: Combining Mean Reversion with Momentum Filtering
Core Concept
The strategy exploits two well-documented market phenomena:
Mean Reversion (IBS): Prices tend to revert after extreme intraday movements
Momentum Filtering: Trend strength validation improves entry timing
Technical Implementation
Internal Bar Strength (IBS)
IBS measures where the close price falls within the daily range:
IBS = (Close - Low) / (High - Low)Values range from 0 to 1, where:
IBS < 0.05: Price closed near the low (oversold)
IBS > 0.95: Price closed near the high (overbought)
Momentum Filters
Two complementary momentum indicators validate trend strength:
Simple Momentum: 32-period price difference
Rate of Change (ROC): 64-period percentage change
Signal Generation Logic
Buy Signal (Enter Long):
IBS < 5th percentile (price weakness)
AND Momentum(32) < ROC(64) (momentum confirmation)
Sell Signal (Exit Long):
IBS > 95th percentile (price strength)
AND Momentum(32) > ROC(64) (momentum reversal)
Backtesting Methodology: Avoiding Common Pitfalls
Critical Design Principles
1. Strict Look-Ahead Bias Prevention
The most common mistake in backtesting is using information that would not have been available at trade execution. Our implementation follows a rigorous flow:
Signal Generation: At market close on day T
Order Execution: At market open on day T+1
Portfolio Valuation: At market open on day T+1
Return Calculation: Open[T+2] / Open[T+1] — 1
This one-day lag ensures we never use future information.
2. Realistic Transaction Costs
Many backtests fail in live trading due to underestimated costs. We implement:
Commission Rate: 0.1% per trade (10 bps)
Slippage Consideration: Execution at open prices
Total Commission Impact: 8.43% over the period (38 trades)
3. No Data Manipulation
No forward-filling or backward-filling of missing data
No synthetic data generation
Strict use of actual historical prices from FMP API
Performance Analysis
Return Metrics
The strategy delivered strong absolute and risk-adjusted returns:
Absolute Performance:
Initial Capital: $10,000
Final Capital: $26,713
Total Return: 167.13%
Annualized Return: 15.71%
Comparison to Benchmark (SPY):
SPY Buy & Hold Return: 122.15%
Strategy Outperformance: 44.98%
Risk Assessment
Volatility Profile:
Annualized Volatility: 19.54%
Sharpe Ratio: 0.80
A Sharpe ratio of 0.80 indicates solid risk-adjusted returns, though below the 1.0 threshold often considered excellent. The strategy compensates with strong absolute returns.
Drawdown Analysis:
Maximum Drawdown: -21.85%
Occurred during: 2022 market correction
The maximum drawdown is significant but not catastrophic. For comparison, SPY experienced similar drawdowns during the same period. The strategy recovered to new highs, demonstrating resilience.
100 Genius Side Hustle Ideas
Don't wait. Sign up for The Hustle to unlock our side hustle database. Unlike generic "start a blog" advice, we've curated 100 actual business ideas with real earning potential, startup costs, and time requirements. Join 1.5M professionals getting smarter about business daily and launch your next money-making venture.
Trade Statistics
Activity Metrics:
Total Trades: 38 (approximately 5–6 trades per year)
Average Hold Period: ~48 trading days
Strategy Type: Low-frequency tactical
The low trading frequency is a significant advantage:
Reduced transaction costs
Lower operational complexity
More sustainable for individual traders
Strategy Strengths
1. Strong Historical Performance
The strategy consistently outperformed its benchmark by 45%, demonstrating genuine alpha generation beyond market beta.
2. Statistical Edge
The combination of mean reversion and momentum filtering provides:
Entry timing advantage (buying weakness in uptrends)
Exit discipline (selling strength before reversals)
Trend alignment (avoiding counter-trend trades)
3. Practical Implementation
Simple rule-based system (no subjective decisions)
Low trading frequency (manageable for part-time traders)
Single-asset focus (reduced complexity)
4. Production-Ready Design
Proper data handling (no look-ahead bias)
Realistic cost assumptions
Full transaction logging for audit trails
Strategy Limitations and Risks
1. Single-Asset Concentration
Issue: 100% exposure to MSFT creates idiosyncratic risk.
Mitigation: Consider diversification across multiple tech stocks or sectors.
2. Market Regime Dependency
Issue: Mean reversion strategies struggle in strong trending or volatile regimes.
Evidence: Performance degradation visible in 2022 during the tech correction.
Mitigation: Implement regime filters or position sizing adjustments based on market conditions.
3. Parameter Sensitivity
Issue: Performance depends on specific parameter choices:
Momentum period: 32 days
ROC period: 64 days
IBS thresholds: 5th/95th percentiles
Concern: These parameters were not optimized out-of-sample, raising overfitting risk.
Recommendation: Conduct walk-forward optimization or parameter stability testing.
4. Survivorship Bias
Critical Consideration: Testing on MSFT, a consistently successful stock, may overstate strategy performance.
Reality Check: Would the strategy work on stocks that became distressed during the period?
5. Limited Downside Protection
Observation: No stop-loss mechanism implemented.
Impact: Maximum drawdown of -21.85% could be psychologically challenging.
Enhancement: Consider adding trailing stops or volatility-based position sizing.
Implementation Considerations for Live Trading
Pre-Deployment Checklist
1. Data Infrastructure
Reliable real-time data feed
Automated signal generation at market close
Order routing capability for next-day open
2. Risk Management
Maximum position size limits
Account-level drawdown triggers
Emergency exit procedures
3. Operational Requirements
Daily monitoring routine
Trade reconciliation process
Performance tracking dashboard
4. Regulatory Compliance
Pattern day trader rules (if applicable)
Tax reporting preparation
Record-keeping requirements
Recommended Enhancements
1. Portfolio Diversification
Extend strategy to multiple assets:
Other large-cap tech stocks (AAPL, GOOGL, NVDA)
Different sectors for correlation benefits
Maintain 5–10 stock portfolio
2. Dynamic Position Sizing
Implement Kelly Criterion or volatility-adjusted sizing:
Position Size = f(account_equity, volatility, win_rate)3. Regime Detection
Add market regime filters:
Bull/Bear market identification
Volatility regime classification
Adjust parameters or pause trading in unfavorable regimes
4. Stop-Loss Implementation
Add downside protection:
Trailing stop: -10% from peak entry price
Time-based exit: Close position after N days in loss
Volatility stop: 2x ATR from entry
Critical Analysis: Why This Strategy Works
The full code for this article is available only for paid subs here
Market Microstructure Foundation
The strategy exploits a well-documented behavioral pattern:
Overreaction Hypothesis: Intraday price movements often overshoot, creating mean reversion opportunities.
Evidence: IBS < 5th percentile indicates extreme selling pressure. When combined with positive momentum (uptrend), this often represents temporary dislocation rather than fundamental deterioration.
Statistical Edge
The dual-filter approach provides:
IBS: Identifies tactical entry points
Momentum/ROC: Ensures trend alignment
This combination reduces false signals common in pure mean reversion strategies.
Historical Context
The 2018–2024 period included:
COVID crash and recovery (2020)
Tech bull market (2021)
Bear market correction (2022)
Market recovery (2023–2024)
The strategy’s performance across diverse conditions suggests robustness, though extended testing periods would increase confidence.
The Production Gap: Research vs. Reality
Many backtested strategies fail in live trading due to the “production gap.” This implementation addresses key gaps:
Research Environment:
Perfect data
No execution delays
Theoretical commissions
Production Environment:
Data quality issues
Order execution risk
Realistic costs
Bridged Elements:
API-based data retrieval (real-world source)
Open price execution (realistic timing)
10 bps commissions (competitive broker rates)
Remaining Gaps:
Slippage (market impact)
Partial fills
Data feed latency
System downtime
Conclusion: A Solid Foundation with Room for Enhancement
This IBS + Momentum strategy demonstrates genuine potential for live trading:
Proven Strengths:
Strong absolute returns (167%)
Significant benchmark outperformance (45%)
Reasonable Sharpe ratio (0.80)
Low trading frequency (38 trades over 7 years)
Areas for Improvement:
Diversification across multiple assets
Parameter robustness testing
Enhanced risk management
Regime-adaptive mechanisms
Path Forward:
For traders considering implementation:
Paper Trade: Execute signals in real-time without capital
Small Capital Test: Deploy with 1–5% of intended capital
Performance Review: Evaluate after 20+ trades
Scale Up: Increase allocation if results align with backtest
Final Recommendation:
This strategy represents a solid tactical approach suitable for:
Experienced quantitative traders
Those comfortable with 20%+ drawdowns
Investors with 3+ year time horizons
Traders seeking low-frequency systematic strategies
However, it should not be deployed blindly. Conduct your own due diligence, understand the risks, and consider it as one component of a diversified approach rather than a complete investment solution.
Technical Implementation
The complete Python implementation is available with full documentation, including:
FMP API integration
Proper signal generation with lag
Realistic commission accounting
Comprehensive performance metrics
Benchmark comparison framework
The code prioritizes production readiness over academic elegance, with extensive comments explaining critical design decisions around look-ahead bias prevention and realistic execution simulation.
Disclaimer: This article is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Trading strategies carry risk of loss. Conduct thorough due diligence and consult with qualified financial professionals before implementing any trading strategy.
The full code for this article is available only for paid subs here