Type: Chaikin OscillatorSharpe: 1.01Return: +67.1%Max DD: -7.2%Win: +52.8%Trades: 36SL/TP: 3% / 5%
We continuously research, build, and validate systematic trading ideas with robust testing, then share transparent results so everyone can access evidence-based quant insights, not just institutions. We backtest quantitative trading strategies across global equity indices, options analysis on US index ETFs, portfolio optimization, sentiment tracking, and market regime detection - all with live data updated daily.
| Strategy Library | 70+ technical indicator-based strategies backtested across 21 global equity indices with 5 years of daily data. Each strategy has a dedicated page with equity curves, performance metrics, parameter optimization, and Python implementation code. |
| Options Strategies | 18 options strategies — from cash-secured puts and covered calls to iron condors, jade lizards, and synthetic longs — backtested on SPY, QQQ, IWM, and DIA using live IV surfaces and Black-Scholes pricing. Each strategy shows per-symbol performance, equity curves, and implementation code. |
| Portfolio Optimization | 30 systematic portfolio strategies built on S&P 500 stocks using factor signals (momentum, volatility, quality, trend). Skfolio-powered optimization comparing Max Sharpe, Min Variance, Risk Parity, HRP, and more across US equity and global indices. |
| Parameter Optimization | Grid search over each strategy's key parameters, optimizing for Sharpe ratio, Sortino, Calmar, win rate, and profit factor. Results visualized as line charts (1-parameter) or scatter heatmaps (2-parameter) showing the full performance surface. |
| Market Analysis | Relative Rotation Graphs for US equity and sector ETFs vs S&P 500, correlation matrix across all strategies, stock sentiment tracker using VADER on financial news headlines, and market regime detection using GMM and hidden Markov models. |
| Project Research | Adaptive portfolio strategies (OLPS algorithms), K-means clustering portfolio construction, OLPS comparison, and market regime detection — each with interactive visualizations, methodology documentation, and source code. |
Data as of 2026-05-14
Live monitoring widget from the full Yield Curve project.
View moreWhat this shows: A compact time-series view of key yield spreads used for inversion monitoring.
How to read it: Values below zero imply inversion for that spread; persistent negative regimes are historically associated with elevated recession risk.
Select a metric to compare the available US universe using the latest generated dataset.
View MoreWhat this shows: Top 30 symbols in the current US universe ranked by Trailing P/E.
How to read it: Bars are sorted in descending order for the selected metric. The expanded dashboard below adds risk-return, value-quality factor map, and sector-level context.
Risk vs Return (1Y)
Value vs Quality factor map
Sector mean comparison (Trailing P/E)
Generated Thursday, May 14, 2026
| # | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | Chaikin Oscillator | Chaikin Oscillator | 1.01 | +67.1% | -7.2% | +52.8% | 36 | 3% | 5% |
| 2 | WMA Crossover | WMA Crossover | 0.95 | +34.1% | -8.3% | +60.0% | 20 | 3% | 5% |
| 3 | Detrended Price Oscillator | Dpo | 0.91 | +51.8% | -8.1% | +45.8% | 24 | 0% | 5% |
| 4 | Twiggs Money Flow | Twiggs Money Flow | 0.88 | +51.7% | -10.3% | +50.0% | 22 | 5% | 5% |
| 5 | Bollinger Bands | Bollinger Bands | 0.87 | +74.3% | -12.8% | +78.6% | 14 | 7% | 10% |
Showing 1 to 5 of 71 strategies
Ranked snapshot of strategy performance metrics.
No fundamental strategy dataset found yet. Run npm run data:fundamental-strategies.
Income
Income
Income
Neutral
Neutral
Directional
Directional
Neutral
| # | |||||||
|---|---|---|---|---|---|---|---|
| 1 | Cash-Secured Put | Income | 1.69 | +47.3% | +5.0% | +93.4% | 4 |
| 2 | Short Puts | Income | 1.69 | +47.3% | +5.0% | +93.4% | 4 |
| 3 | Cash-Secured Put | Income | 1.69 | +47.3% | +5.0% | +93.4% | 4 |
| 4 | Short Strangle | Neutral | 1.50 | +76.2% | +2.0% | +88.2% | 4 |
| 5 | Short Strangles | Neutral | 1.50 | +76.2% | +2.0% | +88.2% | 4 |
| 6 | 1x2 Call Ratio Spread | Directional | 1.14 | +906.2% | +34.7% | +84.2% | 4 |
| 7 | Call Front Spread | Directional | 1.14 | +906.2% | +34.7% | +84.2% | 4 |
| 8 | Short Straddle | Neutral | 1.10 | +702.4% | +35.6% | +85.5% | 4 |
30 systematic strategies using 36 S&P 500 stocks
What this shows: Each bubble is one strategy positioned by annualized volatility (x-axis) and annualized return (y-axis), with bubble size tied to Sharpe ratio.
How to read it: Higher and more leftward bubbles are generally better risk-adjusted candidates; compare bubble sizes to identify strategies with stronger return per unit volatility.
Data as of Thursday, May 14, 2026
| Rank | ||||||
|---|---|---|---|---|---|---|
| 1 | 12-Month Momentum Top 10 | Momentum | 91.9% | 13.9% | 4.77 | -7.1% |
| 2 | Low Vol + High Momentum | Low Volatility | 50.0% | 9.3% | 4.42 | -3.3% |
| 3 | Defensive Low Beta | Defensive | 50.0% | 9.3% | 4.42 | -3.3% |
| 4 | Quality Composite Score | Quality | 62.3% | 11.3% | 4.35 | -4.2% |
| 5 | Above SMA200 Top 20 | Trend | 64.8% | 11.6% | 4.35 | -4.4% |
| 1. | Signal Generation Framework | Modular framework for generating trading signals from multiple data sources. Supports technical indicators, fundamental analysis, machine learning models, and custom signal generators. Includes signal validation, filtering, and combination logic to create robust entry and exit signals. |
| 2. | Execution Engine | High-performance order execution framework with support for multiple broker APIs and exchange connections. Features include order routing, slippage management, fill simulation, and real-time position tracking. Designed for both backtesting and live trading environments. |
| 3. | Risk Management System | Comprehensive risk management framework with position sizing, portfolio-level risk limits, drawdown controls, and real-time risk monitoring. Implements VaR calculations, position concentration limits, and dynamic risk adjustment based on market conditions and strategy performance. |
| 4. | Portfolio Management | Advanced portfolio construction and optimization framework. Supports multiple optimization objectives including Sharpe ratio maximization, risk parity, minimum variance, and custom utility functions. Includes rebalancing logic, transaction cost modeling, and constraint handling. |
| 5. | Data Pipeline & Processing | Scalable data ingestion and processing framework for market data, fundamental data, and alternative data sources. Features real-time data streaming, historical data management, data quality checks, and normalization. Supports multiple data formats and timeframes. |
| 6. | Backtesting Infrastructure | Robust backtesting framework with realistic market simulation, including bid-ask spreads, market impact, and partial fills. Supports walk-forward analysis, Monte Carlo simulation, and out-of-sample testing. Provides detailed performance metrics and attribution analysis. |
| 7. | Strategy Orchestration | Framework for managing multiple strategies simultaneously with resource allocation, priority queuing, and conflict resolution. Includes strategy lifecycle management, performance monitoring, and automated strategy deployment and retirement mechanisms. |
| 8. | Monitoring & Alerting | Real-time monitoring framework for system health, strategy performance, and market conditions. Features customizable alerts, performance dashboards, and automated reporting. Includes anomaly detection and automated response mechanisms for critical events. |
| 1. | Diversified Stock Portfolio Using Clustering Analysis S&P 500 portfolio construction using K-means clustering on risk/return features (correlation, beta, returns, volatility, Sharpe ratio). Backtested vs index. | Active | 2024 | Python, K-means, backtesting |
| 2. | Relative Rotation Graph (RRG) — US Equity Dynamic RRG for US stocks vs S&P 500. JdK RS-Ratio and RS-Momentum with animation. | Active | 2025 | Python, yfinance, Recharts |
| 3. | Adaptive Portfolio Strategies: Sequential Allocation Methods Comprehensive analysis of 14 sequential portfolio allocation strategies on diversified ETF portfolio. Includes momentum-based, reversion-based, and pattern-learning approaches with transaction cost analysis. | Active | 2025 | Python, sequential optimization, backtesting |
| 4. | Optimal Execution with RL Agent (DQN) Deep Q-Learning execution agent for slicing large orders under microstructure-style market impact. Compared against TWAP, passive, aggressive, and random baselines. | Active | 2026 | Python, Gymnasium, Stable-Baselines3, execution simulation |
| 5. | Fundamental Stock Analysis US large-cap fundamental analytics dashboard with deep cross-sectional ranking, distribution diagnostics, sector structure, risk/return mapping, and multi-factor composite interpretation. | Active | 2026 | Python, fundamental screening, interactive charts |
| 6. | Market Regime Detection Using Gaussian Models Comprehensive market regime identification across 21 global indices using Gaussian Mixture Models (GMM) and Greedy Gaussian Segmentation (GSS). Detects bull, bear, and transition regimes for adaptive portfolio management. | Active | 2025 | Python, GMM, GSS, regime detection |
| 7. | Stock Sentiment Tracker US equity sentiment tracker using VADER lexical analysis on financial news headlines. Tracks prices, sentiment scores, and correlations for S&P 500 stocks. Updated daily. | Active | 2025 | Python, VADER, NLP, financial news APIs |
| 8. | Yield Curve Intelligence Yield-curve research project built from yfinance market data: Nelson-Siegel fitting, slope/inversion diagnostics, and regime-aware risk context. | Active | 2026 | Python, yfinance, Nelson-Siegel, macro risk signals |
| 9. | Fama–French Factor Lab Unified factor dashboard: US FF5 and Carhart momentum, multi-asset ETF panel, international sleeve comparison, volatility regimes, risk budgeting, sleeve attribution, SPY research grid, and q-factor extension notes. Refreshed from Ken French + yfinance. | Active | 2026 | Python, pandas, linear factor models, Ken French data, yfinance |
| 10. | Cross-section shrinkage lab (ETF panel) Yahoo Finance ETF panel: PCA spectrum, cross-sectional R² vs K, pseudo-OOS folds, ridge diagnostics. JSON from npm run data:shrinking-cross-section. | Active | 2026 | Python, Recharts, PCA, shrinkage, cross-sectional R² |
| 1. | Adaptive Portfolio Optimization Under Non-Stationary Market Conditions | Journal of Quantitative Finance | 2024 | Novel approach to dynamic asset allocation using regime-switching models and reinforcement learning. |
| 2. | High-Frequency Data Processing: Computational Frameworks | Computational Economics | 2024 | Scalable architectures for real-time processing of tick-level financial data. |
| 3. | Robust Risk Measures in Fat-Tailed Distributions | Risk Analysis | 2023 | Comparative study of tail risk metrics under various distributional assumptions. |
Updated about 19 hours ago (latest item)
| 1. | CMA greenlights solutions’ 100% capital hike through bonus issueThe Capital Market Authority (CMA) grantedArabian Internet and Communications Services Co. (solutions) the approval to increase its capital from SAR 1Sentiment pipeline · about 19 hours ago |
| 2. | Elon Musk's SpaceX IPO Gets Blowback From Pension Funds: Here's What Prediction Markets Are Watching - TeThe three largest US public pension funds demanded Elon Musk rewrite SpaceX's IPO governance, but Polymarket still prices a June listing at 71%.Sentiment pipeline · about 19 hours ago |
| 3. | Aviso's 2025 Year in Review and inaugural Sustainability Report showcase innovation, strategic milestonesTORONTO, May 14, 2026 /CNW/ - Aviso has published its 2025 Year in Review, marking a transformational year defined by outstanding financial performance, groundbreaking innovation, stronger partnerships, and theSentiment pipeline · about 19 hours ago |
| 4. | Retail investors have a new 'toy' for speculation, Barclays saysBarclays analysts said predictions markets are seeing trading volume that rivals other speculative investments popular with retail traders.Sentiment pipeline · about 19 hours ago |
| 5. | These three artworks could sell for $100 million each next week as May auctions beginThe wild card for the May auctions is the Middle East, with the Iran war clouding buyer expectations.Sentiment pipeline · about 19 hours ago |
| 1. | Statistical Modeling | Advanced regression analysis, time series forecasting, and multivariate statistical methods for complex data patterns. |
| 2. | Strategy Comparator | Compare up to 4 strategies side-by-side using Sharpe, return, drawdown, win rate, and trade count. |
| 3. | Stock Sentiment Tracker | US equity only: live prices and news sentiment (VADER) for major US stocks. See Sentiment page. |
| 4. | Risk Analytics | Comprehensive risk assessment frameworks including VaR, CVaR, and stress testing methodologies. |
| 5. | Data Pipeline | High-performance data processing infrastructure designed for large-scale quantitative analysis. |
| 6. | HFT Latency Budget Calculator | Plan per-stage p99.9 tick-to-trade budgets and detect bottlenecks before live deployment. |
| 7. | Portfolio Optimization | Modern portfolio theory implementation with multi-objective optimization and constraint handling. |
