Project /Research Paper Myth Busting
Buckets Example Topics for Project /Research Paper Myth Busting • Average investor can benefit by listening to recommendations from financial experts • Efficient Market Hypothesis – Markets can’t be beat • Markets move after the news hit the wires • Skill always trounces luck in the Markets • The key to the success of a trading system is the “entry signals” • Volatility is a suitable proxy of risk • The frequency and magnitude of past losses in a fund provide a good indication of risk • VaR provides a good indication of worst-case risk • Market Prices fairly reflect a portfolio’s value
Quantitative Fundamentals
• Effect of Return on Capital employed, Earnings Yield, Enterprise Value
• Piotroski F Score – applications
• Magic Formula investing across stock universes
• Can deep-value trounce growth?
• Correlated components of Balance Sheets – which ones really matter
• Focus on Emerging Markets – which Financial Ratios are best? High Frequency Trading and Arbitrage • Designing ultra-low-latency direct market access technologies (“ULLDMA”) • Horizontal Scalability vs low Latency – optimal balance for different HTF strategies • Speed, Low Latency Messaging Considerations • Proximity Hosting / Co-Location to Matching Engines • Stress-testing HFT system designs for trends and market extremes • Systems Design for Irrational Conditions – slowing down sampling periods • Trading in Highly Abnormal Market Conditions • Regression test the system over periods of low and high volatility. • Stress-testing HTF systems – high water mark days like May 6, 2010
Short Term trading Models – Indexes, Futures, Commodities
• Handling Data Mining Biases
• Black, Pink and White Noise -Usage of Hurst Exponent
• Martingale/Anti Martingale Strategies for Mean Reversion Trading
• Improving Signal Precision through a broad market directional filter
• Risk Mitigation for Mean Reversion Systems – the problem of letting your losses run
• Trend Relativity
• Cross Market Analysis
Medium to Long term Trading Models – Indexes, • Swing Trading setups (Dip Trip, Coiled Spring, Finger Finder, Hole-in-the-Wall, Power Spike, Bear Hug etc) • Usage of Psychological (Consensus and Commitment) Indicators • Noise reduction by multi-rate signal processing
Futures, Commodities • Usage of Shannon Entropy to Characterize Information Content in price movements • Dynamic Position Sizing – using Probabilistic Distributions • Removing deterministic Biases – Usage of Monte Carlo Simulation and Genetic Algorithms • Handling market regimen shifts – Dynamic Adaptive systems • Effect of inflation on Momentum Strategies • Beta Slippage in Leveraged ETFs • Tactical Asset Allocation Models • Effect of Roll Yields in Commodities Contracts on system performance
Options
• Modeling Options prices considering Mandelbrotian movement of prices
• Effect of Market Regime on Option Volatility
• Trading Special Situations through Options
• Overnight Edge and Option Theta
• Using Delta Neutral Iron Condors vs Iron Condors with Extra Long Put
• Implied Volatility in Merton’s Jump Diffusion Model
• Option Prices in the Variance Gamma Model
• Range-Based EGARCH Option Pricing Models (REGARCH) Volatility & Risk • Stock Market Returns Based on the State of the VIX Futures Term-Structure • Using VIX Based RSI measures to time markets • Equities Hedge through VXX • Overnight Volatility Handling • Developing alternatives to VaR • The holy grail – non-correlated assets
New Horizons : Crowd sourced Market Forecasts, Behavioral Finance
• Designing and developing crowd sourcing platforms
• Investor Biases
• Prospect Theory
• Misaligned Expectations and Actual Stock Market Movements
• Developing new Quantitative Behavioral Models (QBM) across timeframes – based on behavioral patterns of Scalpers, Speculators, Swing traders and Long-term fundamental investors
• A host of AI powered projects
Interdisciplinary Projects • Using Signal processing algorithms to determine stock trend • A Bayesian model of investing based on investor psychology • Application of information theory to stock prices • Application of AI for image processing on pattern recognition