Performance Disclosure

Lukra AI provides software tools and data analysis services only. We do not provide investment advice, recommendations, or guarantees about future performance. All trading involves risk, and you may lose some or all of your invested capital.

What is Backtesting?

Backtesting is the process of testing a trading strategy using historical data to see how it would have performed in the past. While backtesting can provide insights into strategy behavior, it has significant limitations:

• Survivorship Bias: Historical data may exclude failed companies or delisted securities
• Look-Ahead Bias: Future information may have been inadvertently used in historical tests
• Data Quality: Historical data may contain errors, gaps, or survivorship bias
• Market Regime Changes: Past market conditions may not reflect future market environments
• Transaction Costs: Backtests may not accurately reflect real-world trading costs

Why Backtesting May Not Reflect Live Performance

• Execution Delays: Real trading involves execution delays that backtests don't capture
• Slippage: Actual execution prices may differ from backtest assumptions
• Liquidity Constraints: Large orders may move market prices unfavorably
• Market Impact: Real trading can affect market prices, especially for larger positions
• Technology Failures: System outages or connectivity issues can impact live trading

Common Performance Metrics

The following metrics are commonly used to evaluate trading strategies, but each has limitations:

• Total Return: May not reflect the risk taken to achieve returns
• Annualized Return: May be misleading if based on short time periods
• Sharpe Ratio: Assumes normal distribution of returns, which may not hold in practice
• Maximum Drawdown: Past maximum drawdown may not reflect future worst-case scenarios
• Win Rate: High win rates may be achieved with small wins and large losses
• Profit Factor: May not account for the timing and magnitude of losses

Limitations of Performance Metrics

• Time Period Bias: Results may vary significantly across different time periods
• Market Regime Dependency: Performance may vary across different market conditions
• Overfitting Risk: Strategies may be optimized for historical data but fail in live markets
• Survivorship Bias: Only successful strategies may be reported

Execution Differences

Live trading involves real-world constraints that backtesting cannot fully capture:

• Order Execution: Real orders may be filled at different prices than expected
• Partial Fills: Large orders may be executed in multiple smaller transactions
• Market Hours: Trading is limited to market hours, unlike 24/7 backtesting
• Holiday Closures: Markets are closed on holidays and weekends
• Circuit Breakers: Trading may be halted during extreme volatility

Market Microstructure

• Bid-Ask Spreads: Real trading involves bid-ask spreads that reduce returns
• Market Depth: Limited liquidity may prevent large order execution
• Price Impact: Large orders may move market prices unfavorably
• Timing Delays: Signal generation to execution involves delays

Momentum Strategies

• Trend Reversal Risk: Momentum strategies can suffer during trend reversals
• Whipsaw Losses: False breakouts can lead to multiple losing trades
• Market Regime Changes: Momentum may not work in all market conditions
• Volatility Clustering: High volatility periods can lead to consecutive losses

Mean Reversion Strategies

• Trend Risk: Strong trends can cause significant losses
• Timing Risk: Premature entries can lead to extended drawdowns
• Regime Changes: Market regimes may change, affecting strategy performance

Volatility Strategies

• Volatility Clustering: High volatility periods can lead to consecutive losses
• Mean Reversion Risk: Volatility may not revert to historical averages
• Options Risk: Complex options strategies have unlimited loss potential

Different Market Conditions

Strategy performance can vary significantly across different market regimes:

• Bull Markets: Strategies may perform well during trending markets
• Bear Markets: Performance may deteriorate during declining markets
• Sideways Markets: Range-bound markets may favor different strategies
• High Volatility: Increased volatility can impact all strategies
• Low Volatility: Reduced volatility may limit trading opportunities

Economic Factors

• Interest Rate Changes: Federal Reserve policy can impact all asset classes
• Inflation: Rising prices can affect strategy performance
• Economic Cycles: Recessions and expansions affect market behavior
• Geopolitical Events: Wars, conflicts, and political instability can cause market disruptions

Risk-Adjusted Returns

Performance should be evaluated in the context of risk taken:

• Volatility: Higher returns may come with higher volatility
• Drawdowns: Large losses may occur during adverse market conditions
• Correlation: Strategies may become correlated during market stress
• Leverage: Leveraged strategies amplify both gains and losses

Risk Management Limitations

• Stop-Loss Limitations: Stop-losses may not prevent all losses
• Position Sizing: Risk models may not capture all scenarios
• Correlation Risk: Diversified positions may become correlated
• Model Risk: Risk models may not adapt to new market conditions

System Dependencies

Performance can be affected by various technological factors:

• Data Quality: Inaccurate or delayed data can impact performance
• System Downtime: Outages can prevent trade execution
• Network Connectivity: Internet disruptions can cause missed opportunities
• API Dependencies: Third-party service failures can impact trading
• Software Bugs: Programming errors may cause unintended trades

Model Performance

• Overfitting: Models may perform well on historical data but poorly in live markets
• Model Drift: Market conditions may change, affecting model performance
• Data Snooping: Multiple tests on the same data can lead to false discoveries
• Survivorship Bias: Only successful models may be reported

Performance Reporting Standards

Performance data should be presented in accordance with applicable regulations:

• GIPS Compliance: Global Investment Performance Standards may apply
• SEC Regulations: Securities and Exchange Commission rules may apply
• CFTC Requirements: Commodity Futures Trading Commission rules for futures
• International Standards: Different countries have varying requirements

Disclosure Requirements

• Performance Disclaimers: Clear statements about past performance limitations
• Risk Warnings: Prominent disclosure of investment risks
• Methodology: Explanation of how performance is calculated
• Fees and Expenses: Clear disclosure of all costs and fees

Due Diligence

Before using any trading strategy, consider:

• Strategy Understanding: Understand how the strategy works and its risks
• Historical Performance: Review performance across different market conditions
• Risk Assessment: Evaluate the risks associated with the strategy
• Cost Analysis: Consider all costs and fees associated with trading
• Regulatory Compliance: Ensure compliance with applicable regulations

If you have questions about these performance disclosures or need clarification about specific performance data, please contact us: