Options trading has changed a lot in recent years. While some traders still prefer making decisions based on the experience of discretionary trading, most institutions and professionals now rely on systematic trading strategies. These strategies follow set rules, use data models, and run on algorithms to remove emotions from trading and create a structured approach to trading.
In this article, we will explain systematic options trading in simple terms and understand how to build a strategy step by step, different types of strategies, and the challenges involved.
What is systematic options trading?
Systematic options trading is a rule based process for buying and selling options, relying on quantitative models and historical data rather than intuition. Traders using this approach do not rely on intuition; instead, they develop quantitative models and use historical data to design strategies that work in different market conditions.
Systematic trading eliminates emotions from the equation, unlike discretionary trading, which is based on gut instinct and subjective judgments. The system is based on a defined set of rules that allows the trader to always trade according to logic rather than intuition.
Some of the main advantages of systematic options trading are:
- Consistency: Strategies rely on rules, minimising emotions from clouding the process.
- Backtesting Ability: Traders can backtest their strategies on past data before going live.
- Efficiency: Algorithms can handle far more trades than a human.
- Risk Management: Systematic models are grounded in predetermined risk limits.
Let’s go through it step by step and understand how to create a systematic options trading strategy.
How to trade options systematically: A Step-by-Step Guide
Step 1: Define your trading goals
Setting objectives is the first step in a systematic options trading strategy. Ask yourself:
- What is your risk tolerance?
- Are you in it for short-term profits or long-term gains?
- What are the returns you’re looking to get?
- Do you want to trade weekly, monthly, or quarterly options?
If you happen to be a conservative trader, you would focus more on income-generating strategies (like credit spreads). Those with a more aggressive approach can consider volatility-based options trades.
Step 2: Choose your underlying asset
Systematic options trading starts with choosing the right underlying asset. This could be:
- Stocks
- Indexes
- ETFs
- Commodities
- Currencies
While these are important considerations, other factors should also be evaluated, such as:
- Liquidity: The higher the liquidity, the better execution of trades.
- Implied Volatility (IV): Some assets have predictable volatility cycles.
- Trading Costs: Debt commissions & spreads will need to be factored in.
Step 3: Select a systematic trading approach
Once your objectives are outlined and an underlying asset is selected, the next step is to explore a systematic trading strategy. This includes some common systematic options trading strategies:
1. Trend-following strategies
- Use indicators such as moving averages, Bollinger Bands, MACD to enter and exit trades
- For example, some traders consider buying call options when a stock breaks above its 50-day moving average.
2. Mean reversion strategies
- According to past behavior, that asset prices will return to their historical average
- Detects overbought and oversold conditions using Bollinger Bands, RSI, or statistical models
- For instance, selling put options when the RSI indicator is showing that an asset is oversold
3. Volatility-based strategies
- Concentrates on variations in implied volatility (IV)
- Traded options based on the VIX index or historical volatility measures
- For example, straddles or strangles around earnings when implied volatility is strong
4. Statistical arbitrage strategies
- It involves exploiting short-term mispricings in related securities using quantitative models. These strategies rely on statistical relationships rather than fundamental analysis.
- For example, you could pair trade two stocks that are correlated with options to hedge your exposure.
5. Delta-neutral strategies
- A strategy engineered to book profits from volatility with low directional risk.
- For example, a portfolio of calls and puts with offsetting delta values, a delta-neutral options portfolio.
Step 4: Test your strategy (Backtesting)
After deciding on a strategy, the next step is backtesting it on historical data. This helps determine:
- Profitability
- Risk-to-Reward Ratio
- Win Rate
- Maximum Drawdowns
Step 5: Implement risk management
In systematic trading, if we take losses, we can not allow them to be big. Several common methods of risk management are:
- Position Sizing: Capping how much you risk per trade (e.g., maximum of 2% of your capital per trade).
- Stop-Loss and Take-Profit: Exit rules that protect profits and limit losses.
- Hedging: Implementing options strategies (e.g., spreads or protective puts) to limit downside exposure.
Step 6: Automation of your trading strategy
Now it’s time to automate execution after your strategy is tested. This can be done using automated features in trading platforms or custom-built scripts in Python or R. Tools like MT4 for iOS offer traders the flexibility to monitor and execute their strategies directly from their mobile devices, enabling real-time access to the markets and seamless automation on the go. Automation enables faster execution, reduces emotional bias, and allows you to scale your trading operations efficiently.
- Automated features in trading platforms
- Python or R scripts custom built
Automation enables great speeds, avoids bias and can scale your trading operations.
The Downside to systematic options trading
Systematic options trading has numerous benefits, but it has challenges as well.
1. Model overfitting: Particularly one where many traders will over optimise their models on the historical data, which results in a less than optimal performance when applied to the live market sense. To avoid this, implement data splitting techniques during strategy development.
2. Changing market conditions: Markets change, and what worked six months ago may not work today. They require constant tweak to strategy.
3. Execution risks: Automated strategies rely on speed of execution, and latency, slippage, and order routing all play a role in profitability.
4. Regulatory compliance: However, regulation of algorithmic options trading differs from country to country. Don’t forget that your strategy must also abide by local law.
Conclusion
Systematic options trading allows traders to leverage multi-factor strategies with disciplined execution. By following a structured process like setting objectives, choosing strategies, backtesting, managing risk, and automating execution, traders can aim for greater consistency and efficiency in their trading approach.
However, success in systematic options trading requires flexibility and continuous improvement. As market conditions evolve and technology advances, especially with AI and machine learning, traders must be ready to adapt.
