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Friday, July 28th 2023

Unlocking Profitable Strategies: How ORATS Backtester's Advanced Metrics Reveal Opportunities

Discover your favorite backtests by filtering on several popular performance metrics such as notional return, sharpe ratio, and percent of time in market.

Summary

The ORATS Backtester offers millions of options backtests each with 37 different performance metrics across four different categories: Return, Risk, Profit & Loss, and Other. In this blog, we dive deeper into some of the most important metrics, including notional and margin returns, Sharpe and Sortino ratios, and percent of time in market.

The new ORATS Backtester gives you access to millions of options backtests and a wealth of precise performance metrics. It allows you to dissect and assess a variety of strategies based on meticulously calculated performance metrics, enhancing your understanding and facilitating profitable decision-making. Today, we'll dissect a few of these metrics, including notional and margin returns, Sharpe and Sortino Ratios, and the role of filtering by time in the market to curb overfitting.

Understanding Our Performance Metrics

Before diving into the specifics, let's outline the four categories of performance metrics you'll find in our backtester: Return, Risk, Profit & Loss, and Others.

  • Return: Metrics such as annual returns (overall, 1 year, 5 years, bearish and bullish markets), annual margin return, and best/worst monthly and annual returns.
  • Risk: Quantitative measurements such as Sharpe Ratio, Sortino Ratio, Annual Volatility, Max Drawdown %, Drawdown Days, and Reward to Risk Average.
  • Profit & Loss: Comprehensive data like average P&L % per day, best and worst trade P&L (both in dollar and percentage), average P&L per trade and per day, and total strategy P&L.
  • Others: Metrics including % of time in the market, strategy win rate, average days in trade, total strategy trades, credit/debit per trade average, margin per trade average, and margin to stock %.

Let's dive deeper into some critical metrics:

Notional vs. Margin Returns

Notional and margin returns are both crucial elements for assessing the profitability and efficiency of a strategy. By understanding how these returns work, investors and traders can make informed decisions when it comes to selecting the strategies that are right for them.

In options trading, the notional value of an option refers to the value of the shares controlled if the option were to either expire or be exercised or assigned. For example, if I buy a $5 call option on a $100 stock, because this option controls 100 shares of the underlying, the notional value of the trade would be 100 * $100 = $10,000. However, I would only need to pay $5 * 100 = $500 to open this trade. Thus, the notional return measure the performance relative to the $10,000, while the margin return measures the performance relative to the $500.

It’s easy to see that notional returns are much lower than margin returns. We use notional returns in the backtester because it helps standardize and normalize performance across all different types of strategies and symbols. We show the margin return to highlight how efficiently the strategy used the capital at its disposal. However, you have to be careful with margin returns, as sometimes they are not the most accurate reflection of a real-world trading environment.

Generally, if an investor is using options and stocks, or if you want to normalize and compare disparate trading strategies, the notional calculation is best. If you want to see how much you would make on the amount at risk from a brokerage firms perspective the margin returns are best to use. Brokerage firm’s margin do not always present the actual risk, so care needs to be used. For example, a short put may require 20% margin in portfolio margined accounts or 100% margin in cash accounts. The margin returns would be significantly different in either approaches.

At ORATS, we show margin returns but have more data on notional returns because they are more conservative and consistent and allow better comparisons between backtests.

Sharpe vs. Sortino Ratio

Our backtester also shows both Sharpe and Sortino ratios for each strategy. While they might seem similar at first, each ratio offers a distinct perspective on risk and should be understood separately.

The Sharpe ratio gauges how much excess return a strategy provides relative to the risk taken, using standard deviation as a proxy for risk. It's excellent for understanding a strategy's overall risk-adjusted return, but it falls short in one critical area – it doesn't distinguish between upside and downside volatility.

That's where the Sortino ratio comes in. The Sortino ratio, like the Sharpe ratio, evaluates risk-adjusted return, but it only considers downside volatility. In doing so, it addresses an important asymmetry in trading – traders generally welcome upside volatility while fearing its downside counterpart. A high Sortino ratio signals that a strategy minimizes damaging losses while potentially capitalizing on desirable volatility. By providing both these ratios, our backtester allows traders to examine a strategy's return through multiple risk perspectives.

Filtering Percent of Time in Market

Filtering by the percent of time in market is an important feature of our backtester, mainly to reduce overfitting. By setting a minimum filter, you can focus on backtests with a statistically sound number of market days.

Imagine two strategies: Strategy A has been in the market for 300 days, and Strategy B for only 30 days. While Strategy B might show an impressive return for its short time, its performance metrics might be unreliable due to the small sample size. Our tool allows you to filter out such strategies, preventing overfitting and enabling a more robust evaluation of the strategies' true performance.

You can apply filters to any of the 37 different performance metrics in the table to help narrow down your results. Like percent of time in market, you can apply filters to drawdown days, total strategy trades, and margin to stock % to fine-tune your risk tolerance and trading preferences.

Profit & Loss Metrics

We calculate various measures of profit and loss to provide a comprehensive view of a strategy's performance. The best and worst trade p&l metrics make it easy to quantify your upside potential versus the downside risk of the strategy. Sometimes it’s good to filter the table based on p&l percent per day, as that can be a good baseline for an effective strategy.

Below you can see the trade log for a short put strategy on SPY. The trades are ordered chronologically depending on when they were entered. The total profit is shown on the right, with a breakdown of the entry price and exit price included. You can see how the total dollar profit for each trade is calculated, assuming $0.01 slippage on both the entry and exit. This value is used in many of the calculations related to profit and loss.

Conclusion

The ORATS Backtester is designed to help you make sense of the options trading universe with its advanced features and metrics. Use it to navigate the field confidently, uncovering profitable strategies while understanding the risks and potential returns.

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