A major challenge directional traders face in market consolidation is frequent stop losses due to market volatility. Options naturally as an instrument decay continuously and with market volatility within a tight range, makes it even more difficult to take directional trades.
In market consolidations you’ll very frequently witness wide swings in day’s high and low’s but at the end the instrument may tend to follow minor to no drift. These are market scenarios where High-Low has a lot of volatility but Close to Close does not witness volatility.
The end result is that directional traders lose in either ways trades despite no net movement in the underlying. A few optimizations in stop-loss levels can fix this problem to a large extent. Since these trades are mostly short term, I’ll explain this in the purview of intraday trades .
Technical analysis is a very popular subject especially within the Indian trader’s community and if you follow option charts and applying technical analysis on it, you need to be aware to adjust your levels for theta.
For example, let’s say an option is trading at Rs.50. You expect the option price to rise based on your analysis, charts suggest a stop loss of 45 and a target of 60.
In this situation, if your trade is held for a few hours, due to theta decay both your stop loss level and target level will get affected.
For instance, if you took the trade at the market opening when it was 7 days left to expiry and intended to square off on the same day around market close, due to theta decay your stop loss should have come down to 41 and your target now stands reduced to 56 due to theta decay.
So, even if your forecast on the underlying was correct there can be a situation that due to time and with a marginal pullback in the underlying your static stop loss level can get triggered. To prevent such a situation, you’ll need to adjust theta in advance as per the intended time of the trade being held and accordingly take the trades if feasible and with adjusted stop-loss levels.
Not adjusting for underlying’s volatility is one of the major culprits to interim stop losses. Let’s understand this with an example if you trade for a 2:1 reward to risk in a volatile stock which often moves 2%-3% in a day on average what would happen if you keep a stop loss of 0.5%, probability says that your stop loss will get triggered even in temporary moves. Let’s understand how to adjust for these.
Adding some statistics can help you define a probability to your trades. Here is an approach:
Step 1: Calculate daily returns
The first step will be to calculate the daily returns of the underlying on a percentage basis.
Step 2: Calculate standard deviation
Second step is to calculate the standard deviation of the daily returns on a look back period. If you are trading intraday my best preference for look back period will be 90 days.
Step 3: Calculate the stop loss level for the day
Final step will be to calculate the stop loss for the day. Even though most instruments in real life do not follow a normal distribution but that is still a good approximation. Statistics says that 68% of the data will remain between 1 Standard deviation.
So, deducting 1 Standard deviation from the close price will give you a probability of 84% (explained below) that is temporary moves your stop should not get triggered. This will prevent you from market volatility and if your trade had a forecasting power, it would let you ride in the predicted direction.
Wondering how the probability is 84%? It’s because with 1 standard deviation as stop-loss the risk you hold is only of the left tail, if the instrument exceeds the right tail that’s good for you as you are running in profits. So, you only hold a left tail risk.
Tail Risk: 100% - 68% = 32%
Left Tail Risk: 32% / 2 = 16%
Probability of Stop not being triggered: 100% - 16% = 84%
*Note 84% is not the profit probability it is just the probability of stop not being triggered.
If the given stop loss is too high for the trade, you may resort to position sizing by reducing the intended trading quantity.
Learn and read more about option Spreads from Quantsapp classroom which has been curated for understanding of Long Straddle from scratch, to enable option traders grasp the concepts practically and apply them in a data-driven trading approach.
SHUBHAM AGARWAL is a CEO & Head of Research at Quantsapp Pvt. Ltd. He has been into many major kinds of market research and has been a programmer himself in Tens of programming languages. Earlier to the current position, Shubham has served for Motilal Oswal as Head of Quantitative, Technical & Derivatives Research and as a Technical Analyst at JM Financial.