Volatility for practical trading applications

Striking it Right

The past few sections have helped us understand the fundamental principles of volatility, standard deviation, and normal distribution. Now, let’s look at a few practical trading applications based on this knowledge. Let’s focus on the 2 of them as mentioned below:

Selecting the right strike to short/write

Calculating the stoploss for a trade

We will come back to ‘Relative value Arbitrage (Pair Trading) and Volatility Arbitrage’ at a later stage in another module. For the time being, we will focus on trading options and futures.

It’s time to get going, let’s begin.

The challenge for an option writer is to choose the appropriate strike, write the option to collect the premium, and thus reduce the concern of spot movement going against him. Though one can never escape entirely from this worry, a smart trader is able to minimise it.

Normal Distribution facilitates minimising the trader’s worries and raises his certainty whilst dealing in options.

Let’s have a quick recap:

The depicted bell curve indicates that in relation to the mean (average) value:

Within one standard deviation of the mean, which encompasses a range, there is a 68% likelihood that the data points will fall. In other words, approximately 68% of the data is expected to be within this range

Most of the data is centred near the mean, with a 95% probability of being within the 2nd standard deviation

The vast majority of the data occupies the 3rd SD, with 99.7% probability

Given the fact that Nifty’s returns follow a normal distribution, these characteristics apply to it. What does this mean then?

We can estimate the trading range of Nifty by considering its mean and standard deviation. Let’s consider a different example:

Date: Recent trading day

Days until expiry: 25

Current market price of Nifty: 24,500

Daily average return: 0.06%

Annualised return: 15.6%

Daily standard deviation: 1.1%

Annualised standard deviation: 22.0%

Our focus now is to determine the likely range within which Nifty will trade over the next 25 days.

To calculate the 25-day standard deviation:

25-day SD = Daily SD × √(25)

= 1.1% × √(25)

= 5.5%

To calculate the 25-day average:

25-day average = Daily Avg × 25

= 0.06% × 25

= 1.5%

Using the above values, we can determine the most probable range for Nifty’s movement in the next 25 days.

Upper range:

25-day upper range = 25-day average + 25-day SD

= 1.5% + 5.5%

= 7.0%

To obtain the upper range number:

Upper range number = 24,500 × (1 + 7.0%)

= 26,215

Lower range:

25-day lower range = 25-day average – 25-day SD

= 1.5% – 5.5%

= -4.0%

To obtain the lower range number:

Lower range number = 24,500 × (1 – 4.0%)

= 23,520

Based on these calculations, it is likely that Nifty will trade between 23,520 and 26,215. We can be 68% confident in this estimate, but there is still a 32% chance that it may move outside this range. Any strikes beyond this calculated area might become worthless.

Hence, based on the analysis, we can make the following suggestions:

Selling call options: It would be a good idea to sell any call options expiring above 26,215 to collect their premiums, as it is unlikely that they will become profitable given the predicted trading range

Selling put options: It is advisable to sell any put options with a strike price below 23,520 and take advantage of the premiums they offer, as it is likely that they will expire without any value within the predicted range

Avoid buying certain options: If you were considering buying call options above 26,215 or put options below 23,520, it might be wise to reconsider. These options are highly unlikely to expire in the money, so it’s best to stay away from them

Here is a list of all Nifty call option strikes greater than 26,215 that you can write (short) to generate income from premiums.

Considering the risk (1 Standard Deviation) and reward, today I would opt for the 26,300 or 26,400 strike as my picks. The risk is balanced by potential rewards of Rs 18.50 and Rs 12.25 for each respective lot.

You might be thinking that the premium earned by writing a 26,300 call option, for example, doesn’t amount to much. In fact, it works out to be just Rs 18.50 per lot.

Calculating the total premium:

Rs 18.50 × 50 (lot size) = Rs 925

Many traders overlook the concept of overall return. It is necessary to have a margin amount of approximately Rs 1,35,000 to carry out this trade.

The premium amount of Rs 925 on a margin deposit of Rs 1,35,000 gives us a return of 0.69%, which is quite decent for a period of 25 days. If you can maintain this rate consistently, option writing could grant you an annualised return exceeding 10%.

For those exploring equity investment opportunities through a stock broker or consulting with a financial advisor, understanding volatility applications for strike selection proves essential when navigating the stock market. Whether evaluating trading calls or utilising a stock screener to identify opportunities, comprehending how to apply normal distribution to option writing enables more strategic premium collection whilst managing risk effectively.

Based on my experience, I have developed some useful techniques that I am willing to share.

Preference for call options: I prefer not to short put options due to the potential for fear to overtake greed rapidly. Market prices can plummet faster than anticipated, causing the option you wrote to become either at the money (ATM) or in the money (ITM). It is more favourable to avoid this situation rather than regret it later.

Assessing the appropriate strike price: I carefully evaluate the strike price by considering the standard deviation, averaging calculations, and converting data points based on the number of days until expiry. I finalise my decision in the week before the option expires. This timing is intentional to take advantage of theta and time decay.

Timing: I only short options on the last Friday before they expire. For example, if the options series ends on 27th March, I would go with a call option near the close of trading on 22nd March. This allows me to benefit from theta, as nearing expiry provides the most advantage from time decay.

When writing Nifty options close to expiry, I may only receive a small premium of about Rs 12-15. However, that is equivalent to a 0.8-1.0% return. This provides comfort because, for the trade to go against me, Nifty would have to move one standard deviation over four days, which is relatively uncommon. As expiry approaches, theta works in my favour, and the premiums erode much quicker.

Many may wonder why they should bother with premiums that are small. To be honest, I had this same thought at first, but as time went on, I came to understand that there are certain deals that make perfect sense to me:

It is important to have clear and measurable understanding of the risks and rewards involved in a trade

If a trade proves to be profitable today, it should be feasible to achieve the same level of success in replicating it tomorrow

Maintaining consistency in identifying and seizing opportunities is crucial

It is essential to assess and consider the potential worst-case scenarios before engaging in a trade

I like to write my options 3-4 days before expiry at 1 SD away, but closer to expiry I usually opt for 2 SD away. Ultimately, the higher the SD consideration, the greater your assurance of success, yet the amount you can receive will be lower. As a general rule I never write options when there are more than 15 days left until expiry.

When there are significant market events, such as policy decisions or corporate announcements, I tend to steer away from writing options. This is because the markets often react strongly in response. It’s better to be risk-averse than take a gamble and end up on the wrong side.

I’m well aware of the potential risks in this trade. If I make the mistake of getting caught on the wrong side, then I’ll pay a steep price; I could lose substantial amounts of profits which I’ve made with effort over several months, all gone in one month. Satyajit Das’s aptly titled book “Traders, Guns and Money” refers to this method as ‘eating like a hen but shitting like an elephant’.

The only way to protect yourself against a black swan event is to be mindful that it can happen at any time, once you have written the option. Here’s my advice if you do decide to employ this strategy: monitor the markets and take note of market sentiment. Once you begin to feel something isn’t right, act quickly and end the trade.

Engaging in option writing can be an exhilarating pursuit, occasionally keeping you on the edge of your seat. The fear of a black swan event playing out may temporarily take over, but usually subsides in time. Thus, whilst there are roller coaster feelings that inevitably arise, they may lead to misrepresentations of the market. In the end, this could lead you to exit a potentially profitable trade prematurely.

There is a delicate distinction between a phony signal and an authentic black swan event. The key to managing this situation is developing trust in your investments. Whilst I can’t give you faith, it augments as you conduct more trades (always with sound judgement, not random guesses).

Also, I personally get out of the trade when the option transitions from OTM to ATM.

It is essential to keep your expenses low when you trade, since this will allow you to maximise profits. Examples of these fees include brokerage and applicable charges, meaning that if you short 1 lot of Nifty options and collect Rs 14 in premium, it may be necessary to let go a few points as expense.

An obvious inquisition you possibly have at this juncture, how much capital should I assign to this trade? Do I venture the entirety of my funds or merely a certain percentage? If it’s a percentage, what would that amount be? There’s no easy response to this; thus I’ll take advantage of this moment to outline my asset allocation strategy.

I’m confident in investing my capital (savings) into equities and related products, which disqualifies Gold, Fixed Deposit, and Real Estate. Although I do still recommend diversifying your investments across multiple asset classes.

Here’s how I split my money within equity:

I have put 35% of my funds into equity-based mutual funds using a SIP (systematic investment plan). This money has been further divided between four funds

Around 40% of my capital is invested in an equity portfolio consisting of about 12 equities, with a view to long-term growth over a 5 year period or more. Additionally, I also invest in mutual funds for the same long-term objectives

25% is earmarked for short term strategies

The short-term strategies include a variety of trading approaches, including:

Swing trades based on momentum (futures)

Trades involving futures, options, and equities held overnight

Intraday trades

Option writing

To ensure that I do not put more than a 35% share of my capital at risk, I break up the Rs 8,00,000 across various strategies. That way, no more than Rs 2,80,000 will be exposed to any one approach.

35% of Rs 8,00,000 i.e. Rs 2,80,000 goes to Mutual Funds

40% of Rs 8,00,000 i.e. Rs 3,20,000 goes to equity portfolio

25% of the total capital of Rs 8,00,000, which is Rs 2,00,000, is allocated for short-term trading

The maximum amount I would allocate per trade is 35% of Rs 2,00,000, which is Rs 70,000

Therefore, I will not short more than 3-4 lots of options

An amount of Rs 70,000 corresponds to roughly 8.75% of the total capital of Rs 8,00,000

This self-imposed regulation guarantees that no more than 9% of my total assets are exposed to any short-term strategies, including option writing.

I primarily utilise this strategy on highly traded equities and indices such as Nifty, Bank Nifty, State Bank of India, Infosys, Reliance Industries, Tata Steel, Tata Motors, and TCS. I rarely venture beyond these options for my trading activities.

I recommend starting by computing the standard deviation (SD) and mean for Nifty and Bank Nifty on the morning approximately five to seven days before the expiration date. Identify options that are one SD away from market price and write them on paper. You can then wait until expiry, observe how the trade progresses, and if you are able to, apply this exercise to all the equities previously mentioned. It’s important you constantly do this for a few expiries before investing any money.

As a necessary warning, I must point out that the opinions expressed above reflect my own risk reward preferences, which may differ from your own. All the advice given here is based on experience, and not necessarily accepted trading methods.

I strongly advise keeping these points in mind, to get a better grasp of your risk-reward disposition and adjust your approach accordingly. Hopefully this guidance can assist you with building that attitude.

Nassim Nicholas Taleb’s “Fooled by Randomness” is highly recommended at this point. It will make you question your decisions and reevaluate the way you conduct yourself in markets (and life). Merely being conscious of Taleb’s writings, along with your actions in financial markets—will catapult you to an entirely different level.

For those exploring equity investment opportunities through a stock broker or consulting with a financial advisor, understanding systematic option writing strategies proves essential when navigating the stock market. Whether evaluating trading calls or utilising a stock screener to identify opportunities, comprehending risk management, position sizing, and timing strategies enables more disciplined and profitable options trading approaches.

Volatility-Based Stoploss

This is something that should more appropriately be discussed in the futures trading module, but we’re at the correct point for it nonetheless.

Prior to making any trade, you must identify the stop-loss (SL) price. The SL is a price at which point losses will no longer be taken. For instance, if you’re buying Nifty futures at 24,800, it might be sensible to set 24,600 as your SL; this would thus put 200 points at risk. The moment the Nifty falls under 24,600, exiting the trade and accepting the loss is wise. Thus, an important issue remains—how can we establish an appropriate stop-loss level?

Most traders commonly employ a standard pre-set stop-loss percentage when entering into a trade. For instance, they may set a 2% stop-loss on each trade. In the case of an equity valued Rs 850, the stop-loss price would stand at Rs 833 with risk in this transaction amounting to Rs 17 (2% of Rs 850). However, this tactic is unfavourable because it disregards the daily fluctuations of the security which may range from 2-3%. Consequently, one might be correct about the direction of their investment but still land up striking that ‘stop-loss’. Usually this could lead to disappointment and regret.

An effective way of pinpointing a stop-loss price is to take into consideration the equity’s volatility; this gives insight into how much it can be expected to fluctuate on any given day. This method has the advantage of accounting for everyday market movements, providing a stop that lies outside the normal range of volatility for the equity. With a volatility stop, we are equipped with an appropriate and rationale getaway route if our trade appears to be failing.

Let’s illustrate the implementation of the volatility-based Stop Loss (SL) with an example:

During our analysis of the chart for a specific equity, such as ABC Ltd, we observe the presence of a bullish harami pattern. This pattern suggests a potential opportunity to take a long position in the equity. We decide to set our stop-loss based on the previous day’s low, which also acts as a support level. The target for this trade is set at the immediate resistance level, which is represented by the blue lines on the chart. Let’s consider the following details for this trade, assuming it will take place within 5 trading sessions:

Entry: Long @ Rs 725

Stop-loss: @ Rs 695

Target: @ Rs 780

Risk: Rs 725 – Rs 695 = Rs 30, or approximately 4.1% below the entry price

Reward: Rs 780 – Rs 725 = Rs 55, or approximately 7.6% above the entry price

Reward to Risk Ratio: Rs 55/Rs 30 = 1.83, meaning for every 1 rupee of risk, the expected reward is 1.83 rupees

From a risk to reward perspective, this trade appears favourable. Personally, I consider any short-term trade with a Reward to Risk Ratio of 1.5 or higher as a good trade. However, the key factor is ensuring that the stop-loss level of Rs 695 is reasonable and provides adequate protection.

Let’s perform some calculations and delve deeper to determine if this trade makes sense:

Step 1: Estimate the daily volatility of ABC Ltd. Let’s assume it is 1.8%

Step 2: Convert the daily volatility to the volatility for the desired time period. In our case, the expected holding period is 5 days, so the 5-day volatility is equal to 1.8% multiplied by the square root of 5, which is approximately 4.03%

Step 3: Calculate the stop-loss price by subtracting 4.03% (5-day volatility) from the expected entry price. Rs 725 – (4.03% of Rs 725) gives a value of Rs 695.78. This implies that ABC Ltd could potentially swing to that price within five days. Therefore, a suitable stop-loss level could be placed below Rs 695, for example, at Rs 690, which is 5 rupees below the entry price of Rs 695

Step 4: With the adjusted stop-loss, the Reward to Risk Ratio becomes approximately 1.57 (Rs 55/Rs 35), which still seems acceptable. Thus, we would be comfortable initiating the trade

If we hold the position for a longer period, say 10 days, we would recalculate the volatility as 1.8% multiplied by the square root of 10.

Using a fixed percentage stop-loss alone may not consider the daily fluctuations in equity prices. Traders may set a premature stop-loss level that falls within the normal price fluctuations, leading to the stop-loss being triggered earlier than intended, before reaching the target.

By incorporating the equity’s daily expected volatility when placing stop-loss orders, we account for the inherent price fluctuations, taking into consideration the “noise” in the equity’s movements. This approach allows for a more accurate stop loss placement.

For those exploring equity investment opportunities through a stock broker or consulting with a financial advisor, understanding volatility-based stop loss placement proves essential when navigating the stock market. Whether evaluating trading calls or utilising a stock screener to identify opportunities, comprehending how to set scientifically calculated stop losses based on volatility enables more rational risk management and reduces premature exit from potentially profitable trades.