Volatility for practical trading applications

  1. Trading for professionals: Options trading
    1. Call Option Basics learn the basic Definition with Examples
    2. Call option and put option understanding types of options
    3. What Is Call Option and How to Use It With Example
    4. Options Terminology The Master List of Options Trading Terminology
    5. Options Terms Key Options Trading Definitions
    6. Buy call option A Beginner’s Guide to Call Buying
    7. How to Calculate Profit on Call Option
    8. Selling Call Option What is Writing/Sell Call Options in Share Market?
    9. Call Option Payoff Exploring the Seller’s Perspective
    10. American vs European Options What is the Difference?
    11. Put Option A Guide for Traders
    12. put option example: Analysis of Bank Nifty and the Bearish Outlook
    13. Put option profit formula: P&L Analysis and Break-Even Point
    14. Put Option Selling strategies and Techniques for Profitable Trading
    15. Call and put option Summary Guide
    16. Option premium Understanding Fluctuations and Profit Potential in Options Trading
    17. Option Contract moneyness What It Is and How It Works
    18. option moneyness Understanding itm and otm
    19. option delta in option trading strategies
    20. delta in call and put Option Trading Strategies
    21. Option Greeks Delta vs spot price
    22. Delta Acceleration in option trading strategies
    23. Secrets of Option Greeks Delta in option trading strategies
    24. Delta as a Probability Tool: Assessing Option Profitability
    25. Gamma in option trading What Is Gamma in Investing and How Is It Used
    26. Derivatives: Exploring Delta and Gamma in Options Trading
    27. Option Gamma in options Greek
    28. Managing Risk in Options Trading: Exploring Delta, Gamma, and Position Sizing
    29. Understanding Gamma in Options Trading: Reactivity to Underlying Shifts and Strike Prices
    30. Mastering Option Greeks
    31. Time decay in options: Observing the Effect of Theta
    32. Put Option Selling: Strategies and Techniques for Profitable Trading
    33. How To Calculate Volatility on Excel
    34. Normal distribution in share market
    35. Volatility for practical trading applications
    36. Types of Volatility
    37. Vega in Option Greeks: The 4th Factors to Measure Risk
    38. Options Trading Greek Interactions
    39. Mastering Options Trading with the Greek Calculator
    40. Call and Put Option Guide
    41. Option Trading Strategies with example
    42. Physical Settlement in Option Trading
    43. Mark to Market (MTM) and Profit/Loss Calculation
Marketopedia / Trading for professionals: Options trading / Volatility for practical trading applications

Striking it right

The past few sections have supplied us with the fundamental principles of volatility, standard deviation, and normal distribution. Now, let’s look at a few practical trading applications based on this knowledge. Here I’d like to focus on two of them.

  1. Selecting the right strike to short/write
  2. 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 minimize it.

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

The bell curve above suggests that with reference to the mean (average) value –

  1. 68% of the data can be found within one standard deviation of the mean, which is to say there is a 68% probability that the data lies within this range.
  2. Most of the data is centred near the mean, with a 95% probability of being within the 2nd standard deviation.
  3. 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 make a good estimate of the Nifty’s trading range if we’re aware of its mean and standard deviation. As an example, let’s consider…

  • Date = 11th August 2015
  • Number of days for expiry = 16
  • Nifty current market price = 8462
  • Daily Average Return = 0.04%
  • Annualized Return = 14.8%
  • Daily SD = 0.89%
  • Annualized SD = 17.04%

Identifying the range within which Nifty will trade in the next 16 days is my current focus.

16-day SD = Daily SD *SQRT (16)
= 0.89% * SQRT (16)
= 3.567%
16-day average = Daily Avg * 16
= 0.04% * 16 = 0.65%

The following digits can be used to ascertain the most probable range in which Nifty will migrate in the next two weeks.

Upper Range = 16-day Average + 16-day SD

= 0.65% + 3.567%

= 4.215%, to get the upper range number –

= 8462 * (1+4.215%)

= 8818

Lower Range = 16-day Average – 16-day SD

= 0.65% – 3.567%

= 2.920% to get the lower range number –

= 8462 * (1 – 2.920%)

= 8214

The calculation hints that Nifty will probably trade between 8214 and 8818. We can be 68% confident that the result works in our favour, but there is still a 32% chance it will go outside of this range. This could mean any strikes beyond the calculated area might become worthless.

Hence –

  • It’s a good idea to sell any call options expiring above 8818 in order to collect their premiums, as they are unlikely to become profitable.
  • It is advisable to sell any put options with a strike price below 8214 and take advantage of the premiums they offer, as it is likely that they will expire without any value.

If you were considering buying Call options above 8818 or Put options below 8214, it might be wise to reconsider. It is highly unlikely that these options will expire in the money, so it’s best to stay away from them.

This is a list of all Nifty Call option strikes greater than 8818 that you can write (short) and make money from premiums.


I would opt for 8850 or 8900 as my pick today, as the risk (1 Standard Deviation) is balanced by the reward (7.45 and 4.85 for each respective lot).

It is understandable that you may be thinking the Rs.7.45 premium earned by writing an 8850 Call option doesn’t amount to much. In fact, this works out to be just Rs.7.45 per lot.

= 7.45 * 25 (lot size)

= Rs.186.25

A lot of traders overlook this concept. I’m aware of many who look at the gain or loss according to their exact price and not in terms of overall return.

It is necessary to have a margin amount of approximately Rs.12,000/- to carry out this trade.

The premium amount of Rs.186.25/- on a margin deposit of Rs.12,000/- gives us a return of 1.55%, which is undoubtedly decent for a period of 16 days! If you can keep up this rate month after month, then option writing could grant you an annualized return exceeding 18%.

My experience with developing options has taught me some useful techniques, which I am willing to share.

I prefer to not short PUT options due to the rapidity with which fear can overtake greed. This can cause market prices to plummet much faster than anticipated, and before you know it, the OTM option you wrote may become either ATM or ITM. Avoidance of this situation is more favourable than regretting it in hindsight.

Call Options – Rather than writing put options, writing call options is the better choice. For example, when taking the previously mentioned Nifty example into consideration, for the 8900 CE to become ATM or ITM Nifty has to increase by 438 points within 16 days. This requires there to be substantial enthusiasm in the market…as I noted before, an upswing of 438 points will take a greater amount of time than a decrease of the same amount. Therefore, my inclination is only to short call options.

I carefully assess the appropriate strike price to use, by taking into consideration SD, averaging calculations, converting these data points with regard to number of days till expiry, and only finalizing my decision in the week before it expires. The timing is intentional.

Timing – I only short options on the last Friday before their expire. For instance, given the August 2015 series ends on 27th, I’d go with a call option near the close of trading on 21st August. Why? To benefit from theta. You may recall that ‘time decay’ graph we discussed in the chapter about theta. It’s clear from it that we can get most advantage from theta when nearing expiry.

I may only get a small premium of about 5-6 Rupees for writing Nifty options close to expiry; however, that is equivalent to 1.0% return. I find this to be quite comforting because, for the trade to go against me, Nifty would have to move one standard deviation over four days – something that doesn’t occur too often. Furthermore, 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.

  • Visibility on risk and reward – both should be quantifiable
  • If a trade is profitable today then I should be able to replicate the same again tomorrow
  • Consistency in finding the opportunities
  • Assessment of worst-case scenarios

This strategy ticks well on all counts above, hence my preference.

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.

Option writing can be quite a thrilling endeavour, sometimes leaving 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, while there are roller coaster feelings that inevitably arise, they may lead to misrepresentations of the market. Ultimately, this may even cause you to prematurely exit what could have been a lucrative trade.

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. While 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. 7 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 %? If it’s a %, 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.

So within Equity, here is how I split my money –

  • 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 stocks, 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 bunch of trading strategies such as –

  • Momentum based swing trades (futures)
  • Overnight futures/options/stock trades
  • 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.500,000/- across various strategies. That way, no more than Rs.175,000/- will be exposed to any one approach.

  • 35% of Rs.500,000/- i.e Rs.175,000/- goes to Mutual Funds
  • 40% of Rs.500,000/- i.e Rs.200,000/- goes to equity portfolio
  • 25% of Rs.500,000/- i.e Rs.125,000/- goes to short term trading
  • 35% of Rs.125,000/- i.e Rs.43,750/- is the maximum I would allocate per trade
  • Hence I will not short more than 4 lots of options
  • 43,750/- is about 8.75% of the overall capital of Rs.500,000/-

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 predominantly employ this strategy on liquid stocks and indices like the Nifty and Bank Nifty, as well as SBI, Infosys, Reliance, Tata Steel, Tata Motors and TCS. Rarely do I explore beyond these choices.

I suggest you begin by calculating the SD and mean for Nifty and Bank Nifty on the morning of August 21st, five to seven days prior to expiry. 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 stocks 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 re-evaluate 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.

– 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 8300, it might be sensible to set 8200 as your SL; this would thus put 100 points at risk. The moment the Nifty falls under 8200, 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 a stock valued Rs.500, the stop-loss price would stand at Rs.490 with risk in this transaction amounting to Rs.10 (2% of Rs.500). 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 stock’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 stock. With a volatility stop, we are equipped with an appropriate and rationale getaway route if our trade appears to be failing.

This chart of Airtel indicates a bullish harami, which experienced traders would understand as an opportunity to go long on the stock. Utilizing the previous day’s low (which also coincides with support) as a stoploss, the target should be the immediate resistance – both support and resistance are indicated by blue lines. If you anticipate this trade taking place within 5 trading sessions, these are the details.

  • Long @ 395
  • Stop-loss @ 385
  • Target @ 417
  • Risk = 395 – 385 = 10 or about 2.5% below entry price
  • Reward = 417 – 385 = 32 or about 8.1% above entry price
  • Reward to Risk Ratio = 32/10 = 3.2 meaning for every 1 point risk, the expected reward is 3.2 point

This sounds like a good trade from a risk to reward perspective. In fact I personally consider any short term trade that has a Reward to Risk Ratio of 1.5 as a good trade. However, everything hinges upon the fact that the stoploss of 385 is sensible.

Let us make some calculations and dig a little deeper to figure out if this makes sense –

Step 1: Estimate the daily volatility of Airtel. I’ve done the math and the daily volatility works out to 1.8%

Step 2: Convert the daily volatility into the volatility of the time period we are interested in. To do this, we multiply the daily volatility by the square root of time. In our example, our expected holding period is 5 days, hence the 5 day volatility is equal to 1.8%*Sqrt(5).  This works out to be about 4.01%.

Step 3. Calculate the stop-loss price by subtracting 4.01% (5 day volatility) from the expected entry price. 395 – (4.01% of 395) gives a figure of 379, which implies that Airtel can swing to that point within five days. Therefore, a suitable SL should be placed below 379, for example at 375, which is 20 points below the entry price of 395.

Step 4 : With the new SL, the RRR works out to  1.6 (32/20), which still seems ok to me. Hence, I would be happy to initiate the trade.

Assuming we hold for 10 days, the volatility would then be 1.6*sqrt(10).

Pre-fixed percentage stop-loss doesn’t consider the daily change in stock prices. Therefore, traders may set a premature stop-loss that is inside the regular fluctuation of the stock, which often results in triggering the stop-loss earlier than intended, before reaching their target.

Including a stock’s daily expected volatility when placing stop-loss orders is beneficial since it helps account for the inherent fluctuation of prices. Doing so allows us to factor in the ‘noise’ and establish a more accurate stop loss.


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