Market folklore says that 95% of option buyers lose money. On the contrary, Subhadip Nandy consistently makes money taking directional trades using option strategies.
My discovery was volatility indicators, that too short-term indicator.
Say Infosys is moving in a range of Rs 10 on an hourly bar for the last 8-10 bars but suddenly there is a Rs 20 fall. This will not be captured in the end-of-the-day bar as the price moves by say Rs 40 in a day. But the Rs 20 fall in a single bar when the market was moving in a Rs 10 range for nearly 10 hours alerts me that the tides may be changing. This move gets first captured by volatility rather than trend and momentum.
What I have done is create my own volatility indicator which I monitor regularly for stocks as well as indices that forewarns me about the shifting volatility.
I also mix the volatility indicator with other data from derivatives which give much more information than data from the cash market. The cash market gives the open, high, low and closes along with volume and deliveries. But derivatives gives open interest as well as the entire action of an option chain which help in a more meaningful analysis of the counter.
Now volatility is a price-based indicator while a volume based indicator is an open interest. Majority of my price based study is on volatility and which side will the price break and if it is supported by open interest.
My hunting ground is stocks that are in the low volatility zone from where the stock will make a fresh move. As I am an option buyer and a directional player what I am looking for is a compression in volatility before the stock moves up with expanding volatility one last time.
Volatility has three characteristics they are – cyclicity, persistency and mean reversion. Cyclicity suggests that volatility will move from a high zone to a low one and again from low to high. Persistency says that if the volatility is high today it will again be high tomorrow or if it is low today it will be low again tomorrow. Mean reversion says that volatility will snap back from a high volatility zone to a low one and vice versa.
Now suppose you have a stock that is in the low volatility zone you have two characteristics in your favour. One is that cyclicity will ensure that volatility will move from the low to high zone while mean reversion will also suggest that the volatility will snap back to the mean. All you have to look out for is a breakout in volatility and if that breakout is followed by open interest going up then you are in a very good trade.
This way of trading is good for trading in stock options rather than index options. In index options, the data gets corrupted by varies strategies that FIIs use like synthetic futures (long calls and short put) that one filter out from the open interest data.
My list of stocks is restricted to 10 stocks where the options are liquid, where FIIs are active and it has a long option chain. I am more interested in trading a stock that is moving slowly rather than one that moves 20 percent in a day. I will trade this stock more from a day trading perspective.
Q: Could you share your track record in trading?
A: I trade two strategies. One is a simple bull or bear spread. Here I look to trade with a risk reward of 1:4. What I mean by this is that if there is a Rs 10 difference between two strikes, my spread cost (cost of buying an at-the-money option minus credit from selling out-of-the-money option) will not be more than Rs 2.5.
The risk-reward increases as we near expiry. The Adani spread trade of Rs 170-180, when I entered was at Rs 1 which moved up to Rs 4.5. If the above trade touches Rs 180 I will earn Rs 9 for every Rs 1 risked. But I do not play for the Rs 9. As soon as the spread increases to Rs 2, I square off half my position. When it reaches three times the risk I square off another 25 percent and it is only the last one that I wait for the entire length.
So in this strategy, I do not have to be correct all the time, even if I am right 35 percent of the time I am not losing money. But generally, I am correct over 50 percent of the time.
The other strategy I trade is the profit trap butterfly. This I trade closer to the expiry, actually expiry minus 13 days. Here I try to make an assumption of where the stock will close at expiry. I did this in HDFC Bank a few months back.
My assumption was that the stock would close at Rs 2,200 so I created a short butterfly (selling both calls and put) at 2,200 strikes I then bought 2180 put and a 2220 call. Here the difference in strike price is Rs 20. I take this trade if the risk-reward is 15 percent or less. That means, in this case, the spread for a Rs 20 difference in strike price should be a maximum of Rs 3. I managed to enter the trade at a spread of Rs 2. Here if the profit is Rs 4 I will book 50 percent of the profit.
I also trade intra-day but this is an automated trade where I enter the order if my system tells me. I have a nearly 60 percent success rate in intra-day trades with a risk reward of around 1:2 or 1:2.5.
Having said that there is another filter of risk management that I use. I have a daily, weekly and monthly target for risk as well as reward. I do not take a trade that does not come to me.
I also make it a point of taking a break every month and a half, especially if I am trading too well or have hit a bad patch. The trips help me get back on track from the emotional swings.
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