(Thread) A quick note on strangles

If you are selling strangles in a bullish, low vol environment keep the following in mind:

Assuming you entered a delta-neutral strangle on an index(Nifty/Bnf), any further upmove on the index will change delta of the strangle, i.e. making
+
it -ve, rapidly and more likely to hit SL on the call side. Given vols are already low at entry further decrease in vols contributing to call delta getting supressed is immaterial, i.e. vanna impact is low (check post below on vanna in general), and so
+

call delta will mostly only depend on index moves. In other words, your PnL doesn't have a buffer from vanna effect and is exposed solely to index moves and how good is your SL strategy. The Pnl's movement isn't smooth and adjustments become difficult.
+
Your risk is now on the "view" you have of index' next move (i.e. you're in the prediction zone!) and your SL strategy.

Compare this to a scenario when a strangle was entered at high vol and index turns bullish leading to vols coming down (btw spot going up & IV coming down
+
is not always the case but most of the time is). In this case call side delta increase from index upmove will be suppressed by vanna effect significantly (unless index moves high rapidly) and so you've got a cushion/buffer to be able to react/adjust the strangle
+
and PnL moves smoothly. In this case put side will give better +ve Pnl than the one in low vol scenario as it's sold at high delta (delta of OTMs higher at high vol) and index made an up move i.e. entry is at higher +ve delta and spot makes an upmove hence higher PnL.

(END)

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More from @muskk

21 Nov
(Thread) Trading Ratio Spreads (Part 2)

The main bit!

I’ll mostly focus on credit put ratio spread in this thread.

(yesterday's thread below for linking both)

First let's look at best time to enter the trade.
+

Trade entry point: Two scenarios. One safe and one aggressive. See pic below (pasting pic to reduce length of this thread).

Once we enter, how does the price of PRS behave?

Let’s focus on expiry trading as this is the easier bit compared to trading them on other days or entering positional (which I'll cover in future posts).

First let me quickly mention what I did last Thursday.
+
Read 14 tweets
20 Nov
(Thread) Trading Ratio Spreads (Part 1)

Let’s try to understand what factors impact ratio spreads and how to trade & risk manage them.

As it’s impossible to fit everything into one thread I’m dividing this into two. I’ll cover factors that affect ratio spreads
+
in the first part and then discuss how to trade & risk manage them in the second (which I’ll post tomorrow morning). Finally, I’ll discuss the best case scenario to trade them that has a very good risk reward.

A quick (boring) intro:
Ratio spreads (RS): Short OTM/ATM options
+
and go long options that are more in the money than the options shorted. Quantity of options shorted are in multiples of quantity of options bought.

Factors that affect ratio spreads:

(super important)
Delta wrt TTE – As we near expiry, delta of OTM option goes down(see pic)
+
Read 10 tweets
14 Nov
(Thread) Stochastic processes

Thought of posting a primer on stochastic processes that’ll be useful for any future posts on whether deriving Black’s formula for pricing calls/puts (my next post and should be a quick one) or discussing interpolation of vol surfaces (SVI) etc.
This should also help understanding my VIX derivation post better.

Any let's get started.

Any underlying variable, be it a Nifty/BankNifty, USDINR, crude etc, can be represented as a stochastic process with a drift and a diffusion(random) component.
+
Think of a stochastic process as a random variable evolving with time OR a collection of random variables that have been gathered at different times (Usually all stochastic processes, expectations are always defined under some probability measure but I’m not touching on
+
Read 9 tweets
25 Oct
#Distribution Below is how an index return distribution can "potentially" evolve with time AS OBSERVED at starting time t=0.

As an example, one can view this as a potential #Nifty return distribution with PDFs given by Nov month end options (t=1), Dec month end options (t=2)..
+ Image
and so on (T=1 can be weekly also but I reckon weekly distributions won't look that smooth based on what I observed of option price/IV behavior).

Things to note:

At t=0 nothing is random, everything deterministic and pdf is a dirac-delta function.

+
And with time, probability of index moving away from its mean (colored with orange ticks) goes up and so pdf spreads wider and it's peak value keeps coming down in order to assign more weight to returns away from its mean.

+
Read 4 tweets
17 Oct
(Thread) Forecasting

Once upon a time (many many many years ago!) one of my friends was asked to implement a forecasting project as the last stage of getting an offer from a prop trading firm in Europe. Below is the problem statement:
+
Input data consists of (several hours of) trade and order book data for a listed product.
Order book data consists of time, bid/offer price and size resp. whereas the trade data
consists of time, price and volume.
Objective: Build a quantitative model to trade this instrument.
+
My friend was a uni. chicago booth grad but had a lazy arse so I helped him implement it with the help of a common HFT friend. We both knew shit and the project was all implemented through the HFT guy’s guidance. I’m just presenting the report below. Check out.
+
Read 5 tweets
29 Aug
Thread on deriving India VIX!

Get your pen and paper ready!

The NSE India VIX white paper (link below) only gives the formula and we will derive it in this thread. That'll be the only focus of this thread with more in future threads.
www1.nseindia.com/content/indice…
This is going to be mathematical and my post yesterday about expectation and integration should help. But I’ll try to reduce jargon and leave out unnecessary mathematical details. Some topics such as stochastic processes have been touched upon here. Will post more on that later
+
Let’s say f(x) is any function of a stock (or any other tradable underlying) ‘x’ and whose 1st & 2nd derivatives exist. Following on from the derivation last time of the PDF of any underlying,
‘x’ has a PDF, φ(k), given in fig below.
Image
Read 12 tweets

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