#Strangles A little note on getting into strangles in a bear market scenario

If you're an intra-day trader selling delta-neutral strangles on non-expiry days in the morning and holding them till day end then be careful of the following when market is expected to be bearish.
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Given short strangles are short vol trades (-ve vega) the view is not just on benefitting from theta but more importantly on vols going down during the day. So in a bearish scenario when vols are expected to go up with market going down your strangle position
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will get affected in the following way:

- Loss due to vols going up with this being a -ve vega position. There are other vol factors that you'll be short on such as skew (below), convexity of the vol surface and these increase as well affecting the position negatively.

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- Assuming you make adjustments to keep delta in check due to index down moves, i.e. shift put strike down, there will be loss due to net position turning delta positive with put vols increasing more than call vols(skew) which in turn leads to put delta increasing more than a
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decrease in call delta (effect from vanna).

Result of the above is your Put SLs keep getting hit but profits on calls will hardly compensate for the loss due to increased vols(calls can even freeze after a point!).

If you keep holding your positions and
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keep making adjustments to perhaps recover/reduce your losses then you can end up with a nightmare scenario where vols keep falling till day-end and you either have to book a loss or choose to hold positions overnight which given it's a bearish scenario can result
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in a huge drawdown next day if market opens gap-down. Pnl from theta will hardly be anywhere near loss from vega in such scenarios.

Better to get out once SLs hit or turn the position into a put ratio on the put side or simply close the whole thing and enter a credit call ratio.

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More from @muskk

10 Dec
(A little thread)
#PnlExplain
Whatever options position one enters it's important to know the risks one is taking and hence where the PnL is coming from. As an example if one is taking delta-neutral strangles (say 2% away OTMs on Nifty weeklies) at market open on a Friday and
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within a couple of hours sees a 5pt reduction in the price of the strangle (with delta still neutral) then the PnL is coming from the following:
Vega - given this is a -ve vega/short vol position a decrease in implied vols of both the OTM options in those couple of hours
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results in a positive Pnl

Theta decay - this is technically the decrease in an option price in a given period of time "keeping all other factors constant".

In all likelihood given the current vol levels, Vega would've driven the 5pt Pnl profit more than theta given +
Read 6 tweets
8 Dec
(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
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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
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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.
+
Read 6 tweets
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.
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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.
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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
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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
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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)
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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.
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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
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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)..
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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.

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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.

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Read 4 tweets

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