(Let’s do some math!) Thread on how to retrieve probability density function (PDF) of any underlying from its option prices. We will use this result later on in another thread I’ll post in the future to derive an equation for VIX.
Let's go...
Let’s first look at equation to price a call option at any time t, maturing at time T and with Strike K:
(refer equation1 pic below)
here F is forward, E[] is expectation & B(t,T) is discount factor. I’m excluding a few math details like measures & numeraires to keep it simple.
Let φ be the probability density function (PDF) of the underlying we are trying to recover. Let’s try to solve the expectation above (ignoring discount factor and other parameters C depends on to make equations look simpler)
(refer equation 2 pic below)
Taking first derivative with respect to K we get:
(refer equation 3 pic below)
Taking second derivative wrt K gives the PDF as:
(refer equation 4 pic below)
Let’s write the discretized version of the equation above:
(refer equation 5 pic below)
Guess the numerator on the RHS of equation 5? Yes, it’s a butterfly spread! The PDF at any strike can be obtained from a butterfly around that strike(with a very small spread, δ) divided by squared-strike (one should get similar result for PDF starting with a put instead of call)
That’s our result. Please feel free to correct me if I missed something in the derivation. Note that the above derivation is model independent i.e. no assumptions made on how the underlying behaves (unlike say black’s model). We just retrieve the distribution from option prices.
The next step is to plot the PDF vs strikes. I’ll try to cover that on another thread. That’s a little easier and more interesting part!
(Writing such math posts on twitter is a pain btw. Please let me know if there is a way to write equations rather than posting pics!)
--End
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Objective: an event coming up next day and we want to calculate the expected move in the index/stock implied by option prices
Bro @l_thorizon mentioned on a call about implied move formula the other day (not for the first time)
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..so thought it's time to derive it.
(it’s been ages since I posted a thread so excuse any mistakes pls)
Events can be FED/RBI policy meetings, CPI data release, stock earnings. You can compute these for (say) Reliance, ICICIbank this weekend or for Nifty(or S&P500 if you’re
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into it) before 2nd Nov Fed meeting and see if they’re of any use.
Event Volatility:
We need ATM options with two different expiries T1 and T2 say T2>T1
Event vol, ev = sqrt (365) * sqrt [ IV(T1)^2 * T1/365 - FV(T1,T2)^2 * (T1-1)/365]
Where,
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The author presents an easy way to transform one's expectation of how returns distribution will pan out in the future("user-expected"
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distribution) given current market implied distribution into appropriate trading strategies.
Let's say b(x) is what you expect index/stock returns "x" to be distributed in the future and m(x) is current market implied pdf based on prevailing option prices (see thread
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below to get market implied density function from option prices. To get a continuum of option prices fit an SVI IV surface on option price grid)
Then the strategy that needed to be entered is simply given by:
Given option prices are settled based on average of last half hour prices (correct me if interval is wrong) perhaps in 5min intervals (trust me I couldn't find an NSE doc on this piece🤦♂️) our options
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are actually Asian options.
So,
Asian call payoff : max(avg(S(ti) - strike,0) where S(ti) last 30mins, 5 min intervals prices (say)
and not european i.e. max(S(T) - strike,0)
The impact of averaging feature will be much less when we are away from expiry but gain significance
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As we are closer and specially in the second half of the expiry.
Now I won't bore you with the math of pricing them (which isn't trivial and done by matching 1st, 2nd moments of an assumed log-normal distribution of the averaged price and finding parameters i.e. mean/variance
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I usually don't do the "role model" thingy but if there's anyone I look up to and want to be like (in a couple of years time!) that's Benn Eifert @bennpeifert
@mnopro pointed me to his handle a couple of months ago and I recently watched his mixing with models YT video & gone
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through some of his posts and given my experience interacting with HF friends or interviewing with HFs during my 10years working in London I can honestly say he's right up there with the best. Don't get me wrong there's absolute garbage as well on the HF side (and I'll share
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my thoughts on that some other time), but the CIO folks are altogether different class and Benn seems no different. The clarity with which he speaks about anything Vol related is mind-boggling(!) & something I'd like to aspire to.
Best time to enter zero-cost call ratios or a ladder (shorts at multiple strikes) is when IVs are shooting up combined with mkt going down. Today was a classic example.
If we see the kind of fall we saw today in Nifty keep long leg 100pt OTM and
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short leg atleast 300pts further away and you can increase the ratio higher than 1:3 (you'll have to, to keep it zero-cost). You can make it credit depending on your risk-appetitie and your skill in adjusting these.
So when you enter this you will be net short vega.
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#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.