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It's a fund and nobody besides my group is gonna be dealing with these products. Even for me, I just need to know if the dealer is raping me and also so I can net my risks for exposure purposes.

State of the art is a vague term :) I got Fincad but some of the products we trade need a more involved model then Fincad allowes

Yup. We got Fincad but it does not expose the guts enough for a couple products (like knock-in forward variance) that I want to price.

It's a wrapper around the C++ library, right? What I don't get is if I build a custom payoff, how easy is it to expose it through any of these wrappers?

Mostly light exotic pricing/delta and similar stuff. How easy is it create new payoff models? Is it easy to integrate with python if I write custom pricing models in it?

long-shot, obviously, but maybe someone has good points on getting started? Wanna use it as a side tool with a commercial library

I would think that if you are blindly buying or selling (no attempts to add some form of alpha), being net short risk premium would produce better risk-adjusted return, at least in terms of Sharpe and duration of drawdowns. That's why it's a risk premium (as in premium means it's more expensive...

If this was an index, I can see why you would think it's rich and there is a good reason for it (systematic risk and banking regs), but a pharama stock, really? I will quote here: Anyway, I don't get why you think these tails are expensive? it's 20% vol ATM, spot on with trailing 3m realized...

Yeah, like the infamous Microsoft trade... that was fun :)

-- What do you think is "market makers expected move"? Or, what in your opinion constitutes a tail? -- Why do you think these things are so expensive (at least in your perception)? -- If it's such a bad trade to buy these tails, who are the buyers and why are they buying it? It really depends...

Right, obviously. I would imagine, though, that someone who's got resources can build up a "life boat" of some sort. Build up identities outside the country, have money stashed away etc. Someone like Madoff should have thoughts about it at some point before the heat was on him, don't you think?

That would be me, I assume? :) Put/Call parity is important because it shows you an equivalence of different option positions - for example, it allows you to construct the same payoffs based on different building blocks. For example, the fact that covered call is equivalent to a short put would...

Well, what would be his process? Say you are an Evil Guy and at 3pm you find that you are going to jail? Your first actions?

Was having a conversation with a friend of mine about Madoff and other Ponzi scheme perpetrators. The one thing that always puzzled me is why didn't they run. But if you do run, what are your options? Assuming you have some cash at your disposal, let's say 1-3 mm USD, what would be the action...

Well, in a crisis all correlations go to one so I am not sure it's as easy as the good doctor is saying. You can try playing the relative risk premia game (that's what I do), but it's an active and serious strategy with a lot of moving parts.

I am trying to say that in an ideal world, you want to approach strategy development from first principles. E.g. if you are adding a constraint, the reason for it should be extrenious to the strategy as well as your decision to keep/remove it. Otherwise it's a way to add bias to the strategy.

- you come up with some sort of statistical analysis. - you can't just like you can't predict that it's fair for this event - risk management is usually key for these types of strategies, usually in form of diversity and bet sizing

I think we are talking about different things. In vol space you see a lot of overfitting via introducing spurious parameters (sales desk "strategies" are notorious for that). The worst one I've seen was introduction of a 4-parameter Kalman filter into a vol selling strategy that would have had 4...

Selling risk premium is a good trade when risk premium is rich (it could be skew, vol, roll down, carry - anything). If you make that analysis as a part of your strategy you're doing the right thing.

Depends for what type of analysis. I use robust regression a lot, a fair bit of simple co-integration analysis using regular tool, some noise reduction techniques. No ML or anything fancy.