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The Black-Scholes formula, explained (2019)

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Re: The Black-Scholes formula, explained (2019)

#41
post #31

Earlier quoted context omitted.

Paywalling gender change information seems weird indeed. Edit: docked for bad sense of humor (mine or of downvoters - of that I am not sure)

Explain the joke plz

the joke is the basis for the SNL skit of 'celebrity jeopardy' portraying Sean Connery.

Re: The Black-Scholes formula, explained (2019)

#42
post #19

Earlier quoted context omitted.

Buy-side firms don’t use BS with the same assumptions as market makers. If you’re a fund manager, you are interested in objective estimates of the value. If you’re a market maker you want to show that you can perfectly replicate and thusly hedge your derivatives. Never mind that you have to recalibrate your model every 20 minutes. For a model that is supposed to measure the objective value of an asset, that’s clear f…

> Never mind that you have to recalibrate your model every 20 minutes Let me know when we make a plane or rocket that doesn’t need to recalibrate it’s flight model every millisecond. As I said, market neutral market makers will use different assumptions from directional buy side shops. To say nothing of their vastly different funding costs and structures. Using input heterogeneity or calibration frequency as an estim…

We never recalibrate the g constant in our calculations nor we wait a person to announce what the g for this quarter will be.

Re: The Black-Scholes formula, explained (2019)

#43

Earlier quoted context omitted.

> Never mind that you have to recalibrate your model every 20 minutes Let me know when we make a plane or rocket that doesn’t need to recalibrate it’s flight model every millisecond. As I said, market neutral market makers will use different assumptions from directional buy side shops. To say nothing of their vastly different funding costs and structures. Using input heterogeneity or calibration frequency as an estim…

We never recalibrate the g constant in our calculations nor we wait a person to announce what the g for this quarter will be.

> We never recalibrate the g constant in our calculations nor we wait a person to announce what the g for this quarter will be

Sure. But we do update all manner of atmospheric, gravitometric and similar factors in our flight and orbital models. Once again, calibration frequency is a poor predictor of model quality. There are useless models in every domain involving immutable constants. And there are very good numerical methods that have no constants per se.

Re: The Black-Scholes formula, explained (2019)

#44

Former options trader here. This all checks out correctly, but there's maybe some intuition that enlightens it. BTW option traders are often called volatility traders, because when you look at the formula there's this one free variable (all the rest are somehow given by the market). So when you're trading options, you're trading vol and the actual price is just a sort of formality. Thoughts: - Since you have a right…

All good points. All I would add is that it costs money to flatten the delta every day, or delta hedging your option. Each time the stock changes direction, you pay the bid-ask spread. The number of times this happens is proportional in some way to the volatility—that free variable you mentioned—so you can speculate that the market's number is too high or low.

If the market is too high on volatility: sell the option and you'll end up paying less in delta-hedging costs.

If that market is too low on volatility: do the opposite.

Re: The Black-Scholes formula, explained (2019)

#45

The article is dated and somewhat misleading, > Since its introduction in 1973 and refinement in the 1970s and 80s, the model has become the de-facto standard for estimating the price of stock options The only contemporary use for BS by professionals is as a convention for quoting volatility. As a pricing model it does not account for key effects such as the permanent "volatility smile" appearing in the aftermath of…

It's still useful in options with very long maturities. Then the law of large numbers becomes important, and the vol smile flattens out over decades. These aren't listed, but are occasionally traded over-the-counter or embedded in some financial contracts, like executive stock options, insurance contracts, or convertible bonds.

Re: The Black-Scholes formula, explained (2019)

#46

Earlier quoted context omitted.

Options market makers, the critical mass of dynamic hedgers, don’t blow up any more I wonder if that's true in insanely volatile stocks like GME? People were buying way OTM calls on that stock. Then the stock would move 50% in one day. A market maker would have to be very good at dynamic hedging to keep up with that. Of course options market makers have one incredible thing going for them. While they have market risk…

> lot of "no bid" on many OTM strikes. So it looks like the market makers were simply stepping away Bingo. Self help [1] and circuit breakers [2] negate the unsolvable edge case: large, instantaneous price movements. [1] https://www.reuters.com/article/usa-options-cboe-idUSL2N1H40... [2] https://www.npr.org/2020/03/09/813682567/how-stock-market-ci...

All that promise that innovation like HFT among other things was fine because of the value liquidity they can provide and now they can just choose to not play if they don't want to.

Re: The Black-Scholes formula, explained (2019)

#47

Former options trader here. This all checks out correctly, but there's maybe some intuition that enlightens it. BTW option traders are often called volatility traders, because when you look at the formula there's this one free variable (all the rest are somehow given by the market). So when you're trading options, you're trading vol and the actual price is just a sort of formality. Thoughts: - Since you have a right…

> higher vol [...] makes the option worth more. > Similarly having more time to expiry makes the option worth more [...]

These two observations become unified when one observes that the two variables sigma (vol) and (T-t) (time to expiry) only ever enter the Black-Scholes formula together, as sigma^2 (T-t) (which is the variance of the log return to expiry).

(That leads to the observation that the unit of vol is 1/sqrt(time), normally a^(-1/2) [a=annum=year]).

Next, you alluded to it, but let's make explicit the way to trade implied vol: Suppose (WLOG) that you think implied vol is too low. Then you buy it (buy cheap, sell expensive...) in the market (buy buying calls and/or puts). Now you're long gamma, but short theta, and long vol in two senses: a) if the stock doesn't move, but implied vol goes up, you can turn around and sell the option back for a profit. b) you can delta hedge the option. Every day, you lose money on theta, but gain money on the movements of the stock. If it doesn't move at all, you lose the theta. If the stock moves "as expected" (=as implied by the implied vol), you'll just break even. But if the stock moves more than expected (that is, realised vol is higher than the implied you bought it at), then you make money. If the market comes around to your estimate of the future vol, you can then sell the option at a profit, or you can hold it to the end and keep delta hedging, and that will be profitable if realised vol turns out to be higher than implied.

Re: The Black-Scholes formula, explained (2019)

#48

Earlier quoted context omitted.

All of the inputs of the BS model are forecasts. All of them can be wrong, and they have been wrong countless times. It’s like saying that your linear extrapolation for the stock market mostly works, except for the times it doesn’t.

> the inputs of the BS model are forecasts In the same way a rocket flight model is forecasting the arrangement of air molecules it’s about to run into. They’re instantaneous forecasts that are dynamically updated. No long-term forecasting involved. At the end of the day, options market makers haven’t blown up since the early noughties. (LTCM got sunk by non-options bets.) They are low-margin, low-risk businesses. It…

If options pricing is largely solved, do you think exchanges could provide an API where instead of specifying the price and quantity for hundreds or thousands of options on a stock, market makers could send a much smaller message containing their latest risk and model parameters, and have the exchange run a standard model internally to generate the quotes?

Since the model to convert parameters to prices and quantities would be known in advance to all traders, the next step could be providing a feed of current parameters which traders could use to build their own view of the public book. They'd still need plenty of quotes published piecemeal as now (as not all quotes would be model-generated) but the messaging could be much more efficient, and that could lead to more options trading.

Re: The Black-Scholes formula, explained (2019)

#49

Earlier quoted context omitted.

> That they are correct most of the time? Yup. Options market makers, the critical mass of dynamic hedgers, don’t blow up any more [1]. I left the business ten years ago, and was probably among the last well-paid people to do it. There isn’t much risk anymore which means there isn’t room for ingenuity—it’s execution, mechanical. Between market circuit breakers limiting instantaneous price moves; the tremendous amount…

All of the inputs of the BS model are forecasts. All of them can be wrong, and they have been wrong countless times. It’s like saying that your linear extrapolation for the stock market mostly works, except for the times it doesn’t.

None of the inputs to the BS model are forecasts, except the volatility. What the BS model allows, then, is trading this volatility. (Just as other financial products require other inputs, and thus make them, in a sense, tradable: Cross currency swaps make the cross currency basis tradable, credit default swaps make credit risk tradable, trading index vol versus single stock vol makes correlation tradable, etc.)

Re: The Black-Scholes formula, explained (2019)

#50
post #11

Earlier quoted context omitted.

> formula depends on a normal distribution and financial returns are random but not independent...worse than useless. This is sort of like throwing out physics because Newtonian mechanics don’t account for fluid dynamics. Yes, the original theory assumed that away. And yes, the original theory is taught in undergrad. But the work has been developed far past its original, adjusting for or incorporating away those init…

Having two sets of assumptions for buy and sell side is pretty indicative of the quality of the model.

One should clarify that basically nobody tries to "predict" anything with Black Scholes, just as basically nobody "predicts" share prices by doing a discounted cash flow analysis. Yet, they each provide the conceptual framework for trading (of options and stocks, respectively) in such a way that those that have better predictive power make money, on average, at the expense of those traders that don't. With that, they make the market efficient for traders that trade for other reasons (hedging, investing, gambling, etc.).
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