Benn Eifert 🥷🏴‍☠️ Profile picture
Sep 27, 2022 25 tweets 4 min read Read on X
ok. this references the big daddy of all elementary confusions in derivatives.

Black-Scholes (and related) models, for which Nobel prizes were won: we do NOT use them as models, we use them as normalizations only, as a convenient change of variables.
what do I mean here?

A model, as I mean it, is a simplified description of truth, of how the world works. We make some assumptions and draw some logical, mathematical conclusions.

A normalization is just a different way of describing the same information.
the theory of gravity is a model; it describes how fast an apple will accelerate as it drops from a tree, perhaps simplifying away certain aspects like wind resistance and how it interacts with the shape of the apple
Black-Scholes, taken literally as a model, starts from the assumption that asset prices follow a random process called a geometric brownian motion (GBM).

the only uncertainty in a GBM is the direction of movement of the asset price over each tiny increment of time.
this is analogous to flipping a coin over and over again, and counting up the number of heads minus tails.

boring AF game. no one in Vegas will play that, even with cocktail waitresses bringing free drinks.
a GBM's movement over any period of time is drawn from the same constant probability distribution. the volatility of the asset price is known, the level of uncertainty in the world never changes over any time horizon.

real financial markets are an explosion of chaotic ambiguity.
the implication of Black-Scholes taken literally as a model is that every option, regardless of strike and maturity, trades at a price consistent with a known, constant and identical volatility level in the famous pricing equation.
all of this is obviously absurd. not in the "well, we know its not quite right, its just a model" kind of way; in a "I award you no points, and may God have mercy on your soul" kind of way.
derivatives traders obsess about volatility surfaces -- undulating patterns in option prices that map strike prices and time to maturity into a level of uncertainty about the future price of an asset
those surfaces fully describe the implied probability distribution of future asset prices, which generally look nothing like the normal distribution consistent with a GBM
so why do derivatives traders talk about implied volatility and the Black-Scholes sensitivities of options (delta- how option prices change as the underlying price moves; gamma, or how delta changes as the underlying price moves; etc)?
simple: it provides a convenient normalization of option prices into a common, comparable unit of account, regardless of the underlying price, strike, or time to maturity.
that unit of account is the annualized volatility of the underlying price; the rate of unpredictable change; the standard deviation of the probability distribution of future returns.
"hey, this stock right here has a dec23 50-delta call option trading at $3. this other one has a jun23 50-delta call trading at $0.75!" gives me little useful information.
"the first one is trading at 32% implied volatility and the second one at 16%" gives me a lot more. at a minimum i have some idea that the first one should be about twice as volatile as the second one, perhaps tending to move about 2% and 1% per day on average, respectively
(2% ~= 32% / sqrt(252), because implied volatility is an annualized number, and the standard deviation scales with the square root of time. 252 is the rough number of trading days in a year)
Black-Scholes implied volatilities are much easier to work with than raw option prices. they have comparable economic meaning to each other. they are stationary in the statistical sense (ultimately mean reverting) if compared over time for the same time to maturity
When we use Black-Scholes (or a related method, to handle American options with early exercise) to transform inconvenient prices into convenient implied volatilities, we are just applying a change of variables, not imposing model assumptions.

en.m.wikipedia.org/wiki/Change_of….
Obviously, if we compute a different implied volatility for every strike and maturity, on each day, we are not assuming constant and known volatility! We are respecting the probability distribution implied by market prices.
When we then create models of the dynamics of implied volatility surfaces, describing their shapes and patterns and how they change over time. those models impose structure (much less restrictively than Black-Scholes!) and help us explain and predict option price dynamics
When we use greeks like delta from Black-Scholes, keep in mind that we are treating the implied volatility of any option as a free parameter. **conditional on implied volatility**, the relationship between underlying price and option price holds trivially
delta is not an unconditional forecast of the change in option price for a given change in the underlying price. it is a "true by definition" relationship between spot and option price holding implied vol constant. and analogous for gamma, etc.
that is, all the interesting and meaningful work gets translated into understanding the joint behavior of underlying price and the implied volatility surface, and considering what theoretical or empirical models to apply to that problem.
in sum - we obviously do not live in a world of normal distributions and geometric brownian motion; we use Black-Scholes not as a logical model, but as a market standard for an intuitive normalization of option prices into stationary and economically relevant units.
(was at the doctor's office for an hour, this is what came of it)

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More from @bennpeifert

Dec 6, 2022
To briefly reiterate, on derivatives notional and counterparty risk.

Over the counter (OTC) derivatives are traded bilaterally between two large counterparties, under legal contracts called ISDAs.

Positions are marked daily and cash flows exchanged. No IOU's.

>>
If an insurance company has a billion dollars of notional on an interest rate swap with a bank, the value of that contract changes as interest rates change.

If the position marks $1mm in the insurance company's favor, the bank wires them $1mm.

>>
If the bank goes bankrupt, the insurance company's exposure to the bank is only however much mark-to-market PNL they earn on the swap *after* bankruptcy. Which could be positive or negative.

>>
Read 8 tweets
Dec 5, 2022
Looks like we are doing Get Excited About Gross Derivatives Notionals" today again.

Unfortunately, because of a Bank for International Settlements report. These people should know about things.

A few notes and threads linked below.
Read 7 tweets
Dec 2, 2022
OK. Follow-up story about the transformation of investment bank risk-taking after Dodd-Frank and Basel III, and the rise of toxic Alternative Risk Transfer programs in derivatives. 💥

1
Before the Great Financial Crisis of 2008, the major investment banks used to be the center of aggressive risk-taking and speculation in financial markets.

They operated as dealers and market-makers, but also as massive proprietary risk-takers.

2
The securities divisions of major banks had proprietary trading desks that operated like hedge funds, using the bank's balance sheet to place bets. Many of today's hedge fund managers had their start on a bank's prop desk (present company included).

3
Read 30 tweets
Nov 28, 2022
As promised, a story about how derivatives markets work to transform risk but inevitably tend towards speculative excess.

The context: popular Asian and European structured investment products, exotic derivatives dealers, and enigmatic corridor variance swaps.

(1/n)
First off, I talk about some of this in two episodes of Bloomberg's Odd Lots, if you want more detail they might be worth a listen (2/n)

podcasts.apple.com/us/podcast/odd…

podcasts.apple.com/us/podcast/odd…
OK. Structured products are typically sold by wealth managers and brokers to high net worth and retail clients. They are issued and risk-managed by the exotic derivatives desks ar investment banks. These products were historically much more popular in Europe and Asia.

(3/n)
Read 30 tweets
Nov 19, 2022
a theme that has come up a great deal this year is the perception that equity index tail hedges "aren't working"

important thing to keep in mind here is the robustness of a specific strategy to the path and speed of a market selloff

tail hedge or "flash crash hedge" ?
stocks experienced a slow, choppy grind down, S&P down mid twenties percent at trough, analogous to the feel of the tech bust of 2002-03 but much smaller

last few market stress periods were much faster and more explosive - March 2020 we saw S&P down 34% in three weeks
there is nothing inherent in markets that means equities only crash in a hurry. look at the historical data; long grinding bear markets are a thing

also think about why the tech bust analogy is not a coincidence
Read 13 tweets
Nov 18, 2022
right. if twitter goes down, but you have done your duty and are on my list for the live Zoom event bc you donated to JDRF or pre-ordered Dr. Watson's book, you can email me thru our website, just reference your twitter handle
qvradvisors.com
Read 5 tweets

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