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John Hull

"Briefly speaking, our conclusion is that stochastic volatility does not make a huge difference as far as the pricing is concerned if you get the average volatility right. It makes a big difference as far as hedging is concerned."

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"Briefly speaking, our conclusion is that stochastic volatility does not make a huge difference as far as the pricing is concerned if you get the average volatility right. It makes a big difference as far as hedging is concerned."

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Explore more quotes by John Hull

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John Hull
"Alan White and I spent the next two or three years working together on this. We developed what is known a stochastic volatility model. This is a model where the volatility as well as the underlying asset price moves around in an unpredictable way."
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John Hull
"There are challenges in terms of the measurement of VAR for what are known as nonlinear derivatives, where things like gamma and vega are important dimensions of the risk."
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John Hull
"Our tree is actually a tree of the short-term interest rate. The average direction in which the short-term interest rate moves depends on the level of the rate. When the rate is very high, that direction is downward; when the rate is very low, it is upward."
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John Hull
"I guess any simple idea that is really good will catch on quickly."
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John Hull
"I think VAR is a very healthy development within the industry."
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John Hull
"Our research led on to other things, such as the fact that exchange rates are not lognormally distributed."
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John Hull
"We started giving presentations at practitioner conferences in 1986, and since then all of our derivatives research has been stimulated by contact with practitioners."
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John Hull
"Our starting point then was trying to find a way to incorporate mean reversion into the HoLee model."
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John Hull
"If each of your time steps is one week long, you are not modeling the stock price terribly well over a one-week time period, because you are saying that there are only two possible outcomes."
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John Hull
"One important measurement issue concerns the fat tails problem that I mentioned earlier. VAR is concerned with extreme outcomes. If the tails of the probability distributions we are using are too thin, our VAR measures are likely to be too low."
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