A more evolved model will include some type of Jump metric in it. Stock prices tend to move around earnings announcement or other event outcomes.
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Volatility Model
- Thread starter Mike805
- Start date
opt789
"...conditionally biased" in what way I wonder ?
If this were true then it would imply an edge.
"...conditionally biased" in what way I wonder ?
If this were true then it would imply an edge.
Two more quote from papers on the topic:Quote from Profitaker:
opt789
"...conditionally biased" in what way I wonder ?
If this were true then it would imply an edge.
"The weight of the evidence indicates that implied volatility is not an efficient predictor of intraday volatility but might be an efficient predictor of the volatility of daily futures prices."
"Research has consistently found that Black-Scholes implied volatility (IV) is a conditionally biasedâoverly volatileâpredictor of realized volatility across asset markets. A given change in IV is associated with a larger change in the RV."
Changes in implied vol do give you information about future realized vol but for them to consistently make you money they have to be an unbiased and efficient predictor, which the research has shown they are not. If market makers run out of room to sell then they raise implied vol. It is as simple as order flow imbalance. This change in the implied may or may not lead to a future corresponding change in the underlying on which you can capitalize.
Quote from opt789:
I am sure I am not up to your mathematical background, but I will give you some thoughts. They are only opinions so feel free to ignore them. PHD mathematicians have access to tremendous funds and computing power at the major firms and none of them have ever consistently been able to predict volatility. How do you value an option if a stock can gap up 7 SDs on a takeover, or gap down on a sudden accounting scandal? Did you notice the last SET value in the SPX? The most widely followed index in the world gapped up 15 points at expiration, the April 1480 Calls went out at .50 and settled the next morning at 5.57. Were those correctly priced by the mathematics of the pricing model? Did statistical analysis of historical or implied vol predict it?
My only point is warning you of analysis overload. You can use all the math and statistics you want, but you are still trying to predict future unexpected occurrences based on historical information. How do you predict something that has never happed? The analysis is useful, but trading on it profitably is another story. The best option market makers I worked with were great traders; they did not accomplish it with "decent mathematical models."
Your opinions have merit, however, you imply that certain ârandomâ factors cannot be quantified. In your example you mention accounting scandals and takeover bids. While these events are non-deterministic in nature, general trader sentiment can be modeled by price volume analysis. There do exist neural network models that attempt to forecast M/A activity and bad news via irregular price/volume identification and general trader sentiment. The inner workings of these types of models and their profitability are unknown to my self, likely because if one had such a strategy working, very few would actually hear about it.
I agree with your point about analysis overload, however, you ignore the conditional variance as a useful tool in assessing future risk. Suppose you knew that there was a 10% chance that tomorrowâs volatility would be 5x higher than yesterday with a 80% certainty? This is a conditional variance or likelihood based on historical events that does provide useful information IMO.
Quote from opt789:
Changes in implied vol do give you information about future realized vol but for them to consistently make you money they have to be an unbiased and efficient predictor, which the research has shown they are not. If market makers run out of room to sell then they raise implied vol. It is as simple as order flow imbalance. This change in the implied may or may not lead to a future corresponding change in the underlying on which you can capitalize.
This is a great point and gets to the heart of the issue. IV is directly based on the current market price, hence the current IV cannot provide statistically viable information other than what the *price* of the underlying asset already provides.
GARCH is a historical function fit of realized vola, but, the model does not provide a "confidence measure" of it's output - a future risk prediction.
It is my belief that a model with a "confidence measure" of its output is a better way to go.
Any thoughts?
Mike