By Myron Scholes and Joseph Williams; Estimating betas from nonsynchronous data. Scholes, Myron & Williams, Joseph, “Estimating betas from nonsynchronous data,” Journal of Financial Economics, Elsevier, vol. 5(3), pages Scholes, M. and Williams, J. () Estimating Betas from Nonsynchronous Data. Journal of Financial Economics, 5,
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Estimating betas from nonsynchronous data
Right now, I am blindly guessing it through fom following steps: Estimating betas from nonsynchronous data. How do you estimate the volatility of a sample when points are irregularly spaced? How to interpolate gaps in a time series using closely related time series? First, what you ought to be regressing are returns, not prices.
Second, by interpolating you’re underestimating the variance of the asset price in the interval between index price observations. Through your choice of interpolation method, you’re essentially picking an arbitrary price in the middle.
Estimating betas from nonsynchronous data – EconBiz
What you ought to be doing is maximum likelihood estimation MLE. You’ll have to assume a parameterized family of joint stochastic processes and estimate the parameters given the price observations. Whenever you don’t have synchronous data, you’ll have a probability distribution for the missing price conditional on all other data points in its future and in its past.
There are a lot of different options that might be better in some cases than others. Also, how much effort you put in might depend on what you’re trying to do and what your boss wants.
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This sounds like the same problem faced when doing model fitting on tick and order book data nonsyncrhonous do you have any handy references to the conversion from simple regression to using proper MLE when transitioning to asynchronous event data? Sign up or log in Sign up using Google.
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