why does high sensitivity to asynchronism result in lower correlation estimates?
I remember it as, asynchronism means not synchronized if you are highly not synchronized then you will have a low correlation.
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asynchronus data is created by taking a little data and them making it “longer” by filling in holes w/ values close to the hole you’re filling in (e.g. missing january price, so you use december price again). this results in low volatility = low correlation.
so if i understand it correctly if you have a monthly sequnce of market prices and make then daily, your daily vol and corr will be lower then if the market data would be available daily
i think it’s in the context of only having monthly data for X, but daily data for Y…then you create daily data for X to match up w/ Y…now it’s asychronous w/ low vol/corr.
prockets Wrote: ------------------------------------------------------- > i think it’s in the context of only having monthly > data for X, but daily data for Y…then you create > daily data for X to match up w/ Y…now it’s > asychronous w/ low vol/corr. rgr that