Computation of equation \ref{eq:loglikelihoodEHOconcrete} often fails
even for infrequently traded stocks.
For historical data which has its origin decades ago and therefore the number of daily buys and sells is very small,
these formulations of likelihood functions probably return
reasonable results (i.e. finite and non-NaN
).
However, for any recent data with number of daily buys and sells often higher than 1000 transactions,
more stable implementations are essential to achieve finite function values.
The $\pintext$ literature provides two widely used likelihood factorization which try to minimize the over- and underflow errors.
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