A model for stock return distribution

Abstract

Abstract The Laplace mixture distribution for stock share returns is derived from conditional N(0, σ2) distribution. The conditioning variable, σ2, is assumed to be an exponentially distributed random variable. This offers a natural stochastic interpretation of the risk involved with the stock share. Maximum likelihood (ML) estimates for returns of the 20 most traded shares and the aggregate index of the Helsinki stock market in late 1980s do not reject the Laplace distribution model. The results extend to returns over longer periods than 1 day. Copyright © 2001 John Wiley & Sons, Ltd.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 77 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.