Non-stationary multifractality in stock returns

A Simple Non-Stationary Model for Stock Returns

Non-stationarities in Stock Returns

Modeling nancial returns on longer time intervals under the assumption of station-arity is, at least intuitively, given the pace of change in world's economy, a choice hard to defend. Relinquishing the global stationarity hypothesis, this paper conducts a data analysis focused on the size of the returns, i.e. the absolute values of returns, under the assumptions that, at least locally, the S&P ...

Multifractality in stock indexes: Fact or fiction?

Multifractal analysis and extensive statistical tests are performed upon intraday minutely data within individual trading days for four stock market indexes (including HSI, SZSC, S&P500, and NASDAQ) to check whether the indexes (instead of the returns) possess multifractality. We find that the mass exponent τ(q) is linear and the singularity α(q) is close to 1 for all trading days and all index...

Model for non-Gaussian intraday stock returns.

Stock prices are known to exhibit non-Gaussian dynamics, and there is much interest in understanding the origin of this behavior. Here, we present a model that explains the shape and scaling of the distribution of intraday stock price fluctuations (called intraday returns) and verify the model using a large database for several stocks traded on the London Stock Exchange. We provide evidence tha...

Chaotic Test and Non-Linearity of Abnormal Stock Returns: Selecting an Optimal Chaos Model in Explaining Abnormal Stock Returns around the Release Date of Annual Financial Statements

For many investors, it is important to predict the future trend of abnormal stock returns. Thus, in this research, the abnormal stock returns of the listed companies in Tehran Stock Exchange were tested since 2008- 2017 using three hypotheses. The first and second hypotheses examined the non-linearity and non-randomness of the abnormal stock returns ′ trend around the release date of annual fin...