Evidence of Nonlinearity in Daily Stock Returns

By M. Hinich, Douglas M. Patterson. 1985

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Lin Chen
2. K. Lim
3. Zhilin Qiao
4. Stanislav Volgushev
5. R. Brooks
6. Ruijin Du
7. Chao Wang
8. Minggang Wang

Citations in the corpus

• Which Artificial Intelligence Algorithm Better Predicts the Chinese Stock Market? (2018, background): “…[4]–[9], such as autoregressive integrated moving average (ARIMA) models, artificial neural networks, support vector machine, and neuro-fuzzy based systems, but because of the nonlinear characteristics of stock market behavior, financial economists continue to debate these methodologies [10]–[13].”
• Of Copulas, Quantiles, Ranks and Spectra - An L1-Approach to Spectral Analysis (2011, background): “[1992], Hinich and Patterson [1990, 1985], Hsieh [1989], Vaidyanathan and Krehbiel [1992]).”
• The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature (2011, background): “Hinich and Patterson (1985) blame Jenkins and Watts (1968) and Box and Jenkins (1970) for blurring the definitions of whiteness and independence.”
• Episodic nonlinearity in Latin American stock market indices (2006, background): “Developed capital market like the US (Hinich and Patterson, 1985; Scheinkman and LeBaron, 1989; Hsieh, 1991); the UK (Abhyankar et al, 1995; Opong et al, 1999) and Germany (Kosfeld and Robé, 2001) among others have been studied.”