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Natural sciences have some consensus regarding what constitutes the basic object of study: for example in anomalous diffusions and other areas where fractional calculus has emerged since 1974 into a technology with an encyclopedic treatise by Samko, Kilbas and Marichev and exposition and research by many others see Machado-Kiryakova-Mainardi for a historical review.  Excellent and brilliant scholars such as Andrew Lo, John Campbell, and Craig Mackinlay have worked on univariate statistical time series models for financial time series.  Univariate models of different types for volatility time series (the so-called stochastic volatility is simply $\log(r_t^2)$ where $r_t = log(p_t/p_{t-1})$ from empirical prices $p_t$.  Univariate models can achieve match to stylized features of these series and therefore are useful but they exist in a vacuum which is deceptive.  This vacuum is due to a missing consensus among scientists of finance regarding the fundamental observable of finance and its actual determinants.
Against in-vacuum econometric models is the following result that is not difficult to verify.  Take 1900 historical daily series for American stocks and construct a 1900*1900 correlation matrix and consider the off-diagonal elements $C_{ij}$, let $\sigma$ be the standard deviation of these values and consider the matrix consisting of soft-thresholding the correlation matrix lower triangular values by $3\sigma$.   How many of the correlations should survive intuitively?  Well one might expect no more than 45% of the values to survive the soft-threshold but in fact more than 75% survive.  This tells us that for 1900 stocks the graph with 1900 nodes with edges determined by high volatility correlation is  quite dense.  The density of this graph suggests the error of considering econometric models of univariate time series from finance, for it is impossible to understand the volatility as a proper object of scientific study without the extremely high correlation with the rest of the market defined purely ‘intrinsically’ in terms of volatility correlation with other instruments traded.  In particular, pure scientific interest in the phenomena that drives global financial volatility, often considered from Laplace’s Essay on Probabilities on as determined by fear and exhuberance, the lingo used by Alan Greenspan and refined since by many people including Shiller and Ackerloff in Animal Spirits.