Sentence examples for volatility over time from inspiring English sources

The bridge layer lies in between both extremes, and is characterized by a high volatility over time.

Assessing market integration by comparing two markets for the price instability coefficient is therefore about appraising the dynamics of spatial volatility over time.

During late 2015 and early 2016, prices of nearly all items increased again and again, and exchange rates varied widely, with both variations by location and high levels of volatility over time (CBR-TWG 2016).

While the business cycle would be expected to exert an important influence on state tax revenues, the exceptionally large decline in revenues in the Great Recession, as well as in the 2001 recession, suggests that recession-related volatility may have increased over time.

The parameter \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }$\vartheta $\end{document} is a measure of meta-volatility (volatility of volatility) that determines the variability of the log-volatility over time.

He wrote, "I remember a very different Dale Cox, a person of unquestioned integrity, whose demeanor was always very professional and courteous," adding, "Of course, he may have, by always masking his true volatility, become over time so tightly wound that an explosion was inevitable".

The volatility switches over time subject to a continuous-time Markov chain.

This framework relaxes constancy assumption of classical linear regression (CLRM) model and allows exchange rate volatility and interest rate volatility to evolve over time.

It defines different volatility concepts; the notional volatility corresponding to the sample-path return variability over a fixed time interval; the expected volatility over a fixed time interval; and the instantaneous volatility corresponding to the strength of the volatility process at a point in time.

This is the right result, in theory: emerging markets are riskier (in the sense of being more volatile) and so investors should demand a higher return.The good news is that volatility has declined over time, both in absolute terms and relative to developed markets.

This framework relaxes constancy assumption of classical linear regression (CLRM) model and allows exchange rate and interest rate volatility to evolve over time.