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In feedforward networks, signals ow in only one direction without feedback. Applications in forecasting, signal processing and control require explicit treatment of dynamics. Feedforward networks can accommodate dynamics by including past input and target values in an augmented set of inputs. A m uch richer dynamic representation results from also allowing(More)
This paper relates variation in stock market volatility to regime shifts in stock market returns. We apply a Markov switching model to market returns and examine the variation in volatility in different return regimes. We find that stock returns are best characterized by a model containing six regimes with significantly different volatility across the(More)
The ability to conduct hypothesis tests is among the most important statistical skills that our students can learn. Unfortunately, it is also one of the most difficult skills for them to learn. In our survey of 44 introductory business and economics statistics textbooks, we find that textbook authors differ over the better way to explain one-tailed(More)
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