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Listen to Coronavirus Patient Zero

Embracing America On A Hog And A Hack Without Reservations

RRP $16.30

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If adventure came knocking, would you have the courage to open the door? That was the question Susie had to answer. She was very comfortably established in her hometown routine, semiretired and serene. So it was with some misgivings that she agreed to take a tour around the perimeter of the United States with her husband, Bob. The conveyance? His new dream machine, a Harley-Davidson motorcycle with a sidecar added just for her. With no former riding experience and no little anxiety, she goes along for the ride. She learns a bit about the country, its people, and some very important things about herself. Come along for a virtual ride! But don't get too comfortable, because one day, it might be your door that adventure finds.


A Nonlinear Time Series Workshop

RRP $656.99

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The analysis ofwhat might be called "dynamic nonlinearity" in time series has its roots in the pioneering work ofBrillinger (1965) - who first pointed out how the bispectrum and higher order polyspectra could, in principle, be used to test for nonlinear serial dependence - and in Subba Rao and Gabr (1980) and Hinich (1982) who each showed how Brillinger's insight could be translated into a statistical test. Hinich's test, because ittakes advantage ofthe large sample statisticalpropertiesofthe bispectral estimates became the first usable statistical test for nonlinear serial dependence. We are forever grateful to Mel Hinich for getting us involved at that time in this fascinating and fruitful endeavor. With help from Mel (sometimes as amentor,sometimes as acollaborator) we developed and applied this bispectral test in the ensuing period. The first application ofthe test was to daily stock returns {Hinich and Patterson (1982, 1985)} yielding the important discovery of substantial nonlinear serial dependence in returns, over and above the weak linear serial dependence that had been previously observed. The original manuscript met with resistance from finance journals, no doubt because finance academics were reluctant to recognize the importance of distinguishing between serial correlation and nonlinear serial dependence. In Ashley, Patterson and Hinich (1986) we examined the power and sizeofthe test in finite samples.



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