02091cam a22002417 4500001000600000003000500006005001700011008004100028100002400069245014200093260006600235490004100301500001600342520112100358530006101479538007201540538003601612700002001648710004201668830007601710856003701786856002601823w1105NBER20140723111740.0140723s1983 mau||||fs|||| 000 0 eng d1 aFrankel, Jeffrey A.12aA Relationship Between Regression Tests and Volatility Tests of Market ncyh[electronic resource] /cJeffrey A. Frankel, James H. Stock. aCambridge, Mass.bNational Bureau of Economic Researchc1983.1 aNBER working paper seriesvno. w1105 aApril 1983.3 aVolatility tests are an alternative to regression tests for evaluating the joint null hypothesis of market efficiency and risk neutrality. Acomparison of the power of the two kinds of tests depends on what the alternative hypothesis is taken to be. By considering tests based on conditional volatility bounds, we show that if the alternative is that one could"beat the market" using a linear combination of known variables, then the regression tests are at least as powerful as the conditional volatility tests.If the application is to spot and forward markets, then the most powerful conditional volatility test turns out to be equivalent to the analogous regression test in terms of asymptotic power. In other applications,the volatility test will be less powerful than regression tests against our chosen alternative. However, these results are not inconsistent with the observation that volatility tests may be more powerful against other alternative hypoth-eses, such as that risk-averse investors are rationally maximizing the present discounted utility of future consumption,with a time-varying discount rate. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web.1 aStock, James H.2 aNational Bureau of Economic Research. 0aWorking Paper Series (National Bureau of Economic Research)vno. w1105.4 uhttp://www.nber.org/papers/w1105 uurn:doi:10.3386/w1105