927 resultados para return autocorrelation
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Letter (1 page, typed) to S.D. Woodruff to please return coupons signed by the Jarvis-Conklin Mortgage Trust Co., Nov. 30, 1889.
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Unsigned letter to John Williams stating that before the return of the final estimate, the arch of the bridge must be completed, Sept. 19, 1857
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Note showing the return of time for the preliminary survey of the Port Robinson and Thorold macadamized road for March and April, 1855.
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General return (copy) showing the quantity of each article transported on the Welland Canal during the year ending January 5th 1857 (Port Robinson) (2 pages), 1857.
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General return showing the quantity of each article transported on the Welland Canal during the year ending 1857 and the amount of tolls collected thereon (Port of Maitland) (2 page, printed blank), 1857.
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General return showing the quantity of each article transported on the Welland Canal during the year ending December 31st, 1858 and the amount of tolls collected thereon (Port of Maitland). This is signed by William Turner, collector (2 page, printed blank), 1858.
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General return showing the quantity of each article transported on the Welland Canal during the year ending on the 31st of December 1858 and the tolls collected thereon (office at Port Robinson) (2 pages), 1858.
General return showing the quantity of each article transported on the Welland Canal (Port Robinson)
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General return showing the quantity of each article transported on the Welland Canal (Port Robinson) during the year ending on the 31st of December 1860 and the amount of tolls collected thereon, 1860.
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General return showing the quantity of each article transported on the Welland Canal during the year ending the 31st of December 1860 and the amount of tolls collected thereon. This document was mouldy (now inactive). This does not affect the text. It is signed by William Turner, collector (office at Port Maitland), 1860.
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General return showing the quantity of each article transported on the Welland Canal during the year ending the 31st of December 1861 (office at Port Maitland) (2 pages), 1861.
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General return (copy) showing the quantity of each article transported on the Welland Canal during the year ending the 31st of December 1861 and the amount of tolls collected thereon (office at Port Robinson), 1861.
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Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This makes this framework applicable to linear models with expectation variables that are estimated non-parametrically. Two examples of such models are the risk-return trade-off in finance and the impact of inflation uncertainty on real economic activity. Results show that inference based on Lagrange Multiplier (LM) tests is more robust to weak instruments than Wald-based inference. Using LM confidence intervals leads us to conclude that no statistically significant risk premium is present in returns on the S&P 500 index, excess holding yields between 6-month and 3-month Treasury bills, or in yen-dollar spot returns.
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Full Text / Article complet
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This paper presents gamma stochastic volatility models and investigates its distributional and time series properties. The parameter estimators obtained by the method of moments are shown analytically to be consistent and asymptotically normal. The simulation results indicate that the estimators behave well. The insample analysis shows that return models with gamma autoregressive stochastic volatility processes capture the leptokurtic nature of return distributions and the slowly decaying autocorrelation functions of squared stock index returns for the USA and UK. In comparison with GARCH and EGARCH models, the gamma autoregressive model picks up the persistence in volatility for the US and UK index returns but not the volatility persistence for the Canadian and Japanese index returns. The out-of-sample analysis indicates that the gamma autoregressive model has a superior volatility forecasting performance compared to GARCH and EGARCH models.