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Financial stress index: a lens for supervising the financial system

Bianco, Timothy; Gramlich, Dieter; Oet, Mikhail V.; … - Federal Reserve Bank of Cleveland - 2012

This paper develops a new financial stress measure (Cleveland Financial Stress Index, CFSI) that considers the supervisory objective of identifying risks to the stability of the financial system. The index provides a continuous signal of financial stress and broad coverage of the areas that...

Persistent link: https://www.econbiz.de/10011133759

Advances in forecast evaluation

Clark, Todd; McCracken, Michael W. - Federal Reserve Bank of Cleveland - 2011

This paper surveys recent developments in the evaluation of point forecasts. Taking West’s (2006) survey as a starting point, we briefly cover the state of the literature as of the time of West’s writing. We then focus on recent developments, including advancements in the evaluation of...

Persistent link: https://www.econbiz.de/10009321127

Forecasting and seasonal adjustment

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1985

An examination of whether one should seasonally adjust data before developing multivariate time series models to provide forecasts.

Persistent link: https://www.econbiz.de/10005526635

Forecasting GNP using monthly M1

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1985

A presentation of multivariate time series forecasting in which the data consist of a mixture of quarterly and monthly …

Persistent link: https://www.econbiz.de/10005428190

Comparison of univariate ARIMA, multivariate ARIMA and vector autoregression forecasting

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1986

A comparison of the forecasting abilities of univariate ARIMA, multivariate ARIMA, and VAR, and examination of whether … series should be differenced before estimating models for forecasting purposes. …

Persistent link: https://www.econbiz.de/10005428407

Estimating multivariate ARIMA models: when is close not good enough?

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1987

The purpose of this study is to examine the forecasting abilities of the same multivariate autoregressive model …. The second method is an approximation method as implemented in the MTS system by Automatic Forecasting Systems, Inc. ; The … percent. Using the SCA parameters for forecasting provided smaller mean absolute error (MAE) for 35 of the 40 values, with the …

Persistent link: https://www.econbiz.de/10005729088

Forecasting the money supply in time series models

Bagshaw, Michael L.; Gavin, William T. - Federal Reserve Bank of Cleveland - 1983

A demonstration of time series techniques used to forecast quarterly money supply levels. The results indicate that a bivariate model, including an interest rate and M1 predicts M1 better than the univariate model using M1 only, and as well as a 5-variable model which adds prices, output, and...

Persistent link: https://www.econbiz.de/10005526595

Extension of Granger causality in multivariate time series models

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1983

This paper proposes an extension of Granger causality when more than two variables are used in a multivariate time series model, and it is necessary to consider more than one-period-ahead forecasts.

Persistent link: https://www.econbiz.de/10005526600

Forecasting using contemporaneous correlations

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1984

In this paper, we present a forecasting technique that uses contemporaneous correlations for forecasting in a time … accurate forecasts than the standard time series forecasting method, which does not use contemporaneous data. This procedure is … illustrated with an example of forecasting the gross national product (GNP), given current N-i in a trivariate autoregressive …

Persistent link: https://www.econbiz.de/10005526605

Univariate and multivariate ARIMA versus vector autoregression forecasting

Bagshaw, Michael L. - Federal Reserve Bank of Cleveland - 1987

The purposes of this study are two: 1) to compare the forecasting abilities of the three methods: univariate …

Persistent link: https://www.econbiz.de/10005526611