Abstract ABSTRACT: For many quarterly time series of corporate earnings per share, the data indicate the desirability of incorporating a power transformation into the time series model. Our empirical results suggest that, for such series, this will generally lead to forecasts of improved quality. The resulting forecasts compare more favorably with those of financial analysts than do forecasts derived from models without the transformation parameter.

W. S. Hopwood, J. C. Mckeown, P. Newbold, The Additional Information Content of Quarterly Earnings Reports: Intertemporal Disaggregation, Journal of Accounting Research, Vol. 20, No. 2, Part I (Autumn, 1982), pp. 343-349

Extensive regulatory changes and technological advances have transformed banking systems to a great extent. Banks have reacted to the challenges posed by the new operating environment by creating new products and expanding their activities to some uncharted business areas. In this paper, we study how modern banking which gave birth to the off-balance-sheet leverage activities affected the risk profile of U.S. banks as well as the level of systemic risk before and after the onset of the late 2000s financial crisis. Towards this, we separate on- from off-balance-sheet leverage and capture the latter with different, yet complementary, measures which do not exist in the current literature. Special attention is paid on the deleveraging process that occurred in the banking market after the crisis erupted, which is an additional innovative feature of this study. Our findings reveal that leverage, both explicit and hidden off-the-balance-sheet, increases the individual risk of banking firms making them vulnerable to financial shocks. Reverse leverage, on the other hand, is beneficial for individual banks’ health, but is found to be harmful for financial stability. We also demonstrate that the banks which concentrate on traditional lines of business typically carry less risk compared to those involved with modern financial instruments.

ABSTRACT In this paper, we implement a methodology to identify and measure premia in the pricing of forward foreign exchange that involves application of signal‐extraction techniques from the engineering literature. Diagnostic tests indicate that these methods are quite successful in capturing the essence of the time‐series properties of premium terms. The estimated premium models indicate that premia show a certain degree of persistance over time and that more than half the variance in the forecast error that results from the use of current forward rates as predictors of future spot rates is accounted for by variation in premium terms. The methodology can be applied straightforwardly to the measurement of unobservables in other financial markets.