Working paper series / Johann-Wolfgang-Goethe-Universität Frankfurt am Main, Fachbereich Wirtschaftswissenschaften : Finance & Accounting
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95
Recent changes in accounting regulation for financial instruments (SFAS 133, IAS 39) have been heavily criticized by representatives from the banking industry. They argue for retaining a historical cost based "mixed model" where accounting for financial instruments depends on their designation to either trading or nontrading activities. In order to demonstrate the impact of different accounting models for financial instruments on the financial statements of banks, we develop a bank simulation model capturing the essential characteristics of a modern universal bank with investment banking and commercial banking activities. In our simulations we look at different scenarios with periods of increasing/decreasing interest rates using historical data and with different banking strategies (fully hedged; partially hedged). The financial statements of our model bank are prepared under different accounting rules ("Old" IAS before implementation of IAS 39; current IAS) with and without hedge accounting as offered by the respective sets of rules. The paper identifies critical issues of applying the different accounting rules for financial instruments to the activities of a universal bank. It demonstrates important shortcomings of the "Old" IAS rules (before IAS 39), and of the current IAS rules. Under the current IAS rules the results of a fully hedged bank may have to show volatility in income statements due to changes in market interest rates. Accounting results of a partially hedged bank in the same scenario may be less affected even though there are economic gains or losses.
57
We present an empirical study focusing on the estimation of a fundamental multi-factor model for a universe of European stocks. Following the approach of the BARRA model, we have adopted a cross-sectional methodology. The proportion of explained variance ranges from 7.3% to 66.3% in the weekly regressions with a mean of 32.9%. For the individual factors we give the percentage of the weeks when they yielded statistically significant influence on stock returns. The best explanatory power – apart from the dominant country factors – was found among the statistical constructs „success“ and „variability in markets“.