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The Special Data Dissemination Standard Plus (SDDS Plus) was established in October 2012 to reinforce and supplement the Fund's Data Standards Initiatives and assist Fund members who decide to adhere to the SDDS Plus with regard to the publication of comprehensive, timely, accessible, and reliable economic and financial statistical data in a world of continuing economic and financial integration. The SDDS Plus also requires adherents to disseminate metadata to promote public knowledge and understanding of their compilation practices with respect to the required data categories. During the Ninth Review of the Fund's data Standards Initiatives in May 2015 executive directors supported changing the transition period to meet all SDDS Plus requirements to five years after the adherence date. On July 1, 2015, the Executive Board approved the proposed change. The existing rules governing the SDDS Plus are superseded by the new SDDS Plus legal text.

Bank assets.

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It is widely acknowledged that many financial markets exhibit a considerably greater degree of kurtosis (and sometimes also skewness) than is consistent with the Geometric Brownian Motion model of Black and Scholes (1973). Among the many alternative models that have been proposed in this context, two have become especially popular in recent years: models of jump-diffusions, and models of stochastic volatility. This paper explores the statistical properties of these models with a view to identifying simple criteria for judging the consistency of either model with data from a given market; our specific focus is on the patterns of skewness and kurtosis that arise in each case as the length of the interval of observations changes. We find that, regardless of the precise parameterization employed, these patterns are strikingly similar within each class of models, enabling a simple consistency test along the desired lines. As an added bonus, we find that for most parameterizations, the set of possible patterns differs sharply across the two models, so that data from a given market will typically not be consistent with both models. However, there exist exceptional parameter configurations under which skewness and kurtosis in the two models exhibit remarkably similar behavior from a qualitative standpoint. The results herein will be useful to empiricists, theorists and practitioners looking for parsimonious models of asset prices.

Bank assets.

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Asset-liability management --- Bank assets

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This book investigates the determinants of bank capital structure and procyclical behavior of leverage. A panel data analysis is developed to find out the relation between different types of leverage ratios and asset growth of banks. Furthermore, possible impacts of bank specific and macroeconomic variables on the bank capital structure are discussed. The book concludes that the leverage of Turkish banks is procyclical, which is the outcome of a positive relation between asset growth and leverage. The procyclical leverage could contribute to higher instability in the financial sector and the overall economy. Therefore, further regulations are assumed to be necessary. Size, profit, number of banks, inflation, exchange rate, and gross domestic product are the factors that affect Turkish banks' capital structure.

Bank capital --- Bank assets --- Business cycles

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Government securities --- Bank assets --- Liquid assets --- Law and legislation