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银行的金融数据分析外文翻译(适用于毕业论文外文翻译+中英文对照).doc

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Banks analysis of financial data Andreas P. Nawroth, Joachim Peinke Institut fu¨ r Physik, Carl-von-Ossietzky Universita¨ t Oldenburg, D-26111 Oldenburg, Germany Available online 30 March 2007 Abstract A stochastic analysis of financial data is presented. In particular we investigate how the statistics of log returns change with different time delays t. The scale-dependent behaviour of financial data can be divided into two regions. The first time range, the small-timescale region (in the range of seconds) seems to be characterised by universal features. The second time range, the medium-timescale range from several minutes upwards can be characterised by a cascade process, which is given by a stochastic Markov process in the scale τ. A corresponding Fokker–Planck equation can be extracted from given data and provides a non-equilibrium thermodynamical description of the complexity of financial data. Keywords: Banks; Financial markets; Stochastic processes; Fokker–Planck equation 1.Introduction Financial statements for banks present a different analytical problem than manufacturing and service companies. As a result, analysis of a bank’s financial statements requires a distinct approach that recognizes a bank’s somewhat unique risks. Banks take deposits from savers, paying interest on some of these accounts. They pass these funds on to borrowers, receiving interest on the loans. Their profits are derived from the spread between the rate they pay for funds and the rate they receive from borrowers. This ability to pool deposits from many sources that can be lent to many different borrowers creates the flow of funds inherent in the banking system. By managing this flow of funds, banks generate profits, acting as the intermediary of interest paid and interest received and taking on the risks of offering credit. 2. Small-scale analysis Banking is a highly leveraged business requiring regulators to dictate minimal capital levels to help ensure the solvenc
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