【正文】 and taking on the risks of offering credit. 2. Smallscale analysis Banking is a highly leveraged business requiring regulators to dictate minimal capital levels to help ensure the solvency of each bank and the banking system. In the US, a bank’s primary regulator could be the Federal Reserve Board, the Office of the Comptroller of the Currency, the Office of Thrift Supervision or any one of 50 state regulatory bodies, depending on the charter of the bank. Within the Federal Reserve Board, there are 12 districts with 12 different regulatory staffing groups. These regulators focus on pliance with certain requirements, restrictions and guidelines, aiming to uphold the soundness and integrity of the banking system. As one of the most highly regulated banking industries in the world, investors have some level of assurance in the soundness of the banking system. As a result, investors can focus most of their efforts on how a bank will perform in different economic environments. Below is a sample ine statement and balance sheet for a large bank. The first thing to notice is that the line items in the statements are not the same as your typical manufacturing or service firm. Instead, there are entries that represent interest earned or expensed as well as deposits and loans. 3 As financial intermediaries, banks assume two primary types of risk as they manage the flow of money through their business. Interest rate risk is the management of the spread between interest paid on deposits and received on loans over time. Credit risk is the likelihood that a borrower will default on its loan or lease, causing the bank to lose any potential interest earned as well as the principal that was loaned to the borrower. As investors, these are the primary elements that need to be understood when analyzing a bank’s financial statement. 3. Medium scale analysis The primary business of a bank is managing the spread between deposits. Basically when the interest that a bank earns from loans is greater than the interest it must pay on deposits, it generates a positive interest spread or interest ine. The size of this spread is a major determinant of the profit generated by a bank. This interest rate risk is primarily determined by the shape of the yield curve. As a result, interest ine will vary, due to differences in the timing of accrual changes and changing rate and yield curve relationships. Changes in the general level of market interest rates also may cause changes in the volume and mix of a bank’s balance sheet products. For example, when economic activity continues to expand while interest rates are rising, mercial loan demand may increase while residential mortgage loan growth and prepayments slow. Banks, in the normal course of business, assume financial risk by making loans at interest rates that differ from rates paid on deposits. Deposits often have shorter maturities than loans. The result is a balance sheet mismatch between assets (loans) and liabilities (deposits). An upward sloping yield curve is favorable to a bank as the bulk of its deposits are short term and their loans are longer term. This mismatch of maturities generates the interest 4 revenue banks enjoy. When the yield curve flattens, this mismatch causes interest revenue to diminish. in a business using Six Sigma174。P Industrial index plete some form of a cash flow assessment. but did not present insights regarding accounts receivable and inventory management. or the variations of any current asset accounts or liability accounts across industries. Thus. mixed evidence exists concerning the use of working capital management techniques. Theoretical determination of optimal trade credit limits are the subject of many articles over the years (.. Schwartz 1974。 Gas Utility industry. which ranked second in CCE and fourth in DWC. The two industries with the worst working capital rankings were Textiles and Apparel. Textiles rank twentysecond in CCE and twentysixth in DWC. The apparel industry ranks twentythird and twentyfourth in the two working capital measures 9. Results for Bayer data The Kramers–Moyal coefficients were calculated according to Eqs. (5) and (6). The timescale was divided into halfopen intervals assuming that the Kramers–Moyal coefficients are constant with respect to the timescaleτin each of these subintervals of the timescale. The smallest timescale considered was 240 s and all larger scales were chosen such that τi＝ *τi+1. The Kramers–Moyal coefficients themselves were parameterised in the following form: This r