银行的金融数据分析外文翻译.doc

Banks analysis of financial dataAndreas P. Nawroth, Joachim PeinkeInstitut fu r Physik, Carl-von-Ossietzky Universita t Oldenburg, D-26111 Oldenburg, GermanyAvailable online 30 March 2007AbstractA 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 . A corresponding FokkerPlanck 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; FokkerPlanck equation1.Introduction Financial statements for banks present a different analytical problem than manufacturing and service companies. As a result, analysis of a banks financial statements requires a distinct approach that recognizes a banks 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 solvency of each bank and the banking system. In the US, a banks 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 compliance 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 income 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. 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 banks 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 net interest income. 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, net interest income 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 banks balance sheet products. For example, when economic activity continues to expand while interest rates are rising, commercial 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 net interest revenue banks enjoy. When the yield curve flattens, this mismatch causes net interest revenue to diminish.4.Even in a business using Six Sigma methodology. an “optimal” level of working capital management needs to be identified. The table below ties together the banks balance sheet with the income statement and displays the yield generated from earning assets and interest bearing deposits. Most banks provide this type of table in their annual reports. The following table represents the same bank as in the previous examples:First of all, the balance sheet is an average balance for the line item, rather than the balance at the end of the period. Average balances provide a better analytical framework to help understand the banks financial performance. Notice that for each average balance item there is a corresponding interest-related income, or expense item, and the average yield for the time period. It also demonstrates the impact a flattening yield curve can have on a banks net interest income. The best place to start is with the net interest income line item. The bank experienced lower net interest income even though it had grown average balances. To help understand how this occurred, look at the yield achieved on total earning assets. For the current period ,it is actually higher than the prior period. Then examine the yield on the interest-bearing assets. It is substantially higher in the current period, causing higher interest-generating expenses. This discrepancy in the performance of the bank is due to the flattening of the yield curve. As the yield curve flattens, the interest rate the bank pays on shorter term deposits tends to increase faster than the rates it can earn from its loans. This causes the net interest income line to narrow, as shown above. One way banks try o overcome the impact of the flattening of the yield curve is to increase the fees they charge for services. As these fees become a larger portion of the banks income, it becomes less dependent on net interest income to drive earnings. Changes in the general level of interest rates may affect the volume of certain types of banking activities that generate fee-related income. For example, the volume of residential mortgage loan originations typically declines as interest rates rise, resulting in lower originating fees. In contrast, mortgage servicing pools often face slower prepayments when rates are rising, since borrowers are less likely to refinance. Ad a result, fee income and associated economic value arising from mortgage servicing-related businesses may increase or remain stable in periods of moderately rising interest rates.When analyzing a bank you should also consider how interest rate risk may act jointly with other risks facing the bank. For example, in a rising rate environment, loan customers may not be able to meet interest payments because of the increase in the size of the payment or reduction in earnings. The result will be a higher level of problem loans. An increase in interest rate is exposes a bank with a significant concentration in adjustable rate loans to credit risk. For a bank that is predominately funded with short-term liabilities, a rise in rates may decrease net interest income at the same time credit quality problems are on the increase.5.Related Literature The importance of working capital management is not new to the finance literature. Over twenty years ago. Largay and Stickney (1980) reported that the then-recent bankruptcy of W.T. Grant. a nationwide chain of department stores. should have been anticipated because the corporation had been running a deficit cash flow from operations for eight of the last ten years of its corporate life. As part of a study of the Fortune 500s financial management practices. Gilbert and Reichert (1995) find that accounts receivable management models are used in 59 percent of these firms to improve working capital projects. while inventory management models were used in 60 percent of the companies. More recently. Farragher. Kleiman and Sahu (1999) find that 55 percent of firms in the S&P Industrial index complete 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 (e.g. Schwartz 1974; Scherr 1996). with scant attention paid to actual accounts receivable management. Across a limited sample. Weinraub and Visscher (1998) observe a tendency of firms with low levels of current ratios to also have low levels of current liabilities. Simultaneously investigating accounts receivable and payable issues. Hill. Sartoris. and Ferguson (1984) find differences in the way payment dates are defined. Payees define the date of payment as the date payment is received. while payors view payment as the postmark date. Additional WCM insight across firms. industries. and time can add to this body of research. Maness and Zietlow (2002. 51. 496) presents two models of value creation that incorporate effective short-term financial management activities. However. these models are generic models and do not consider unique firm or industry influences. Maness and Zietlow discuss industry influences in a short paragraph that includes the observation that. “An industry a company is located in may have more influence on that companys fortunes than overall GNP” (2002. 507). In fact. a careful review of this 627-page textbook finds only sporadic information on actual firm levels of WCM dimensions. virtually nothing on industry factors except for some boxed items with titles such as. “Should a Retailer Offer an In-House Credit Card” (128) and nothing on WCM stability over time. This research will attempt to fill this void by investigating patterns related to working capital measures within industries and illustrate differences between industries across time. An extensive survey of library and Internet resources provided very few recent reports about working capital management. The most relevant set of articles was Weisel and Bradleys (2003) article on cash flow management and one of inventory control as a result of effective supply chain management by Hadley (2004). 6.Research MethodThe CFO Rankings The first annual CFO Working Capital Survey. a joint project with REL Consultancy Group. was published in the June 1997 issue of CFO (Mintz and Lezere 1997). REL is a London. England-based management consulting firm specializing in working capital issues for its global list of clients. The original survey reports several working capital benchmarks for public companies using data for 1996. Each company is ranked against its peers and also against the entire field of 1.000 companies. REL continues to update the original information on an annual basis. REL uses the “cash flow from operations” value located on firm cash flow statements to estimate cash conversion efficiency (CCE). This value indicates how well a company transforms revenues into cash flow. A “days of working capital” (DWC) value is based on the dollar amount in each of the aggregate. equally-weighted receivables. inventory. and payables accounts. The “days of working capital” (DNC) represents the time period between purchase of inventory on acccount from vendor until the sale to the customer. the collection of the receivables. and payment receipt. Thus. it reflects the companys ability to finance its core operations with vendor credit. A detailed investigation of WCM is possible because CFO also provides firm and industry values for days sales outstanding (A/R). inventory turnover. and days payables outstanding (A/P). 7.Research Findings Average and Annual Working Capital Management Performance Working capital management component definitions and average values for the entire 1996 2000 period . Across the nearly 1.000 firms in the survey. cash flow from operations. defined as cash flow from operations divided by sales and referred to as “cash conversion efficiency” (CCE). averages 9.0 percent. Incorporating a 95 percent confidence interval. CCE ranges from 5.6 percent to 12.4 percent. The days working capital (DWC). defined as the sum of receivables and inventories less payables divided by daily sales. averages 51.8 days and is very similar to the days that sales are outstanding (50.6). because the inventory turnover rate (once every 32.0 days) is similar to the number of days that payables are outstanding (32.4 days). In all instances. the standard deviation is relatively small. suggesting that these working capital management variables are consistent across CFO reports. 8.Industry Rankings on Overall Working Capital Management Performance CFO magazine provides an overall working capital ranking for firms in its survey. using the following equation:Industry-based differences in overall working capital management are presented for the twenty-six industries that had at least eight companies included in the rankings each year. In the typical year. CFO magazine ranks 970 companies during this period. Industries are listed in order of the mean overall CFO ranking of working capital performance. Since the best average ranking possible for an eight-company industry is 4.5 (this assumes that the eight companies are ranked one through eight for the entire survey). it is quite obvious that all firms in the petroleum industry must have been receiving very high overall working capital management rankings. In fact. the petroleum industry is ranked first in CCE and third in DWC (as illustrated in Table 5 and discussed later in this paper). Furthermore. the petroleum industry had the lowest standard deviation of working capital rankings and range of working capital rankings. The only other industry with a mean overall ranking less than 100 was the Electric & 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 twenty-second in CCE and twenty-sixth in DWC. The apparel industry ranks twenty-third and twenty-fourth in the two working capital measures9. Results for Bayer dataThe KramersMoyal coefficients were calculated according to Eqs. (5) and (6). The timescale was divided into half-open intervalsassuming that the KramersMoyal coefficients are constant with respect to the timescalein each of these subintervals of the timescale. The smallest timescale considered was 240 s and all larger scales were chosen such that i0.9*i+1. The KramersMoyal coefficients themselves were parameterised in the following form:This result shows that the rich and complex structure of financial data, expressed by multi-scale statistics, can be pinned down to coefficients with a relatively simple functional form.10. Discussion Credit risk is most simply defined as the potential that a bank borrower or counter-party will fail to meet its obligations in accordance with agreed terms. When this happens, the bank will experience a loss of some or all of the credit it provide to its customer. To absorb these losses, banks maintain an allowance for loan and lease losses. In essence, this allowance can be viewed as a pool of capital specifically set aside to absorb estimated loan losses. This allowance should be maintained at a level that is adequate to absorb the estimated amount of probable losses in the institutions loan portfolio. A careful review of a banks financial statements can highlight the key factors that should be considered becomes before making a trading or investing decision. Investors need to have a good understanding of the business cycle and the yield curve-both have a major impact on the economic performance of banks. Interest rate risk and credit risk are the primary factors to consider as a banks financial performance follows the yield curve. When it flattens or becomes inverted a banks net interest revenue is put under greater pressure. When the yield curve returns to a more traditional shape, a banks net interest revenue usually improves. Credit risk can be the largest contributor to the negative performance of a bank, even causing it to lose money. In addition, management of credit risk is a subjective process that can be manipulated in the short term. Investors in banks need to be aware of these factors before they commit their capital.银行的金融数据分析Andreas P. Nawroth, Joachim Peinke物理研究所，Carl-von-Ossietzky奥尔登堡大学，D - 26111奥尔登伯格，德国摘要财务数据随机分析已经被提出，特别是我们探讨如何统计在不同时间记录返回的变化。财务数据的时间规模依赖行为可分为两个区域：第一个时间范围是被描述为普遍特征的小时间区域（范围秒）。第二个时间范围是增加了几分钟的可以被