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of its corporate life. As part of a study of the Fortune 500’s 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 company’s fortunes than overall GNP” (2002. 507). In fact. a careful review of this 627-page textbook finds

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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 Bradley’s (2003) article on cash flow management and one of inventory control as a result of effective supply chain management by Hadley (2004).

6.Research Method

The 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.

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the collection of the receivables. and payment receipt. Thus. it reflects the company’s 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

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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 measures

9. Results for Bayer data

The Kramers–Moyal coefficients were calculated according to Eqs. (5) and (6). The timescale was divided into half-open 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＝0.9*τi+1. The Kramers–Moyal 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

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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 institution’s loan portfolio. A careful review of a bank’s 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 bank’s financial performance follows the yield curve. When it flattens or becomes inverted a bank’s net interest revenue is put under greater pressure. When the yield curve returns to a more traditional shape, a bank’s 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.

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