Sunday, March 31, 2013

Thơ gửi hiệp hội Bất Động Sản

 

MARCH 31, 2013 BY ALAN PHAN LEAVE A COMMENT

29 March 2013

“Mặt trời trong tôi lặn để bình minh lại đến…My sun sets to rise again” – Robert Browning

Kính thưa Quý Vị

Dù chỉ mới nhận được 15 câu hỏi “chất vấn” của Quý Vị qua báo chí, tôi cũng xin phản hồi sớm vì sự mong đợi của rất nhiều đọc giả; cũng như để tỏ lòng tôn kính với “1,000 (?) đồng nghiệp” của tôi. Tôi cũng đã từng làm một nhà đầu tư dự án BDS (real estate developer) ở tận xứ Mỹ xa xôi vào cuối thập niên 1970’s. Sau 7 năm huy hoàng với lợi nhuận, tôi và các đối tác đã trắng tay trả lại mọi vốn và lời trong dự án lớn ở Arizona vào năm 1982. Do đó, tôi khá đồng cảm với trải nghiệm “của thiên trả địa” hiện tại của Quý Vị.

Tôi không quen bị “chất vấn”, không phải là một cậu học trò phải thi trắc nghiệm, cũng không có “quyền lợi” hay “nghĩa vụ” gì trong tình huống này, nên xin phép được trả lời các bậc đàn anh theo phong cách của mình. Vả lại, những chi tiết nhỏ nhặt của 15 câu hỏi đã được “trả lời” qua các bài viết của tôi trong vài năm qua (còn lưu lại tại www.gocnhinalan.com). Thêm vào đó, nhiều BCA (bạn của Alan) cũng đã ra công sức phản biện qua các lời bình trên trang web này và các mạng truyền thông khác. Quý Vị tự tìm tòi nhé.

Cốt lõi của vấn đề

Một khuynh hướng chung khi tìm giải pháp cho vấn nạn BDS hiện nay của Việt Nam là đóng khung bài toán trong các công thức tài chánh. Vài doanh nghiệp BDS nhờ tôi tư vấn tìm vốn vì họ nói không thể tiếp cận được các nguồn tài trợ. Câu trả lời của tôi là vấn đề BDS thuộc chuyện thị trường.

Vốn trong dân tại Việt Nam được các nhà chuyên gia nước ngoài ước tính vào khoảng 60 tỷ US dollars; và vốn từ Việt kiều và các nhà đầu tư ngoại có thể lên thêm khoảng 20 tỷ (các số liệu này có thể sai nhưng chúng ta sẽ không bao giờ tìm được một thống kê chính xác và chính thống về các con số nhậy cảm ở Việt Nam). Tuy nhiên, dù với con số nào, số tiền này cũng thừa đủ để giải quyết mọi hàng BDS tồn kho.

Trên góc cạnh thị trường, khi người bán đáp ứng được nhu cầu người mua về sản phẩm và dịch vụ (gồm nhiều yếu tố, nhưng quan trọng nhất là giá cả và chất lượng) thì giao dịch xẩy ra. Do đó, câu hỏi cốt lõi là những BDS mà quý vị đã và đang sản xuất có mức giá và chất lượng theo đúng nhu cầu của người tiêu dùng chưa? Theo tôi biết, nhu cầu về phân khúc nhà cho người thu nhập thấp rất cao; nhưng sản phẩm gần như quá ít. Trong khi đó, nguồn cung cầu tại phân khúc nhà cao cấp lại mất cân bằng và lượng tồn kho có thể phải mất 10 năm mới tiêu thụ hết.

Tóm lại, khủng hoảng BDS hiện nay là một tính toán sai lầm của nhà sản xuất BDS về giá cả và loại hàng.

Giá thành quá cao?

Nhiều người trong Quý Vị biện bạch là giá BDS cao ngất trời vì giá đất, giá nguyên vật liệu, chi phí hành chánh và bôi trơn…quá cao. Thật tình, lý giải này chỉ chứng tỏ tính chất làm ăn thiếu hiệu quả vì không biết những tính toán căn bản về đầu tư cho dự án; cũng như cho thấy yếu kém của các quyết định bầy đàn và chụp giựt.

Nhưng đôi khi, tình thế ngoại vi cũng có thể làm sai trật mọi tính toán. Chẳng hạn khi tôi bắt đầu dự án Arizona nói trên vào 1979, chúng tôi đã không ngờ là lãi suất lên đến 16-18% mỗi năm khi hoàn tất, thay vì 8-9% như dự tính. Giá nhà vẫn hợp lý, nhưng phần lớn người Mỹ mua nhà bằng tín dụng, nên dự án phải phá sản. Dù không phải lỗi của chủ quan, nhưng chúng tôi hiểu rõ luật chơi của thị trường và cúi đầu chấp nhận.

Người mua nhà, hay ngay cả vợ con bạn bè của Quý Vị, thật sự không quan tâm đến lý do tại sao giá nhà lại cao hay thấp thế này? Vừa mua thuận bán thôi.

Một chút lịch sử

Dĩ nhiên, tất cả bàn luận trên đây dựa trên quy luật thị trường. Nhiều bạn sẽ nói là nền kinh tế chúng ta có “định hướng xã hội” nên chánh phủ phải nhẩy vào can thiệp hay cứu trợ khi “con cái” gặp hoạn nạn.

Chắc Quý Vị còn nhớ, có khi giá nhà đất lên cao cả mấy trăm phần trăm mỗi năm vào thập kỷ 1995-2006, không ai kiến nghị chánh phủ phải can thiệp để cứu người tiêu dùng bằng cách ngăn chận mọi sự tăng giá (nhiều khi phi pháp). Các nhà sản xuất BDS quên mất “định hướng xã hội” của Viêt Nam và ủng hộ triệt để nguyên lý thị trường.

Bây giờ, vào nửa hiệp sau của trận bóng, các cầu thủ lại yêu cầu trọng tài áp dụng một luật chơi mới? Tính bất nhất này làm mọi biện luận của Quý Vị trở nên ngây ngô cùng ngạo mạn.

Hệ quả khi bong bóng BDS nổ

Trước hết, khi nói về hệ quả, tôi xin mọi người ghi nhận công trạng của những nhà đầu cơ BDS trong việc tạo ra khủng hoảng hiện nay. Tất cả những suy thoái, trì trệ và việc kém hiệu quả trong các đầu tư để công nghiệp hóa hay gia tăng sản lượng nông, hải , sản…đều có thể truy nguồn đến những bong bóng tài chánh như BDS, chứng khoán và ngân hàng. Khi dòng tiền tấp nập chảy về lãnh vực này để hưởng lợi nhuận dễ dàng và nhanh chóng, chúng ta đã hy sinh những đầu tư xã hội cần thiết và dài hạn như y tế, giáo dục, công nghệ cao, nông nghiệp…Tai hại của sự lãng phí và tham ô trong việc sử dụng tài lực quốc gia này sẽ làm cả dân tộc trả giá trong nhiều thập kỷ sắp đến.

Nếu nhìn từ định hướng CNXH, các doanh nhân và quan chức có liên hệ đến việc đầu cơ, thao túng và lèo lái dòng tiền đầu tư…để thổi phồng các bong bóng tài sản đều có thể bị kết tội dưới nhiều luật lệ. Hú hồn. May mà Quý Vị còn chữ “kinh tế thị trường” để mà núp bóng.

Ngoài ra, về các hệ quả tương lai khi bong bóng BDS nổ, Quý vị đã tự đặt cho mình một vị trí quá quan trọng trong nền kinh tế chung. Dĩ nhiên có thể hơn 50% các doanh nghiệp kinh doanh BDS và vật liệu xây dựng cũng như 50% các ngân hàng nhỏ yếu sẽ chết vì nợ xấu…nhưng tôi chắc chắn là “không có Mợ thì chợ vẫn đông”. Thực ra, những doanh nghiệp, ngân hàng…này cũng đã chết lâm sàng rồi. Họ kéo dài hơi thở để đợi chút oxygen từ tiền thuế và phí của người dân. Hiện tại, họ không đóng góp chút gì cho sản lượng quốc gia trong khi tiếm dụng một phần nguồn lực không nhỏ.

Về các doanh nghiệp sản xuất vật liệu xây dựng, một số lớn đã ngất ngư vì không thể cạnh tranh với sản phẩm của Trung Quốc, Thái Lan…tại sân nhà hay sân người. Đổ lỗi cho tình hình BDS chỉ là một thủ thuật phát sinh từ thói quen lười biếng.

Con ngáo ộp thứ hai Quý Vị đem ra hù dọa là con số vài chục ngàn trong số 53 triệu công nhân toàn quốc (với tỷ lệ thất nghiệp khoảng 2.2% theo thống kê nhà nước) sẽ bị ảnh hưởng khi bong bóng BDS nổ tung. Nếu nền kinh tế chúng ta phát triển bền vững và bài bản, sự tạo ra việc làm cho các công nhân này chỉ là chuyện nhỏ.

Con ngáo ộp thứ ba của Quý vị là các người dân bỏ tiền trong các ngân hàng sẽ chịu mất mát khi vài ngân hàng đóng cửa. Theo tôi hiểu, mỗi tài khoản hiện nay được bảo hiểm đến 50 triệu VND và đang được NHNN đề xuất lên 100 triệu VND (vì lạm phát nhiều năm qua). Tỷ lệ mất mát cho những tài khoản trên 100 triệu VND tại các ngân hàng sẽ rất nhỏ; vì các nhà đa triệu phú thường không ngu để mất tiền như Quý Vị tiên đoán. Họ có nhiều giải pháp sáng tạo hơn Quý Vị và nhà nước nhiều.

Những hệ quả tích cực

Trong bài “Thị trường sẽ cứu chúng ta” (www.gocnhinalan.com) tôi đã ghi nhận 5 hệ quả tích cực hơn khi bong bóng BDS nổ. Đó là số lượng vài trăm ngàn gia đình lần đầu sở hữu một căn nhà vừa túi tiền, hiện tượng tâm lý “an cư lạc nghiệp” tạo cú kích cầu tiêu dùng, gây lại niềm tin cho kinh tế, loại bỏ các thành phần phi sản xuất yếu kém, tăng thu ngân sách và thu hút đầu tư nội ngoại.

Trong đó, quan trọng nhất là việc tạo một tầng lớp trung lưu mới, hết sức cần thiết cho mọi sự phát triển bền vững. Nhìn qua các xã hội đã mở mang tại Âu Mỹ Nhật Úc, tầng lớp trung lưu với những tài sản thâu góp được thường là đầu tàu cho chiếc xe kinh tế. Họ tạo ra thị trường tiêu dùng lớn nhất, họ đóng thuế nhiều nhất, họ làm việc cần cù nhất, họ nợ nhiều nhất (tốt cho ngân hàng và các ông chủ), họ có niềm tin cao nhất vào đất nước …vì họ có quá nhiều thứ để mất. Một xã hội bất ổn là khi phần lớn người dân không có gì để mất.

Hệ quả khi bong bóng không nổ

Tôi thì lại lo sợ về những hệ quả trái ngược nếu quyền lực của Quý vị thành công và thuyết phục nhà nước bơm tiền dân cứu Quý Vị và các ngân hàng yếu kém.

Trước hết, nền kinh tế zombies (xác chết biết đi) này sẽ kéo dài ít nhất là một thập kỷ nữa.

Khi phải in tiền đủ để cứu trợ, nạn lạm phát sẽ bùng nổ lại và tỷ giá VND sẽ rơi. Nhiều người đã quay qua Mỹ quan sát về các gói cứu trợ ngân hàng tư và đề nghị NHNN dùng giải pháp này cho Việt Nam. Một ghi chú nhỏ: chánh phủ Mỹ cho các ngân hàng này vay vốn với lãi suất cực rẻ; nhưng không cứu các doanh nghiệp hay giá BDS; và sau khi gây lại vốn sở hữu bị mất trong cuộc khủng hoảng tài chánh 2008, hầu hết các ngân hàng đã trả tiền lại cho chánh phủ. Giải pháp này không thể thực hiện ở Việt Nam vì các ngân hàng thương mại Việt không đủ uy tín, thương hiệu, tầm cỡ, tính minh bạch hay khả năng quản trị để tiếp cận nguồn vốn nội hay ngoại (vẫn rất dồi dào).

Chánh phủ hiện đã bội chi vì các vấn đề kinh tế xã hội từ khủng hoảng và nguồn thu từ thuế và phí đang bị thu hẹp đáng kể. Dùng những tài lực hiếm hoi để nuôi các zombies phi sản xuất là kéo dài cuộc suy thoái cho các thành phần khác trong nền kinh tế.

Nhưng tệ hại nhất là khi tung tiền cứu nguy cho “bồ nhà”, chánh phủ sẽ gởi một thông điệp bào mòn mọi niềm tin còn sót lại của các nhà đầu tư trong và ngoài nước. Đó là: “mọi sai phạm lầm lẫn sẽ được che đậy và bảo vệ; và các quy luật của thị trường có quyền đi “nghỉ mát” khi quyền lợi của các nhóm lợi ích bị xâm phạm”.

Những giải pháp sáng tạo

Sau cùng, nếu con phượng hoàng có thể bay lên từ đống tro tàn thì các zombies cũng có thể tái tạo lại một đời sống mới. Trong nền kinh tế trí thức toàn cầu này, sáng tạo vẫn là một điều kiện tiên quyết cho mọi doanh nghiệp.

Tôi không kinh doanh BDS từ năm 1982, nên tôi không dám “múa rìu qua mắt thợ”. Nhưng tôi nhận thấy có những đại gia “thật lớn” của BDS đã phát triển mạnh trong khủng hoàng này. Bầu Đức của HAGL chọn giải pháp “xuất ngoại” khi bán tháo BDS tại Việt Nam và đem tiền đổ vào Lào và Myanmar. Ngài Vượng của Vincom đạt được danh tỷ phú đô la với phân khúc trung tâm thương mại cao cấp trong thời bão táp. Mr. Quang của Nam Long thì thành công với vốn ngoại và mô hình EHome cho phân khúc trung lưu. Các trường hợp phát triển như anh Thìn Đất Xanh hay anh Đực Đất Lành là những thí dụ khác.

Trong lãnh vực vật liệu xây dựng, sản phẩm nhà tiền chế theo dây chuyền hay các vật liệu từ công nghệ cao và xanh đã biến nhiều doanh nhân thế giới thành tỷ phú. Trí tuệ Việt chắc chắn phải có rất nhiều…Ngô Bảo Châu…trong ngành BDS. Đây là tương lai của BDS Việt trong mong đợi của mọi người; không phải hình ảnh của các zombies níu kéo vào dây trợ sinh trên giường bệnh.

Thay cho lời kết

Tôi thực sự khâm phục khả năng lobby của Hiệp Hội BDS và các thành viên. Tạo được một bong bóng khiến giá trị BDS lên đến 25 lần thu nhập trung bình của người dân là một thành tích đáng ghi vào kỷ lục Guinness. Tôi cũng tiên đoán là chánh phủ rồi cũng sẽ tung nhiều gói cứu trợ BDS mặc cho sự can gián của nhiều chuyên gia và đa số người dân. So với Quý Vị, tiếng nói của chúng tôi không đủ trọng lượng để chánh phủ lưu tâm.

Do đó, cuộc tranh cãi nên dừng lại ở đây để những người dân chưa có nhà không nên kỳ vọng vào một phép lạ trong tương lai gần.

Nhưng trong sâu thẳm, tôi vẫn mang nhiều hy vọng. Có thể một lúc nào đó, những tinh hoa của đất Việt sẽ quên đi quyền lợi cá nhân của mình và gia đình…để san sẻ lại cho các người dân kém may mắn hơn. Không phải để làm từ thiện, mà nhận trách nhiệm rộng lớn hơn với cộng đồng, và với thế đứng của Việt Nam trên thương trường quốc tế. Để doanh nhân Việt được tự hào với tư duy sáng tạo cởi mở và khả năng vượt khó bền bỉ. Để thế hệ sau còn có chút niềm tin và lực đẩy khi họ phải ra biển lớn cạnh tranh.

Riêng đối với những vị đã mất mát tài sản vì sai phạm đầu tư, tôi xin chia sẻ nơi đây câu thơ của tiền nhân mà tôi tự an ủi mình sau khi ký giấy trao lại cho ngân hàng toàn bộ dự án Arizona và ra đi với bàn tay trắng,” Thế Chiến Quốc, thế Xuân Thu…Gặp thời thế thế thì phải thế”. Dù sao, chỉ 3 năm sau đó, tôi lại kiếm được nhiều tiền hơn trong một mô hình kinh doanh khác.

Mong Quý vị mọi điều may mắn và mong tinh thần “kẻ sĩ” mãi cháy sáng trong cuộc đời Quý vị.

Thân ái,

Alan Phan

Tham khảo: Các bài về BDS từ trang 185 của cuốn sách “Đi Tìm Niềm Tin Thời Internet” của Alan Phan do nhà sách Thái Hà xuất bản (2012). Và các bài về BDS trên web site www.gocnhinalan.com.

Những ảnh hưởng tích cực sau đây sẽ quay về giúp nền kinh tế tiến về một định hướng bền vững hơn.

  1. Khi đa số người dân sở hữu một căn nhà, tầm nhìn và niềm tin của họ vào tương lai vững vàng hơn. Bây giờ họ có một tài sản gì để mất; do đó, sự đóng góp của họ vào nền kinh tế sẽ năng động và tích cực.
  2. Niềm tin này mới là “gói kích cầu” quan trọng hơn cả cho thị trường tiêu dùng và nó sẽ kích hoạt các cơ sở công nghiệp cũng như nông nghiệp gia tăng sản xuất, giảm lượng tồn kho và cải thiện năng suất lao động để cạnh tranh. Nên nhớ là tiền dự trữ trong dân nhiều gấp 3 lần tiền dự trữ của chánh phủ;
  3. Khi các zombies (xác chết biết đi) bị loại bỏ khỏi hệ thống ngân hàng và thị trường chứng khoán, những định chế sống sót sẽ mạnh hơn nhờ thị phần gia tăng; sẽ chăm chú hơn vào ngành nghề cốt lõi (sau bài học đầu tư đa ngành) và lo trau luyện những kỹ năng cần cho sự cạnh tranh dài hạn;
  4. Lạm phát hay tỷ giá sẽ không tăng tốc lâu dài, vì chánh phủ không cần in tiền thêm để cứu ai (một thông điệp rất rõ cho các DNNN) và ngân sách sẽ bội thu nhờ thuế phí tăng thu từ sự tăng trưởng GDP; cũng như nguồn ngoại tệ sẽ dồi dào hơn với sinh lực mới của khu vực xuất khẩu;
  5. Khi kinh tế vĩ mô ổn định và khi luật thị trường thay thế luật “hành dân”, niềm tin quay lại với các nhà đầu tư quốc tế và kiều hối. Kênh ngoại tệ này sẽ thâu ngắn sự hồi phục và giúp chúng ta một lợi thế cạnh tranh mới.

Tuesday, March 19, 2013

Using cash flow ratios to predict business failures.

 

Subject:

Management research (Analysis)
Cash flow (Analysis)
Ratio analysis (Usage)
Business failures (Analysis)

Authors:

Rujoub, Mohamed A.
Cook, Doris M.
Hay, Leon E.

Pub Date:

03/22/1995

Publication:

Name: Journal of Managerial Issues Publisher: Pittsburg State University - Department of Economics Audience: Academic; TradeFormat: Magazine/Journal Subject: Business; Human resources and labor relationsCopyright: COPYRIGHT 1995 Pittsburg State University - Department of Economics ISSN: 1045-3695

Issue:

Date: Spring, 1995 Source Volume: v7 Source Issue: n1

Accession Number:

16838779

Full Text:

Cash flow may be viewed as the lifeblood of a corporation and the essence of its very existence. Numerous empirical studies that use financial and accounting measures to predict business performance (i.e., success or failure) emphasize the importance of cash flow information in predicting bankrupt and nonbankrupt firms (Bernard and Stober, 1989; Gentry, 1984 and 1985; BarNiv, 1990, Carslaw and Mills, 1991). Most of those studies conclude that the level of cash inflows and outflows from various activities are highly interrelated. A failure of any part of the system to operate may endanger or cause the entire firm to fail (Largay and Stickney, 1980).
The primary objective of this study is to assess the usefulness of cash flow disclosures as required by Statement of Financial Accounting Standards No. 95 (SFAS 95) in the prediction of bankruptcy, and whether cash flow data provide a superior prediction of business failure over the models employing conventional accrual accounting data. The business failure prediction criterion was used for two reasons: (1) Business success or failure has been causally linked to the volume of net cash inflow and outflow components from various activities (Gentry, 1985). For example, the inability of a firm to generate enough cash from its operations may force the firm to borrow more money or to dispose of its capital investments to meet its obligations. If this situation persists over an extended period of time, it may lead to an involuntary bankruptcy. (2) This criterion, which is empirically testable, has been successfully used for investigating the usefulness of accounting information in other studies (Altman and Spivack, 1983).
A second objective of this study is to present some new financial ratios derived from cash flow data and to highlight their potential use in financial analysis and prediction of business performance. Some of these are new ratios which have not been used in other studies.
MOTIVATION
The motivation for this study came from two important developments in the business world: (1) the multitude of business failures across all types of business, and (2) the emphasis placed on cash flow information by the Financial Accounting Standards Board in SFAS 95. Could the use of cash flow data help predict business failure and thus help prevent business failure?
The link between cash flow data and corporation net worth has been established in earlier research (Rayburn, 1986). However, these studies were done before the issuance of SFAS 95 and used different measures of cash flow from operations. Numerous studies show that financial ratios based on accrual accounting data possess significant ability to predict bankruptcy (Altman and Spivack, 1983; Beaver, 1966, 1968; Libby, 1975; Ohlson, 1980). Most of these studies concluded that companies with weak and unstable financial indicators (ratios) are more likely to fail than those companies with stronger and more stable financial indicators (ratios). However, these models did not emphasize cash flow data.
An ideal approach is probably an integrated one, such as the approach suggested in this study. This paper provides evidence on the usefulness of cash flow data in the prediction of business failure and whether the integration of cash flow data with accrual accounting data can provide a superior measure over accrual accounting data alone for predicting bankruptcy. It should be noted that this study does not suggest overlooking these earlier predictive methods, but rather it addresses whether cash flow information can complement the information already provided by accrual accounting data.
There are at least four key differences between the prior studies and this study. First, financial ratios based on conventional accrual accounting are modified to include cash flow information. Second, while prior studies use different approaches to measure cash flow from operations, this study bases its measures of cash from operations on those criteria required by SFAS 95. Third, this study uses the format in SFAS 95 requiring cash flow data to be divided into cash from operations, cash from investing and cash from financing activities. None of the preceding studies has used this approach. Fourth, none of the previous studies used the cash flow ratios which have been emphasized in this study.
RESEARCH HYPOTHESES
For testing the major objective of the research, three hypotheses, stated in the alternative form, have been examined. These include:

Ha1: The discriminant ability of cash flow data, in the form of financial ratio models, to predict bankruptcy is significant.
Ha2: The classification accuracy of cash flow information, in the form of financial ratio models, to predict bankruptcy is greater than the classification accuracy of accrual accounting information, in the form of financial ratio models.
Ha3: The use of cash flow data in conjunction with accrual accounting data, in the form of financial ratio models, can improve the overall classification accuracy of accrual accounting models to predict bankruptcy.
RESEARCH DESIGN
The discussion of the research design starts with sample and variables selection, and then addresses each of the three hypotheses.
SAMPLE SELECTION
The Wall Street Journal Index (WSJI), the Standard and Poor's Compustat (SPC) Industrial Annual Research File of Companies, and the Compustat Industrial Files (CIF) were employed to choose a sample consisting of 33 failed firms and 33 nonfailed firms for a five year period following the issuance of SFAS 95. The sample was limited to those companies who provided a statement of cash flows or sufficient data for the statement for at least three years prior to failure. Failure of firm was defined as the act of filing a petition for Chapter 11 bankruptcy (Zmijewski, 1984). Failed and nonfailed firms were identified and matched on the basis of their industry and asset size. The sample cut across various types and sizes of firms. Because there are many more nonfailed firms than failed firms equal sized groups were used. Similar sampling techniques have been used in other studies (Zmijewski, 1984; BarNiv, 1990).
VARIABLES SELECTION
The approach used in this study involves the use of financial ratios in the prediction models. Ratios are used for two key reasons: (a) financial ratios have been successfully used in other empirical studies (Largay and Stickney, 1980; Ohlson, 1980; Giacomino and Mielke, 1995) and (b) the use of financial ratios can make comparisons of corporations of different sizes more meaningful than the use of absolute figures. The financial ratios used in the tests were divided into two groups: (a) those ratios derived from cash flow data, and (b) those ratios based on conventional accrual accounting.
RATIOS DERIVED FROM CASH FLOW DATA
The ratios derived from cash flow data are classified under the following groups as suggested by Mielke and Giacomino (1988): (1) management financial decisions, (2) quality of earnings, (3) mandatory cash flows, and (4) discretionary cash flows. These ratios used data as classified in the Statement of Cash Flows required by SFAS 95 (FASB, 1987). This classification is: (1) cash inflows and outflows for operating activities (primarily income statement ordinary activities), (2) cash inflows and outflows from investing activities (sale or purchase of plant assets, long-term investments, etc.) and (3) cash inflows and outflows from financing activities (increase or decrease in financing from owners or long-term creditors).
As can be seen from Table 1, eighteen financial ratios based on cash flow data were used in the research analysis. Some of these are new ratios developed for this study, as indicated in Table 1. Then, stepwise discriminant procedures were used for selecting the financial ratios that are most useful in discriminating between bankrupt and nonbankrupt firms. Eight financial ratios derived from the cash flow data, which were found to be significant, were selected and used in the final models.
The ratios selected for this study are:
(1) External financing index ratio = Cash from operations/Total external Financing sources (debt)
This ratio shows a firm's ability to provide sufficient cash from its operations to meet its external obligations when they mature. Generally speaking, the higher the ratio, the stronger the firm's liquidity, the greater the firm's ability to meet its obligations as they become due, and the greater the probability of success of the firm. This ratio is significant because it is important to view the liquidity of a firm from an external conservative point of view.
(2) Cash sources component percentages ratio = Cash from financing/Total sources of cash
This ratio relates the cash from financing activities to total cash sources during the period. In this computation, the cash generated from financing activities is compared with the total cash generated from all activities. This ratio also indicates how much the firm relies on debt and investment by owners rather than cash generated internally from operating activities or from investing activities. In general, the lower the ratio, the better the firm's financial position and the greater the probability of success of the firm. This ratio may be compared with industry average and competitive firms or be analyzed by trend analysis over time. For example, it may be used in assessing and comparing the use of outside financing versus internal financing over time.
(3) Financing policies ratio = Cash from financing activities/Total Assets
This ratio shows the percentage of assets that were funded by creditors and owners during the period. This ratio also helps accounting information users to evaluate a firm's financing policies. In general, the lower this ratio, the better the firm's financial position. A high ratio may indicate that the firm is not using its resources (assets) effectively or to best advantage. A high ratio also may indicate that the firm faces a problem due to additional cash burden in the future as the interests and loans repayments become due.
(4) Operating cash index ratio = Cash from operations/Net income
This ratio assists current or potential investors and creditors in evaluating the "quality" of a firm's earnings. It compares accrual net income and the related cash from operations. Earnings are judged to be of high quality if they are stable, the major source appears to be the operating activities, and the methods used in determining earnings are conservative. Determining net income under accrual accounting requires the use of judgmental decisions in measuring depreciation, estimating bad debts, etc. Cash flow from operations is considered to be a more objective measure. Generally, the higher this ratio, the better the quality of earnings. This ratio also indicates a firm's ability to produce cash internally from its ongoing operations. Further analysis may be made by comparison with industry data and by trend analysis over time.
(5) Operating cash inflow ratio = Cash from operations/Total sources of cash
This ratio indicates what proportion of cash inflows is generated internally from operating activities. In general, the larger the ratio, the greater will be the firm's ability to withstand adverse changes in economic conditions. A high ratio generally indicates a strong financial position for the company. In this case, the firm will probably be less dependent on external sources of funds.
(6) Operating cash outflow ratio = Cash used in operations/Total sources of cash
This ratio indicates what proportion of total cash generated from all sources is used in operations. This ratio also helps users of accounting information in evaluating a firm's ability to control and contain costs. In general, the lower the ratio, the higher the profitability and the greater the probability of success of the firm.
(7) Long-term debt payment ratio = Cash applied to long-term debt/Cash supplied by long-term debt
This ratio compares a firm's cash disbursements to pay long-term liabilities with cash receipts from long-term liabilities. Generally, the higher the ratio, the stronger the firm's ability to settle its long-term liabilities as they become due. This ratio may be used by current or future long-term creditors who must evaluate the probability of obtaining repayment in the future for any funds loaned to the company.
(8) Productivity of assets ratio = Cash from operations/Total assets
This ratio shows the percentage of cash generated from operating activities on each dollar of asset invested and measures the productivity of assets. It also helps accounting information users in assessing a firm's financial flexibility and management's ability to generate cash and control costs. Financial flexibility may be viewed in terms of a firm's ability to produce enough cash internally to respond to unforeseen problems and utilize profitable opportunities. An evaluation of a firm's ability to survive an unexpected drop in revenues, for example, may include a review of its past cash flows from operations. In general, the higher the ratio, the greater the efficiency of the use of assets and the better the firm's financial position.
FINANCIAL RATIOS BASED ON CONVENTIONAL ACCRUAL ACCOUNTING
As can be seen from Table 2, thirty financial ratios based on conventional accrual accounting have been used in earlier studies for predicting business failure (Beaver, 1966, 1968; Altman and Spivack, 1983). These were divided into six "common elements" groups. Only one ratio from each group was found to be a significant predictor of bankruptcy in the previous studies.
These six ratios were thus selected for use in the final bankruptcy models in this study. These ratios are:
(1) Net income to total assets
(2) Cash flow to total debt
(3) Current assets to current liabilities
(4) No credit interval (defensive assets minus current liabilities to fund expenditures for operations)
(5) Working capital to total assets
(6) Current liabilities plus long-term liabilities to total assets
TEST OF HYPOTHESIS ONE
Multivariate Discriminant Analysis (MDA) was used to test each of the three hypotheses. MDA is a statistical technique that can be used to classify observations into one of two or more categories - bankrupt or nonbankrupt (Hair et al., 1979). Bankruptcy models were constructed for all three tests for one, two, and three years prior to the bankruptcy, using equal prior probabilities and an equal cost of misclassification. The MDA bankruptcy model to test hypothesis one, using the eight selected cash flow ratios, is expressed mathematically as follows:
Zi = B1X1i + B2X2i + B3X3i + B4X4i + BSX5i + B6X6i + B7X7i + B8X8i
Where:
Zi= discriminant function (i.e., bankrupt and nonbankrupt firms)
B1, B2 ........., B8= the weighing coefficient
X1i = external financing index ratio X2i = cash sources component percentage ratio X3i = financing policies ratio X4i = operating cash index ratio X5i = operating cash inflow ratio X6i = operating cash outflow ratio X7i = long-term debt payment ratio X8i = productivity of assets ratio
This model can be used for classifying a firm as either bankrupt or nonbankrupt. The MDA model is appropriate only under the following conditions: (1) the groups being classified are categorical (i.e., zero and one, or failed and nonfailed firms), (2) each observation in each group can be measured by a set of (X) continuous independent variables, and (3) these (X) variables are assumed to have a multivariate normal distribution in each population and equal covariances. In order to test whether the accounting data used in this research meet the assumptions of normality and equal covariance matrices, the Kolomogrov (D) statistical technique and the likelihood ratio test were performed. When nonnormality of the data was observed, transformation was performed in an attempt to eliminate or reduce the extent of the violation.
The classification accuracy of the Multivariate Discriminant Analysis (MDA) may suffer from potential upward search bias which may be due to the fact that the discriminant coefficient, the reduced ratio sets (models), and the group distribution are derived from the original (same) sample. In this study, the Frank and Morrison (1965) approach and the Jackknife (U-Method) technique were used to determine whether such bias occurs in the classification accuracy derived. It was found that the model can be used to discriminate between bankrupt and nonbankrupt firms, using samples other than that sample used to derive the discriminant coefficient of the model. This result suggests that there is significant statistical evidence to show that search bias is not significant. Therefore, the results of the tests explained below are not affected by search bias.
TEST OF HYPOTHESIS TWO
For testing hypothesis two, bankruptcy models were constructed by using the six selected financial ratios based on conventional accrual accounting. The MDA bankruptcy model is written as follows:
Zi = M1Y1i + M2Y2i + M3Y3i + M4Y4i + M5Y5i + M6Y6i
Where:
Zi= discriminant function (i.e., bankrupt and nonbankrupt firms)
M1, M2, ...., M6= the weighing coefficient
Y1i = Net income/Total assets Y2i = Cash flow/Total debt Y3i = Current assets/Current liabilities Y4i = No credit interval Y5i = Working capital/Total assets Y6i = Total liabilities/Total assets
The outcome of this accrual accounting model and that based on cash flow data as described above were then compared by using the McNemar tests of changes. The McNemar test is a nonparametric statistical technique that may be used for analyzing frequency data from related samples (Daniel, 1990). This test can be used to examine whether there exists a differential rate of classification accuracy between cash flow data and accrual accounting data. Accordingly, the set of classification accuracy for each firm in the sample was classified into one of four categories: (1) firms which were classified correctly by the cash flows and accrual accounting data, (2) firms which were misclassified by the cash flow information and by accrual accounting data, (3) firms which were classified correctly by the cash flow data and misclassified by the accrual accounting data, and (4) firms which were classified correctly by the accrual accounting data and misclassified by the cash flow data.
TEST OF HYPOTHESIS THREE
For testing hypothesis three, bankruptcy models were constructed by using the eight selected ratios based on the cash flows data in conjunction with the six selected ratios based on conventional accrual accounting data. The MDA bankruptcy model is written as follows:
Zi = B1V1i + B2V2i + B3V3i + B4V4i + B5V5i + B6V6i + B7V7i + B8V8i + M1Y1i + M2Y2i + M3Y3i + M4Y4i + M5Y5i + M6Y6i
Where:
Zi = discriminant function (i.e., bankrupt and nonbankrupt firms)
B1, B2 ........., B8= the weighing coefficient cash flow data
M1, M2 ........., M6= the weighing coefficient of accrual accounting data.
V1i, V2i ........, V8i= cash flow variables
Y1i, Y2i ........., Y6i= accrual accounting variables
The results of this combined bankruptcy model and that based on accrual accounting data alone were compared using the McNemar test of changes. This test was used for comparison of the classification accuracy of both models. Accordingly, the set of classification accuracy for each firm in the sample was classified into one of four categories: (1) firms which were classified correctly by both models, (2) firms which were misclassified by both models, (3) firms which were classified correctly by the combined model and misclassified by accrual accounting data, and (4) firms which were classified correctly by accrual accounting data and misclassified by the combined model.
RESULTS OF TESTING HYPOTHESIS
The remainder of this paper is devoted to presenting the results of tests of the research hypotheses.
RESULTS OF TESTS OF HYPOTHESIS ONE
The first hypothesis tested was to determine whether cash flow data can be used to discriminate between bankrupt and nonbankrupt firms. The results of testing hypothesis one are presented in Table 3. The null version of this hypothesis was rejected at the 0.0003 and 0.0360 level of significance for data one year and two years prior to bankruptcy, respectively. Cash flow data classify 86.36% and 78.79% of the total sample correctly for one year and two years prior to failure, respectively. These results suggest that cash flow data can generate information needed to derive statistically significant bankruptcy prediction models. This led to the conclusion that cash flow models provide information useful to users of accounting information for predicting business failure. It appears that by understanding what cash flow data reveal about a firm's ability to meet its obligations users of accounting information may be able to use such data as indicators of potential financial trouble for a firm.
The data for three years prior to bankruptcy produced lower classification performance. This result suggests that cash flow data are useful for predicting bankruptcy up to two years prior to bankruptcy but not for three years prior to bankruptcy. It appears that bankruptcy indicators become less clear three years prior to bankruptcy.
RESULTS OF TESTS OF HYPOTHESIS TWO
The classification accuracy of accrual accounting data for one year, two years, and three years prior to bankruptcy is presented in Table 4. For testing the second research hypothesis, the McNemar test for related samples was performed to investigate whether there exists a differential rate of classification between the cash flow and accrual accounting model. The results of this test indicate that the cash flow data appear to provide predictive power superior to that of the accrual accounting model. The null version of this hypothesis was rejected at the 0.053 level of significance. Cash flow data provide a basis for discriminating correctly between bankrupt and nonbankrupt firms in 86.36% and 78.79% of the cases for one year and two years [TABULAR DATA FOR TABLE 3 OMITTED] prior to bankruptcy, respectively. Accrual accounting data provide a basis for discriminating correctly between bankrupt and nonbankrupt firms in 81.82% and 71.21% of the cases for one year and two years prior to bankruptcy, respectively.
RESULTS OF TESTS OF HYPOTHESIS THREE
The third hypothesis tested was to determine whether the combined data can improve the overall ability to predict bankruptcy. The eight cash flow ratios and the six accrual financial ratios were used in the final model for testing this hypothesis.
The classification accuracy for data one year, two years, and three years prior to bankruptcy is presented in Table 5. As can be seen from Table 5, the predictive accuracy of cash flow data plus accrual accounting data for one year prior to bankruptcy was significant at the 0.0002 level of significance. This result suggests that this model was found to be useful for predicting business failure. This model classifies 90.91% of the total sample correctly (i.e., 81.82% (27/33) of the failed firms and 100.00% (33/33) of the nonfailed firms were classified correctly).
The classification accuracy of the combined cash flow data and accrual accounting model for two years prior to bankruptcy was significant at the 0.0131 level of significance. For the test using data three years prior to bankruptcy, Table 5 shows that the predictive accuracy of the combined model was not significant at the .05 level of significance (P-value = 0.3213). These results suggest that the combined cash flow and accrual accounting data model can be used [TABULAR DATA FOR TABLE 4 OMITTED] [TABULAR DATA FOR TABLE 5 OMITTED] [TABULAR DATA FOR TABLE 6 OMITTED] to predict bankruptcy up to two years prior to bankruptcy.
The McNemar test of related samples was performed to examine whether there exists a differential rate of classification between cash flow data plus accrual accounting data model and accrual accounting data model alone. The results of this test suggest that when cash flow data are combined with accrual accounting data, the results outperform accrual accounting data alone in discriminating between bankrupt and nonbankrupt firms. The null version of this hypothesis was rejected at the 0.017 level of significance. These results suggest that cash flow data combined with accrual accounting data produces superior discriminant power over accrual accounting data alone (90.91% versus 81.82% and 86.36% versus 71.21% for one year and two years prior to bankruptcy, respectively). Thus, cash flow data can improve the overall accuracy of predicting business failure when used in combination with accrual accounting data.
CONCLUSIONS AND IMPLICATIONS FOR MANAGERIAL USE
This study has attempted to examine whether cash flow data can provide a superior measure to predict bankruptcy over accrual accounting data. Several financial ratios, based on cash flow data, were used as independent variables for the investigation. Some of these are new and have never been used before in other studies. From these, eight financial ratios derived from cash flow data were selected as best predictors and used in the final models, along with six ratios based on accrual accounting used in previous studies.
In testing the research hypotheses, it was found that (a) cash flow data predict bankruptcy better than accrual accounting data, and (b) the use of cash flow data in conjunction with accrual accounting data improves the overall predictive power of accrual accounting data used in previous studies for predicting business failure. This comparison is shown in Table 6. These findings, as in other studies, may be subject to some limitations because a limited number of firms were used and selected in a nonrandom sample. Additional research in this area might be useful to add credence to the results.
In summary, these results lead to the conclusion that cash flow data, in the form of financial ratios, are useful by themselves or as a supplement to accrual accounting data in predicting bankruptcy.
The implications of the study from the standpoint of management or other users are many. For example, the volume of net cash inflows from operations may indicate whether an enterprise can generate funds internally and meet its current and future obligations. Therefore, measuring the change in the volume of the cash flow components is considered to be critical in determining the future success or failure of a corporation. The inability, of a corporation to generate cash from its operations over time may cause a default on its debt and bankruptcy. This situation indicates a basis for discriminating between financially successful and financially troubled enterprises.
The models used in this study may help users of accounting information to detect the deterioration of a firm's financial position. Management may use this information to forecast business failure and take the necessary action to avert a potential failure. Management may also use cash flow information as a planning tool. Some of the significant ways in which management may use this information for planning and managing purposes encompass: (1) to establish goals and allocate internal resources effectively by integrating this information into the budgeting process, (2) to coordinate cash dividends policy with other actions of the company, (3) to evaluate investment opportunities such as financing of new product lines, additional machinery, or acquisition of other competitors, (4) to evaluate the efficiency and effectiveness of managers and units, and (5) to find ways of strengthening a weak cash position or credit lines.
External users such as investors, creditors, auditors and others may use cash flow information to make more effective decisions. For example, investors may use this information to evaluate the quality of management and whether it is pursuing corporate goals stated by stockholders. Investors may also use this information to update their prior beliefs regarding their current and future investments. Creditors such as bank loan officers may use this information to aid in improving critical lending decisions and monitoring loans. Improvements could be exhibited in many areas, such as a reduction in loans made to potential defaulters, and an increase in loans made to clients that repay their debt in a timely manner. Cash flow data may provide valuable information to auditors. It might help auditors in determining the analytical review (audit) procedures and in making critical and necessary decisions as to whether the firm is solvent and will stay in existence for awhile as a going concern.
Finally, the eight ratios emphasized in this study, based on cash flow data, may be useful as individual ratios. Management or investors may use these ratios, perhaps with other analytical procedures, to detect problems in various areas of the firm and take corrective action. For example, the External Financing Index Ratio (1) shows the firm's ability to provide sufficient cash from its operations to meet its external obligations when they mature. Generally speaking, the higher the ratio the stronger the firm's liquidity, and the greater the probability of success of the firm. The Cash Sources Component Percentages Ratio (2) relates the cash from financing activities to total cash sources during the period. In general, the lower the ratio the better the firm's financial position and the greater the probability of success. The Financing Policies Ratio (3) helps accounting information users to evaluate a firm's financing policies. In general, the lower this ratio, the better the firm's financial position. Operating Cash Index Ratio (4) assists current or potential investors and creditors to evaluate the "quality" of the firm's earnings. Generally, the higher this ratio, the better the quality of earnings.
Operating Cash Inflow Ratio (5) indicates what proportion of cash inflows is generated internally from operating activities. A high ratio generally indicates a strong financial position for the company. Operating Cash Outflow Ratio (6) indicates what proportion of total cash generated from all sources is used in operations. In general, the lower the ratio the higher the profitability. Long-Term Debt Payment Ratio (7) compares a firm's cash disbursements to pay long-term liabilities with cash receipts from long-term liabilities. Generally, the higher the ratio, the stronger the firm's ability to set fie its long-term debt. Productivity of Assets Ratio (8) measures the productivity of assets. In general, the higher the ratio the greater the efficiency of use of assets.
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Libby, R. 1975. "Accounting Ratios and Predictors of Failure: Some Behavioral Evidence." Journal of Accounting Research 13 (Spring): 150-161.
Mielke, D.E., and D.E. Giacomino. 1988. "Analysis Using the New Statement of Cash Flows." Corporate Accounting 6 (March): 10-16.
Ohlson, J.A. 1980. "Financial Ratios and the Probabilistic Prediction of Bankruptcy." Journal of Accounting Research 18 (Spring): 109-131.
Rayburn, T. 1986. "The Association of Operating Cash Flow and Accruals With Security Returns." Studies on Alternative Measures of Accounting Income, Supplement to Journal of Accounting Research 24:112-133.
Wahlen, J.M. 1994. "The Nature of Information in Commercial Bank Loan Loss Disclosures." The Accounting Review 69 (July): 455-478.
Zmijewski, J.W. 1984. "Methodological Issues Related to the Estimation of Financial Distress Prediction Models." Studies on Current Econometric Issues in Accounting Research, Supplement to Journal of Accounting Research 22: 59-85.
RELATED ARTICLE: Table 1
Ratios Derived from Cash Flow Data
Group I - Management Financial Decisions
(1) Productivity ratio = Cash from operations/Capital investment
(2) External financing index = Cash from operations/Total external financing sources (debt)
(3) Cash sources component percentages ratio = Cash from financing/Total sources of cash
(4) Financing policies ratio = Cash from financing activities/Total assets
Group II - Quality of Earnings
(5) Cash flow adequacy ratio = Cash from operations/Capital investments + inventory additions + dividends + debt uses
(6) Operating cash index ratio = Cash from operations/Net income
(7) Operating cash inflow ratio = Cash from operations/Total sources of cash
(8) Reinvestment (investment) ratio = Capital investments/Depreciation + Sale of assets
(9) Capital investments per dollar of cash ratio = Capital investments/Total sources of cash
(10) Productivity of assets ratio = Cash from operations/Total assets
Group III - Mandatory Cash Flows
(11) Operating cash outflow ratio = Cash used in operations/Total sources of cash
(12) Long-term debt payment ratio = Cash applied to long-term debt/Cash supplied by long-term debt
(13) Percentage of cash sources required for long-term debt = Cash applied to long-term debt/Total sources of cash
(14) Short/long-term ratios = Current debt sources/Total debt sources and Long-term debt sources/Total debt sources
Group IV - Discretionary Cash Flows
(15) Discretionary cash index ratio = Cash used for investing + Dividends/Total sources (inflows) of cash
(16) Dividend payout of cash from operations = Dividends/Cash from operations
(17) Investing policies ratio = Cash from investing activities/Total assets
(18) Cash changes to assets ratio = Total changes in cash/Total assets
Ratios 2, 3, 4, 6, 7, 10, 11, 12 were selected and used in the final bankruptcy models in this study.
Source: Ratios 4, 7, 10, 11, 17, 18 developed by authors; others from Mielke and Giacomino, 1988.
RELATED ARTICLE: Table 2
Financial Ratios Based On Conventional Accrual Accounting
Group I - Cash Flow Ratios
(1) Cash flow to sales (2) Cash flow to total assets (3) Cash flow to total debt (used as a predictor in this study) (4) Cash flow to net worth
Group II - Net Income Ratios
(5) Net income to sales (6) Net income to total assets (used as a predictor in this study) (7) Net income to total worth (8) Net income to total debt
Group III - Debt to Total Assets Ratios
(9) Current liabilities to total assets (10) Long-term liabilities to total assets (11) Current liabilities plus long-term liabilities to total assets (used as a predictor in this study) (12) Current liabilities plus long-term preferred stock to total assets
Group IV - Liquid Assets to Total Assets Ratios
(13) Cash to total assets (14) Cash and receivables to total assets (15) Current assets to total assets (16) Working capital to total assets (used as a predictor in this study)
Group V - Liquid Assets to Current Debt Ratios
(17) Cash to current liabilities (18) Cash and receivables to current liabilities (19) Current assets to current liabilities (used as a predictor in this study)
Group VI - Turnover Ratios
(20) Cash to sales (21) Accounts receivable to sales (22) Inventory to sales (23) Quick assets to sales (24) Current assets to sales (25) Working capital to sales (26) Net worth to sales (27) Total assets to sales (28) Cash interval (cash to fund expenditures for operations) (29) Defensive interval (defensive assets to fund expenditures for operations) (30) No credit interval (defensive assets minus current liabilities to fund expenditures for operations) (used as a predictor in this study).
Where:
Cash flow = Net income + Depreciation + Depletion + Amortization Net worth = Common stockholders' equity + Deferred income taxes Cash = Cash + Marketable securities Quick assets = Cash + Accounts receivable Working capital = Current assets - Current Liabilities Fund expenditures for operations = Operating expenses - Depreciation - Depletion - Amortization Defensive assets = Quick assets
Source: Beaver, 1966, 1968; Altman and Spivack, 1983.

Gale Copyright:

Copyright 1995 Gale, Cengage Learning. All rights reserved.

22 Largest Bankruptcies in World History

 

Posted in ArticlesFebruary 3rd, 2010 By Anders Ross

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A year and half ago, Lehman Brothers began the largest bankruptcyproceedings in history, joining the many other large and venerable companies that have sunk to the bottom during this economic crisis. Everyone saw that how the collapse of Lehman Brothers pushed capitalism to the brink. The Wall Street titan’s bankruptcy triggered a system-wide crisis of confidence in banks across the globe.

22 Largest Bankruptcies in World History

It’s also been said that these last few many years are marked in history as biggest global economy crisis. In fact, eight of the 22 largest bankruptcies have happened during the last three years of recessions. Here in this post, you’ll find Top 22 cases of Largest Bankruptcies in World History with brief details to give you actual idea about these Bankruptcies.

For those who don’t know what Bankruptcy means in terms of economics then “Bankruptcy” is a legally declared inability or impairment of ability of an individual or organization to pay its creditors. Creditors may file a bankruptcy petition against a debtor (“involuntary bankruptcy”) in an effort to recoup a portion of what they are owed or initiate a restructuring. In the majority of cases, however, bankruptcy is initiated by the debtor (a “voluntary bankruptcy” that is filed by the insolvent individual or organization). [Read More..]

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Largest Bankruptcies in World History

Most of you already know that bankruptcy is a way of dealing with debts where a court makes an order against you if you are unable to pay your debts. Nearly 19% of individual bankrupts are under the age of 30, In the last few years there’s been a noticeable trend in the rise of the number of young people declaring bankruptcy, with the majority of individual bankrupts being under the age of 30. Corporate Bankruptcies is somewhat different than individual Bankruptcy. Let’s have a look at some of the world’s largest corporate bankruptcies starting with “Lehman Brothers”.

01. Lehman Brothers Bankruptcy

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  • Bankruptcy Date: 09/15/2008
  • Assets: $691 billion

Lehman Brothers Holdings Inc. was a global financial-services firm which, until declaring bankruptcy in 2008, participated in business in investment banking, equity and fixed-income sales, research and trading, investment management, private equity, and private banking. It was a primary dealer in the U.S. Treasury securities market.

Lehman Brothers filed for Chapter 11 bankruptcy protection on September 15, 2008. The bankruptcy of Lehman Brothers is the largest bankruptcy filing in U.S. history with Lehman holding over $600 billion in assets. According to Bloomberg, reports filed with the U.S. Bankruptcy Court, Southern District of New York (Manhattan) on September 16 indicated that J.P. Morgan provided Lehman Brothers with a total of $138 billion dollars in “Federal Reserve-backed advances.” The cash-advances by JPMorgan Chase were repaid by the Federal Reserve Bank of New York for $87 billion on September 15 and $51 billion on September 16.

It was well known that Lehman, an Alabama cotton trader turned banking behemoth, was the biggest bankruptcy in US history. But nobody anticipated quite what would follow – a week that has become known on Wall Street as the great panic of 2008.

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02. Washington Mutual Bankruptcy

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  • Bankruptcy Date: 09/26/2008
  • Assets: $327.9 billion

On September 26, 2008, Washington Mutual, Inc. and its remaining subsidiary, WMI Investment Corp., filed for Chapter 11 bankruptcy. Washington Mutual, Inc. was promptly delisted from trading on the New York Stock Exchange, and commenced trading via Pink Sheets. All assets and most liabilities (including deposits, covered bonds, and other secured debt) of Washington Mutual Bank’s liabilities were assumed by JPMorgan Chase. Unsecured senior debt obligations of the bank of were not assumed by the FDIC, leaving holders of those obligations with little meaningful source of recovery.

On Friday, Sep. 26, 2008, Washington Mutual Bank customers in the branches were given a letter that said the combined JPMorgan Chase and Washington Mutual Banks have 5,400 branches and 14,200 ATM’s in 23 states. Washington Mutual account holders were able to continue banking as normal. Deposits held by Washington Mutual became now liabilities of JPMorgan Chase.

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03. WorldCom Bankruptcy

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  • Bankruptcy Date: 07/21/2002
  • Assets: $103.9 billion

WorldCom founded in 1963, it grew to be the second largest long-distance provider in the U.S. It was purchased by WorldCom in 1998 and became MCI WorldCom, and afterwards being shortened to WorldCom in 2000. WorldCom’s financial scandals and bankruptcy led that company to change its name in 2003 to MCI. The MCI name disappeared in January 2006 after the company was bought by Verizon.

WorldCom’s bankruptcy filing in 2002 was the largest such filing in U.S. history. The WorldCom scandal is regarded as one of the worst corporate crimes in history, and several former executives involved in the fraud faced criminal charges for their involvement. Most notably, company founder and former CEO Bernard Ebbers was sentenced to 25 years in prison, and former CFO Scott Sullivan received a five-year jail sentence, which would have been longer had he not pleaded guilty and testified against Ebbers. Under the bankruptcy reorganization agreement, the company paid $750 million to the Securities & Exchange Commission in cash and stock in the new MCI, which was intended to be paid to wronged investors.

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04. General Motors Bankruptcy

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  • Bankruptcy Date: 06/01/2009
  • Assets: $91 billion

General Motors Company, also known as GM, is a United States based automaker with headquarters in Detroit, Michigan. By sales, GM ranked as the largest U.S. automaker and the world’s second largest for 2008. GM had the third highest 2008 global revenues among automakers on the Fortune Global 500. GM manufactures cars and trucks in 34 countries, recently employed 244,500 people around the world, and sells and services vehicles in some 140 countries.

GM filed for Chapter 11 Bankruptcy protection in the Manhattan New York federal bankruptcy court on June 1, 2009 at approximately 8:00 am EST. June 1, 2009 was the deadline to supply an acceptable viability plan to the U.S. Treasury. The petition is the largest bankruptcy filing of a U.S. industrial company. The filing reported US$82.29 billion in assets and US$172.81 billion in debt.

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05. CIT Bankruptcy

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  • Bankruptcy Date: 11/01/2009
  • Assets: $71 billion

CIT Group, Inc. is a large American commercial and consumer finance company, founded in 1908. The company filed for Chapter 11 bankruptcy in 2009. The company is included in the Fortune 500 and is a leading participant in vendor financing, factoring, equipment and transportation financing, Small Business Administration loans, and asset-based lending. The company does business with more than 80% of the Fortune 1000, and lends to a million small and medium businesses. Like many other financial institutions, the New York-based small business lender spent years on a debt-fueled growth binge. But when Lehman Brothers’ failure drained the Wall Street liquidity pool, CIT was left high and dry.

The firm hastily won approval to become a bank holding company and took TARP funds, but regulators kept CIT Bank on a short leash. Starved of cash, the firm sought a second federal bailout in July but was rejected — forcing it to take a $3 billion loan, later expanded to $4.5 billion, from big bondholders.

CIT later dropped its CEO and tried a big debt swap, but it was no use. The century-old company was sunk the day the easy money dried up.

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06. Enron Bankruptcy

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  • Bankruptcy Date: 12/02/2001
  • Assets: $65.5 billion

Enron Corporation (former NYSE ticker symbol ENE) was an American energy company based in Houston, Texas. Before its bankruptcy in late 2001, Enron employed approximately 22,000 and was one of the world’s leading electricity, natural gas, pulp and paper, and communications companies, with claimed revenues of nearly $101 billion in 2000. Fortune named Enron “America’s Most Innovative Company” for six consecutive years. At the end of 2001 it was revealed that its reported financial condition was sustained substantially by institutionalized, systematic, and creatively planned accounting fraud, known as the “Enron scandal”.

The Enron scandal, revealed in October 2001, eventually led to the bankruptcy of the Enron Corporation, the dissolution of Arthur Andersen, which was one of the five largest audit and accountancy partnerships in the world. In addition to being the largest bankruptcy reorganization in American history at that time, Enron undoubtedly is the biggest audit failure.

Enron was estimated to have about $23 billion in liabilities, both debt outstanding and guaranteed loans. Citigroup and JP Morgan Chase in particular appeared to have significant amounts to lose with Enron’s fall. Additionally, many of Enron’s major assets were pledged to lenders in order to secure loans, throwing into doubt what if anything unsecured creditors and eventually stockholders might receive in bankruptcy proceedings.

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07. Conseco Bankruptcy

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  • Bankruptcy Date: 12/17/2002
  • Assets: $61 billion

Conseco, Inc. is a publicly traded holding company headquartered in Carmel, Indiana. Conseco, Inc. is not an insurance company. Conseco, Inc. is engaged in insurance and consumer finance operations through a number of subsidiary companies. As a holding company, Conseco, Inc. is a separate legal entity that is distinct and apart from its subsidiary insurance companies. On December 17, 2002, Conseco, Inc., (Conseco) along with several subsidiaries, including CIHC, Inc. and Conseco Finance Corp., filed for permission to reorganize under Chapter 11 bankruptcy protection in the U.S. Bankruptcy Court in Chicago. The company collapsed under a huge debt load resulting from a rash of acquisitions in the 1990s, including the $6 billion purchase of Green Tree, the nation’s largest lender to mobile-home buyers.

Under the terms of a tentative bankruptcy agreement, Conseco Finance Corp. will be sold to CFN Investment Holdings LLC. Conseco Finance became insolvent after it failed to make a $4.7 million payment that was due Dec. 4.

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08. Chrysler LLC Bankruptcy

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  • Bankruptcy Date: 04/30/2009
  • Assets: $39 billion

Chrysler Group LLC is a U.S. automobile manufacturer headquartered in the Detroit suburb of Auburn Hills, Michigan. Chrysler was first organized as the Chrysler Corporation in 1925. From 1998 to 2007, Chrysler and its subsidiaries were part of the German based DaimlerChrysler AG (now Daimler AG).

On April 30, 2009, President Obama forced Chrysler into federal bankruptcy protection and company announced a plan for a partnership with Italian automaker Fiat. On June 1, Chrysler LLC stated they were selling some assets and operations to the newly formed company Chrysler Group LLC. Fiat will hold a 20% stake in the new company, with an option to increase this to 35%, and eventually to 51% if it meets financial and developmental goals for the company.

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09. Thornburg Mortgage Bankruptcy

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  • Bankruptcy Date: 05/01/2009
  • Assets: $36.5 billion

Thornburg Mortgage Inc. was an American publicly traded corporation headquartered in Santa Fe, New Mexico. Founded in 1993, the company is a real estate investment trust (REIT) that originates, acquires & manages mortgages, with a specific focus on jumbo and super jumbo adjustable rate mortgages.

During the Financial crisis of 2007–2010 the company experienced financial difficulties related to the ongoing subprime mortgage crisis, and on April 1, 2009 Thornburg Mortgage, Inc. and four of its affiliates (collectively, the “Debtors”) filed petitions in the United States Bankruptcy Court for the District of Maryland seeking relief under chapter 11 of the United States Bankruptcy Code. After the sale of all remaining assets, it would no longer exist as a going concern.

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10. Pacific Gas and Electric Co. Bankruptcy

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  • Bankruptcy Date: 04/06/2001
  • Assets: $36.1 billion

This company, with its headquarters in San Francisco, was founded in 1905 and supplies natural gas and electricity to most areas of Northern California. This company did well initially and had gas power, several hydroelectric and steam plants. Under the electricity market deregulation, the company sold off its natural gas power plants and retained the hydroelectric plants. But with the selling of the gas power plants, the generating capacity went down and it had to buy power from other energy generators. The company had to buy at fluctuating prices and sell at fixed prices, which led to losses and eventually bankruptcy. In 2004, the company emerged from bankruptcy and established itself extremely well and was named one of the most profitable companies for 2005 on the Fortune 500 list.

Bankruptcy cases are always filed in the United States Bankruptcy Court and are governed by federal law. State laws are also applied when it comes to property rights. There have been several other notable bankruptcies in American history, such as Texaco, Inc. and Financial Corp. of America. While some companies survived a bankruptcy and came out strong, others faded into oblivion.

PG&E was one of the most profitable companies on the Fortune 500 list for 2005 with $4.5 billion in profits out of $11 billion in revenue.

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11. Texaco Bankruptcy

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  • Bankruptcy Date: 04/12/1987
  • Assets: $34.9 billion

Texaco was an independent company until it merged into Chevron Corporation in 2001. It began as the Texas Fuel Company, founded in 1901 in Beaumont, Texas, by Joseph S. Cullinan, Thomas J. Donoghue, Walter Benona Sharp, and Arnold Schlaet upon discovery of oil at Spindletop. For many years, Texaco was the only company selling gasoline in all 50 states, but this is no longer true. In February 1987 the Texas Court of Appeals upheld the decision. In order to protect Texaco’s assets while continuing its appeals, the company filed for protection under Chapter 11 of the United States Bankruptcy Code.

Texaco spent most of 1987 in Chapter 11 while continuing its litigation. As a result, it incurred its first operating losses since the Great Depression, finishing the year $4.4 billion in the red. After the Texas Supreme Court refused to hear an appeal, New York financier Carl Icahn began buying Texaco’s rapidly depreciating stock in an attempt to force it to settle with Pennzoil. A few weeks later Texaco agreed to pay Pennzoil $3 billion rather than appeal the decision to the Supreme Court, allowing it to begin planning for its emergence from Chapter 11.

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12. Financial Corp. of America Bankruptcy

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  • Bankruptcy Date: 09/09/1988
  • Assets: $33.8 billion

The Financial Corporation, the former holding company for the American Savings and Loan Association, filed for reorganization under Chapter 11 of the United States Bankruptcy Code on Sept. 9, 1988. Robert M. Bass Group of Fort Worth injected $350 million and took over the company as part of a Chapter 11 filing. The company eventually liquidated in February 1989.

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13. Refco Bankruptcy

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  • Bankruptcy Date: 10/17/2005
  • Assets: $33.3 billion

Refco was a New York-based financial services company, primarily known as a broker of commodities and futures contracts. It was founded in 1969 as “Ray E. Friedman and Co.” Prior to its collapse in October, 2005, the firm had over $4 billion in approximately 200,000 customer accounts, and it was the largest broker on the Chicago Mercantile Exchange. The firm’s collapse came about ten weeks after it sold shares for the first time to the public. The company was under investigation for hiding a $430 million debt and the Chief Executive Officer and Chairman; Phillip Bennett pleaded guilty of fraud and sentenced to 16 years.

After a securities fraud Refco, Inc. filed for chapter 11 for a number of its businesses, to seek protection from its creditors on October 17, 2005. At the time, it declared assets of around $49 billion, which would have made it the fourth largest bankruptcy filing in American history. This New York-based financial services company sold its regulated futures and commodities business to Man Financial in November.

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14. IndyMac Bancorp, Inc. Bankruptcy

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  • Bankruptcy Date: 07/31/2008
  • Assets: $32.7 billion

“IndyMac” was a generally accepted contraction of the formal name Independent National Mortgage Corporation. Before its failure, IndyMac Bank was the largest savings and loan association in the Los Angeles area and the seventh largest mortgage originator in the United States. The failure of IndyMac Bank on July 11, 2008, was the fourth largest bank failure in United States history, and the second largest failure of a regulated thrift. IndyMac Bank’s parent corporation was IndyMac Bancorp (Pink Sheets: IDMCQ) until the FDIC seized IndyMac Bank.

IndyMac Bancorp has filed for Chapter 7 bankruptcy, hit by the subprime-mortgage crisis. Federal regulators seized the company and run a successor company, IndyMac Federal Bank FSB. On March 19, 2009, OneWest Bank Group LLC acquired IndyMac Federal Bank for $16 billion.

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15. Global Crossing, Ltd. Bankruptcy

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  • Bankruptcy Date: 01/28/2002
  • Assets: $30.1 billion

Global Crossing Limited is a telecommunications company that provides computer networking services worldwide. It maintains a large backbone and offers transit and peering links, VPN, leased lines, audio and video conferencing, long distance telephone, managed services, dialup, colocation and VoIP, to customers ranging from individuals to large enterprises and to other carriers.

Global Crossing, Ltd. filed for chapter 11 on January 28, 2002. The result of this bankruptcy was said to be the loss of 9000 jobs. Global Crossing is an American telecommunications company based in Bermuda, providing computer networking services throughout the world. In its filing, the company listed its total assets of $22.4 billion and debts amounting to $12.4 billion. It has since recovered from bankruptcy and succeeded in turning around its performance.

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16. Bank of New England Corp. Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 01/07/1991
  • Assets: $29.7 billion

The Bank of New England Corporation was a regional banking institution based in Boston, Massachusetts, which was seized by the Federal Deposit Insurance Corporation in 1991 as a result of heavy losses in its loan portfolio and was placed into Chapter 7 liquidation. At the time, it was the 33rd largest bank in the United States, and its federal seizure bailout was the second largest on record. At its peak it had been the 18th largest bank and had over 470 branch offices. The liquidation company was named Recoll Management Corporation and its bankruptcy estate has continued to exist to pay out claims against the company.

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17. General Growth Properties, Inc. Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 04/16/2009
  • Assets: $29.5 billion

General Growth Properties is a publicly traded real estate investment trust in the United States. It is based in Chicago, Illinois at 110 North Wacker Drive, a historic building designed by architectural firm Graham, Anderson, Probst & White. The company owns and manages shopping malls throughout the United States.

GGP failed to reach a deal with its creditors; and on April 16, 2009, filed for Chapter 11 bankruptcy: the largest real estate bankruptcy since at least 1980, and the largest ever failing by a mall operator.

According to its bankruptcy filing, GGP had about $29.6 billion in assets at the end of 2008, and $27.3 billion in debt. GGP suspended its dividend, halted or slowed nearly all development projects and cut its work force by more than 20%. GGP also sold some of its non-mall assets. Chief Executive Adam Metz said “While we have worked tirelessly in the past several months to address our maturing debts, the collapse of the credit markets has made it impossible for us to refinance maturing debt outside of Chapter 11.” GGP obtained $375 million in debtor-in-possession financing. Mall gift cards remained usable.

On November 19, 2009, it has been reported that GGP may be acquired by its larger rival Simon Property Group in a deal that may be worth up to $30 billion if GGP is acquired in its entirety. Simon has hired property investment firm Cohen & Steers, as well as the Lazard investment bank and the Wachtell Lipton Rosen & Krantz law firm to explore the possibility of acquiring GGP.

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18. Lyondell Chemical Company Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 01/06/2009
  • Assets: $29.3 billion

LyondellBasell Industries (LBI) is a privately-held multinational chemical company based in the Netherlands. It was formed in December 2007 by the acquisition of Lyondell Chemical Company (the third-largest independent, US-based chemicals company, headquartered in Houston, Texas) by Basell Polyolefins for $12.7 billion. The European finance division and American operations of LyondellBasell have filed for bankruptcy effective January 6, 2009 due to facing a huge debt load and slumping demand for its products.

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19. Calpine Corporation Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 12/20/2005
  • Assets: $27.2 billion

Calpine Corporation is a Fortune 500 power company founded in 1984 in San Jose, California as a high technology provider of “clean and green energy”. Calpine’s headquarters were permanently moved from San Jose to Houston, Texas in 2009. The company’s stock was traded on the New York Stock Exchange under the symbol CPN until it was delisted on December 5, 2005 due to low share price. On 1/31/08, Calpine emerged from bankruptcy and now trades on the NYSE under the ticker symbol CPN. The company is headquartered in the Calpine Center in Downtown Houston.

On December 12, 2005 Calpine Corp., the U.S. power plant owner saddled with more than $22 billion in debt, filed for bankruptcy protection after soaring natural gas prices left it unable to make loan and bond payments. The filing in U.S. Bankruptcy Court in New York followed the ouster of top executives after they lost a fight with bondholders over using asset sale proceeds for plant fuel.

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20. New Century Financial Corporation Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 04/02/2007
  • Assets: $26.1 billion

New Century Financial Corporation was founded in 1995 by a trio of former managers at Option One Mortgage, including former CEO Brad Morrice and is headquartered in Irvine, California. New Century Financial Corporation was a real estate investment trust that originated mortgage loans in the United States through its operating subsidiaries, New Century Mortgage Corporation and Home123 Corporation.

On March 9, 2007, New Century Financial Corporation reported that it had failed to meet certain minimum financial targets required by its warehouse lenders and disclosed that it is the subject of a federal criminal investigation. New Century Financial Corporation further indicated that it does not have the cash to pay creditors who are demanding their money. On April 2, 2007, New Century Financial Corporation and its related entities filed voluntary petitions for relief under Chapter 11 of the United States Bankruptcy Code in the United States Bankruptcy Court, District of Delaware located in Wilmington, Delaware. New Century Financial Corporation listed liabilities of more than $100 million.

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21. UAL Corporation Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 12/09/2002
  • Assets: $25.1 billion

UAL Corporation is an airline holding company, incorporated in Delaware with headquarters in Chicago, Illinois. UAL owns and operates United Air Lines, Inc., one of the world’s largest air carriers, and a founding member of the Star Alliance. After been many ups and downs the company ended 2001 with a record loss of $2.1 billion.

As losses continued in 2002, Glenn Tilton, a former Texaco CEO with experience operating a company in bankruptcy, was brought in by UAL’s Board of Directors to try and prevent bankruptcy, or, if needed, successfully guide the company through a bankruptcy process. Tilton was appointed Chairman, President, and CEO of UAL Corporation and United Air Lines, Inc. in September 2002. Tilton sought wage cuts from employees and applied for a U.S. government loan guarantee to avoid filing for bankruptcy. By early December, the company had reached agreements with most of its unions for wage reductions, but its loan application was rejected Dec. 4. Unable to secure additional capital, UAL Corporation filed for chapter 11 bankruptcy protection on December 09, 2002. The ESOP was terminated, although by then its shares had become virtually worthless. Blame for the bankruptcy has fallen on the events of September 11, which triggered financial crisis in all the major North American airlines, coupled with the economic slowdown that was underway. UAL quickly received debtor-in-possession (DIP) financing to allow it to continue “business as usual” while it reorganized its debt, capital and cost structures.

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22. Delta Air Lines Bankruptcy

instantShift - Largest Bankruptcies in History

  • Bankruptcy Date: 09/14/2005
  • Assets: $21.8 billion

Delta Air Lines, Inc. is a United States airline based and headquartered in Atlanta, Georgia. It is the world’s largest airline in terms of passenger traffic and fleet size. Delta operates an extensive domestic and international network, spanning North America, South America, Europe, Asia, Africa, the Middle East, the Caribbean, and Australia.

The Company has been facing financial difficulties for a long time and ever since 2004, tried to stave off bankruptcy by restructuring the company with job cuts and expansion plans. However, in September 2005, it filed for bankruptcy for the first time in its 76-year history. The company cited high jet fuel prices and high labor costs as the two main factors. Delta was in $20.5 billion debt at the time of filing. On April 30, 2007, the airlines emerged from bankruptcy protection as an independent carrier.

Managing your business’s cash flow

Creating a reliable cash flow system is vital to the success of any business. Learn how you can maintain enough cash on hand to keep your business solvent and growing.

A healthy cash flow is an essential part of any successful business. Some business people claim that a healthy cash flow is even more important than your business's ability to deliver its goods or services,

That may be placing a bit too much importance on your cash flow, but consider this — if you fail to satisfy a customer and lose that customer's business, you can always work harder to please the next customer. But if you fail to have enough cash to pay your suppliers, creditors or your employees, you're out of business.

Maintaining a viable cash flow system relies on six important aspects:

  • Understanding cash flow is the first step in effectively managing your cash flow. There's more to it than just a fancy term for the movement of money into, and out of, your business checking account.
  • Analyzing your cash flow will help you spot some of the problem areas in the cash flow cycle of your business. As in any good analysis, you need to look individually at each of the important components that make up the cash flow cycle to determine if it's a problem area or not.
  • Developing a cash flow budget provides a good way of predicting your business's cash flow for the next month, six months or even the next year.

Included among the Business Tools is a cash flow budget worksheet. The worksheet is an Excel template that can be used over and over again after you download it once.

The worksheet is set up to be used for projecting your cash flow for six months. We've formatted the worksheet and put in most of the cash inflow and outflow categories for you. All you have to do is put in your numbers and print it.

Once you've downloaded the worksheet, feel free to modify the worksheet to fit your own needs.

 

  • Improving your cash flow will, without a doubt, make your business more successful. Accelerating your cash inflows and delaying your cash outflows are key factors for improving and managing your cash flow. The cash flow budget is also a handy tool to use in the improvement and management of your cash flow.
  • Filling your cash flow gaps: from time to time, almost every business experiences the need for more cash than it has. If you find yourself in this position, you may have to borrow money to fill the gap.
  • Handling any cash surplus is just as important as the management of money into and out of your cash flow cycle. With the proper management of your cash flow, you might find yourself with a little extra cash, on which you can earn investment income.

Understanding How Cash Flow Works

 

In its simplest form, cash flow is the movement of money in and out of your business. It could be described as the process in which your business uses cash to generate goods or services for the sale to your customers, collects the cash from the sales and then completes this cycle all over again.

Keeping Inflows Flowing

Inflows are the movement of money into your cash flow. It's, understandably, the cash flow component every small business owners wants to grow. Inflows are most likely from the sale of your goods or services to your customers. If you extend credit to your customers and allow them to charge the sale of the goods or services to their account, then an inflow occurs as you collect on the customers' accounts. The proceeds from a bank loan also count as cash inflow.

Delaying Outflows as Long as Possible

Outflows are the movement of money out of your business. It's, also understandably, the cash flow component every small business owner wants to decrease. Outflows are generally the result of paying expenses. If your business involves reselling goods, then your largest outflow is most likely to be for the purchase of retail inventory. A manufacturing business's largest outflows will mostly likely be for the purchases of raw materials and other components needed for the manufacturing of the final product. Purchasing fixed assets, paying back loans and paying accounts payable are also cash outflows.

Why Managing Your Cash Flow Matters

As you likely already surmised, optimizing your cash flow is crucial because: 

  • Smart cash flow management is vital to the health of your business. Hopefully, each time through the cycle, a little more money is put back into the cash flow cycle than flows out.
  • Our case study illustrates what can happen to your business if you don't carefully monitor your cash flow, and take corrective action when necessary.
  • Your profit is not the same as your cash flow. It's possible to show a healthy profit at the end of the year, and yet face a significant money squeeze at various points during the year.

The Ideal Cash Flow Situation

If you were able to do business in a perfect world, you'd probably like to have a cash inflow (a cash sale) occur every time you experience a cash outflow (pay an expense). But you know all too well that business takes place in the real world, and things just don't happen like that.

Instead, cash outflows and inflows occur at different times and never actually occur together. More often than not, cash inflows lag behind your cash outflows, leaving your business short of money. Think of this money shortage as your cash flow gap. The cash flow gap represents an excessive outflow of cash that may not be covered by a cash inflow for weeks, months or even years. (Don't worry—you're not a bad entrepreneur if your business isn't cash flow positive immediately.)

Managing your cash flow allows you to narrow or completely close your cash flow gap. It does this by examining the different items that affect the cash flow of your business. Examining your cash inflows and outflows, and looking at the different components that have a direct effect on your cash flow, allows you to answer the following questions:

  • How much cash does my business have?
  • How much cash does my business need to operate, and when is it needed?
  • Where does my business get and spend its cash?
  • How do my income and expenses affect the amount of cash I need to expand my business?

If you can answer these questions, you're managing your cash flow!

Case Study: The Cash Flow Gap

This example shows how easily a cash flow gap—a shortage of cash caused by the mismatching of cash outflows and cash inflows—can occur in a small business.

For example, John makes custom furniture for professional decorators and furniture retail shops. In addition to himself, John has two other employees. John pays himself and his employees every other week (bi-weekly). When a customer places an order for a piece of furniture, John receives a 10 percent down payment of the total sales price. The customer is then billed for the remainder of the sale after the furniture is completed and delivered.

The total sales price of a recently ordered dining room set is $10,000. The material needed for this job is priced at $2,500 and will come from one supplier. This supplier offers a 2 percent discount if John pays for the supplies within 10 days after receiving them. John always takes advantage of early payment discounts.

The following graphic, illustrating the cash flow effects of the sale from start to finish, will help you identify John's cash flow gap.

 

Breaking down the sale of the dining room set, and tracing it step-by-step through the cash flow, identifies John's cash flow gap. In John's case, a cash flow gap starts on day 13 and continues to grow, reaching $4,450 just prior to collecting the customer's account. Although this example has been simplified, it's typical of the cash flow gap that occurs in many small businesses.

The cash flow gap creates the need for effective cash flow management. Effective cash flow management can help reduce the amount of time between John's cash inflows and cash outflows. This in turn, will help reduce or close John's cash flow gaps.

Cash Flow Management Illustrated

If you were able to do business in a perfect world, you'd probably like to have a cash inflow (a cash sale) occur every time you experience a cash outflow (pay an expense). But you know all too well that business takes place in the real world, and things just don't happen like that.

Instead, cash outflows and inflows occur at different times, and never actually occur together. More often than not, cash inflows lag behind your cash outflows, leaving your business short of money. Think of this money shortage as your cash flow gap. The cash flow gap represents an excessive outflow of cash that may not be covered by a cash inflow for weeks, months or even years. (Don't worry—you're not a bad entrepreneur if your business isn't cash flow positive immediately.)

Managing your cash flow allows you to narrow or completely close your cash flow gap. It does this by examining the different items that affect the cash flow of your business. Examining your cash inflows and outflows, and looking at the different components that have a direct effect on your cash flow, allows you to answer the following questions:

  • How much cash does my business have?
  • How much cash does my business need to operate, and when is it needed?
  • Where does my business get and spend its cash?
  • How do my income and expenses affect the amount of cash I need to expand my business?

If you can answer these questions, you're managing your cash flow!

Case Study: The Cash Flow Gap

This example shows how easily a cash flow gap can occur in a small business. A cash flow gap is a shortage of cash caused by the mismatching of cash outflows and cash inflows.

For example, John makes custom furniture for professional decorators and furniture retail shops. In addition to himself, John has two other employees. John pays himself and his employees every other week (bi-weekly). When a customer places an order for a piece of furniture, John receives a 10 percent down payment of the total sales price. The customer is then billed for the remainder of the sale after the furniture is completed and delivered.

The total sales price of a recently ordered dining room set is $10,000. The material needed for this job is priced at $2,500 and will come from one supplier. This supplier offers a 2 percent discount if John pays for the supplies within 10 days after receiving them. John always takes advantage of early payment discounts.

The following graphic, illustrating the cash flow effects of the sale from start to finish, will help you identify John's cash flow gap. (Click on each of the blue or yellow bars to see a detailed explanation of business events affecting John's cash flow each week.)

 

Breaking down the sale of the dining room set, and tracing it step-by-step through the cash flow, identifies John's cash flow gap. In John's case, a cash flow gap starts on day 13 and continues to grow, reaching $4,450 just prior to collecting the customer's account. Although this example has been simplified, it's typical of the cash flow gap that occurs in many small businesses.

The cash flow gap creates the need for effective cash flow management. Effective cash flow management can help reduce the amount of time between John's cash inflows and cash outflows. This in turn, will help reduce or close John's cash flow gaps.