Financial Statement Analysis and Evaluation (1st part)

Slide 11

"Part two: The basic financial statements take a hard look at the information disclosed in balance sheet ( stato patrimoniale ) income statement ( rendiconto economico ) and statement of cash flow ( rendiconto di flusso di cassa ) . Under scrutiny, terms such as value and income begin to look murried than they appear when considered in the abstract. "Even cash flow ( flusso di cassa) a concept commonly tought to convey clarification , is vulnerable to stratagems designed to manipulate the perception of investor and creditors."

MATLAB fraud detection source code

% Create fraud detection model based on training datafraudModel = TreeBagger(nTrees,xTrain,yTrain); % Apply fraud detection model to new dataisFraud = predict(fraudModel, xNew); Toolbox used , advanced statistics to compute individual fraud indicators, and machine learning to create the classification model. In addition to the bagged decision trees discussed here, many other machine learning techniques are available in MATLAB, Statistics and Machine Learning Toolbox, and Deep Learning Toolbox™, enabling you to extend or alter the proposed solution according to the requirements of your project.

Big Baths

A big bath is an unethical accounting tactic whereby income in a bad year is made to look even worse than it actually is. Often undertaken in a bad earnings year, this tactic is intended to artificially inflate future earnings figures. Big Bath in accounting is an earnings management technique whereby a one-time charge is taken against income in order to reduce assets, which results in lower expenses in the future. The write-off removes or reduces the asset from the financial books and results in lower net income for that year.

Cash Flows

Analyze cash flows including annuities, amortization and depreciation, present and future value, and rates of return Financial Toolbox provides a collection of financial tools to compute cash flows and sensitivities for annuities, amortization and depreciation, present and future value, and rates of return.

Slide #10

Any company employing it would turn away many potential customers who posed almost no threat of delinquency. Even Cutoff Point B which allows more business to be written but produces no credit losses (zero Perdita) is less than optimal.

2nd lesson Slide #12

Aside from accounting rules, cash flow, and definitions of standard ratios, analysts must consider the motivation of corporate managers, as well as the dynamics of the organizations in which they work. Neglecting these factors will lead to false assumption about the underlying intent of issuers communications with users of financial statements.

Balance Sheet

Assets = Liabilities + SHE

Rudimentary

Basic, fundamental, not elaborated or perfected

Bona Fide Profit versus Accounting profit

Bona Fide Profits = Rev-Costs After a company earns a bona fide profit, its owners are wealthier than they were beforehand. There can be no bona fide profit without an increase in wealth. Bona fide profits are the only kind of profits that truly matter in financial analysis. An accounting profit is whatever the accounting rules say it is.

What Is Expected Credit Loss?

Credit and regulatory risk teams quantify the expected loss using: Asset classification, through statistical and machine learning methods Macroeconomic modeling Scenario generation and scenario analysis Instrument pricing and risk sensitivity Stochastic modeling of default and recovery Automated reporting, reflecting point-in-time model and data selection

MATLAB Fraud Detection

EXAMPLE: We will use monthly returns data from January 1991 to October 2008 from three hedge funds: - Gateway Fund - Growth Fund of America - Fairfield Sentry Fund The Fairfield Sentry Fund is a Madoff fund known to have reported fake data. As such, it offers a benchmark for verifying the efficacy of fraud detection mechanisms.

What is expected credit loss?

Expected credit loss is a probability-weighted estimate of credit losses during the expected life of a financial instrument. The estimation method requires point-in-time (PIT) projections of probability of default (PD), loss given default (LGD), and exposure at default (EAD). Most credit instruments have a quantifiable risk of default. Accounting for credit risk in the entire portfolio of instruments must consider the likelihood of future impairment and is commonly measure through expected loss and lifetime expected credit loss.

Exposures at Default

Exposure at default is the total value of a loan that a bank is exposed to when a borrower defaults. For example, if a borrower takes out a loan for $100,000 and two years later the amount left on the loan is $75,000, and the borrower defaults, the exposure at default is $75,000.

Face Value and Present Value

Face value is the value of the item immediately, without regard for the future. For example, the "face value" of a $20 dollar bill is 20 dollars. I remember this because it is, literally, written on the face of the money. The present value includes a valuation of the future of that money.

Info about MATLAB

Financial professionals worldwide use MATLAB and other MathWorks tools to rapidly develop financial models and freely deploy customized algorithms to decision makers such as investment managers, actuaries, and traders. Find out how MATLAB can help you significantly reduce the time it takes to analyze financial data and develop custom financial models.

Further Cash Flows MATLAB Functions

Functions - Annuities - Amortization and Depreciation - Present and Future Value - Rates of Return - Currency and Price Conversion

Hedge Funds

Hedge funds pool investors' money and invest the money in an effort to make a positive return. Hedge funds typically have more flexible investment strategies than, for example, mutual funds.

Slide #4

In addition flat out financial reporting fraud continued to flourish outside the U.S. According to the legislation a top corporate executive who knowingly signs of on a false financial report is subject to a 10 years prison term and a fine of up to 1 million. The penalties raise to 20 year and $5 million if the misconduct is willful. In practice, few executives were convicted or even charged with false certification in the first decade after passage of Sarbanes-Oxley."

Definition of Profit

In view of all these essential economic functions, one might suppose that users of financial statements would have long since devised a universally agreed upon definition of profit. This is the case, however, only at the following, extremely rudimentary level: Profit = Revenue - Costs Profit = Revenue - Costs What is revenue? Which costs count? Or more precisely which costs count now, and which count later ? Because these questions can be answered in many ways, countless definition of profit are in common use. For analyst of financial statement, the most important distinction to understand is between bona fide profits and accounting profits.

Sarbox (SOX)

Is a federal law enacted in July 2002 by the United States government. The Sarbanes-Oxley Act, also knows as the Public Company Accounting Reform and Investor Protection Act of 2002 and commonly called Sarbanes-Oxley. "Government responded to the outrage over financial frauds by enacting the Sarbanes-Oxley Act of 2002. Under its provisions, a company's chief executive officer and chief financial officer were required to attest to the integrity of the financial statements. Sarbanes-Oxley has had a profound effect, True, the fourth edition of Financial Statement Analysis examined several major financial reporting frauds that came to light later than 2002.

Credit Managers who seek to maximize profits aim for Cutoff Point C.

It represent a level of credit extension at which losses on receivable occurs but are slightly more than offset by the profits derived from incremental customers.

2nd lesson slide #13

Moreover, analysts may make incorrect interferences about the quality of their own work if they fail to understand the working of their own organizations. If a conclusion derived from thorough financial analysis is deemed wrong, it is important to know whether that judgement reflects a flawed analysis or a higher-level decision to override analysts' recommendations.

Slide #15

Part three: "a closer look at profits" We zero in on the lifeblood of the capitalist system. Our scrutiny of profit highlights the multiple ways in which earnings are exaggerated or even fabricated.

Income Statement

Revenues - Expenses = Net Income

Slide #9

Since misbehavior or fraud in hedge funds manifests itself mainly in misreported data, academic researchers have focused on devising methods to analyze and flag potentially manipulated fund returns. We compute metrics introduced by Bollen and Pool2 and use them as potential indicators for fraud on the reported hedge fund returns. For example: - Discontinuity at zero in the fund's returns distribution - Low correlation with other assets, contradicting market trends - Unconditional and conditional serial correlation, indicating smoother than expected trends - Number of returns equal to zero - Number of negative, unique, and consecutive identical returns - Distribution of the first digit (Does it follow Benford's law?) and the last digit (Is it uniform?) of reported returns

Slide #19

Small Profits and Big Baths The securities and Exchange Commission and the Financial Accounting Standards Board prohibit corporations from going too far in prettifying their profits to pump up their share prices. These regulators refrain from indicating exactly how far is too far , however. Inevitability , corporations hold diverse opinions on matters such as the extent to which they must divulge bad news that might harm their stock market valuations.

What is Revenue?

Suppose for example, that an entrepreneur launches a restaurant franchising business. The fictitious Salsa Meister International does not operate any Salsa Meister restaurant. It merely sells franchises to other entrepreneurs and collects franchise fees. The franchised restaurant, sad to say, consistently lose money. That fact has no bearing on Salsa Meister International's accounting profit, however, the restaurants 'operations are not part of Salsa Meister International, their revenues are not its revenues, and their costs are not its costs. Salsa Meister Internationals income consists entirely of franchise fees, which it earns by rendering the franchisees such services as developing menus, providing accounting systems, training restaurant employees, and creating advertising campaigns. An astute analyst will ask how money -- losing franchisees come up with cash to pay fees.

The purpose of Financial Reporting

The following case study demonstrates how an overly trusting user of financial statements can be missed. MATTEL'S ACCOUNTING GAMES : On August 2, 2019 , PricewaterhouseCoopers(PwC) , Mattel's outside auditor , received a whistleblower letter suggesting that accounting errors had occurred in earlier periods and questioning whether PwC was truly independent. The toymaker disclosed the letter's receipt on August 8, 2019, and the following day its stock plunged by 15.8 percent while the Standard & Poor's 500 Index registered a minor decline of 0.7 percent. Mattel's board directed the audit committee to investigate the matter.

Things to know about Profit

The necessity of producing profits imposes order and discipline on business organizations. It fosters cost-reducing innovations, which in turn promote the efficient use of scarce resources. The profit motive also encourages saving and risk taking, two indispensable elements of economic development. Finally, profitability is a yardstick by which business people can measure their achievements and justify their claim to compensation,

The purpose of Financial Reporting

The primary goal in financial reporting is the dissemination of financial statements that accurately measure the profitability and the financial condition of a company. The purpose of financial reporting is to obtain cheap capital.

Which costs count

The willingness to take accounting profits at something other than face value is an essential element of genuinely useful financial statement analysis. It is likewise imperative that analysts exercise care in deciding what to substitute for a GAAP definition of profit. Once they leave the GAAP world of agreed -upon rules, analysts enter a free marker of ideas, where numerous parties hawk competing versions of earnings Despite the critical importance of measuring profit , business people cannot produce a definition that is satisfactory in every situation . Even the simple formula of revenue minus costs founder on the malleability on accounting - based revenues and costs. Financial analysts must walk a fine line. On the one hand, they must not lose touch with economic reality by hewing on accounting orthodoxy. On the other hand, accept the version of reality that seekers of cheap capital would like to foist on them. Analysis should be skeptical of claims that a business alleged cost are mere accounting conventions and that anyone who believes otherwise is a fuddy-duddy

2nd Lesson Slide #9

This example shows how to work with consumer (retail) credit panel data to visualize observed probabilities of default (PDs) at different levels. It also shows how to fit a Cox proportional hazards (PH) model, also known as Cox regression, to predict PDs. In addition, it shows how to perform a stress-testing analysis, how to model lifetime PDs, and how to calculate the lifetime expected credit loss (ECL) value using portfolioECL.

Gross Profit

Total Revenue - COGS

Probability of Default

is the likelihood that a loan will not be repaid and will fall into default. It must be calculated for each borrower

Slide #2 of 1st week

- A FSAE Gov perspective following the several accounting scandals by financial statements - The US Government responded to the outrage over financial frauds

Fraud Analytics?

- Fraud analytics are technical methods to detect and monitor fraud, which occurs when people intentionally act secretly to deprive another of something of value. Fraud analytics can take place either before the transactions are completed (fraud prevention) or after they occur (fraud detection). Fraud analytics help organizations reduce costs associated with fraud. Financial fraud can be corporate, such as when a financial statement is falsified, when hedge funds falsely report returns, or when stock markets manipulation jeopardizes regulation compliance. Fraud can also happen in healthcare and insurance and through methods such as identity theft (credit cards), money laundering, and tax evasion. Hedge fund returns manipulation is more prone to fraud, due to fewer regulations. It results from misbehavior when managers have discretion in valuing illiquid investments or commit outright fraud. The most commonly used techniques in fraud analytics are artificial intelligence (AI), machine learning, deep learning, and statistical analysis.

MATLAB fraud detection

You can apply these techniques with MATLAB® to detect which banking transactions are potentially fraudulent. Machine learning (supervised or unsupervised) gives you an indication of the likelihood of fraud with a high degree of accuracy at detecting anomalies. In supervised learning (regression, classification), historical transactions are labeled as fraudulent or genuine. Then these records are used to train an algorithm that infers a function able to classify a future transaction as either legitimate or not. A typical example in regression is to predict the amount of fraud. Unsupervised learning does not require historical observations to be labeled as fraudulent or non-fraudulent and is useful for companies that don't have historical fraud data available. Data mining and pattern recognition are used to detect meaningful patterns or trends among the data that relate to fraud. Statistical analysis consists of an analytical framework to calculate statistical parameters to identify outliers that could indicate fraud patterns. Finally, Benford's law could be used as an indicator to detect fraud. Other indicators used for fraud analytics include return-based and text-based. For more on fraud analytics, see Statistics and Machine Learning Toolbox™, Deep Learning Toolbox™, and Text Analytics Toolbox™.

Technical Methods

of or concerned with the actual doing or use of something rather than with theory and ideas.

Def of Amortization

the action or process of gradually writing off the initial cost of an asset.

Loss Given Default

value a bond investor will lose if the issuer defaults