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This paper aims to explain the weaknesses and inconsistencies inherent in the Dodd-Frank Act of 2010 (USA).

The approach is entirely theoretical and multi-disciplinary (and relies on some third-party empirical research), and it consists of a literature review, critique and the development of theories which are applicable across countries.

The Dodd-Frank Act is inefficient and inadequate as a response to the global financial crisis. The Dodd-Frank Act has not resulted in significant economic growth and has increased transaction costs and compliance costs for both government agencies and financial services companies.

The author developed the theories introduced in the paper.

There’s a broad, smiley, grin in the face of “Jack”, the corporate mascot of Jack in the Box (JBX), one of the leading fast‐food restaurant chains in the USA. And why wouldn’t he be smiling, being the figurehead of a company that has got more than 1,940 outlets in 17 states and 44,000 employees and is part of an industry which is still growing – and fast? Many more franchises will follow to satisfy an increasing demand for fast food. Whatever economies people make in other aspects of their daily life, food is not a luxury and changing lifestyles and work patterns have played a part in pushing up demand for the services provided by JBX and competitors such as McDonald’s, Burger King and others.

This paper analyzes economic, legal, behavioral and public policy issues pertaining to the accounting for employee stock options. The paper explains why employee stock options (ESOs) are superior to other forms of incentive compensation, why ESOs in their present form are inefficient and why particular accounting, legal and tax treatments will provide the optimal results for the economy, the government, management/employees and shareholders. The issues discussed in this article are relevant in ESO accounting, regulation of ESOs, incentive compensation, human resources analysis, tax policy, corporate governance, fraud, valuation of companies, derivatives regulation, behavioral analysis of law/rules, portfolio management and management strategy.

To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision‐making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theory; and develop the foundations for a new model of decision making and risk named “belief systems”.

Critiques existing academic work in different contexts. Analyzes the shortcomings of various measures of risk, and group decision making, which was not addressed in developing Prospect Theory and Cumulative Prospect Theory. Develops the characteristics of a mew model for decision making and risk named “belief systems”, and then differentiates it from belief networks.

Decision making is a multi‐factor, multi‐dimensional process that often requires the processing of information, and thus, it is inaccurate to impose rigid models in decision making; the existing metrics for quantifying risk are inadequate; Prospect Theory and Cumulative Prospect Theory were developed using questionable methods and data, and are impractical; the analysis of probabilistic insurance and most of the theories and “effects” developed by Kahneman and Tversky's articles are invalid and impractical; Prospect Theory, Cumulative Prospect Theory, Expected Utility Theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making; risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative and qualitative factors; belief systems can better account for the multi‐dimensional characteristics of risk and decision making.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models; Prospect Theory and Cumulative Prospect Theory are abstract, rigid, and are not practical models for decision making; and existing market‐risk models are inaccurate, and thus the international financial system may be compromised.

The issues discussed are relevant to government regulators, central banks, judges, risk managers, executives, derivatives regulators, stock exchange regulators, legislators, psychologists, boards of directors, finance professionals, management science/operations research professionals, health‐care‐informatics professionals, scientists, engineers, and people in any situation that requires decision making and risk assessment.

The purposes of this article are to evaluate models of stock market risk developed by Robert Engle, and related models (ARCH, GARCH, VAR, etc.); to establish whether prospect theory, cumulative prospect theory, expected utility theory, and market‐risk models (ARCH, GARCH, VAR, etc.) are related and have the same foundations.

The author critiques existing academic work on risk, decision making, prospect theory, cumulative prospect theory, expected utility theory, VAR and other market‐risk models (ARCH, GARCH, etc.) and analyzes the shortcomings of various measures of risk (standard deviation, VAR, etc.).

Prospect theory, cumulative prospect theory, expected utility theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making. Risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative, and qualitative factors. Belief systems (a new model developed by the author) can better account for the multi‐dimensional characteristics of risk and decision making. The market‐risk models developed by Engle and related models (ARCH, GARCH, VAR, etc.) are inaccurate, do not incorporate many factors inherent in stock markets and asset prices, and thus are not useful and accurate in many asset markets.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models. Existing market‐risk models are inaccurate – many international banks, central banks, government agencies, and financial institutions use these models for risk management, capital allocation, portfolio management, and investments, and thus the international financial system may be compromised.

The critiques, ideas, and new theories in the article were all developed by the author. The issues discussed in the article are relevant to a multiplicity of situations and people in any case that requires decision making and risk assessment.

The US restaurant industry and the food‐service industry have undergone tremendous changes during the last decade owing to demographic changes, changes in the family structure, the increase in the number of working women and senior citizens, advances in technology (inventory management, customer order processing, accounting/financial systems, etc.), availability of financing, changes in the real estate industry (location, negotiation with malls, relationships with developers, etc.), intense competition, the growth in the types and number of marketing channels (including the Internet), increasing number of drive‐through customers, employee training requirements, changes in labor laws, the rate of implementation of technology, changes in food sourcing/purchasing, the growth of the franchising business model, and increasing regulation. These factors have combined to shape the strategic, legal, economic and operational considerations that executives and decision makers should thoroughly understand. This article discusses the issues and challenges facing one company in these two industries and how management and banks have reacted, and then explains strategies for the future. Also discussed are relevant considerations for financial sponsors and companies. Most data and analysis are as of April 2000.

Corporate accountability and quality of corporate disclosure have impacted on many companies and banks, particularly those grown through mergers and acquisitions (M&A) and companies have had to restate their financial statements. The growth of service and technology companies (particularly by M&A) presents numerous public policy, legal, regulatory and accounting issues. Some of these companies have substantial intangible assets and the accounting for M&A and investments can be manipulated to affect reported assets and earnings. The exchange of securities and conflicts of interest in such transactions can affect financial statements – all of these factors can distort strategic planning, legal analysis, performance analysis and credit analysis. Fraudulent conveyance has typically not been considered in detail in many real life transactions (processed by law firms, the SEC, accounting firms and banks), even though it is the major means of unfair and illegal wealth transfer and fraud in corporate transactions. This paper highlights some of these issues, and illustrates the role and benefits of proper legal analysis in corporate transactions, and the convergence of corporate financial analysis and legal analysis and tax/accounting analysis.

To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision‐making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theory; and develop the foundations for a new model of decision making and risk named “belief systems”.

Critiques existing academic work in different contexts. Analyzes the shortcomings of various measures of risk, and group decision making, which was not addressed in developing Prospect Theory and Cumulative Prospect Theory. Develops the characteristics of a mew model for decision making and risk named “belief systems”, and then differentiates it from belief networks.

Decision making is a multi‐factor, multi‐dimensional process that often requires the processing of information, and thus, it is inaccurate to impose rigid models in decision making; the existing metrics for quantifying risk are inadequate; Prospect Theory and Cumulative Prospect Theory were developed using questionable methods and data, and are impractical; the analysis of probabilistic insurance and most of the theories and “effects” developed by Kahneman and Tversky's articles are invalid and impractical; Prospect Theory, Cumulative Prospect Theory, Expected Utility Theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making; risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative and qualitative factors; belief systems can better account for the multi‐dimensional characteristics of risk and decision making.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models; Prospect Theory and Cumulative Prospect Theory are abstract, rigid, and are not practical models for decision making; and existing market‐risk models are inaccurate, and thus the international financial system may be compromised.

The issues discussed are relevant to government regulators, central banks, judges, risk managers, executives, derivatives regulators, stock exchange regulators, legislators, psychologists, boards of directors, finance professionals, management science/operations research professionals, health‐care‐informatics professionals, scientists, engineers, and people in any situation that requires decision making and risk assessment.