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PurposeThis paper sets out to analyze the current global financial crisis that originated in the US subprime mortgage market through the lens of the Kindleberger‐Aliber‐Minsky (KAM) paradigm as set forth in Kindleberger and Aliber's Manias, Panics and Crashes, to first examine the bubble's origins in the displacement caused by the internet collapse, the subsequent US recession, and the aggressive lowering of US interest rates. It shows how these events, combined with other technological and regulatory factors, resulted in a US housing bubble fueled by the aggressive securitization of mortgages by many large financial institutions, a reduction in their credit standards, and a lack of regulatory oversight. In this way it assesses the prime players in the process in terms of motivation and performance.Design/methodology/approachThe paper explores how the process peaked and began to unravel as cash flows at the base of the financial pyramid built through securitization slowed. Once the supporting cash flow came under pressure and was questioned, several major players went bankrupt or took tremendous losses. It became apparent that risk and innovation had been improperly balanced, a prime characteristic of the KAM paradigm. Indeed, greed, innovation, and technology had combined to substantially reduce credit quality and increase leverage, vastly expanding the likelihood of a liquidity crisis and a substantial drop in the value of asset‐backed securities.FindingsThe analysis then examines why this effect had significant global dimensions, unlike, for example, the Japanese real estate and stock market collapse or the US internet boom and bust. The analysis also shows how market reactions have been in line with what might be expected under the KAM paradigm. It also conforms with what Robert Shiller and Edward Gramlich anticipated and with normal bank behavior in a credit crisis.Originality/valueThe paper assesses the policy responses to the crisis and their likely success under a KAM paradigm analysis. The proposed remedies already include the aggressive fiscal and lender of last resort monetary responses typical of the KAM paradigm but regulatory measures too. Further, as KAM notes, almost all booms and crashes involve scandals and scams. So not surprisingly there has been growing recourse to the courts seeking criminal and civil remedies. Also typical of such a dramatic boom and bust, governments are examining regulatory and legislative actions to address the current difficult economic and credit situation and to make sure that similar things do not occur in the future. But politics and a US presidential election are driving significant differences in approach. Under these circumstances what can the lens of the KAM paradigm tell us about the actions taken or proposed and what is or is not likely to work?

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper describes an approach for simulating and appropriately valuing complex E&P projects containing multiple prospects. The approach uses a Monte Carlo simulation model, which is described, that simulates a play containing multiple prospects. The play evaluated can consist of pure exploration prospects, or may contain a mixture of discovered reserve opportunities (DRO's) and exploration prospects. Resource (reserve) size distributions, dependent geologic prospect risks, risk tolerance, stand-alone commercial threshold sizes, and tie-back thresholds are some of the key drivers of the play simulation.The simulation generates expected commercial reserve levels and commercial risks for each prospect included in the play, as well as an overall project commercial reserve distribution and risk level. In addition, and more importantly, discrete development scenarios for high (P90), mid (P50), and low (P10) reserve cases can be generated. These development scenarios can then be used to determine a valuation range for the prospects.The value of this approach is that it provides a consistent methodology to generate a range of discrete development scenarios that span the reasonable range of project successcase expectations. Development plans for those scenarios can then be applied and the scenarios can be deterministically evaluated to determine the range of the project's economic value. This hybrid approach of a stochastic play model combined with deterministic economic evaluations avoids some of the common pitfall of most pure stochastic or pure deterministic approaches.Methodology is also described for logically grouping discrete prospects into "super-prospects" for the purpose of evaluating projects that contain an unwieldy number of small prospects.

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