An Introduction of Jameel’s Advanced Stressed Economic and Financial Crises Models and to Dramatically Increasing Markets Confidence and Drastically Decreasing Markets Risks

Jamilu Auwalu Adamu


Quantitative Financial Risk Management has tremendously change the way markets’ Practitioners, Regulators and Supervisors, Investors, Academics, Economists, Politicians, Policy Makers and Civil Society perceived financial and commodities markets. The generous invention of Black – Scholes – Merton (1973) Formula is of course the advanced turning point. The Normality Assumption (which causes overreliance, overconfidence, overvaluation or undervaluation of assets, overleveraging and underestimation of risks by the market participants) is the fundamental pillar in question, because returns are not normally distributed, returns have fat tails consisting bubbles and crashes for instance like IT-bubble, stock market bubble, housing bubble and commodities bubbles. Nassim N. Taleb (2007) called these Black Swans or Low – Probability, High – Impact events. The formulae in question receives serious criticisms especially in the United States of America to the extent of Tim Harford (2012) published an article entitled ‘The Black – Sholes: The Maths Formula linked to the Financial Crash’. Jamilu (2015) using his criterion and Advanced Methods attempted to capture the popular Black Swans (Low – Probability, High – Impact). The aim of this paper is to use Jameel’s Advanced Stressed Methods and Criterion to incorporate fat –tailed effects into the existing stochastic Economic and Financial Models thereby tremendously increasing markets confidence and drastically decreasing markets risks. Based on the various presentations of results and graphs obtained, it can be observed, the Jameel’s Advanced Stressed Economic and Financial Models can traces the trajectories of the past and future Economic and Financial Crises given reliable, accurate, sophisticated, valid and sufficient models’ independent variables.

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International Journal of Social Science Studies   ISSN 2324-8033 (Print)   ISSN 2324-8041 (Online)

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