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An Introduction to Risk - by Vikram Sankhala
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An Introduction to Risk - by Vikram Sankhala


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A brief introduction to Uncertainty

A brief introduction to Uncertainty

  • Dear Quant,
    You may like to develop this slide presentation into overview of risk management by including aspects of game theory, chaos, rationality, decision theory etc. This will provide glimpses of efficacious mathematical approach to arrive at complex economical decision in a given environment for uninitiated. And, bring a logical conclusion to the relevance of probability in business processes. An avoidance or mitigation of risk is solution to the problem being identified by quantifying risk/ uncertainty or the most probable outcome of an event. To quote a recent example, it was essential for Ms. Angelina Jolie to know that she has inherited faulty BRC1 genes which is a risk factor for breast and ovarian cancer but more important is pro-activeness or a decision to undergo double mastectomy to rule out or minimize most likely outcome due to high degree of susceptibility. And, prioritize sequence of treatment by going first for mastectomy, a more complex surgery rather than removal of ovary which is less likely to get affected by previous recorded experiences.
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  • Thanks Vikram,
    It is a great share from you time, Thansk for sparing yoru time to share your knoledge with us. This is a must read
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  • sample presentation will illustrate the Power of PowerDESIGNS. We start off by selecting a background template from the PowerTEMPLATES collection.
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  • Transcript

    • 1. Introduction to Risk VIKRAM SINGH SANKHALA
    • 3. Immediate Symptoms Sudden Chest Pain Sweating Anxiety YOU SEEK Palpitations HELP Shortness of Breath Nausea and Vomiting
    • 4. Risk Factors• Previous cardiovascular disease• Older age• Tobacco smoking• High levels of certain lipids and low levels of high density lipoprotein• Excessive alcohol consumption and drug abuse• Diabetes• High blood pressure• Obesity• Chronic kidney disease• Heart failure• Chronic high stress levels
    • 5. Modeling and Predicting a Heart Attack Why does it arise Can we make it an outcome of a Mathematical function of Factors (Independent Variables)
    • 6. Where is the ProblemUnpredictability Given the Same set of Risk factors, one person may have a heart attack and another may not. 33% 67% Risk Uncertainty
    • 7. Can we measure Risk Uncertainty – A State of Having Limited Knowledge 40% Probabilities are assigned to 30%each possible state or outcome 20% 10% Measurable Factors Uncertainty
    • 8. What is Risk – A set of measured uncertainties – Where some possible outcomes have an undesired effect or significant loss – There is also scope for the upside i.e. profit
    • 9. What is Predictability Is it possible to predict the Dependent Variablestate of the system S (t+k) at time= t+k Independent Variable x 1% Independent Variable y 4% Independent variable z 15% Independent Variable a 80% Consider a system whose state at the initial state S(t) at time t.
    • 10. Financial Risk
    • 11. IllustrationCan we predict the movement of Stock Markets
    • 12. What is RandomnessRandom Process1. A random process is a repeatingprocess2. whose outcomes follow nodescribable deterministic pattern,3. but follow a probabilitydistribution,4. Such that the relative probabilityof the occurrence of each outcomecan be approximated or calculated.
    • 13. When do we call events random Statistical Properties- Is there a Correlation- Are the Events Independent
    • 14. How do we study Randomness Probability theory is the branch of mathematics concerned with analysis of random phenomena RAIN MAYBE NO RAIN2% Decrease 3% Increase Statistics is used to infer the underlying probability distribution of a collection of empirical observations.
    • 15. Random Walk Hypothesis - NoWhat is a Random Walk ? A random walk, sometimes denoted RW, is a mathematical formalization of a trajectory that consists of taking successive random steps. What does the Random Walk Hypothesis say ? The random walk hypothesis is a financial theory stating that stock market prices evolve according to a random walk and thus the prices Random │ Walk │ Hypothesis
    • 16. Against the Hypothesis - Yes Professors Andrew W. Lo and Archie Craig MacKinlay Professors of Finance at the MIT Sloan School of Management and the University of PennsylvaniaVolatility Besed Equation• Xt is the price of the stock at time t• μ is an arbitrary drift parameter• εt is a random disturbance term Random │ Walk │ Hypothesis
    • 17. Some ConceptsFailure of key businessesDeclines in consumer wealthSubstantial financial commitments incurred by governmentsSignificant decline in economic activity Markov Process Stochastic Monte Carlo Processes Methods Simulation
    • 18. Stochastic Process Counterpart to a deterministic process Stock MarketsEven if the initial condition isknown, there are many possibilitiesthe process might go to, but some Exchange Ratepaths are more probable and others Fluctuationsless. Brownian Motion
    • 19. Markov ProcessMathematical model for the random evolution of aMemory-less system Process for which the likelihood of a given future state, at any given moment, depends only on its present state, and not on any past states Andrei Markov │ Russian Mathematician │
    • 20. SimulationA model in science is a physical, mathematical, or logicalrepresentation of a complex reality. A simulation brings a model to life and shows how a particular object or phenomenon will behave.
    • 21. Some Methods of Simulation Historical Use of Parametric Information Random Distribution Numbers PAST DATA ASSUMPTION GENERATION Historical Parametric Monte Carlo Simulation Simulation Simulation
    • 22. Monte Carlo Simulation Use Random Numbers to Generate DataMake your StochasticModel Plot Distribution Analyze Distribution
    • 23. Financial Crisis Components Failure of key businesses Declines in consumer wealth Substantial financial commitments incurred by governments Significant decline in economic activity Business Failure Economic Consumer Activity Wealth Government Commitments
    • 24. US Mortgage Crisis Between 1997 and 2006, the price of the typical American house increased by 124% 124% INCREASE Housing Prices: •peaked in early 2005 •started to decline in 2006 •Led to US Mortgage Crisis
    • 25. Objective of Risk Management Take Care of Uncertainty
    • 27. Warren BuffetRisk comes from not knowingwhat youre doing.