RISK MODELING

This course covers Monte Carlo Simulation with the Palisade @RISK Add-In and consists of 50 topics.
 
  • Introduction to @Risk – In this video we use the classic news-person problem with discrete demand to introduce Monte Carlo Simulation with @RISK.
  • Simulations With The Normal Random Variable – In this video we solve the classic news-person problem with normal demand to introduce Monte Carlo Simulation with @RISK. We also illustrate the different graphs that can be used to summarize an @RISK simulation.
  • Using Riskstatistical Functions – In this video we show how to use the RISKMEAN and RISKSTDDEV functions to update the mean and standard deviations of a simulation as the simulation is run.
  • Introduction To Capital Budgeting And The Triangular Random Variable – In this video we use @RISK and the triangular random variable to determine if GM should produce a new car.
  • Modeling The Product Life Cycle And Sensitivity Analysis With @Risk – In this video we show how to model sales volume over time using the product life cycle and explain how @RISK can be used to determine the input random variables that have the most influence on simulation output cells.
  • RiskGeneral Random Variable – In this video we show how the RISKGENERAL random variable can be used to model a continuous random variable.
  • The RiskCumul Random Variable – In this video we show how the RISKCUMUL function can be used to model a continuous random variable.
  • The RISKTRIGEN Random Variable – In this video we show how the RISKTRIGEN function is used to generalize the triangular random variable.
  • Statistical Analysis Of @Risk Outputs – In this video we show how to find a 95% confidence interval for the average value of a simulation output cell and a range that includes 95% of the actual values for an @RISK output cell.
  • Should We Drill For Oil? – In this video we ask the question, “How can we use @RISK to determine whether it is a good idea to drill for oil?”
  • The Scenario Approach To Capital Budgeting – In this video we show how uncertain market share and development expenses can be modeled by defining scenarios for product acceptance.
  • Plugin Means For Option Pricing – In this video we use a simple option pricing example to show that replacing a random future stock price by its mean does not yield the correct mean for the output cell (cash flow from the option).
  • Valuing An Acquisition – In this video we show how to value an acquisition, including the concept of Terminal Value.
  • Using @Risk’S Goal Seek Capability – In this video we use @RISK’s Goal Seek Capability to determine the terminal growth rate that makes an acquisition a good deal.
  • Simulating The NBA Finals- In this video we show how to determine the chance that a team wins a best of 7 NBA series. We also determine the probability that the series will go 4, 5, 6, or 7 games.
  • Simulating Craps – In this video we show how to determine the chance of winning at craps.
  • Three Dimensional Random Walk – In this video we analyze a three dimensional random walk and show that like Charley on the MTA (Kingston Trio) you may never return!
  • Birthday Problem – In this video we show that with 23 people in the room there is a 50-50 chance that at least two people have the same birthday.
  • Finding Your Best Partner – In this video we show how to determine how many people to interview in order to maximize your chance of finding your best partner.
  • Calculating Poker Probabilities – In this video we use @RISK to determine the chance of getting one pair, two pair, or a full house in 5 card draw poker.
  • The Optimal Bid – In this video we show how @RISK can be used to determine the optimal bid on a construction project.
  • Introduction To RISKOPTIMIZER- In this video we show how RISKOPTIMIZER allows you to generalize a RISKSIMTABLE and solve for the order quantity of calendars that maximizes expected profit in the presence of uncertain demand.
  • Multi-Product Newsperson Problem – In this video we use RISKOPTIMIZER to solve a multi-product newsperson problem.
  • Scheduling Hospital Nurses – In this video we find the minimum number of nurses needed to ensure that during during a week there is at most a 5% chance of not having enough nurses.
  • Bid Optimization With RISKOPTIMIZER – In this video we show how to use RISKOPTIMIZER to determine a bid that maximizes expected profit in the presence of uncertainty.
  • Rescuing The Iran Hostages – In this video we show how @RISK could have increased the chances of a successful rescue of the hostages during the 1980 Iran Hostage Crisis.
  • Sequencing Jobs With Uncertain Duration – In this video we use RISKOPTIMIZER to sequence jobs of uncertain duration to minimize the expected number of late days.
  • Choosing A Portfolio Of Capital Budgeting Projects – In this video we use RISKOPTIMIZER to choose a subset of capital budgeting projects that meet a spending constraint.
  • Modeling Correlated Random Variables – In this video we show how to use the RISKCORRMAT function to model correlated (non-independent) random variables. You will also learn how to overlay multiple simulation outputs on a single graph.
  • Creating Multiple Instances of Correlations – In this video we show how you can create multiple instances of correlated random variables. For example, the percentage change in the price of each of 4 stocks on day N may be correlated, but none of the day N percentages are correlated with any other day.
  • Generating Future Investment Scenarios – In this video we use re-sampling to generate future scenarios for returns on important asset classes.
  • Optimal Portfolios Using Var And Sharpe Ratio – In this video we show how to find portfolios that optimize Value at Risk (VAR) and the Sharpe Ratio.
  • Optimal Portfolios Using Stress Testing And Downside Risk – In this video we show how to find portfolios that maximize a portfolio’s worst case or minimize a portfolio’s downside risk.
  • Optimal Portfolios Controlling A Portfolio’S Beta Or Conditional Var – In this video we show how to find portfolios that control risk by setting the portfolio’s Beta or maximizing the portfolio’s Conditional VAR.
  • Fitting A Discrete Distribution To Data – In this video we use @RISK’s Distribution Fitting Feature to show that goals scored in an NHL game follow a Poisson random variable.
  • Fitting A Continuous Random Variable To Data – In this video we use @RISK’s Distribution Fitting Feature to show that the margin of victory in an NFL game follows a normal random variable.
  • The Winner’s Curse – In this video we show how to incorporate the Winner’s Curse into your optimal bidding strategy.
  • The Black-Scholes Option Pricing Formulas – In this video we show how to use the Black-Scholes formula to price European call and put options.
  • Using The Lognormal Random Variable To Simulate Stock Prices – In this video we show how to use financial data from Yahoo.com and the Lognormal random variable to model future stock prices.
  • Butterfly or Straddle? – In this video we discuss the relative merits of a Butterfly or Straddle strategy involving options of Microsoft stock.
  • Introduction To Utility Theory – In this video we show how utility functions can be used to make decisions under uncertainty which incorporate the decision-maker’s attitude towards risk.
  • Exponential Utility – In this video we describe how to use the exponential utility function to model a decision-makers attitude towards risk.
  • Asset Allocation Via Expected Utility – In this video we show how to use utility theory to tailor an asset allocation to a decision-makers attitude towards risk.
  • Project Management With @Risk – In this video we show how to use @RISK to model the uncertain duration of a project.
  • Finding The Probability That Activities Are Critical – In this video we use @RISK to estimate the probability that each of a project’s activities are critical.
  • Introduction To Re-Sampling – In this video we show how re-sampling can be used to replace many hard to remember statistical hypothesis tests.
  • Is a New Cancer Drug Worthwhile? – In this video we use re-sampling and results from 12 patients to show a new cancer drug is a significant improvement over an old cancer drug.
  • Was The 1970 Draft Lottery Fair? – In this video we use re-sampling to show that the 1970 draft lottery was not random.
  • Beta Re-Sampling – In this video we use re-sampling to show that there is an 80% chance that Dell has the highest beta among a list of 6 stocks.
  • A Bidding Paradox – In this video we use @RISK to resolve a bidding paradox.
  • Heads Or Tails? – In this video we show that when tossing a coin repeatedly it is much more likely that THH comes before HHH.
  • Should We Have Known Madoff Was A Fraud? – In this video we use the Sharpe Ratio and re-sampling to to show that the SEC should have realized well before 2008 that Madoff’s fund was a fraud.
  • How to Hedge FX Risk?- In this video we use @RISK to show how a company can hedge FX risk.
  • Fashion Ordering Part One – In this video we use RISKOPTIMIZER to determine how a fashion retailer can maximize expected profit when early sales of a product are a good indicator of future demand.
  • Fashion Ordering Part Two – In this video we continue our discussion on fashion ordering.
  • Introduction To Supply Contracts – In this video we introduce a simple supply chain where coats are manufactured in Asia for a US retailer.
  • Buyback Contracts – In this video we show that when the manufacturer is willing to buy back leftover coats both the retailer and manufacturer benefit.
  • Revenue Sharing Contracts – In this video we show that if the retailer shares some revenue with the manufacturer and the manufacturer reduces the wholesale price, then the performance of the supply chain improves.
  • Optimizing The Whole Supply Chain – In this video we show how buy back and revenue sharing contracts drive the supply chain to maximize expected profit.
  • Pricing Path dependent options by Simulation – In this video we show how to use simulation to price path dependent options.
  • Risk Neutral Valuation – In this video we show how simulation and the risk neutral approach to asset valuation allow us to use simulation to price a European call and put option.
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