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» Risk and Decision Assessment Training using @RISK, Part II
» Improving Estimates and Budgets
PMI Global Congress 2007 – North America
Society of Actuaries Annual Meeting and Exhibit
INFORMS Annual Meeting 2007
SPE Annual Technical Conference and Exhibition - 2007
38th Annual Meeting of the Decision Sciences Institute - DSI 2007
IRM Risk Forum
88% of Actuaries Running
The survey, entitled “Actuaries excel: but what about their software?” was presented by independent consultant Louise Pryor at the 2006 General Insurance Convention in Vienna, Austria, on 26 September 2006.
“We have long had a strong customer base in the actuarial and insurance market,” said Palisade President Sam McLafferty. “This latest survey confirms the trends we have been seeing. Through meetings like the Society of Actuaries, coverage in a variety of insurance and actuarial publications, as well as sales, we have seen dramatic expansion of @RISK for actuarial applications.”
Boeing to Build
Monte Carlo Simulation May Help Increase Mutual Fund Return
“The idea that you need 160 or 88 stocks to diversify is simply ludicrous,” says James Montier, head of global equity strategy at Dresdner Kleinwort Group Ltd. in London. “You can have a return profile with roughly the same volatility as the overall equity market by holding around 30 to 40 stocks.”
As a result, investors may be paying exorbitant fees for lackluster returns. According to Montier, using Monte Carlo simulation can allow fund managers to concentrate on absolute returns, instead of buying a variety of unwanted stocks in an attempt to mimic benchmark results.
@RISK Used for Large-Scale
DecisionTools and Training:
“The course was useful and the presenter was knowledgeable. There was a good mix of background material and working through actual problems.” — Marvin Schwedock, General Atomics
Move over night-long slogs on mundane outsourcing jobs. The $9-billion business process outsourcing (BPO) sector has graduated to the third generation services, or BPO Ver 3.0. Sample the work in BPO 3.0: developing structured products for investment banks, using Monte Carlo simulation based patent valuation, and more.
» A close-up on pancreatic disease:
Pancreatic cancer is among the deadliest of today's cancers due to limited tools for early diagnosis and few effective treatments. Research takes a closer look at pancreatic cancer and the promising new applications of technology that will improve survival rates in the coming years. Overall, the neural network based model was very accurate in classifying pancreatic cancer, with an area under ROC curve of 0.93.
Some climate change models will produce heavy rain over a region while in others the same location will be bone dry. There are now an increasing number of regional model simulations to compare. Recent projects apply the Monte Carlo technique to refine their probability distributions, with the stated goal of producing “a probabilistic estimate of uncertainty in future climate.”
» Netflix prize still awaits a movie seer
» Analytic Innovations LLC's CEO and VP of
The executives will discuss the company's findings across concrete areas where significant debit fraud risk and loss can be mitigated and managed: purchase-limit evaluation, cardholder behavior analysis after a fraud-related card reissue, and neural network review and evaluation.
The numerical method for derivatives analysis uses Monte Carlo simulations in a Black-Scholes world. The algorithm makes heavy usage of floating-point math operations such as logarithm, exponent, square-root, and division. In addition, these computations must be repeated over millions of iterations. The numerical Black-Scholes solution is typically used within a Monte Carlo simulation, where the value of a derivative is estimated by computing the expected value, or average, of the values from a large number different scenarios, each represents a different market condition.
The United Planters' Association of Southern India (UPASI) has urged the Tea Board and National Tea Research Foundation (NTRF) to make available tea quality monitoring instrument “E-nose” to the industry at the earliest. The system is capable of sensing volatile compounds of tea and reliably predicting tea taster like scores with a high degree of accuracy. Neural Network based 'soft computing techniques' are used to tune near accurate co-relation smell print of multi-sensor array with that of the Tea Tasters' scores.
Poker-playing software programs are great at calculating odds and keeping, so to speak, a straight face. But the bluff -- that highest art of the game, the ability to intuit when and how to successfully play a low pair like a full house -- has always been beyond the grasp of their code. All that may have changed. Based on a neural network algorithm typically used to predict the stock market, Hurwitz's bots weren't pre-programmed with the rules of a card game.
» Riverdale Oil and Gas Corp. announces its natural gas development program in the Gulf Coast region of Texas
Riverdale Oil and Gas Corp announced a natural gas program to develop reserves trapped in the shallow Frio and Miocene sands of the gulf coast of Texas. The Company is in final negotiations with Nettlecombe Oil Co., Inc., a geophysical consulting company located in Houston, Texas. Nettlecombe will utilize Neural Networks and Artificial Intelligence, which are powerful extensions to its 3D seismic analysis.
» Insurance companies not reaping full
Many insurance companies aren't taking full advantage of technology when it comes to fighting fraud, suggests a recently released report from Boston-based research and advisory firm Celent. Several newer techniques — including neural networks — have gone underutilized. Insurance lags behind the credit card and banking industries regarding fraud technology adoption.
Decision trees, decision trees, decision trees. I believe one of the biggest errors (myself included) that investors make is attributing results to decisions, rather than to decision trees.
» Decision aid tool could cut the number
A computerized decision analysis program which helps women decide on the type of birth that is most appropriate for them could cut the number of caesarean sections performed in England and Wales by 4000 a year, according to a study published today.
Citigroup increases price target on Dow Jones & Company Inc (NYSE: DJ) to $55. Citigroup analyst says, “Our price target is $55 (prev. $37) and is based on a decision-tree analysis of potential outcomes.”
There is renewed interest in supply chain “simulation” at multiple levels; and new concepts (for the supply chain) that straddle optimization and simulation approaches, such as “stochastic optimization.” The key is that demand (or other key inputs) aren’t static, but are more dynamic. It is possible to use techniques such as “Monte Carlo” analysis to have demand or other variable populated more or less randomly over some period.
Tap water has been taken for granted as a daily resource for many people, but it may not be well known that genetic algorithm optimization has been playing an important role in managing and operating municipal drinking water systems by means of hydraulic and water quality models.
Expert Answers to Technical Questions
Can I represent uncertain factors in my PrecisionTree models using @RISK? For instance, I have chance nodes and payoff nodes that are really continuous ranges of outcomes.
@RISK is a perfect companion to PrecisionTree. @RISK allows you to 1) quantify the uncertainty that exists in the values and probabilities which define your decision trees, and 2) more accurately describe chance events as a continuous range of possible outcomes. Using this information, @RISK performs a Monte Carlo simulation on your decision tree, analyzing every possible outcome and graphically illustrating the risks you face.
With @RISK, all uncertain values and probabilities for branches in your decision trees and supporting spreadsheet models can be defined with distribution functions. When a branch from a decision or chance node has an uncertain value, for example, this value can be described by an @RISK distribution function. During a normal decision analysis, the expected value of the distribution function will be used as the value for the branch. The expected value for a path in the tree will be calculated using this value.
However, when a simulation is run using @RISK, a sample will be drawn from each distribution function during each iteration of the simulation. The value of the decision tree and its nodes will then be recalculated using the new set of samples and the results recorded by @RISK. A range of possible values will then be displayed for the decision tree. Instead of seeing a risk profile with a discrete set of possible outcomes and probabilities, a continuous distribution of possible outcomes is generated by @RISK. You can see the chance of any result occurring.
In decision trees, chance events must be described in terms of discrete outcomes (a chance node with a finite number of outcome branches). But, in real life, many uncertain events are continuous, meaning that any value between a minima and maxima can occur.
Using @RISK with PrecisionTree makes modeling continuous events easier using distribution functions. And, @RISK functions can make your decision tree smaller and easier to understand!
E-mail comments or suggestions to:firstname.lastname@example.org
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