It is difficult to estimate very unlikely things like earthquakes

Investors often overreact to good and bad news. When a company’s quarterly earnings become slightly below expectations, its share price may drop by 20 percent or more. Thus, when theoretical models of stock market models assume that price changes correspond to a bell-shaped curve of normal distribution, this assumption is more favorable than credible.

Another inconvenient fact is that many investors tend to follow trends either up or down. After the stock’s price rises, they rush to buy, which pushes the price up. When these two facts meet head-on, stock returns are sometimes very good or very bad than what might be true in a normal distribution.

On October 19, 1987, the S&P 500 Stock Price Index was down 20.3%. If changes in stock prices are normally distributed with the historical average and standard deviation, then it should not happen once in a trillion years. Two days later, the market was up 9.7%, which shouldn’t happen either in a trillion years. So something that shouldn’t happen once in a trillion years happened twice in three days. Twenty years later, in 2007, price changes occurred, which should have occurred only once every 10,000 years, three days in a row.

The occurrence of such extremely unlikely events is called a black swan event. Once upon a time, people in Great Britain did not believe in black swans because all the swans they saw or read about were white. However, no matter how many white swans we see, these observations can never prove that all swans are white. It is certain that a Dutch explorer found the black swan in Australia in 1697.

The fact that until October 19, 1987, the S&P 500 never rose or fell by more than nine percent in a single day, did not prove that it couldn’t happen. In practical terms, how do we reliably estimate the chances of an event that never happened? The convenient, but unrealistic assumption that changes in stock prices are distributed naturally – with no fundamental opportunity for very large price movements – set off many risk management models.

Outside of the stock market, there is ample evidence that people have difficulty evaluating the chances of low-probability and high-impact events. Amos Tversky and Daniel Kahneman have argued that likelihood assessments “are not very well behaved near endpoints, and very small probabilities can be either exaggerated or neglected.” For example, surveys have shown that people generally overestimate the likelihood of developing a rare disease, while most homeowners who live in New York City’s flood plains underestimate the likelihood of flooding caused by hurricanes.

It is also difficult to quantify the chances of a devastating earthquake. James Young and I looked at whether the two most recent major earthquakes in California had major impacts on nearby home prices, indicating that homeowners have underestimated the risk.

The 2014 South Napa earthquake sequence took place 80 kilometers north of San Francisco, in the heart of the Napa Valley wine industry. The United States Geological Survey (USGS) identified 12 major earthquakes in this region from August 24, 2014 through September 11, 2014, the strongest of which was a magnitude 6.0 earthquake on August 24. One person was killed and 200 injured, for $ 500 million in estimated damage.

The 2019 Ridgecrest earthquake sequence occurred approximately 200 kilometers northeast of Los Angeles and consisted of 67 major shocks from July 4, 2019 through July 16, 2016, and included shocks of magnitude 6.4 on July 4, 5.4 on July 5, 5.0 and 7.1. , 5.5 and 5.0 on July 6. One person died, 25 were injured, and there was an estimated $ 1 billion in damage to homes, gas lines, highways and other private buildings and $ 5 billion in damage to the Naval Air Weapons Station at Lake China.

James and I used the property sales data for the previous and next six months for each sequence of these earthquakes to investigate the effects on home prices. Taking into account specific home features, such as square foot space and number of bedrooms and bathrooms, we estimated that these earthquakes lowered market prices for nearby homes by an average of 5 percent in Southern Napa and 12 percent in Ridge Crest. The impacts on individual home prices were directly related to the intensity of earthquake feel at each home location.

Although it is difficult for homeowners to assess the chances of significant seismic damage, it presents a greater challenge to computer algorithms. As with stock prices, it would be a fatal mistake to calculate previous earthquake losses. The best predictions, such as the Uniform Prediction of Earthquake Rupture in California, are based on complex theoretical models of the geological factors that cause earthquakes. The model is not an artificial intelligence (AI); It is based on real intelligence.

In 2017, “AI” was chosen as Marketing Word of the Year, a startup called One Concern raised $ 20 million to “prove the world in the future” using an AI algorithm to provide real-time estimates of mass-intensity against damage from earthquakes. They said emergency teams could use their estimates to guide rescue efforts. The company describes itself as follows:

A finest artificial intelligence company with a mission to save lives and livelihoods before, during and after disasters. Founded at Stanford University, One Concern enables cities, businesses and citizens to embrace a future free from disasters.

Calling AI is misleading and the promise of a disaster-free future is boring. The original AI programs train with massive amounts of data, but data about earthquakes of similar sizes at similar locations is scarce. If the algorithm extrapolates data from earthquakes of specific magnitudes to earthquakes of other magnitudes, from earthquakes in certain geographic locations to other locations, and from certain types of buildings to other buildings, it will be fooled by imaginary patterns.

How relevant is the data on damage from a shallow 7.3-magnitude earthquake to a one-story home built in 1990 in Indonesia to predict damage to a 4-story apartment building built in 1950 from a 6.5 deep earthquake in San Francisco, or vice versa? It’s like training for Go by playing dozens of games from tic-tac-toe.

However, after a flurry of favorable news stories, One Concern received millions in financing and contracts with several cities, including San Francisco and Los Angeles. Then it turned out that her product did not match the hype. For example, in August 2019, The New York Times published an article titled “This High-Tech Disaster Response Solution May Be Too Good To Be Right” by Pulitzer Prize-winning reporter Sherry Fink.

San Francisco was terminating its contract with One Concern. Seattle also had doubts about the program’s cost and reliability. In one test simulation, the program ignored a large Costco warehouse because it relied primarily on residential data. When One Concern revised the program to include the missing Costco, the University of Washington mysteriously disappeared. With each iteration, the forecast of damage changed dramatically.

An article in Fast Company, a follow-up to a previous positive article, concluded this

As the Times investigation shows, the startup’s early success with $ 55 million in venture capital financing, advisors like retired general, former CIA director David Petraeus, and team members such as former FEMA chief Craig Vogat, was built on misleading claims and elegant design. With faulty technology that is said to be not as accurate as the company says, One Concern could put people’s lives at risk.

Katherine Schwab, “This popular startup has pledged to save lives with AI. Now, it’s a cautionary tale” at Fast Company (August 13, 2019)

True AI can deliver amazing and miraculous results in many situations when there are clearly defined actions, consequences, goals, and massive amounts of data to train on. In other situations with indeterminate actions, uncertain consequences, multiple goals, and limited relevant data, AI does not match real intelligence.

You may also like to read these articles by Gary Smith:

The retrogression effect: why most medical treatments are so disappointing. Artificial intelligence is not a solution to this problem, as Walmart may soon discover.

And the

Why would a smart woman marry less intelligent men – try to avoid competition at home as well as at work? Or is there a statistical reason we’re ignoring?

What Are The Main Benefits Of Comparing Car Insurance Quotes Online

LOS ANGELES, CA / ACCESSWIRE / June 24, 2020, / Compare-autoinsurance.Org has launched a new blog post that presents the main benefits of comparing multiple car insurance quotes. For more info and free online quotes, please visit https://compare-autoinsurance.Org/the-advantages-of-comparing-prices-with-car-insurance-quotes-online/ The modern society has numerous technological advantages. One important advantage is the speed at which information is sent and received. With the help of the internet, the shopping habits of many persons have drastically changed. The car insurance industry hasn't remained untouched by these changes. On the internet, drivers can compare insurance prices and find out which sellers have the best offers. View photos The advantages of comparing online car insurance quotes are the following: Online quotes can be obtained from anywhere and at any time. Unlike physical insurance agencies, websites don't have a specific schedule and they are available at any time. Drivers that have busy working schedules, can compare quotes from anywhere and at any time, even at midnight. Multiple choices. Almost all insurance providers, no matter if they are well-known brands or just local insurers, have an online presence. Online quotes will allow policyholders the chance to discover multiple insurance companies and check their prices. Drivers are no longer required to get quotes from just a few known insurance companies. Also, local and regional insurers can provide lower insurance rates for the same services. Accurate insurance estimates. Online quotes can only be accurate if the customers provide accurate and real info about their car models and driving history. Lying about past driving incidents can make the price estimates to be lower, but when dealing with an insurance company lying to them is useless. Usually, insurance companies will do research about a potential customer before granting him coverage. Online quotes can be sorted easily. Although drivers are recommended to not choose a policy just based on its price, drivers can easily sort quotes by insurance price. Using brokerage websites will allow drivers to get quotes from multiple insurers, thus making the comparison faster and easier. For additional info, money-saving tips, and free car insurance quotes, visit https://compare-autoinsurance.Org/ Compare-autoinsurance.Org is an online provider of life, home, health, and auto insurance quotes. This website is unique because it does not simply stick to one kind of insurance provider, but brings the clients the best deals from many different online insurance carriers. In this way, clients have access to offers from multiple carriers all in one place: this website. On this site, customers have access to quotes for insurance plans from various agencies, such as local or nationwide agencies, brand names insurance companies, etc. "Online quotes can easily help drivers obtain better car insurance deals. All they have to do is to complete an online form with accurate and real info, then compare prices", said Russell Rabichev, Marketing Director of Internet Marketing Company. CONTACT: Company Name: Internet Marketing CompanyPerson for contact Name: Gurgu CPhone Number: (818) 359-3898Email: [email protected]: https://compare-autoinsurance.Org/ SOURCE: Compare-autoinsurance.Org View source version on accesswire.Com:https://www.Accesswire.Com/595055/What-Are-The-Main-Benefits-Of-Comparing-Car-Insurance-Quotes-Online View photos