Will the Market Crash?

The most common question that market technicians get asked daily is, “will the market crash”. 

A philosophical approach to the character of stock market crashes, is to look at them much like auto crashes at busy intersections.

As a fact, crashes happen. Infrequently, but they still happen periodically.

Are they likely and possible? Absolutely possible.

Can we predict them? Yes, but only to the extent that we have data available to us in advance.

Fortunately, we learn the rules for the road, and how to safely operate a motor vehicle.

We learn how to adhere to traffic signals and signs.

We learn about “traffic lights”, that help drivers to navigate busy intersections.

When people see ‘green’, they know what to do. There’s no confusion about what should be done at a green light. And when drivers see the ‘red’ light, they also know what to do.

Every single day, we entrust our lives and our family’s lives to this system of signals. Similarly, our approach to the stock market is very much the same.

In the pH14 Plan, we use our ability to identify and read signals, lots like traffic lights, to help guide us safely to our intended financial destination.

Forecasting car crashes isn’t something that most people do on a regular basis, however.

While everyone generally knows the rules for the road to encourage safe driving, few people take the time and effort to attempt “forecasting” car crashes.

The likelihood of anyone’s mortality being the result of a car crash (40k yearly) is low compared to heart disease (633k yearly), cancer, lower respiratory diseases, etc.  Few successful businesses spend their R&D dollars, investing into studying infrequent events and rare problems.  Nevertheless, defensive driving tactics are always encouraged.

Taking the leap into *predicting* car crashes, typically would begin with a thorough review of common characteristics of car crashes.

Various data sources might be examined – – let’s review simply the Mother’s Against Drunk Driving statistics. It reveals quickly…

  • Who is more likely to get into car crashes? Teenagers?
  • When are teens most likely to be in crashes? When they’ve consumed alcohol.
  • When are there more Drunk drivers? At night, when drivers are also sleepy.
  • Which nights? Weekends.

After going through this type of exercise more thoroughly, any artist can begin drawing a picture of what a street or intersection looks like BEFORE a crash.

Many cars are now even being built with technology that enables defensive driving tactics, such as a safe following distance and other ‘driver assist’ packages. The data the cars use typically comes from sensors and cameras, based upon the proximity of your vehicle to another.

That said, the inherent limitation of this approach, is that we’re only able to forecast a crash with today’s technology to the extent that the senors and cameras can ‘see’ the oncoming vehicle.

Just as we can forecast car crashes, we could elect to study previous stock market crashes to examine what are the common characteristics prior to the incident.

In the pH14 Plan, we spend considerably LESS time studying crashes, primarily because market crashes are extremely rare events.

We do not spend our time building filters and alerts to find market crashes. Conversely, our approach to building and constructing the algorithms for screens and filters, requires that we spend our time finding and studying….

  • profitable patterns
  • that display with the highest frequency and
  • smallest draw downs.

Opposed to studying the imperfections of the market, we spend most of our R&D time discovering, learning, and “painting the picture” of the PERFECT and IDEAL scenarios of the past, so that we may recognize those patterns if they emerge ‘today’.

We encourage defensive “money management” tactics, and provide a reading list for members who are interested in studying the best practices.

Accessible upon registration, we review historical case studies of sector tops and major market tops.

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Author: pH14 Plan Staff

pH14 Plan is an economic development model for all U.S. households' participation. You can support this research by subscribing for more access, or contact us to make a gift.

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