Stock Prices and Poker Bets
As a kid who is new to Data Science and Information Science as a whole, I have never really thought about information for the sake of information. Despite being surrounded by information constantly, I have always consumed it without considering how its presented, how it effects my decisions and what other information I would like to have. Given that some of my hobbies are built on the ability to use information to make decisions like poker and trading stocks, it is weird that those questions have rarely crossed my mind. After this past week of classes, I have realized that even though I have never explicitly thought about how I develop my predictions based on new information, many of my methods and tactics in poker and trading are designed to facilitate that exact process.
One example is in stocks. One method I have for predicting a price is to take in relevant information on a stock and its company, come up with a sort of hypothesis for it, and then wait for the price of the stock to either confirm the hypothesis or nullify it. An example of this can be seen with in the chart here: https://upload.wikimedia.org/wikipedia/en/b/ba/PaychexSupportResistanceChart.JPG. Once I see the stock testing the support price level in Aug. 2001, May 2003, and Sept. 2004, I start hypothesizing that there is a support level at the $29.64 price. Once the stock starts creeping back down to that level around Jul. 2005, I watch the price to see if it confirms my hypothesis. As it hits the level and then starts to bounce off and move back up, I know that my hypothesis has more credibility to it, and I buy the stock.
After buying the stock and making a massive fortune, I’ll take my profits to the poker table. This game, like the stock market, is all about making critical decisions with imperfect information. One of the biggest parts of the game is determining what cards your opponents hold. Now, in Hollywood, it is as easy as staring the guy down and dramatically telling him what he holds. Usually… it isn’t that easy. The method that I usually use relies on deducing the possible range down based on the new information as in this link: http://www.pokerlistings.com/strategy/how-to-put-your-opponent-on-a-range. When the cards are dealt and your opponent decides to bet, you have just received a piece of information. There is only a certain range of hands that your opponent would reasonably bet with. As the rounds continue and your opponent proceeds to bet, you gain additional information and are able to keep narrowing down the reasonable range of hands your opponent holds. While that seems easy, the challenge two-fold: collecting the information and deciding what information to collect. It takes time and practice to be able to collect and dissect all the information presented to you at the table. But the best players are not only efficient at collecting information, but they know what information is valuable. They know the opponent’s tendencies, the know the opponent’s visual tells, and much more.
As I start my journey on Data and Information Science, I begin to realize that I have actually thought about Information and how to collect it, but just in terms of stocks prices and poker bets.
