Interview Link: https://www.labxchange.org/library/pathway/lx-pathway:b5121779-9f49-49db-93d9-80d5d67dadb3/items/lx-pb:b5121779-9f49-49db-93d9-80d5d67dadb3:lx_simulation:f10b9110?source=%2Flibrary%2Fclusters%2Flx-cluster%3AModernPrediction
One thing that surprised me from the interview on behavioral economics with David Laibson was that Professor Laibson said the stock market is approximately a “random walk,” making it incredibly difficult to predict what the value of a particular stock or index will be in the future. A random walk in econometrics or statistics refers to a model in which a variable's value in a given period is simply equal to its value in the previous period plus some random error. While I knew that it was very difficult to predict stock market trends given the multitude of factors that can influence stock prices, I expected that a company’s inherent value could help predict an individual company’s stock price and general economic trends could predict the overall market’s trajectory. Perhaps the random walk approximation is more pertinent in the short run, while we see that the stock market as a whole tends to trend upwards in the long run.
If I had conducted the interview with Professor Laibson, I would have asked: how do we explain the many people who are employed to make predictions about the future of the stock market? If stock volatility is approximately random, why do we trust financial analysts to predict how stocks will perform? It may be that we have too much trust in traders on Wall Street and should simply invest in stock indexes on our own rather than trusting “experts” to invest for us. However, it seems like financial institutions would need to have predictive frameworks that are more accurate than random guesses in order to retain investors as clients.