Understandably, economists are always asked about the economy. We rely on our training, and our experience, while trying to be mindful of our philosophical leanings between the Austrian, the Keynesian, and Supply-side schools of economics.
Some try to avoid the discussion by relying on "technical analysis," which means lots of charts and spooky terms like "double-inverted head & shoulders." My thinking is that technical analysis is just an interesting way to avoid thinking.
Some months ago, I ran across a quote from Oliver Wendell Holmes. He said . . . "When I want to understand what is happening today, I try to decide what will happen tomorrow; I look back; a page of history is worth a volume of logic."
As a lover of all-things Williamsburg and a proud graduate of William & Mary, his statement resonated with me. I promptly shifted my reading program more toward history, reading such books as The Panic of 1907 and Manias, Panics, and Crashes. While reading history is an important part of making predictions, it provides mostly anecdotal lessons and is more useful in predicting the economy than predicting the stock market, which is more quantitative or numbers-driven.
If you look at the stock market as a system of mathematical relationships over time, computers should be able to help make sense of that history. Finally, some bright, young guys from M.I.T. are making significant strides. Their company name is Hidden Levers, which implies that non-obvious connections can impact each particular portfolio differently. It is a massive multiple regression analysis between 14,000 stocks and 15,000 mutual funds and 130 economic indicators, requiring literally millions of computations everyday.
As an example, the program tells me that a particular client's portfolio will go down 8.1% if Congress takes us over the Fiscal Cliff. That doesn't mean I believe it will go down 8.1%. It tells me the obvious, of course -- that it will go down. It also tells me that the mathematical probability is that it will go down somewhere between 5% and 10%. It tells me how vulnerable this particular portfolio is, compared to all other portfolios I manage. It even tells me some suggested changes I could make now to prevent that loss later. It tells me a lot!
Will any computer ever predict the future? No, not precisely!
Will any computer ever be able to predict "black swan" events? Not a chance!
Will any computer replace human judgment? No sane computer should even try!
Will any computer make me a better financial advisor? I think so!
Will any computer improve investment management? Of course, it already has!
For now, I have a bright, shiny new tool in my toolbox, and I like it!
Some try to avoid the discussion by relying on "technical analysis," which means lots of charts and spooky terms like "double-inverted head & shoulders." My thinking is that technical analysis is just an interesting way to avoid thinking.
Some months ago, I ran across a quote from Oliver Wendell Holmes. He said . . . "When I want to understand what is happening today, I try to decide what will happen tomorrow; I look back; a page of history is worth a volume of logic."
As a lover of all-things Williamsburg and a proud graduate of William & Mary, his statement resonated with me. I promptly shifted my reading program more toward history, reading such books as The Panic of 1907 and Manias, Panics, and Crashes. While reading history is an important part of making predictions, it provides mostly anecdotal lessons and is more useful in predicting the economy than predicting the stock market, which is more quantitative or numbers-driven.
If you look at the stock market as a system of mathematical relationships over time, computers should be able to help make sense of that history. Finally, some bright, young guys from M.I.T. are making significant strides. Their company name is Hidden Levers, which implies that non-obvious connections can impact each particular portfolio differently. It is a massive multiple regression analysis between 14,000 stocks and 15,000 mutual funds and 130 economic indicators, requiring literally millions of computations everyday.
As an example, the program tells me that a particular client's portfolio will go down 8.1% if Congress takes us over the Fiscal Cliff. That doesn't mean I believe it will go down 8.1%. It tells me the obvious, of course -- that it will go down. It also tells me that the mathematical probability is that it will go down somewhere between 5% and 10%. It tells me how vulnerable this particular portfolio is, compared to all other portfolios I manage. It even tells me some suggested changes I could make now to prevent that loss later. It tells me a lot!
Will any computer ever predict the future? No, not precisely!
Will any computer ever be able to predict "black swan" events? Not a chance!
Will any computer replace human judgment? No sane computer should even try!
Will any computer make me a better financial advisor? I think so!
Will any computer improve investment management? Of course, it already has!
For now, I have a bright, shiny new tool in my toolbox, and I like it!
