Before we start a discussion into what seems like science fiction made real, let’s look into the past. Artificial Intelligence (AI) is a term that was coined by John McCarthy, a legendary American computer and cognitive scientist, in the 1950s. He is widely regarded as one of the "founding fathers" of AI. Alongside other luminaries like Alan Turing, Marvin Minsky, Allen Newell, and Herbert A. Simon, McCarthy played a pivotal role in shaping the field.

McCarthy, a Stanford professor and Turing Award recipient, developed the programming languages known as LISP and ALGOL. LISP was pivotal in AI development and research while ALGOL popularized the concept of time-sharing in computing, allowing multiple users to interact with a computer at the same time – a key concept for those that would expand McCarthy’s work in the decades to come.

Outside of financial reporting, articles on inflation rates usually quote the Consumer Price Index, or CPI. But financial writers in-the-know will reference “the Fed’s preferred measure of inflation,” the Personal Consumption Expenditures price index, or PCE. Today we’ll take a look at the two measures of inflation, how they are determined and why the Federal Reserve prefers one over the other.

But before we dive in, let’s take a look at some of the economic news released last week. Punxsutawney Phil, the famous weather-casting groundhog, didn’t see his shadow last Friday, and so predicted an early spring. Let’s see if the economy looks as rosy.

I have been in the investment business for 28 years. This will mark my seventh Presidential election cycle over that period. Without fail, clients have questions and concerns about market performance during each presidential election cycle.  It is a common question and I always give the same answer – it varies but in general performance is pretty good.

I know we have been writing a lot about the Federal Reserve lately. Like it or not, the Fed is the single most influential financial entity on the planet. Period. No other central bank comes close to the sheer scope and global impact of the Fed. What they do and how they do it shapes virtually all global financial markets.

Of the tools the Fed has at its disposal, the most esoteric (and that is saying something) and most stimulative, is the balance sheet. But what is it?

From Investopedia, “Seasonality is a characteristic of a time series in which the data experiences regular and predictable changes that recur every year. Seasonality can affect different aspects of a business or economy based on the seasons, such as consumer spending, inventories, staffing and growth.”

That’s a bit dry, even for me. Another way to think of seasonality is that there are some months that are better for investment returns than others. Seasonality is present in individual stocks, sectors, sub-sectors and the broader markets. Each may have similar or wildly different seasonality characteristics. For this discussion I am focusing on the S&P 500 (SPX) over the last four market cycles. A market cycle is a five-year period. Seasonality data is available going back decades.

The Fed was a completely different animal in the 1970s. Notable bond trader Richard Stuttmeier wrote,

“It's a different world than in 1972. When I began my career as a bond trader at one of 12 primary dealers, Arthur Burns was the Fed chair. Fed policy at the time was much more direct, but considerably less transparent.

Policy changes were handled in secret, with tactics implemented through the Open Market Trading Desk of the New York Federal Reserve Bank, which bought and sold securities through primary dealers to achieve the desired federal funds rate.

Rate decisions weren't announced publicly after each meeting of the Federal Open Market Committee, so traders had to pay attention to the market. When the Fed bought securities, it increased the amount of money in the banking system, which tended to bring the rate down. And vice versa.”

Think about that as compared to how vocal the Fed is today. I like to think of these past years as the Fed’s good old days.