Looking Through a Dark Glass - Old models rethought, New playing field

 

Photo by Barbara Platek

I have waited to write another blog on the economy because things have been slowing down a bit lately. Slowing down is a relative term of course. Financial news and gurus would like nothing better than to have massive activity or perceived activity to generate something to write about. It doesn’t matter what point they argue just that they can argue. I have found three articles discussing topics that I think may be interesting and possibly somewhat informative.

The first two articles are from the Financial Times and CNBC, written in mid and late December. I like them because someone is asking about how successful the various central banks have been in predicting and handling the most recent recession and interest rate crisis. They have not been particularly successful in either predicting or dealing with the crisis. The article is pretty good about pointing out a couple of good thoughts. However, the central banks only admit that they applied the wrong thinking to the problem. They now know where they went wrong (or so they say) and the problem won’t happen again. Don’t believe them. They haven’t got it right this time. We will continue to have crisis and they will continue to make the wrong corrections.

Central bankers are rethinking their approach to economic forecasting after their high-profile failures to spot the most recent inflationary outburst, as officials argue for greater candour with the markets about the uncertainties they are confronting. … “What we should have learned is that we cannot just rely only on textbook cases and pure models. We have to think with a broader horizon,” she said. (Christine Lagarde) (a)

The second article discusses the difficult nature of forecasting. If only the world were linear or bell curve shaped or predictable our models would have performed just fine. But because the world is unpredictable (who would have thought) we (the economists and central bankers) can’t be expected to be able to make accurate forecasts. So we will continue to use the old models with a few adjustments and expect the world to get in line and be linear or bell curve shaped. Because if it does conform to our view of the world then, of course, our models will get it right. Their models will not get it right, trust me on this.

Firstly, a “multi-polar world” and an “increasingly fragmented global order” are leading to the “end of hyper-globalization,” Little said. Secondly, fiscal policy will continue to be more active, fueled by shifting political priorities in the “age of populism”, environmental concerns and high levels in inequality.  Thirdly, economic policy is increasingly geared towards climate change and the transition to net zero carbon emissions. [More so in Europe but the Biden administration is determined to drag the US into the morass of massive spending, extreme regulation and ill-thought out initiatives.]

“Against this backdrop, we anticipate greater supply side volatility, structurally higher inflation and higher for longer interest rates.” Little said. “Meanwhile economic downturns are likely to become more frequent as higher inflation restricts the ability of central bands to stimulate economies.” (b)

 

New interest rate & inflation thinking

I like the below quoted Reuters article from early January. There is still a lot of sentiment that the Fed will be successful in a soft landing. You will notice that this discussion has been going on since early 2022 with an ever changing end date. The discussion of the recession, regardless if it crashes or is in fact a “soft landing” makes for good press so as long as it is never resolved there is good storytelling. Expect to see much discussion even after it is finally decided we are either in recession or had a soft landing

 “[A] well-known economist and former Fed official earlier this year argued the Fed has managed soft landings more often than is generally believed. But many investors and executives think the probability is low [for a soft landing at this point].

Investors are betting that the Fed could cut rates by as much as 1.5% by the end of 2024, but that would still leave policy rates at close to 4%, higher than where it has been for most of the past two decades. At that level, monetary policy will still be a drag on growth, as it would be above the so-called neutral rate at which the economy neither expands nor contracts.” (c)

What does this mean for you and me? More uncertainty and higher interest rates for quite some time and the likelihood of rollercoaster inflation and less inflation. For the last 30 years we have had it fairly nice. The central banks kept interest rates artificially low by pumping massive amount of money into world economies. We all benefited from cheap money. We are now, finally paying the price because the banks can’t kick the can down the road anymore. There was so much excess money (the central banks have actually been reducing their balance sheets some recently) that the whole world system began to collapse. That was when the world banks finally panicked and slowed the river of money. That is the catalyst for the current recession (starting in early 2022) and why it is still hanging on. Most previous recessions lasted from 4 to 10 months at the longest. We are still drying out from our massive, massive binge and it is being slowly done. So expect to see recession / inflation talk to continue (remember it makes for good press). See excerpts from the Reuters article below to see a pretty good discussion of what can and may very well happen and why.

“Interest rates underpin everything, from economic growth to the price of financial assets and how much it costs to borrow to buy a car or a house.

Higher rates make riskier assets, such as technology stocks and cryptocurrencies less attractive, as investors can earn a decent return without having to take on much risk.

With money harder to come by, riskier bets can fail and bubbles burst, leading to events such as the U.S. regional banking crisis last March. As businesses struggle, they retrench. People lose jobs and new ones get scarce.”

“While the Fed and other banks have been raising rates for well over a year, the world is yet to complete the transition from the time when money was free to a period when it no longer is. 2024 is likely to be the year when the effects of that transition manifest more clearly.

That means companies – and in some cases, entire countries -- will have to restructure their debt liabilities, as they can no longer afford to pay interest.

For consumers, while savings would yield more, higher borrowing costs will require an adjustment. Many U.S. adults have only known low interest rates for their 30-year mortgages, for example. They'd need to come to terms with rates that are more than twice as high and make the math work for their budgets.

Bottom line: investors' convictions will likely get tested, as everyone will have to figure out how to live with higher interest rates.” (c)

So, hang in there. Us old timers (me included and my generation) lived through this kind of uncertainty and massive upheaval in the 70’s and 80’s. We survived. We had to be more frugal and things cost more including anything that required borrowing or debt. Because the costs were higher we had to scale back on our expectations and it did impact our ability to spend and save. When we came out of that time period the world governments opened the money spigots to keep inflation low because they were so afraid of inflation that they would do anything to avoid it again. It appeared to work for 30+ years. Now it doesn’t work and you (the younger generations) are paying the price as are we. My generation went from tight money to loose money and we loved it. This younger generation is going from loose money to tight money and it is painful and will be so for a while. Good luck. Remember what is important and it isn’t easy money. It’s family, friends, neighbors and your spiritual wellbeing. Not what the world would have you believe.

Articles quoted:

‘(a) Financial Times, “Central banks rethink forecasting after failures on inflation”

Sam Fleming in London, Martin Arnold in Frankfurt and Colby Smith in Washington 

December 27 2023  https://www.ft.com/content/5d7851f3-ef7c-4599-8a5c-c34cecb83511

‘(b) CNBC ‘Bonds are back’ as markets enter a ‘new paradigm,’ says HSBC Asset Management

Published Thu, Dec 14 2023 2:45 am EST  https://www.cnbc.com/2023/12/14/bonds-are-back-as-markets-face-new-paradigm-hsbc-asset-management.html

‘(c) REUTERS, “For investors, 2024 is year of transition to a new economic order”, By Paritosh Bansal, January 2, 202410:07 am MST  https://www.reuters.com/markets/investors-2024-is-year-transition-new-economic-order-2024-01-02/

Playing in the Sand Pile – Observations About Sand in Your Shoes – Part II

             I really am more organized than I sometimes seem. I had an outline of the topic I wanted to write about tonight. I started about four hours ago thinking I would be done in an hour or so. Well, it isn’t an hour later (as my previous sentence suggests) and I deviated quite a bit from the original outline. However, I feel that I need to lay this groundwork tonight. I cannot over emphasize the importance of being wary of economic and financial models or money schemes or the best investment you could ever make. Regardless of what Ben Bernanke (of the Fed) or Tim Geithner (of the Treasury Department) or leading economists (with lots of letters and abbreviations behind their names) or your neighbor (it is such a hot tip) or your best friend or a member of your religious congregation or your financial planner, tells you - be suspicious (in a nice way if you think you need to).     

             Previously we touched on the idea of the sand pile effect in nature and modeling. It includes such  concepts as nonlinearity and the critical state, is often known as complexity theory and sometimes called chaos theory. These ideas and concepts are discussed by Mark Buchanan in his book Ubiquity Why Catastrophes Happen, who we looked at briefly last blog and Nassim Nicholas Taleb in Fooled by Randomness who we have discussed several times.

             Let’s illustrate nonlinearity. Suppose we are enjoying a day at the beach with nothing better to do than build a sand tower as high as we can. As the tower increases with each bit of sand we add there comes a point that one more bit of sand causes the entire tower to collapse and slide down. This illustrates a nonlinear effect resulting from a linear force exerted on an object. Our tower suffered a disproportionate collapse from a very small additional input, namely a little bit of additional sand. It the sand pile would have reacted in a linear fashion we would have expected the small bit of sand to have a small impact. There are some idioms that incorporate this idea, the straw that broke the camel’s back or the last straw, or the drop that caused the water to spill. I can remember my father saying something like “that was the last straw” as he explained to me why I was being punished for what I thought was a fairly minor infraction and not worthy of the severity of the particular punishment I was receiving.

Taleb suggests that the nonlinear dynamics has what he calls the bookstore name of Chaos Theory. Taleb further suggests this is a misnomer because the theory has nothing to do with chaos or randomness instead, chaos theory does concern itself mainly with functions in which a small input can lead to a disproportionate response. A little bit of sand generates a massive sand slide. Buchanan suggests a slightly different but similar definition in his comment on what he calls the critical state. He says it represents “…a special kind of organization characterized by a tendency toward sudden and tumultuous changes, an organization that seems to arise naturally under diverse conditions when a system gets pushed away from equilibrium.” Buchanan says this is the first landmark discovery in the emerging science of nonequilibrium physics. Remember he is science writer and has a Ph.D. in theoretical physics.

             Look at the sand pile example again. Suppose you were to apply the nonlinearity principle to your commute home. A trip could take from a few seconds to months. Or suppose you are coming to the corner of the street. What is the likely height of the next person to come around the corner towards you. If we are in the sand pile the person could be from inches to miles high. Yet we have examples that follow this nonlinearity. Why is Bill Gates so rich. Is it because he is an intellectual giant compared to the rest of humanity. Or perhaps he is so much more intelligent than the rest of us. He may very well be of above average intelligence and superior work ethics and have high personal standards. But is he so much better as to deserve to be so wealthy. An element of nonlinearity or luck would better account for it. Economies, markets and social arenas tend to be nonlinear.  There really isn’t a mathematical model that can successfully model this type of activity. The model has to have a random element. Having said that, there are many who try to model parts and bits of things but the full, rich experience which makes up the world around us is difficult and complex. Think of weather models, how successful are we in predicting how much rain will fall on our backyard tomorrow, then one month later. If weather was linear we should be able to predict both time periods with great accuracy. Taleb suggests that one reason we get in trouble with economic and financial models is that some “…intelligent people who felt compelled to use mathematics just to tell themselves that they were being rigorous in their thinking, [and] In the great rush [to develop models] decided to introduce mathematical modeling techniques… without considering the fact that either the class of mathematics they were using was too restrictive for the class of problems they were dealing with, or that perhaps… the precision of the language of mathematics could lead people to believe that they had solutions when there were none.“  The purveyors of economic and financial models may try to convince us that their models do include enough “mathematics” to describe the particular situation but from our examples of tonight it seems very unlikely that the models will stand any test of time or uncertainty.

Playing in the Sand Pile of History – Part I

             A problem in modern economics has been the unpredictability of things. A cacophony of voices have tried from the beginnings of civilization to predict the next big thing. Just imagine the problem an Egyptian stone mason had trying to figure out the next big pyramid job. How was he going to know what and when to order stone so the competition didn’t get the jump on the big contract. Mark Buchanan in his book Ubiquity Why Catastrophes Happen tackles the problem head on and in my mind with that single mindedness of the scientist convinced that there is a mathematical equation somewhere that will hold the answer to life, the universe and everything. Those who model these chaotic systems talk about complexity and the greater problem some call upheavability. Buchanan suggests that chaos is limited in its ability to explain extreme events (I would say Black Swans – you recognize that term) because many models do not generate upheavals.

             Buchanan is good enough to suggest that predicting the long-term future of any chaotic system is practically impossible. I will suggest that it is presently quite unlikely that current models and modeling techniques will successfully model financial and economic systems with any degree of success or accuracy. Further, what little successes we may have is inversely proportional to model time horizon and the complexity of the system.  We will tend to have limited modeling success in the short term with simplistic systems. However, Buchanan does have some interesting suggestions for looking at complex systems which I think may help in understanding both the complexity and the pitfalls inherent in economic and financial modeling. He uses the term critical state to suggest  a special kind of organization characterized by a tendency toward sudden changes, maybe radical changes. Using his physics background he suggests that instead of trying to find mathematical equations to describe these complex systems that an alternative is to use mathematical games, much simpler equations, to understand specific portions of complex systems. We are going to explore one of these modeling technique, the sand pile, in later blogs. Today we need to set some parameters.

             We need to look at some basic principles regarding modeling and models. I want to start with what Emanuel Derman and Paul Wilcott, financial quantitative analysts, term the Modelers’ Hippocratic Oath. Derman and Wilcott are considered part of the elite group of financial modelers and have been in the financial industry before, during and after the great recession of 2008. Many feel that quants as the financial modelers are known are responsible for the severity and length of the recession and its attendant losses. In many respects this is accurate. Derman and Wilcott’s Oath shows some of the problems inherent in trying to model complex financial systems that many people seem to forget. Models are tools – blunt, limited, and easily breakable.

 Modelers’ Hippocratic Oath

·       I will remember that I didn’t make the world, and it doesn’t satisfy my equations.
·       Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.
·       I will never sacrifice reality for elegance without explaining why I have done so.
·       Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.
·       I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.
 

             I have a copy of this hanging by my desk. Any time I encounter a financial or economic model or a discussion of one I look at the oath and attempt to see if the author / originator has applied all the points to his model and the information I have about it. If there is any part of the oath that I suspect the author did not consider or incorporate in his model I am immediately suspect of the model, its conclusions and most of all its recommendations. All financial and economic models are suspect, period. Always assume there are errors in the model. Errors in logic, in assumptions, in data points included and excluded, in the equations, and in conclusions. Once you have looked at a model in this light it can be reviewed and analyzed to see if there are portions that may have some value. If you get the sense that models are potential death traps to your financial health and to the forecasting of economic conditions, that is accurate. One doesn’t have to be able to break down models to their component parts but one does need to realize that every model has problems, many of them significant problems. What is a person to do, be very skeptical of the output of any financial or economic model and run away from anyone who says, “trust me, you don’t need to know what is in the ‘black box’ “. If the person can’t or won’t explain the black box (for example, a new financial product guaranteed to get you 25% return in today’s environment) you don’t want to be involved, ever. Remember the old adage, if it’s too good to be true it probably is.

             Next time, how to look at a sand pile –  what can we learn and how can we use it.