What makes a good economist?

 

“There is only one difference between a bad economist and a good one: the bad economist confines himself to the visible effect; the good economist takes into account both the effect that can be seen and those effects that must before seen. Yet this difference is tremendous; for it almost always happens that when the immediate consequence is favorable, the later consequences are disastrous, and vice versa. Whence it follows that the bad economist pursues a small present good that will be followed by a great evil to come, while the good economist pursues a great good to come, at the risk of a small present evil.” 

- Bastiat 

I love this explanation of the difference between a good and bad economist. You have to think about the longer-term or second order effects form some policy action. This is especially true when being a macro economist in finance. The Fed lowers rate which may have an immediate effect on short rates, but you have to think about how this changes expectations and impacts other markets. It is not the immediate effect bur rather the impact on expectations that matters.

Forecasts - we get it wrong - a year-end reminder

At the end of the year, Wall Street makes annual predictions. Wall Street is a prediction machine. Markets are in the prediction business through expectations embedded in prices. Yet, the judgement or value in these predictions is poor. Just look at the predictions of the stock market.  Surprisingly, the stock predictions are more conservative than reality.

For the bond markets, the futures prices are a poor forecast of future rates. During the QE period, markets expected rising rates that never occurred, and more recently, the markets were not able to predict the Fed rise in rates. Now, the forward prices are expecting strong declines. if the past is a predictor, don't bet on it.

 

Factor and price momentum across the globe

 

Many have tried to to explain away price momentum as driven by factor effects, but a recent study that looks at a large set of anomalies across a large set of countries fins that price momentum is still a key factor, see "Factor momentum versus price momentum: insights from international markets" The question answered in this paper was simple, does factor momentum drive stock price momentum? 

Now, factor momentum is strong across most international markets, but factor momentum cannot entirely explain stock and industry momentum; however, factor momentum based on principal components does a better job than traditional factor modeling. Nevertheless, price momentum often does a better job of explaining factor momentum. So, we can conclude that price momentum is distinct and cannot just be a combination of factor momentums. The paper provides an interesting display of comparisons between price and factor momentum that makes the story more compelling.

What make a historian important - perspective

The worst historian has a clearer view of the period he studies than the best of us can hope to form of that in which we live. The obscurest epoch is today. 

 - Robert Louis Stevenson 

History majors are becoming rarer at universities. Who wants to study the past? How is history going to help me with my job? I am only looking to the future. 

Yet, historians if they do their job correctly, try to make sense of what is often viewed as nonsense. The historian thinks about context. He thinks about cause and effect and what information can be found to support a set of explanatory arguments. There may be a model, but the model does not focus on the elegance of methodology but centers on the ability of explain and give some sense of order to disparate events. This is a skill which if often lacking when we are in the heat of the moment. 

The passions of the current are only tempered with time, but time is not possible when events are unfolding.

Knowledge would be fatal, it is the uncertainty that charms one. A mist makes things beautiful. - Oscar Wilde 

"If everyone is thinking the same, someone is not thinking" - a variation

Gentlemen, I take it we are all in complete agreement on the decision here. Then, I propose we postpone further discussion of this matter until the next meeting to give ourselves time to develop disagreement, and perhaps gain some understanding of what the decision is all about.

-Alfred P. Sloan 

Everyone talks about diversity of crowds, but the crux of the issue is having diversity of opinions and disagreement. Of course, disagreement for the sake of being disagreeable to worthless. Disagreement requires deep thought. It requires thinking about pros and cons. It requires an attempt to eliminate ignorance whenever possible. Agreement is caused from a lack of thinking and assuming that all the information necessary to make the right decision is available.

Of course, disagreement may lead to paralysis, so someone must decide but the decision has to be made through a blend of choices. 

What is the cause of the valuation between the US and the rest of the world?

Valuation for US stocks are higher than the rest of the world. What is the cause? Vanguard does a good job of visually providing a breakdown for the last ten years. Clearly, a clear driver is valuation from investors, but what is very clear is the strong impact of revenue growth. Revenue has been much stronger in the US than the rest of the world. What is surprising is the relatively small impact of profit margin expansion versus what is seen in the ACWI ex-USA. US companies have grown the top-line and have been rewarded with higher valuations even though margins have not expanded. The big gains in the US equity index are all driven by the huge gains in revenue and valuations within the information technology sector. Overall, the US and global differences could mean that US companies are more sensitive to any changes economic growth or investor sentiment related to valuations. 

 

Yes, we live in a non-linear world - get with it

 

We act as though we are in a linear world because it is easier to calculate behavior in the linear world. It does not matter if the linear model does a poor job, we can make the calculations. Nevertheless, the machine learning explosion has led to better and easy to apply non-linear models which allows researchers to make better forecasts. The latest AQR paper, "Can machines build better stock portfolios? The virtue of complexity in the cross-section of stocks" shows what kind of improvement you can get from using non-linear techniques. While modeling should always strive for simplicity, adding complexity can have significant benefits.

Surprisingly some techniques are easy to implement and just adjust for non-linear relationships at the extremes, yet using these techniques will generate significant improvement in Sharpe ratio. The two exhibits from the paper show the improvement with nonlinear models and provide a simple picture of what it means to have a non-linear relationship.  In this case, the AQR folks use ridge regression as the technique to gain the Sharpe improvement. These improvements can come even when looking at simple value and momentum factors. 

so, the Fed says the inflation problem is not solved?

The data-driven Fed lowered rates by 25 bps and made a major adjust for 2025 by suggesting there will only be two rate cuts in 2025. Of course, we now know that GDP will be steady, but PCE inflation and core PCE inflation will both be higher in 2025 and not reach the 2 percent target until 2026-2027. If that is the case, why cut now and why suggest any cuts in 2025. Why pretend that you have a plan when the actions taken are not consistent with the plan nor are the actions going to get you to the goal.

The stock market tells us that the expected action from the Fed for 2025 is a surprise. Think about the almost panic at the fed before the September meeting only now to see the fed wants to slow-walk further action in 2025. The 50 bps cut and SEP forecasts in September now look like a mistake. 

The VIX is telling us the market is in panic beyond the overall market decline. We are not at August carry trade debacle numbers, but we are heading in that direction. The dollar shot up like a rocket and the bond market and the long bond fell to levels not seen since June. This Fed action changes equity forecasts for 2025.

 

All ML for predicting stocka returns are not alike

 

Choices. Choices. What machine learning tool should I use? A recent paper, "Design choices, machine learning, and the cross-section of stock returns",  looked at over a thousand machine learning models applied to a single problem and found wide variation in results. You may think you are engaged with systematic investing, but there is a significant amount of discretion when making model design choices. Nevertheless, the idea that you should try and account for nonlinearities is critical in the choice. The key advancement with machine learning is accepting the idea that we live in a non-linear world.

The authors of this study compared algorithms, target variable, target transformation, post-publication treatment, feature selection, training window, and training sample which leads to over a thousand combinations that are tested on a common set of features to analyze out of sample results. The range in performance between the top and bottom monthly returns is greater than 15x. The difference in Sharpe ratios is more than 20x. Design choices matter. 

This is a critical piece of research. New techniques have to be benchmarked against the techniques that they are expected to replace. Why choice a new ML model unless you can say something about how it fits within the other choices available. 

Yellen gaslighting the bond market

 

This is an incredible comment from the outgoing US Treasury secretary. We have heard in the past that deficits do not matter. At times, they do not but as the size getting larger there is a choke point where rates have to go higher to clear the market. We have seen longer rates move higher while inflation is coming down, but it is hard to decompose the drivers of the rate change. Growth is expected to be higher in 2025, inflation is not expected to fall as quickly, deficits are expected to stay high, and term premium are expected to rise. 

Nevertheless, the mendacity of telling the markets that you are concerned about fiscal responsibility just reduces the creditability of Secretary Yellen. She actively pushed issuance of Treasury bills higher to reduce the impact on longer rates. It was her job, but there was no push to support lower spending. She will retire but we will be left with the bill. 

Competition across nations starts at home

I was recently discussing the Draghi report on EU competitiveness and stated thinking about the old work of Michael Porter and his work The Competitive Analysis Across Nations which was an extension of his work on competitive analysis of firms. Porter developed the five forces diagram which is followed by most business students when they study strategy analysis.

For his study of nations, Porter developed his four diamond graph which is based on analyzing: factor conditions, the endowment of resources; the firm strategy or domestic conditions; demand conditions for what is needed, and the infrastructure of other industries. Governments can help with the environment, but countries do not have competitive advantage, industries do. Governments cannot make companies be more competitive. It can only create an environment that allow for competition. The private sector is where there is innovation and gains in productivity. If the EU wants to be more productive, then let companies compete gain scale and meet market demand. 

30 years of momentum research and it is only getting stronger

 

It has been over 30 years since the first major work on momentum was presented in a leading finance journal (Jegadeesh and Titman). Prior to that study, the conventional wisdom of efficient markets believed there was no trend or momentum effect. The world has changed and over the last three decades we have extensive research that has improve the initial research and strong explanations for why momentum exists. There are both behavioral and risk-based explanation for momentum and they have stood the test of time. Markets will under and overreact to new and will have different time dimensions. There is also a systematic risk component that can provide a reasonable explanation for momentum.

Momentum does not just exist in equity markets but is present around the global, in commodities, currencies, and fixed income. There is also commonality in stock momentum through industries and factors. Momentum is one of the strongest, most pervasive, and well researched factors in the marketplace. 

Of course, the strong long-term research results do not mean that momentum will always work as has been tested, momentum works strongest when there is a strong overall market sentiment. When more investors expect momentum is a given, it is more likely to have a poor performance year. There is a range of performance. 

All if this work is nicely presented in a review, see "Momentum: what do we know 30 years after Jegadeesh and Titman's seminal paper?" 

The out of control momemtum factor - can it continue?

 

The exceptional factor for 2024 is momentum. There are many ways to calculate this factor, but a simple equity benchmark is from S&P which has a broad suite of equity factors. The momentum factor is up 48% through the first eleven months of the year and is more than 50% higher than any other year and any other factor. Strong momentum factor performance does not mean a reversal in the next year, but the size of this move is extraordinary. Of course, the driver a just a few stocks which means that is not likely that this can continue if these key stocks have any slowdown or reversal. The high momentum winners may see a reversal after the one-year mark, but the follow-through on these names which have lasted for more than a year suggests that it is not a given that there will be a January effect. 

Realize that factor extremes can happen but does not suggest that there will be continuity. The rebalancing of names can support factor returns but looking at distribution properties leads to caution in holding the momentum factor.

Using generative AI for economic forecasting

 

Generative AI can be used to enhance economic forecasts through simple aggregation from corporate conference calls. We know that corporate CEO's provide economic outlooks on their earnings conference calls. It is part of the job, and it is critical that they get their forecasts right. The cost of being wrong high. Firm profits may suffer.

These conference calls provide a unique and special insight on the direction of the economy when all this information is aggregated. It is possible to aggregate all the verbal comments from transcripts using generative AI. All the information in conference call transcripts can be aggregated to form an index through highlighting key words and phrases like many other LLM models. An AI Economy Score can be employed to improve forecasts of GDP. 

Researchers have found that there is positive incremental value from using the score from the conference call transcripts. See "Harnessing Generative AI for Economic Insights". This paper scratches the surface on using AI to help with macro forecasting, but it provides a good foundation of how new tools can support better global macro decisions.

Factor investing across different regimes

Factor risk premiums are time varying and a simple approach of breaking the economy into a four quadrant macro regime world will have significant benefit. The mayor regime is based on rising or falling inflation and the composite leading indicators for the US. Both are easily obtained, and the four quadrants can be easily generated using monthly information.  Based on the factor premium indices from S&P Global Intelligence, we can identify changing factor return profiles. For the full story, see "A Historical Perspective of Factor Index Performance Across Macroeconomic Cycles". 

Specific regimes may last for long time periods only to see significant uncertainty as regime shifts come frequently. These factor returns will vary significantly. Clearly falling growth and rising inflation is worst environment followed by falling growth and falling inflation. The best environment is when growth is rising and falling inflation. 

The quality factor index shows the best returns overall returns followed by the low volatility strategy. While outperformance and hit ratios are clear during different regimes, the gains may seem small relative to transaction costs, yet a simple strategy of regular rebalancing will lead to significant gains over the longer run.    

 

The sobering impact of consequences and facts

 “Wisdom consists of the anticipation of consequences.” 

— Norman Cousins

“Consequences are unpitying.”

 — George Eliot

"Facts don't care about your feelings"

 - Ben Shapiro

“Should facts get in the way of truth?” Or, “Should truth get in the way of facts?”  

- Brad Feld  

The core of decision-making is accepting that there are consequences from actions. It is not a forecast or prediction that is the consequence. It is the action from the prediction that creates gains and losses. It is the action that has consequences.  

Similarly, facts are not feelings. Facts may differ from the truth you may want. Of course, there are interpretation of facts that may differ, but if the consequence of your interpretation is wrong, it is not the fact that is wrong. It is the interpretation. 

This may all seem obvious, yet it often requires reinforcement.  

Lord Kelvin's dictum on measurement - applies to finance

 

“When you can measure what you are speaking about, and express it in numbers, you know something about it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts advanced to the stage of science.”  - Lord Kelvin's dictum 

This is a good rule to follow in any financial work, yet once you are done measuring, you have to focus on what cannot be measured and make some conjectures for what is not explained.

As an aside:

Ogburn, a onetime head of the Social Sciences Division, was also responsible for perhaps the most contentious carving on campus. Curving around an oriel window facing 59th Street is a heavily edited quote from Lord Kelvin: “When you cannot measure, your knowledge is meager and unsatisfactory.” Ogburn was a hearty proponent of quantification in the social sciences, a view that some of his colleagues definitely didn’t share. In a 1939 symposium, economist Frank H. Knight Jr. (a teacher of Milton Friedman, AM’33) snarkily suggested that the quote be changed to “If you cannot measure, measure anyhow.” Fellow economist Jacob Viner chimed in with a suggested addendum: “If you can measure, your knowledge is still meager and unsatisfactory.”

"NIllius in verba" - "take nobody's word for it" especially in finance

 

The motto of the Royal Society, which is the science academy of the United Kingdom has a useful motto "Nillius in Verba" which is Latin for "take nobody's word for it". Science is not settled but is dynamic and to disprove the conjectures of the present. 

This motto is a useful guide for assessing all of the ideas and works that are done in economics and finance. Do not follow the story, follow the numbers. Live in a skeptical world when there is money involved. 

Categorize EM before running analysis

There are several ways of classifying emerging markets. JP Morgan Wealth Management has looked at a system of three key factors: economies with a large private sector which focuses on making money in a competitive environment; economies where companies generate high earnings per share; and economies with strong and growing export industries. The likelihood of success should be higher with holding country exposure in these economies. It does not guarantee success, but these are the countries which have a good environment for generating higher returns. There are five countries in this intersection. Four are in Asia and one is our southern neighbor. More focus should be spent on studying the dynamics of these countries. 

The weak link between EM returns and growth

Focusing on macro relationship and how they can be exploited in a model, we have looked at the relationship between growth and equity returns. We have been disappointed by the fact that the link has varied significantly across countries. In places like the US and Japan, equity returns have far exceeded nominal GDP over the last 15 years. In many other countries, GDP growth have exceeded equity returns. These numbers will be impacted by the percentage of companies within a country that have global business, but there is the impression or assumption that there should generally be a positive link between GDP and returns especially in the long run. Simple data does not suggest a link and deeper analysis is necessary. 

China GDP and investor returns - the big disconnect

 

The large macro disconnect in China is between its significant growth earnings, and stock returns. If we just look at China growth since 2010, we will see that the size of the economy increased by a factor over 3x. Earnings have increased, but little has changed in the last ten years. The stock market is almost flat since 2010. This is not the story that investors expected. Of course, the macro link between GDP and stock performance is far from perfect, but if you were given the growth numbers, most investors would have expected strong returns especially given the strong China export numbers. The negative view toward China is closely associated with the poor quality of this macro link.

The big rate breakout in historic context

 

There are short-term, medium, and long-term trends, but these are all usually inside a half a year for most trend-followers; nevertheless, it is good to focus on the very long-term to get a sense of the regimes that dominate the market view. If you look at trends over the last few decades, you will the great upward move of the 70’s and the 40+ year downtrend. The shorter-term cyclical credit trends show rates going up only with the market being hit with crisis which causes a reversal. Each shorter-term peak is at a lower high, but the chart is not the end of the story because we have not included the added two year period to November 2024. Look at the current level of 4.30 is way outside what anyone was thinking given the long trade. The last two years has been the great bond yield breakout and is nothing like we have seen in terms of a reversal of the bond channel. Discussion should always start with the new world bond view. 

The dollar trend is consistent with macro trends

The Fed is easing albeit less than what was expected eve three months again and the rest of the world seems to be willing to ease more than the US. The result has been a stronger dollar that is on the high end of the range for the last two years since the easing cycle began. This does not seem surprising. The US economy is stronger than expected, inflation has come down, and longer-term interest rates are more attractive to foreign investors. There is little reason for a dollar reversal even without accounting for tariffs and a new administration.

The dollar trend is consistent with macro trends with provides more confidence in this price move. 

The link between earnings, market returns, and GDP is not strong

One of the key problems with macro equity investing is that the link between earnings growth, market return and GDP growth are not often in lockstep. The chart shows that in the US earnings and market growth has been significantly higher than GDP growth, yet in many countries earnings and market growth have not been able to keep up with GDP growth. The link between GDP forecasting and market and earnings forecasting is not strong. You can be a great macro forecaster but that does not translate into making money in the equity markets.

Fractal Markets Hypothesis as an alternative to efficient markets

 

We know that the efficient markets hypothesis as originally positioned by Fama is not true. The behavioralists put a stop to the idea that markets are always rational and embed all information in prices, so good science requires an alternative hypothesis or a different way of thinking about how markets use information and generate price dynamics. We have earlier mentioned one alternative "The Discovering Markets Hypothesis - Worth a close look to add to our thinking of market dynamics" which focuses on how competing narratives impact prices. Another alternative has been developed by Edgar Peters who focuses on fractals and the fact that different investors have different time horizons that change with uncertainty. The fractal approach has merit when looking for regime shifts but may be harder to explain the day-to-day movements in price. The work of Peters has been around for some time yet has not taken hold. Neither has the work associated with Discovering markets. We will have to wait while further work is developed. 

The Fractal Markets Hypothesis of Edgar Peters states:

1. The market consists of many investors with different investment horizons.
2. The information set that is important to each investment horizon is different. The longer-term horizons are based more upon fundamental information, and shorter-term investors base their views on more technical information. As long as the market maintains this fractal structure, with no characteristic time scale, the market remains stable because each investment horizon provides liquidity to the others.
3. When long-term investors begin to question the validity of their information, their investment horizon shrinks, making the overall investment horizon of the market more uniform.
4. When the market’s investment horizon becomes uniform, the market becomes unstable because trading becomes based upon the same information set, which is interpreted in a more uniform way. So good news causes increased buying while bad news results in increased selling.
5. Liquidity dries up, causing high volatility in the markets, because most of the trading is on one side of the market.
6. Eventually the long term becomes more certain and stability returns to the market as investment horizons broaden and become more diverse.
7. During periods of low uncertainty, markets will exhibit well-behaved, finite variance statistics. In high uncertainty environments, markets will exhibit fat-tailed risks and unstable variance more associated with the stable Paretian distribution as described by Mandelbrot (1964).

"Inflation is a social phenomenon" - Not quite

"Inflation is a social phenomenon," Powell said. "If people believe that inflation will be higher, then it probably will be. And if they believe that inflation will come down, then people who make and take prices and wages, they will make sure that it does come down. So, it's absolutely critical that we be credible."

- Powell press conference 

Should we give him the benefit of the doubt or just call out the craziness of this comment. Of course, inflation is effected by expectations but where do those expectations come from? Perhaps the Fed itself as the the producer of money! 

You cannot just say that if you believe something, it will happen. Are expectations always rational? No. is a component of inflation expectations backward looking? Yes. However, if you are the head of the Fed, you have to take responsibility for your actions.  

The Discovering Markets Hypothesis - Worth a close look to add to our thinking of market dynamics

There are alternative views on how markets operate that are different from the efficient markets hypothesis which has taken a beating since the development in behavioral finance. Andrew Lo came up with the concept of Adaptive markets, but Tom Mayer and Marius Kleinheyer have developed an alternative called the Discovering Markets Hypothesis (DMH) which is based on three key points. Information held or learned by investors should be viewed as subjective not objective knowledge and this knowledge is adjusted when it compared against the behavior of others. Investors will communicate with others to cross-check their subjective knowledge. The communication of knowledge is through narrative. Narratives compete through their influence on prices. 

Facts influence subjective knowledge which is then shared with others through narratives. These narratives compete with others through their influence on prices. Prices, of course, will then provide feedback on the quality of the narrative. As subjective knowledge changes, there will be an impact on prices. Facts or new information will drive the changes in subjective knowledge. Because subjective knowledge cannot be counted or measured with certainty, there will be inherent uncertainty in markets which will cause prices to change in ways that are not always expected. 

The wild card for bond yields - the term premium

 

Treasury yield have moved higher while the Fed has lowered interest rates. This was not supped to happen. The question now is determining what is the fair value for Treasury yield out the curve. The usual method is to determine the real rate of interest which usually is about 2% plus some estimate of expected inflation which can be argued to be at level above 2%. So, if we use a real rate of 2% and an inflation rate of 2.5% we are at 4.5% as a good starting point; however, we need to add a term premium for the risk from holding these bonds out the curve. That number has been negative for an extended period but is now positive and rising. The current term premium is at the highest level in over a year; however, a longer history suggests that it can increase by a multiple of the current levels. One reason could be the lower liquidity in Treasuries, yet the recent fall is not seen in the term premium. Forecasting the term premium is now the Treasury yield forecast will card.