The big divergence in confidence

 

What is surprising is the large difference between the confidence of institutional investors versus individual investors, according to the International Center of Finance at Yale University survey. There is some lag with the data. The most recent data comes from May, yet it shows that institutions are very bullish while individuals are moving in the opposite direction, albeit recent data has demonstrated improvement. While this data shows unusual behavior in the last year, the gap is surprising. Nevertheless, this survey data with information on valuation suggests that the market can go higher - expectations are not discounting higher valuations

The power of combining value and momentum factors

 

One of the more interesting combinations of factor exposures is value and momentum. Value and momentum have both delivered strong excess returns, and blending them together also has strong benefits, even though the value and momentum strategies are negatively correlated. 

An interesting new paper looks at the combination by trying to explain the excess returns through a pricing kernel that uses nine latent variables from the combined value and momentum cross-section, see "Value and Momentum Leftovers". The combination has proven to be much better than investing in each factor by itself. However, there is an issue of what the pricing kernel should be to help combine these two factors because there is a significant alpha after trying to price the combination. Additionally, the idea that you can just blend the value and momentum as a 50/50 combination may not be effective. 

We will not go into the details of this "leftover" argument other than to say that the use of latent variables can help price these two key factors and can lead to better factor combination outcomes. The blend of value and momentum can be improved through well-defined pricing techniques. 

Thematic investing - How does that work?

 

One of the most significant trends in equity investing is the development of thematic portfolios; however, there has been limited testing of this concept. Thematic investing is presented in a model framework in the new paper, "Thematic Investing: A Risk-based Perspective". 

In the paper, the authors cite several definitions: “Themes are structural trends expected to significantly impact economies and redefine business models.” .... “Thematic investing can be seen as an additional dimension in portfolios.” and  “.... themes may pertain to macroeconomic or structural trends that transcend the traditional business cycle.” 

More formally, their model looks at the residuals for a set of assets. Cross-sectionally, these residuals should be uncorrelated after accounting for their main factors. In the case of a theme, there should be positive pairwise correlation across the set of assets identified in a theme. There is a relationship that cannot be accounted for by other known factors. Surprisingly, the pairwise correlations are relatively low within a theme. A theme is a set of assets that are identified by a narrative with a common trend. It is trend-following associated with a narrative.

Many identified themes do not prove to be correct, so there is an art to forming themes and not a science.

Choose your modeling technique wisely

 

One of the key challenges for any quantitative modeler is selecting the appropriate modeling technique. This involves not selecting the features or predictors to be included in the model, but rather the statistical techniques that will generate the best predictions. Not all modeling approaches are the same, so knowing when to use the best techniques is an important skill. The paper "From OLS to neural nets: Comparing regression models in systematic trading" is not the final word on this question. Still, it does a good job of making comparisons across techniques. It does not address all the machine learning techniques, yet it does compare many of the simple techniques that most researchers may employ. 

The tables from the paper are nice to have handy for anyone starting out when thinking about modeling.

Macrodrivers of stocks and bonds

 

The determination of the macroeconomic drivers of stocks and bands is a topic that has received much attention. If you can crack the holy grail of what drivers the major asset classes, you will be in a great position to manage any diversified stock bond portfolio. 

We know that the corrrelaiton between these two assets follows wide regime changes from positive to negative and then back again, so it is critical to find the key relationships. The recent CFA Institute brief, "Macroeconomic Drivers of Stocks and Bonds," utilizes an extensive dataset of macroeconomic variables to identify the key drivers. 

The focus of the paper is on factor selection using LASSO regression, which facilitates the stability selection of variables, and out-of-sample random forest regressions to enhance the prediction of key variables. 

The brief finds that LASSO regression can help narrow the set of factors used in finding these key relationships, and the use of random forests can lead to a significant reduction in the root mean squared error of the forest. Both are valuable tools with for helping any macro analyst improve their predictions. 

Nevertheless, the most interesting result is that you don't need many factors to explain a large amount of the variation in stock and bond returns. A keep-it-simple approach, combined with some stronger machine learning tools, will add significant value to any model-building. 

Trend market performance not all the same

PremiaLab Research has issued a new paper titled "Navigating Market Shifts with QIS Trend and Momentum Strategies," which analyzes trend and momentum behavior in 2025 and the last five years using their pure factor models. First, trend-following has not performed well across all major asset classes; however, an equity cross-sectional momentum approach did very well. The directional changes associated with the high uncertainty in 20205 have hurt those following trends. Trend-following is a pure directional strategy, while a momentum strategy focuses on relative movement to create a long/short portfolio.

Over the longer term, equity momentum continues to perform well, but there were also substantial gains focused on short-term interest rates. Clearly, there are no exploitable trends in all assets, and the secret to good trend-following is to balance exposures across all asset classes. 

 

Ken Rogoff's new book - A great way to understand international finance

 

This is a book that is a historical retrospective of the many key issues that Ken Rogoff researched over the last four decades. It is autobiographical as Rogoff walks through how he was engaged with many of the key topics of international finance. It was quite a run of problems: 

• The Cold War
• The Asian currency crisis
• The rise of China 
• The issue of Japan and currency moves
• The single currency in Europe 

All of these policy and economic issues required fundamental research to make the right choice and understand the crises being faced. Rogoff makes all of the issues approachable. The complexities are presented clearly, mixed with personal stories. If you want to understand the problems of international finance over the last few decades, you could not do better than read this book. 

Commodities march differently than gold

Gold is going higher, so it must be the case that commodities are also going higher? The data tells us otherwise. Commodities, on average, have been rangebound, but the gold versus commodity ratio tells a different story. The gains in gold are the result of something different. It is driven by the demand for a safe asset, not for its use in some production process or for consumption.  

Does this mean that commodity prices should see a gain in the future? There could be a general commodity rise, but it is not in the card based on a ratio. Sometimes a charge is interesting but not informative.

 

Opprtunity cost is the critical measure

 

The simple genius of Charlie Munger: 

“All intelligent people should think primarily in terms of opportunity cost. When deciding whether to do something compare it with the best opportunity you have.”

from farnanstreeetblog.com

Every finance decision, in fact every decision, has to be compared with the opportunity cost associated with the next best decision. Any use of time has to be compared with the next best alternative. Every decision has to be compared against other options every day. This is not supposed to drive a decision maker crazy because there are costs with changing decisions. Still, the idea of continuously measuring the opportunity cost is the basis for improving the use of time, energy, and money.

The loss of dollar dominance

I have written that the dollar decline is significant, but the fall only places the current dollar value near the long-term average. However, we need to acknowledge the extreme moves in the dollar over the last six months. The reason for the dollar decline is truly self-inflicted on the part of the US.

The dollar decline is not driven by systematic factors that would have been picked up by a quant model. The trend/momentum would have called for a short signal, but the exogenous factors have not been seen in past data. Growth in the US is not below the rest of the world. There is the threat of a recession, but the numbers do not suggest lower relative growth. Inflation is still higher than desired, but again the numbers do ot suggest a dollar decline. 

The three areas of concern are uncertainty, trade, and debt. Usually, higher uncertainty will lead to a flight toward safety, but in this case, the uncertainty is with the US. The trade and tariff issue is real, but we lack sufficient evidence of past tariff changes to accurately determine the correct dollar response. In the case of debt, there is clear evidence that large deficits will impact currency demand. Here is where the problem is centered, and there is no clear solution. The current deficits will not be solved with the budgets being suggested. There is a potential credit crisis with the dollar. 

Momentum and reversal related to turnover

 

Momentum is a key factor found across all asset classes. It is persistent and perhaps the most used of the major risk factors. A paper I had not read before provides more light on the topic by showing that you can have both reversal and momentum with 1-month returns if you sort on turnover. The low turnover decile shows short-term reversals, while the high turnover decile shows momentum. See "Short-term Momentum".

Reversal and momentum can coexist once you account for turnover. Large liquid stocks are less sensitive to price pressure effects. The price pressure effect is the main driver for short-term price moves and reversals, but turnover does matter. Don't fight short-term reversal unless you account for the turnover issue.

Dollar - Down but not out - Look at longer-run

 

The dollar has reversed two years of gains against advanced economies, but the moves are more muted compared to the broad dollar index and emerging markets. The speed of the decline is a concern, yet the dollar is still within a long-term range after a substantial gain. The question is whether the dollar is declining because there is less confidence in the US economy and financial system. It is a signal of US weakness, and that is a problem. 

The dollar remains the reserve currency, primarily due to its role as a medium of exchange; however, the store of value argument is problematic.

Conditional betas solve a classic problem

Beta is time-varying. There is no dispute about this. The traditional approach to addressing this problem is to utilize a rolling window to adjust beta over time; however, this method does not account for the changing environment. It just increases the use of new information.

A new paper, "Conditional Betas: A Non-Standard Approach," attempts to find a new method to account for changing beta. It compares the quality of beta forecasts with one of the leading alternatives of windsorizing the data for beta. The overall effect of a simple machine learning approach is very positive. Results are strong and only based on past price data. This is worth further exploration. 

I cannot tell you how frustrating it is to see a hedge balanced trade fall apart because the beta estimate is wrong. Market neutral is no longer market neutral. This may not seem like a significant issue for long-only managers, but for a long/short portfolio, it is a substantial problem.

Gold as a safe asset - an alternative to debt.

 

One of the topics that has received attention in microfinance research is the discussion of what constitutes a safe asset and whether it is in short supply. 

During a crisis, there is an increased demand for safe assets that are information-insensitive and serve as a means to protect wealth. A simple example of a safe asset is the US Treasury bill. When there is high uncertainty, investors tend to sell risky assets and shift to safer ones. However, if there is a shortage of these safe assets, the price will be bid up, placing downward pressure on interest rates. 

Nevertheless, there is the assumption that the supposed safe asset will really be safe. That is, the risk or market uncertainty cannot come from the producer of the safe asset. If there is an increase in risk from the safe asset, it will lose its convenience yield, and it will no longer be uncorrelated with risky assets. 

In this case, there will be a demand for alternative safe assets. One alternative is gold. Gold is often uncorrelated with risky assets during times of stress. It is negatively correlated with volatility and uncertainty, and it often protects against higher inflation that impacts the real value of debt-safe assets. It is information-insensitive, and it can be used as collateral. 

Many have suggested that gold is in a bubble, but that narrative shifts if you view gold as a safe asset substitute. If the US debt is less secure, then there will be a stronger demand for gold, which will push its value higher. If the relative safety shifts to gold and away from debt, then there will be stronger upward pressure on gold. The price increase has been significant, but it will be sustained if the safety feature continues to drive demand.

Performance at that the half year mark - nothing expected

We have lived through uncertainty, a war, trade battles, and various events that should have pushed markets lower; yet, we are at the highs in the core US market indices. This does not feel expected or normal.

One of my favorite exercises is to play out scenarios - what would you have expected to happen if a particular event occurred, and then examine the reality. No one would have expected the current outcome. This sharpens your intuition and also tests expected relationships.

We are now in a place with US stock indices touching all time highs and a widening of breath beyond the large cp tech sector. The markets have looked through uncertainty. Some of that uncertainty has been resolved, but that does not alter the underlying view that we are in an environment with a wide range of views. Of course, investors focus on downside uncertainty. There is also upside uncertainty, or a positive reaction to the unexpected., 

There is still a rotation effect toward international stocks; however, this bias is closing. High bet stocks and momentum have been the key drivers. In general, all of the worst case scenarios have proven to not be true. The overheated rhetoric has subsidies and the world seems. The doom reporting of the last six months may not be realized.