Economics and the need for history

"Forty years of investment in mathematizing economics has made it less acceptable among economists to admit ignorance of mathematics than to admit ignorance of history" - Deirdre McCloskey

You cannot be an economist today without knowing your math. To complete any PhD program, you will need to possess a strong understanding of mathematics, statistics, and econometrics. You will also likely have strong programming skills. Finance is being dominated by quants. 

You will not need to know history in this environment; yet, as I get older, understanding history becomes a critical skill. All policy analysis needs context for what has worked in the past. You need history to describe "experiments" in the past. The past determines the path for the current and future. 

In finance at the local level, you need to know the history of companies; their evolution is relevant. At the macro level, we need to know the specifics to appreciate our generalizations. It seems that one semester of economic history is not too much to ask for our experts.

This has been a common theme on how we think.

Finance needs more history to help with the future

Financial amnesia and the need for financial history

Don't just follow history, act on it

The value of history for economics from Charles Kindleberger

History in five crashes - Finance in the last century

Counterfactuals, history, and market analysis

History, linear thinking, and addressing market noise

Financial crises are inherent within our system

 

Gary Gorton provides a good history of financial crises in the US financial system from the free banking period to the Great Financial Crisis. These crises are not one-off events but are inherent in our financial system. There will be credit booms and busts,  and our history is filled with them. What is unusual is that we had a long period from the Great Depression to the 1980s when there were no crises. Innovations that change the financial landscape, moral hazard issues, too-big-to-fail, and shortages of bank capital all contribute to liquidity crises and contraction of credit. Through following economic history, we can see how the seeds of crises are sown. Gorton does a good job in this short book of providing the history and theory for why we should always be concerned about the possibility of a financial crisis.

The Richard Stone Diagram of models, policies and plans

 

I came across the Model, Policies, and Plans diagram from the 1984 Nobel Prize winner Richard Stone. It attempts to explain the production process for economic knowledge. It is a helpful picture of how economists first blend facts and theory to form a model. A model is mixed with objectives to form policy. Controls on the policy will create a plan, and events will impact the plan, leading to our set of experiences. We then go back to the beginning and repeat. This is an iterative process. As we get new facts, we will adjust theories and models. In the case of monetary policy, we should ask how the Stone diagram works inside the Fed.

Managers outperform mid and small cap benchmarks

The SPIVA report from S&P provides a good measure of the quality of alpha generation from long-only equity managers. The numbers are usually not very good. Managers usually underperform the large cap benchmark. Managers typically do better than mid- and small-cap benchmarks, although they still generally fail to beat the corresponding benchmarks. For 2025, equity managers are performing much better than the benchmarks by a much wider margin. 

Why are managers doing better? The simple answer is that it is a better stock-picking environment, yet that does not tell what the characteristics are that are causing this better environment. We argue that the dispersion in the stock market is higher and the cross-correlation is lower in the associated indexes. If there is more equity dispersion, the choices that are made by managers will lead to added performance. The choices improve when there is less correlation between stocks

 

The cause and effect link is not always obvious

This comic addresses many economic problems. There is no reason to think about unintended consequences or second-order effects, but you don't get the cause and effect right. 

Currently, there is an increased focus on cause-and-effect thinking within finance, as a result of the proliferation of factors used to explain returns. Some have stated that there are hundreds of factors that may drive returns, yet they often do not work outside of the training period, or they seem to periodically move in and out of favor. The problem is that there is insufficient consideration of the relationship between cause and effect. Factors are found and stories are developed to explain why a factor may be relevant, but that is not the same as positing a theory and then testing it. Correlation with a story is not causal.

Liquid Alternative Beta (LAB) performance for August

 

The Liquid Alternative Beta (LAB) indexes, available from HedgeIndex, formerly Credit Suisse, offer a comprehensive view of the performance of various hedge fund strategies in August. All the hedge fund strategies were positive for the month. Returns were consistent with the overall market, SPX, which gained 2.03% for the month. The LAB indexes beat the S&P500 growth and momentum factor-based indexes. The global strategy and managed futures indexes were able to take advantage of the tail winds from positive international equities and bond returns. This places most strategies with positive returns for the year, except for the managed futures and liquid indexes. The managed futures strategy has started to find trends after a difficult first half of the year. 

The LAB indexes have lower volatility than the long-only benchmark strategies. 

Prediction is not optimization

Many researchers and practitioners have questioned how the input parameters of MVO should be estimated. To this, Markowitz is said to have responded with wit and grace, “That’s your job, not mine.”

- Stephen C Sexauer and Laurence B Siegel. 2024. Harry Markowitz and the philosopher’s stone. Financial Analysts Journal

With the quant revolution, there have been significant advancements in the methods and types of optimization that can be used for portfolio management. However, the key to successful optimization remains the accurate predictions of expected return, volatility, and correlation. Optimization on the wrong inputs is a fool's errand. 

The machine learning explosion has to focus on system predictions across a large set of assets, which can then be used as inputs into a traditional optimizer. Before using an optimizer, focus on the input variables. 

European versus American trend-followers

 

A recent paper, "The Science and Practice of Trend-following System", makes the interesting observation that there is a difference between European and American CTAs or trend-followers. The paper tries to provide a unified system for trend-following, a noble cause. However, what piqued my interest was the authors' comment that there were three major trend-following classifications: European, American, and time series momentum. 

I have always believed and commented that there is a difference between the major European and American trend-followers. I have stated that Americans are ideologues who adhere to a system developed in the 70's and 80's, while Europeans are pragmatists who focus on any technique that seems to generate profits. Sepp and Lucic hold the view that European CTA focuses on continually adjusting positions based on current risk, coupled with exponential moving average systems. American trend-followers emerge from the technical system world, focusing on breakout systems that involve full positions based on the signal. The third system focuses on time series momentum systems, which are correlated with moving average crossover systems. 

You might think that these approaches are all the same, but you would be wrong.  The American system has the highest Sharpe ratio, but the other methods are not far behind. In a given year, there will be differences, but it is hard to say that one approach is superior to another. You are left with the issue of finding a strategy that works for your risk tolerance, and in this case, risk tolerance is based on your comfort with the return generation process. 

The hedge fund industry - Changed with Bernie Madoff

In our last post, we focused on the upheaval to the hedge fund industry from the GFC. The downside risk caused surviving hedge funds to innovate through forming management structures that attempt to gain scale and scope. Size and diversification as a form of hedging downside risk.

In this post, we focus on the second major upheaval to the hedge fund industry - the Bernie Madoff scandal. While hedge funds realized that they needed to gain scale and scope to save their businesses. Investors demanded more professional management and a broader scope of functions, as seen in other industries, in response to the uncertainty within the hedge funds in which they invested. Call it the rise of super due diligence. Of course, the government increased regulation, but investor due diligence also rose in response to fraud. The costs, especially for running a small hedge fund, increased because investors were not going to pare back due diligence because the manager was smaller. In fact, the risk of failure or fraud was likely higher for smaller funds. 

The Madoff change led to stronger internal controls, legal, and compliance departments. There was also a greater demand for transparency and contact with the manager, which increased the need for investor relations and marketing. The demand for risk management and exposure reporting led to the creation of separate departments from the investment business. 

Once the demand for transparency and more formal due diligence took hold, hedge funds had to provide many of the same investor services as long-only managers. The market shifted assets to larger firms, which in turn led hedge funds to focus on scale and scope, adopting more formal organizational structures.

The hedge fund industry - Changes from the GFC

The hedge fund industry - Changes from the GFC

 

The hedge fund industry has undergone significant changes since the Great Financial Crisis (GFC), which have not received sufficient attention. The focus is usually on performance, yet it is essential to consider hedge funds as a financial industry, one that evolves and adapts to the market environment. 

Hedge funds have not really developed new ways of generating alpha. They have adopted a greater use of quantitative tools, which represents a significant innovation in enhancing existing methods for generating alpha. However, the real innovation has been the movement toward vertical integration, a widening of scope through product development, and the formalization of management structure. 

The hedge fund industry was not immune to the significant declines in returns from the financial crisis. Many firms went out of business, and many experienced severe declines in cash flows. Assets under management declined, and the expected incentive fees were reduced or eliminated. The industry had to change because the surviving focused star manager could not survive another downturn like the GFC. 

The choices were clear, no different from those in other industries that underwent upheaval. First, the innovation of the hedge fund industry was to diversify the firm's offerings. This could be the same fund but with a broader market focus. It could also be different products within the same asset class or across asset classes, or it could be some customized product with features set for a large client. Second, there was a need to gain scale and better control costs through better professional management. This could take the form of formal marketing. It could also be a separate legal and compliance department, as well as separate risk management and trading departments. 

The desire for scale and cost control meant that the small shop, with its focused manager or personality, needed to become a departmentalized, professionally managed organization. There was an end to personality and a shift to departments that focused on specific tasks, overseen by the manager/owner.

This process was observed in many other industries in the US prior to the turn of the twentieth century. This is the story of American business and its pursuit of scale and scope. The hedge fund industry is not special. It follows the pattern of other industries.