Inertia - An application to investments as simple go to rule

 

“An object at rest will remain at rest unless acted upon by an external and unbalanced force. An object in motion will remain in motion unless acted upon by an external and unbalanced force” 

- The first law of Newtonian physics  

I don't want to get into the battle of whether finance is like physics, but Newton's first law of motion is a good framework for thinking about markets with respect to trends and reversals. 

A market in trend will stay in trend until there is a force to stop it. Similarly, a market at rest and rangebound will stay rangebound until there is a force that exerts the market to move it either up or down. Yes, as a starting framework, this is simple, but it serves as a good foundation. Reversals will occur when there is a reason or shock to the market. Markets will trend when there is a force pushing expectations and there is no change in that driver. 

The hard part is determining what are the forces that will drive prices. These can be macro and associated with central bank announcements or with economic data. For individual stocks, the force may be an earnings announcement. Of course, there are multiple forces that may exist outside of these announcement shocks. There is rebalancing, changing of sentiment based on volatility, reaction to news, and the general flow of funds across strategies and trading groups. Nevertheless, a key role of investing is identifying the forces that will drive markets to trend or reversal.

However, the foundation of trend-following and price-based models is that the forces driving price motion are hard to identify and even harder to properly link to prices. The reaction of economic agents and the impact of expectations make the link between force and price noisy. Hence, the focus for many is on extracting the signal from prices.

Commodity skewness is a risk factor for excess returns

Skewness matters because it tells us something about the tilt in sentiment and crowd behavior in commodity markets. By looking at the skew for a portfolio of commodity markets and sorting by quantiles of low to high skew based on the rolling prior year of information, it is found that there is significant gains from buying the lowest skew and selling the highest skew. This factor has been measured to be stronger than other well-known commodity risk factors, see "The Skewness of Commodity Futures Returns".  The impact is statistically significant and cannot be explained by other pricing models like the overall commodity market portfolio (equal weighted) momentum, term structure, or hedging pressure.

The argument for holding these negative skewed commodities is that investors prefer lottery tickets and are affected by prospect theory; those commodities that have positive skew which will be overpriced in the marketplace. Those commodities that have negative skew need compensation to hold these skewed assets. There is also a selective hedging story that places longer hedges for positive skew (producers hedge less and consumers hedge more) and shorter hedges for negatively skewed assets (producers hedge more and consumers hedge less). It is found that negative or low (high) skew have more backwardated (contango) characteristics, but the skew effect cannot be explained by other factors.

The positive value (premium) from skew works for both time series and cross-sectional analysis and provides another way to measure risk premia within the commodity markets. 

Does bank regulation need to be streamlined? Should the Fed be the key bank regulator?

 

Who is the top regulator of banks? The Fed. Yet, the Fed is not a government agency. It was formed by an act of Congress but is a public/private combination where there are 12 regional banks with board of directors from member banks in a region. The banks must hold stock in the regional Fed bank, but all excess profits from the Fed are sent to the Treasury. The Fed and its regional banks have their own budgets, but the Chairman is required to report to Congress and the Board of Governors of the Federal Reserve System are selected by the president subject to approval by the Senate. Within this structure, the regional banks will regulate member institutions. 

To put it simply, the regional Fed banks will regulate banks that can have executives on their board of directors. That was the case for SVB. The supervisors have a conflict with their member boards. It may not occur, but the appearances or chance for conflicts seems high. 

All the problems with SVB were evident by reading their SEC filings, so what were the bank supervisors doing? What effective oversight were they providing? What should be their role to limit bad behavior before we have a tun on a bank? 

The Fed has supervision of national banks so that it can ensure the safety and soundness of the financial system and the execution of monetary policy. A streamlined regulatory system makes sense, but is that what we currently have? 

Just in case you need a refresher, here is a simple map of current regulatory oversight from Chris Skinner.  So, who is responsible for overseeing bad management? If everyone is in charge, then no one is in charge.

Here are two more graphs which should make the point clearer from everycrsreport.com. So, can you tell me who is the chief regulator and who should be held accountable? There should be clarity and no conflicts. I don't know if we have that.

Cheap money can give very expensive lessons

 

Cheap money can lead to very expensive lessons. Unfortunately, the time between an era of cheap money and the expensive lesson can be long, so we do not often make the important connection. 

There are two problems here: one, investors don't realize that there is a disconnect between cheap money and expensive lessons, and two, the learning of this lesson is confounded by the delay between the event and consequences. We learn quickly when the time difference between cause and effect is short. If there is a delayed response, learning is slow. A quick feedback loop is a "kind" learning environment, while a long lag will often be called a "wicked" learning environment.

Cheap money means that we will accept projects that have a lower return based on the assumption that cheap money will last forever.  When the market moves back to normal, investors will be holding lowering returning projects that can only be sold at a loss. If cheap money exists for a longer period of time, investors get used to it or in some cases get addicted to it. They will not be prepared for more expensive money. The reach for yield at lower absolute levels must be reversed. Remember just a few years ago, there was well over a trillion dollars of global government debt at negative rates. That seems like ancient history.

The key banking problem is that financial institutions were living off cheap deposits that can move anywhere for higher yields. The flow could be to larger banks or to MMF that do reverse repos with the Fed which causes a reduction of reserves. Those cheap deposits funded longer term assets at low yields. Now, the cheap money game is over, so banks must adjust and reprice their low yielding asset portfolios.

See "Kind" versus "Wicked" learning environment - Financial markets are not kind

Financial crises - Not what was unforeseen but what was unaddressed

"Nothing about this crisis was unforeseen, it was just unaddressed." 

- Karen Shaw Petrou referring to a past financial crisis

Perhaps the unaddressed is always what is the problem not what was unforeseen. As we explore the details about the current bank failures, we see that there was no surprise event that drove the crisis. We are again learning that, after the fact, all the information concerning a problem was readily available. 

A crisis occurs not from a surprise but from a cascade of change after the information is internalized or realized by a critical mass of investors. An event may serve as the wake-up call, but the underlying risks already existed. The problem is when everyone realizes there is a problem at the same time. 

Silicon Valley Bank - The huge asset-liability mismatch was well known and reported in their financial statements. The strong deposit growth which had to be invested was well-known. The large funding from the FHLB was well-known. Regulators at the San Francisco Fed were fully aware of the problem.  

Signature bank - The excess of uninsured deposits was well-known. The risks with it being a bank for crypto firms was well know. It was the focus of regulators.

Republic Bank - The excess of large deposits and significant inflows from Silicon Valley firms was well-known.

Credit Suisse - The poor management, losses, and regulatory problems were all well-known earlier. It was a bank filled with problems which could have been addressed earlier by regulators. Investor clearly had issues as evidenced by the stock price. It was just a matter of time.

All were hit with the problem of higher rates which again was not a surprise. Poor early action has led to crisis times. We cannot just say that "mistakes were made", nor can we say that these firms were hit by a shock. They were already working with poor odds. In all these cases, a critical mass of depositors acted on this awareness in a cascade which caused a run.

Trend-following - Living on long volatility and dying on short volatility

 

There are two key concepts that are fundamental to my view of trend-following. One, trend-following is a divergent trading strategy. Money is made when markets diverge from equilibrium; however, the time and size of divergence must match with the trends being identified. A strong or sharp short-term divergence may not for a long-term trend-follower Two, trend-following is long long volatility and short short volatility. Money is made when there is longer-term dispersion in markets and money is lost when there is a spike in short-term volatility which stops out longer-term positions. If there is no dispersion in prices, there are no strong trend profits. If there is a spike in short-term prices, positions are knocked-out. Trading with stops is a knock-out option strategy. 

Given the wide combination of divergences and volatility, there is a good reason to hold a portfolio of trend-followers who use different time frames, different strategies to access markets and manage risk, and different strategies that hold a diverse set of assets.

These two intersect when there is a condition of a longer-term divergence. A change in market fundamentals from the existing price range that is not immediate seen by investors will lead to profitable trends.  We saw this environment during the GFC, the pandemic and aftermath. 2022 was a great year as the market adjusted to higher inflation. Unfortunately, these ripe conditions do not exist in 2023. The SG Trend index shows one of the worst declines since inception which reversed half of the 2022 gains.

In this 2023 case, we have had a market divergence, a bank crisis, that is turning into a banking crisis. First, there has been an unexpected market shock which has led to a spike in short-term volatility that has caught the market wrong-footed relative to existing trends. The result has been swift and strong. Strong losses in bond trading and choppy market behavior in equity indices. The divergence has been arrested by government policies to contain the shock. The longer trends may prove profitable but the short-term has been a period of position adjustment surrounded by losses. These losses will be offset if the market divergence continues. Any continuation will be a function of government policies; nevertheless, the restriction on policy choices from inflation may mean that longer-term trend following may still be profitable in 2023.

Investment information - Do we really want it all?

 

Investment success is all about gathering information and using it to create a decision edge. Unfortunately, we are drowning in information. The excess of information means that we will not always see pertinent facts. There is a problem of inattention. We also don't always want to know all the facts.  There is a problem with the reaction to information.

We often look for information that will give us positive feelings and avoid those facts that will create negative feelings. Facts don't have feelings, but the people looking at the information do, and that causes problems with avoidance. There also is a desire to look for confirming information which usually gives us good feelings. The contradictory information is going to give us negative feelings. There will be information that we don't want to know. We will go out of way to not use information if we think it will not make us feel good.  This is not just an investment problem. 

Information will also have instrumental value which can either be positive or negative. Still, we will want to avoid bad information that conflicts with what we want to hear. I don't want to read the warning level that may be associated with a favorite activity. 

Information is always subject to a cost benefit analysis by the receiver of the information, so we must  always ask, what is our willingness to pay for any set of information. The willingness to pay (WTP) is not the same as the price of information. 

In a more general case, what will you pay to have warnings labels or labels on nutritional value? In the investment case, what will you pay for more information on companies? What is the WTP for different pieces of data. Will you use all the information that is available. What is the price for that data?  

In the case of SVB bank, the data was all available. Was it used? Did investors and depositors want to hear this information? 

Some of these issues are discussed in an older book by Cass Sunstein, Understanding What You Don't Want to Know. It is worth a read to think about how we use information.  

An ensemble of models is not the same as an ensemble of experts

 

There is the idea that there is a power with group decision-making - an ensemble of thinking will improve predictions. In reality, group decisions and dynamics are difficult and not always productive. An ensemble of experts in a committee is not the same as an ensemble of models. When people refer to the wisdom of crowds they are often thinking of the collective wisdom from averaging opinions and not their collective deliberations. 

An ensemble of models will usually be uncorrelated by construction. These correlations may change with market conditions, but they will not change because a set of models win an argument on which is better. These predictions can be averaged but we will know their level of independence. 

An ensemble of models can be tested backed through time. An ensemble of experts cannot usually be tested or stressed to find how it will react to new situations.

Models are independent of each other. The crowd is not independent. The crowd can be subject to herding or information cascades.  Group dynamics can move to extremes in ways not possible with a collection of models. 

Collective behavior in models will be good especially in periods of uncertainty. The collective behavior of a group may be good, but it is not a given. 

Group dynamics can lead to poor decisions, so be on your guard

 

There has been the strong view that there is wisdom within crowds. Research has shown that a group will do better than the individual at predicting. The collected wisdom and ensemble from the group will be closer to reality than any one person.  

A closer look suggests that group dynamics have some major problems with making good decisions. There is a big difference between a statistical group, wisdom from the average forecast of a group, and the deliberative group as a predictor. Generally, we don't poll members of group and form their average. The normal approach is that the group will deliberate and come together to solve a problem, make a decision, or prediction.

In the case of asset management, the core group is the investment committee and when you look closely at the mechanics of an investment committee, you will likely conclude that many are dysfunctional and not very good at their core task. 

The problem with most groups is that they can amplify errors through behavioral biases no different than individuals. There can be cascade effects that opinions are swayed by a few that push the rest to a decision. There can be polarizations that is driven to greater extremes, and there is often focus on shared information and not on new information. Not much hope for the group, yet there are some simple changes that can support better group thinking. 

The solutions follow a simple framework that emphasizes using data, rewarding successes, and ensuring equal weight toward alternative opinions. 

The power of models or even an ensemble of models is that they will not have the problems of group dynamics. The issues associated with group dynamics and potential solutions is discussed in the book Wiser: Getting Beyond Groupthink to Make Groups Smarter by Cass Sunstein and Reid Hastie. Everyone should work on improving group dynamics but there is clear value with allowing an ensemble of models serve as the group. 

Disintermediation - A word very relevant for banking today

 

Financial disintermediation has always been an important topic for financial institutions, but it has not been the focus of research when rates were close to zero. There was disintermediation from the reach for yield, so depositors kept balances low. For their liquid funds, there was not a lot of shopping for higher rates, because all rates were low. There was not advantage of moving to a money market funds because the excess yield was limited, and the absolute yield was low. 

Go to the pandemic and the world changed. First, deposits exploded given all the extra money in the economy. Banks could not lend the money and yields were low. However, inflation grew, and the Fed started to raise rates. It is now very rational to shop your deposits to higher yielding alternatives.  

Depositors will shop for higher yields at other institutions. They will shop at money market funds. They will use their excess balances for purchases. The result is a decline in deposits which means that something must happen on the other side of the balance sheet.  Assets must be sold. 

Banks that are not competitive with rates on deposits will see disintermediation. Firms with excess deposit balances will be drawing them down. If asset liability management has a gap, there will be a real cost to equity. We have seen the extremes with several banks, but this is a global problem. 

Credit tightening is already here, but will get worse

Bank failures and crises leads to a tightening of credit. This is the secondary effect that is often overlooked. The focus is on the immediate failure and the depositors, yet the economy will be driven by the credit channel as well. The credit situation was difficult before the bank closures. 

The bank credit standards are tightening across the board and closing in on the highs from the pandemic. There is little to suggest that this trend will change. 

Bank credit growth is slowing. Less loans are being made although a 5% growth is respectable. The trend is falling. M2 money supply growth is now negative. Of course, the supply is still high given past growth, and we will see an increase with the Fed injection of money, but the trend is lower.

The short-term credit has improved with the bank bail-out, but the combination of higher rates, tightening standards, and slowing loan growth does not paint a pretty picture. 

 

Dunning-Kruger Club and knowing your limitations

 “The first rule of the Dunning-Kruger club is you don’t know you’re a member of the Dunning-Kruger club.”— David Dunning

"A man's got to know his limitations" - Dirty Harry (Clint Eastwood)

We just have too much confidence relative to our knowledge. This is once again seen with the current banking crisis. We have overconfident bankers and we have overconfident regulators. Both think they can make predictions about the future; the future of rates and the future of the bank environment. Both are not aware of their limitations.

If there is too much uncertainty, there needs to be more humility on what can happen. A lack of knowledge does not mean that there should be a failure to act. Action may be required, but the policy response should be measured to ensure that the unintended consequences will drive and constrain the future.  There are many alternatives between no action and complete bail-outs. All should be considered.

The hazard of experts - How do you avoid this hazard effect with hedge fund managers?

Belief superiority and belief confidence - Watch out if you think you are superior

Ignorance, Risk, and Uncertainty - Knowing our limitations

 

Surprises - You should be surprised when they don't happen

 

“Everybody’s all surprised every time this stuff happens. It surprises me everybody gets surprised because it happens every year like this that there are surprises. The most surprising thing would be if there weren’t any surprises. So, therefore, in the final analysis, none of it’s really that surprising." 

- Mike Leach football coach 

Coach Leach's language may be convoluted, but the message is always the same. There will be surprises. Of course, sometime there are good surprise and other time there will be downside surprises. 

These are the risks that we face. It would be unusual if there were no surprises. Hence, the good investor should expect and prepare for any surprises. You will not be able to predict them, but you can  try and mitigate their effects. 

Financial history and those damn facts - How to we interpret the past

 

Investors are always looking for patterns and analogies from the past. Analysts look at a specific event today and then discuss how it is similar to a past period. We extrapolate from these cases to form an idea of what we may see in the future. We look at past rate increases and compare them to stock market changes. We look at past periods of inflation or unemployment and compare with interest rates. However, there is a problem that gets in the way; those darn facts of how data are collected.

The stock index of today is not the same as the index 10 years ago or 20 years ago. Tech companies represent the largest capitalized companies today. Decades ago, energy companies were the drivers. It is hard to say that the volatility or response to a macro event today is close to the response to the same type of phenomena from 20 years ago. We can calculate sensitivities, but they change through time. Beware. 

The way we calculate inflation or unemployment have also changed. We know that in the case of inflation the basket of goods today is not the same as the basket in 1980. Narratives of inflation can be told, but detailed analysis of the past for trading is a different story. 

Looking back on return data from 50 to 100 years should only be done carefully. We can see the numbers but that does not mean we know the numbers. Of course, the answer is to not avoid the work but to recognize the limitations.

Clayton Christensen on disruption - more complex than you think

 Clayton Christensen is the father of thinking about disruptive technology, but he has stated that most people do not understand what he really means. See  "Clay Christensen says everyone misunderstands his theory of disruption — here's what it really means". 

• Disruption is a process, not a moment in time.
• Disrupters typically utilize different business models, not just different products or services, from incumbents.
• Disruptive innovation does not guarantee success.
• A company does not necessarily have to disrupt its core offering when it is being disrupted.

This is a more nuance view of disruption which thinks of disruption as a process not an event. Most examples of disruption focus on products when the disruption can come in the form of a strategy or model.  Most stories also focus on the successful disruptors, but a disruptor can be wrong. The timing can be off. The execution can be wrong, and others may be better able to take advantage of the disruption. Incumbent firms do not have to change their strategy in the face of disruptors. They can compete with the new ideas. 

The finance industry is filled with disruptions, yet firms often do not focus on how to deal with or take advantage of change. Hedge funds must constantly think about disruptive strategies and models and accept that disruption is a constant. 

Silent bank runs - Is there a need for withdrawal restrictions

 

When we think of a bank panic, the image that comes to mind is a long line of desperate depositors all scrambling for their money. Depositors are fighting to get to the front of the teller line. For institutions, there is the image of corporate treasurers on the phone yelling at bank employees to wire money. This is not reality. Bank runs are currently silent, a click of a button. There is a new spend with withdrawing money or sending funds.  There is no noise, no friction, just action. Money can move faster than  ever and many depositors will not even know it is happening.

There is a question of whether there needs to be more frictions in the financial system to combat panics. Funds have gating provisions which are usually not reviewed until the gate goes up. Of course, there will new responses if frictions are added, but the question should be asked; could we reduce the chance of a bank run by forcing withdrawal restrictions in depositors. I am not for it, yet technology creates new issues that must be matched by new regulations. 

The "Great Repricing of Bonds" is the problem

 

Banks are not the problem. Banks are the symptom of the problem. Bank management does dumb things and leverage always hurts if you are on the wrong side of a trade. Panics will occur if there is the view is that this problem exists for more firms. 

However, the real issue is the "Great Repricing of Bonds". Interest rates are going up and this is going to last a longer time even if inflation is under control. 

Banks hold bonds and if they are not floating rates, they will be repriced with unrealized or realized losses. Just look at the amount of losses at banks from the repricing. This is system wide. This is a global issue. There is no getting around this problem unless rates fall across the world. Of course, the real value of bonds will also fall with inflation. Wealth is being destroyed and there is no way to effectively hedge this problem.

Panics - Is the SVB event another perfect storm?

 

Robert Bruner and Sean Carr laid out 7 reasons in their book The Panic of 1907 why 1907 was a perfect storm for bank runs and a massive financial crisis:

1. Complexity. Complexity makes it difficult to know what is going on and establishes linkages that enable contagion of the crisis to spread.

2. Buoyant growth. Economic expansion creates rising demands for capital and liquidity and the excessive mistakes that eventually must be corrected.

3. Inadequate safety buffers. In the late stages of an economic expansion, borrowers and creditors overreach in their use of debt, lowering the margin of safety in the financial system.

4. Adverse leadership. Prominent people in the public and private spheres wittingly and unwittingly may implement policies that raise uncertainty, thereby impairing confidence and elevating risk.

5. Real economic shock. An unexpected event (or events) hit the economy and financial system, causing sudden reversal in the outlook of investors and depositors.

6. Undue fear, greed, and other aberrations. Beyond a change in the rational economic outlook is a shift from optimism to pessimism that creates a self-reinforcing downward spiral. The more bad news, the more behavior that generates bad news.

7. Failure of collective action. The most well-intended responses by people on the scene prove inadequate to the challenge of the worst crises.

from Ben Carlson - A Wealth of Common Sense 

Can we say that this is another perfect storm? Perhaps there is no such thing as perfect storm, but this is close. 

1. Complexity - This should be simple, but the accounting for banks is not simple. There is Hold to maturity (HTM) and available for sale (AFS) that have made studying bank risk more difficult.

2. Buoyant growth - The deposit growth for the three years before mid 2022 was very strong, much stronger than loan growth which created an investment problem.

3. Safety buffer - Many banks have reached for yield with longer duration which changes the safety buffers. 

4. Leadership - We are moving from a period of zero interest rates and QE to higher rates and QT. The guidance from the Fed has been mixed which has added to uncertainty. Bank leadership has followed strategies that have created more ALM risk.

5. Shocks - Between the pandemic and rising rates, the markets have suffered from an uncertain environment.

6. Fear and greed - Concerns or fear has caused a run on deposits.

7. Collective action - The funding of new equity failed. The panic was not stopped, and buyers of the bank could not be found.

SVB is not a unique situation. It is more of the same from over 100 years ago.

Anticipatory Thinking and becoming a better investor

 

A good analyst is supposed to be a good predictor. Successful forecasting matters, yet many are not very good at it. Being a good forecasting for investment success is a high bar, and unfortunately, very little time is spent in business schools teaching how to be a better forecaster. MBA students are taught about to find an expected return and study finance models, but little focus is spent on how to make better decisions. There may be course on decision science, but here the focus is on how to use empirical tools to make forecasts and not on how to make decisions in an uncertain world. There has been some very good work in this area, but not with respect to finance. Finance has spent a lot of time and effect on measure cognitive errors but not a lot of time on how to make better decisions other than to say that you should avoid cognitive errors and biases. Prediction is not the same as decision-making.

An interesting twist has been to focus not on prediction but anticipatory thinking. A prediction states that a given event will occur by a certain date with a probability of "X". Anticipatory thinking tries to generate the events that will then have to be predicted. 

Anticipatory thinking is an important macrocognitive function necessary for successful investing. Simply put, anticipatory thinking is the ability to prepare for specific problems and opportunities. In the current environment where we have just had the failure of SVB, anticipatory thinking works through the preparation for what may occur. What may I expect? How should I deal with different scenarios or events? If this happens, what will I need to do? What will be my response given an event? Anticipatory thinking is functional and not focused on handicapping what will happen. Recognition of events is a precursor. Anticipation of hazard is different from predicting hazards.  

Some forms of anticipatory thinking: pattern matching, trajectory tracking, and conditional analysis. Pattern matching looks for similarities from past studies that may enlighten thinking. The classic analysis of comparing current events with past historical events is a simple form of pattern matching. Trajectory tracking looks at the trend or trajectory of events and then tries to get ahead of the curve. If I am tracking a ball when playing catch, I must try place myself in a position where I can make the catch. I am getting ahead of the curve. Conditional thinking is what we often engage with as part of our prediction process. If I don't do "X", there will be bad outcomes. Conditional on these events, certain scenarios are more likely regardless of whether I am making a formal prediction. 

Anticipatory thinking is not the same as using models or data science to help formalize possibilities. It is not a data problem. It is a not a matter of reducing biases. It is not just increasing vigilance. Rather it is looking at possibilities and looking at scenarios. It is work necessary to make better decisions and predictions. Think less about prediction and more about anticipation.

Bank risks and deposits - Looking at insured and uninsured deposits

 

An important issue with the SVB bank failure was the run on the bank with billions flowing out before the government took control. All depositors are likely to pull money if there is the expectation of a failure, but the probability increases if the deposits are above the $250,000 threshold which is protected with deposit insurance. You may still have restrictions on when the money will be available, but the threat of loss is less. 

The real worry is that those depositors above $250,000 will pull their money. Large depositors will create a run on the bank through their actions because there is a greater risk that they will not get their money back. Hence, there is an incentive for these depositors to leave early. 

Large deposits are hot money, so banks that have a higher percentage of their deposits base in uninsured accounts are more likely to see a run on the bank. Their "hotness" exists even if there was no risk of a bank failure because that money should be more sensitive to rate changes. If Treasuries yield more than deposit rates, the money will flow toward Treasuries. The decline in SVB deposits started before the bank risk increased.

The table below shows deposits less than $250,000 as a percentage of total deposits. Those institutions with low numbers are more likely to face bank run risk. We should expect that those banks have a higher equity premium.

Bank failures always the same: The case of SVB

“Happy families are all alike; every unhappy family is unhappy in its own way.” - Anna Karenina

It is one of the most famous lines by Leo Tolstoy and is true about families but may not be true of not bank failures. A bank failure like Silicon Valley Bank (SIVB) has some very familiar characteristics. The facts are still being sorted out, but we can say that this failure has similar characteristics of other bank failures. 

The classic failure characteristics were obvious risks that went unnoticed by all parties. There was an asset liability issue. There was herding and contagion. There was a liquidity issue. There was no black swan event but a pink flamingo risk staring at us. Of course, most of the events always seem obvious after the fact.

SIVB was a simple story. Large deposit growth in 2019-2021 relative to the loan portfolio meant that the bank invested in Treasuries and mortgages to stay liquid and gain a return. These bonds were place in the HTM (held to maturity) account unhedged given they were held at book value. Losses on the bond portfolio grew as rates rose, but the losses were not realized given they were held at book. 

Deposits started to decline as rates rose. This is a bank industry problem. Money markets and Treasury rates were higher than bank deposits, so investors pulled money from banks to grab the higher yields from Treasuries. We see this in flows through the growth in Treasury holding by households and the decline in deposits especially at non-money center banks. 

To meet the depositor withdrawals, Treasuries had to be sold at a loss. These losses eat into bank capital. The problem is not based on bad credit but bad asset liability management which is a liquidity issue. Their assets have a longer maturity than liabilities. This was a rate bet that went wrong.

Once these issues become apparent to many investors, the contagion and herding takes place. As more deposits leave, more assets have to be sold, and a further decline in equity. The spiral of decline accelerates which leads to the current failure.

Now investors will start to look at other banks with the same characteristics. The rise in rates is now becoming a stress point for banks. 

Business cycles impact growth trend - hysteresis

 

There is the trend in economic growth and then there is the business cycle which fluctuates around the trend. Many economists think of these as separate questions or issues. Figure out the trend and lock that into your thinking. It is usually associated with demographics and productivity and around 2%. Around the trend, there will be cycles. Unfortunately, life is more complex. The recession of today will have an impact on the long-term growth of tomorrow. Hysterersis studies the longer-term impact of these shorter-term cyclical shocks. Many economists call this the scarring from past events. 

How do we think about economic scarring? During a recession, business close, firms must change strategies, households lose wealth. If a business goes bankrupt, it does not matter if growth returns, the firm is gone.  A lost job cannot be immediately solved if an industry shrinks. Training will take time and wages may not return to old levels.

Similarly, during the pandemic, business operations changed, and they are not going to return to the pre-pandemic world. We are seeing this type of scarring with central business real estate. We have recovered but the traffic through downtown office building will not be the same. Markets will have to adjust, and this may not be seen in macro aggregates.  

The study of hysteresis is now the cutting edge of business cycle analysis, and it should be the cutting edge of macro investment research. There is a fundamental change in the pricing of assets if there is scarring that will change productivity and long-term growth. Businesses must see these changes and adapt. Governments must see these changes and adjust policies to offset scarring effects. Policies of just providing financial support may not be sufficient if there is persistent scarring.

The world is non-linear, and there are endogenous effects from shocks that impact growth. An issue is whether these shocks are permanent or just persistent and whether they can be overcome through changes in behavior and policies. Regime switching can be more involved than just identifying the phases of a business cycle.

Who are the winners and losers, post-recession or post-shock? Market sectors may be fundamentally changed. For example, the excess valuation of digital companies during the pandemic may not return. The poor valuations of energy companies may be reversed given the knowledge of energy scarcity sick the Russia-Ukraine War. 

See "Hysteresis and Business Cycles" for the pure academic macro perceptive on this issue.

Rational inattention - An important concept for investors

 

In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.

- Herbert Simon 

Attention matters. Where we focus our attention will make all the difference with whether we are successful investors. Miss the details and you miss the returns. Miss the right data and you will fail. Use the right information and you will be a success. Show the right attention and you are a winner. This is why we go back to the core statements from Herbert Simon.

All the information is out there, you just need to know where to look and what to process. Unfortunately, the more information the less likely you will use all of it. Economist have turned this discussion into an analysis of rational inattention; the acquisition or use of information is costly because we are cognitively limited, so you must choose wisely what information to look at. See "Rational Inattention: A Review"

The effective quant strategy is one that knows where to place the right information attention to better process information versus the market. Winning at the inattention problem is focusing in on the right information and reducing noise at the right time. 

There are several ways to fight the rational inattention problem. One is to try and use all information and be a super-processor of information. This may be a fool's game, yet the best fundamental analysts try and to play it and are at times successful at this game. However, one slip of attention and the downside risk will be great. The other extreme would be hold an index fund. You don't have to worry about inattention because you are not processing any information. 

There are other alternatives. One view would be to focus on price signals. Price aggregate information so this is a natural to focus our attention. If a price is trending up, it should capture our attention. If a price jumps, it should capture our attention. The trend-follower solves the rational inattention problem through a focus on searching through prices. Another alternative is to combine trends with fundamental information in a quant model. Let a computer focus attention through looking at the link between trends and other information. A computer programs can have infinite attention but only at those things that it is programmed to focus on.

Behavioral biases exist because of our cognitive limitations, so a crucial issue is trying to train ourselves to avoid inattention issues.

See also: 

Information and attention

Intuition is recognition - Get better at observing

Factors have momentum that can be exploited beyond the momentum factor

 

There is momentum in individual stocks which is related to the momentum in factor returns. Factors show positive autocorrelation so that factors that had positive returns last year will also have positive reruns this year.  If the strong underlying factors that describe a stock are showing momentum, the stock will show momentum. Follow the factors and you will understand the drivers of stock momentum.  This is the result found in the work "Factor Momentum and the Momentum Factor". Factor momentum is related to the persistence of sentiment that can carry over the factor returns.  For example, the persistence of sentiment concerning small cap or value returns will then create a momentum effect for stocks with these other factor characteristics. 

The overall conclusion is that momentum is not a distinct factor. It is an aggregation of the momentum seen in other factors. This idea has strong implication for how you think about the time series behavior of stocks and the factor risks. It suggests that following factor risks and their behavior through time will provide insights on the stocks that will likely show momentum.