Quotes from the FT lunch with Eugene Fama

Economist Eugene Fama: ‘Efficient markets is a hypothesis. It’s not reality’

from A lunch with Eugene Fama FT article - 

When asked about his views of Richard Thaler the behavioral economist and Nobel Prize winner also at the Booth School, Fama stated, “We agree on the empirical data, but we disagree on the interpretation. When people ask me what I think about behavioural economics, I just say that all of economics is a behavioural science. The difference is whether you think the behaviour is irrational or rational.”

When asked about whether markets are efficient, he said “The question is whether it is efficient for your purpose. And for almost every investor I know, the answer to that is yes. They’re not going to be able to beat the market so they might as well behave as if the prices are right,”

When asked about the recent rise in AI stocks, he stated “The world is betting that AI is going to rule the world and that Nvidia will have a near monopoly, but who really knows? Efficient markets is a hypothesis. It’s not reality. I can live with things like that, for sure.”

Now there is a fiscal r-star and it is worth comparing with the monetary r-star

 

We have lived through the period of focus on r-star, the neutral rate of interest, the long-run equilibrium interest rate, or the natural rate. This is the short-term rate that would prevail when the economy is at full employment and has stable inflation. In this environment, monetary policy is neither expansionary nor contractionary. In that sense, when we reach r-star monetary policy is neutral. Of course, we cannot observe the natural rate. This neutral rate is below 1%. See the recent presentation R-star: A Global Perspective by NY Fed president Williams. It has fallen out of favor because the narrative suggests that monetary policy is very contractionary. Note that there has been recent work on r-double star which focuses on the rate necessary for financial stability.

Now we have fiscal r-star which is developed in the following paper "Fiscal R-Star: Fiscal-Monetary Tensions and Implications for Policy" which is the real rate required to stabilize debt levels when the primary is set by exogenously through some authority. It is the rate that stabilizes a country's debt to GDP ratio given a deficit path with output growing at its potential and inflation is at its target level. Of course, this rate is not observable but has to be calculated. There can be a measurable policy tension between the monetary authority and fiscal authority if there is a gap between the fiscal r-star and the monetary r-star. Of course, this is at the r-star level; however, tight monetary policy when there are huge fiscal deficits will mean monetary and fiscal policy are at odds. 

 

 

Sector performance comes and goes - Prepare for mean revisions

 

Markets mean-revert. Sectors also mean-revert. The importance of a given sector within the overall equity markets will change through time. The revisions may take decades, yet the importance of a given sector will rise and fall with new technology, sentiment, and competition. Fromm Schumpeter, creative destruction is an essential part of capitalism. It can come from competition, but it also comes from changing tastes and demand both for a product and for expectations of future earnings. 

The extremes in computer software, internet services, and computer components will not last, yet a forecast is hard to make. Even passive investors will be impacted by the changing weights of sector capitalization. The euphoria of today will be hard to sustain for long periods when discounting cash flows.

The opening up of new markets, foreign or domestic, and the organizational development from the craft shop and factory to such concerns as US Steel illustrate the same process of industrial mutation-if I may use that biological term-that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one. This process of Creative Destruction is the essential fact about capitalism. 

Joseph Schumpeter, Capitalism, Socialism and Democracy, 1942; Third Edition, 2014. Part II, Chapter VII, pg.83

So what is the right bond interest rate level? it may not be much lower

What is the right level of interest rates? if you ask investors what rates will be in the next year, the answer is lower, a lot lower. However, it may be worth stopping for a second and think about the history of interest rates. 

There usually is a term premium in the yield curve. Long rates are riskier than short rates. There is duration risk and there is more systematic risk when the correlation between stocks and bonds is positive. If the front-end of the curve declines, there is no guarantee that long rates will also fall in lockstep. The curve is likely to get steeper. Without QE and with large budget deficits, there also is upward pressure on longer-term rates. 

Real rates are usually positive and near the long-term growth rate of the real economy. A zero real rate environment is not usual, so just because inflation has fallen does not mean that real rates will again fall to zero or lower. 

The economy may be slowing, but that is not the same thing as an economy going into a recession. Without a recession, it may be hard to argue that long rates will see a significant fall.

As usual, market sentiment will often get overly pessimistic or optimistic and a more tempered view may be appropriate.

 

How can you make data talk? Mistakes can be made

Hat tip to Jure Sah from twitter.

There are a lot of ways to make data talk through curve-fitting. yes, there is a science with the math behind these techniques for fitting, yet the choice of which technique is more art. There is no simple way to compare all the techniques, so you must make some guess on which approach is better. 

For example, with trend-following, you can use different moving averages, or you can use some form of times series forecasting. Which is better? The proof is in the returns, but those returns can be generated from the choice of the portfolio, or the risk management employed. 

At the least any curve-fitting should be compared against a few techniques to explore differences. The extra work will give anyone more confidence in the end results.

Carry and trend - the match for CTA's

 

Trend-following is a good stand-alone strategy, yet there are many investors that find the swings in performance hard to take. Of course, when trend is added in a portfolio the overall portfolio will do better; however, investors often focus on the risk of individual assets and not the risk of the portfolio to their detriment. This bias of focusing on the parts and not the whole is hard to break. The answer that investors should just get over it does not seem to be helpful. The alternative is to mix strategies in a portfolio in a thoughtful way that will produce the desired return profile. It may be viewed as suboptimal, yet it may allow investors to get closer to the preferred mix at the portfolio level.

So, what mixes well with trend-following? Trend-following is concentrated in futures and across all asset classes, so it would be helpful to integrate another strategy trough futures in a manner that can take advantage of the inherent leverage in futures. Additionally, an investor would like an additional strategy that will complement trend-following and do well when trend returns are subpar and see drawdowns when trend-following exceed expectations. This strategy would be carry.

Carry strategies can be applied to all major asset classes. In the case of commodities, backwardation and contango can be exploited. In currencies, the interest differential can be played. In bonds, the roll-down the yield curve as well as term premium can be gained. In equities, dividend yields can be exploited. The table from Nick Baltas provides the basics of carry across asset classes.

The advantage of carry combined with trend in futures markets is that the two can be integrated. If you are long futures form trend, and the market is in backwardation, the trend can be adjusted through moving to a different point on the futures curve. Clearly, the trend returns, especially when held for the longer-term, will be impacted by the shape of the futures curve. The same can be said for currencies and bonds. The carry effects will either enhance or detract from trend. Although it is a second order effect, carry will supplement trends, so it should be integrated with trend strategies even if there is no explicit embedded carry strategy. In fact, one could argue that carry cannot be separated from trend within the futures markets.

Tech bubbles - When valuation is hard and euphoria is high

Bubbles are often associated with new technology. First, the new technology is hard to value since there is little past information. Second, there can be euphoria associated with the new technology. Expectations exceed reality. This does not mean the technology will be a failure. It just may take longer to be adopted than expected or the actual usage case will be less than extrapolated. Finally, when there is a tech bubble, not all firms will be winners. In fact, there may be high failure rates and even the best companies may not meet expectations. The economy may be better off even after the bubble bursts; however, there can be wealth destruction for those who invested in these firms. 

As a side note, we can add the nifty 50 from the 60's and early 70's and the tech firms of the 1920's which included radio, refrigeration, and autos. We have also had oil booms which were driven by discovery and technology. Of course, there have been housing bubbles which have ended poorly.

A great history of monetary and fiscal policy

 

If you had to read one book on monetary and fiscal policy in the US, Blinder's easy to read work, A Monetary and Fiscal History of the United States 1961-2021 will fit the bill. This book is clear, at times humorous, and always insightful. Blinder writes with confidence as someone who has been studying this topic for decades as well as having a ringside seat as both an academic and policymaker. 

Blinder is clearly a Keynesian, so he is sympathetic to its policy prescriptions, yet his review of the last five decades is very compelling. He makes the case that policy, whether fiscal or monetary, is driven by politics. Forget that the Fed is independent, it is political which at times pushes it to independent policy but at other times, it will be consistent with fiscal policy. Fiscal policy through the lens of Keynesianism, has seen ebbs and flows between acceptance and avoidance; however, there is now a clear bias toward deficit financing whether from Republicans or Democrats. All may not call it that, but the result is that the political process does not allow for automatic stabilization that will smooth deficits. Republicans can act like Keynesians as well as any Democrat. It is not always a pretty picture of thoughtful policymaking. The Fed is said to be independent which at time allows for quick action, yet monetary policy cannot solve all problems and the pressure not the Fed is strong. 

I can say that a learned a good amount of monetary and fiscal history from this book. Policymaking is complex and the theories of academic economists have often not been helpful in this process. I have lived many of the events, but Blinder has a great way of synthesizing and summarizing the key issues at different times which makes for good reading. Macro finance is often about knowing how to place current events in context and Blinder's book will help you do it.

Other readings that place this book in context:

• Friedman, Milton, & Anna J. Schwartz. 1963. A Monetary History of the United States, 1867-1960. Princeton: Princeton University Press.

• Stein, Herbert. 1969. The Fiscal Revolution in America: Policy in Pursuit of Reality. Chicago: University of Chicago Press.

Connectedness and contagion tied to institutional structures

 

There is a lot of talk about connectedness and contagion in markets, yet the institutional structures are often overlooked as major contributors to the cause or control of major market shock events that are associated with panics. Hal Scott in his book Connectedness and Contagion: Protecting the financial system from panics. As a lawyer Scott has a different perspective than most economists, but this is a useful book for any economist who is studying panics. The focus is on the policies and their impact on markets from the Great Financial Crisis. Some policies have been critical at mitigating any panic and contagion, but Scott also suggests that policy changes and structures can add to potential risks. 

We often find that markets are more connected than expected during a crisis. Whether third party creditors, derivative counterparties, prime brokerage, structured securities, or money market funds, there are a myriad of connections that lead to connectedness and higher correlations. The contagion during the GFC was significant across the banking system, money markets, and brokerage firms. There have been changes in the system, but we again found that significant connections existed during the Great Pandemic. Solve one problem and a new one will arise. 

All the panic problems are attempted to be solved through the lender of last resort, yet the idea of lending freely in a crisis is not as easy as waiving some magic monetary or fiscal wand. The rules and programs that need to be in place or are in place can be very complex. Unfortunately, Scott makes the case that some of the rules post-GFC have reduced the ability of the Fed and the government to serve as the lender of last resort, and rules can add significant complexity to the marketplace. There is not uniformity of rules across all central banks, so if there is a global contagion, it is not clear how different central banks will respond. 

Banking rules such as the Basel III framework are complex, yet other supposedly simple approaches will not solve the problem. The designation of globally systematically important banks, risk-weighted assets, leverage ratios, stress tests, liquidity requirements, living wills, contingent capital, or other attempts to solve contagion may lead to other problems which are not obvious. Money market funds like banking institutions have similar problem with trying to regulate away crises. However, rules are needed because bailouts are expensive and in a crisis mistakes will be made.

The watch words form this book - know your institutions and regulation before a crisis because once a panic comes it will be too late to try and understand the system.     

Trend-following as negative crisis beta as well as crisis alpha

 

Trend-following has been described as crisis alpha. This has been a useful depiction of the strategy, but it focuses on the idea of alpha creation when trend-following is also focused on dynamic beta. There is return unassociated with beta, the alpha of trading other markets than equities, and there is dynamic beta associated with returns based on market timing. There is alpha during crises, but when looked at all periods, the value of beta return is greater than the alpha return contribution.

There is diversification of assets classes, but trend-following, because it allows for long and short positions, is really about market-timing which creates long and short beta. It is this changing beta which is the true driver of returns and diversification. This focus on change beta is described in the Quantica Capital "Negative crisis beat and the hidden market timing ability of trend-following CTAs".

The focus of this paper is that the core value-added of trend-following can time markets. In particular, it has the ability to time equity markets which will mean that its beta will move between positive and negative values. Over the long run, this time will lead to a beta that is close to zero for equities. This will still lead to risk mitigation, but the form of this mitigation is through timing. This applies to all the markets traded, but Quantica focuses on the equity exposure. 

Quantica argues that 2/3rds of the the industry's total retune has been generated during the 16 worst calendar quarters for equity markets while the 81 remaining quarters are associated with the remaining third for the period from 2000 to 2024.

About 80% of the total trend-following performance can be attributed to equity beta either positive or negative and it made a positive contribution in 70 of 97 quarters. Negative crisis beta led to a positive contribution in 15 of 16 worst quarters which was about 40% of trend-following in those periods. Trend-followers have equity market timing ability. If you restrict long equity exposure will have a significant negative impact on performance, so don't restrict equity exposure for trend-following. Allow trend-followers to take their timing risk and you will see both return improvement and risk mitigation.

Nevertheless, crisis alpha still exists and is a significant contribution to returns during periods of negative equity returns. Trend-following is not just a crisis alpha story, and it is not a crisis beta story. It is a combination of timing with diversification.

The three C’s of systemic risk Connectedness, Contagion, and Correlation

The three C’s of systemic risk are Connectedness, Contagion, and Correlation. Systemic risk can increase because institutions are tied structurally through funding, common portfolios, and behavior. 

Connectedness is about the plumbing. It is also about the rules of the game. Regulation can increase or decrease connectedness. 

Contagion is when an event sweeps across institutions that may not be connected. It is a behavior issue. It usually cannot occur if there is no connectedness. Herding will occur during a crisis as expectations condense into specific common beliefs. 

Correlation is the result of connectedness and contagion. If there is a crisis, we know that correlations will increase and trend to 1. There is a common view and common behavior. We will not know how much connectedness or contagion will exist until we see the correlations across markets rise. 

Any discuss about systemic risk should thinking about the 3 C's. Any discussion concerning the prevention of systemic risk or crisis will try and answer what may happen with the 3 C's.

The importance of finance to economics

 

Economics without finance is like Hamlet without the prince. -  Claudio Borio

There is often the view that Wall Street can and should be separated from each other. The very dichotomy suggests that these are separate streets, yet the reality is that we cannot separate the two just like we cannot separate economics from finance. All macro decisions must include the price of time which is the rate of interest. All economic issues which describe saving decisions need finance. All businesses which need to fund operations need finance. All governments that run deficits need finance. Finance is more than oil in the engine of finance. It is the glue that helps push consumption either forward or into the future. This is even more important when we think about global development. The movement of capital to where it is needed is fundamental to economics and is the role of finance. 

Banks from too small to too big - Is there room for innovation?

From too small to survive to too big to fail, there has been a significant change in bank risk given the huge economies of scale and consolidation in this sector. 

In the 1930's the problem in banking was an issue of too small to survive. Banks during the Depression were failing left and right. The same thing happened during the great thrift upheaval in the late 1980's. The problem was not size but number. 

Now the banking sector has changed. The small banks have been under the pressure of consolidation, and with commercial real estate problems, the issue of further consolidation will again be on the table, yet the real threat is too big to fail. 

The government will bail-out any large institution based on the threat of contagion. This does not mean that banks are cheap or good investments for shareholders, but it does tell us there is limited discipline with large institutions beyond what is required by regulations. With systematic stress testing, there will be greater similarity with large banks who meet stress-testing requirements. Regulation will drive many key decisions which will increase systematic behavior.

Can there be innovation in banking in a too big to fail environment? This is a question I have been thinking about and not sure of the answer. What have been the new innovations in banking? We know that technology has been used to control and cut costs, but this does not fall under product development.    

A classic framework that never goes out of style - Porter's 5 forces

 

Just keep the company analysis simple. You want to look at the balance sheet and the income statement, but you are also going to have to make a judgement about the company's position in the competitive landscape. The financials are all public information and backward-looking. It is hard to get an edge, but the assessment of the competitive landscape is forward-looking and can lead to better return assessment. The problem is that it is hard to quantify the competitive five forces. If there can be a ranking or coring of the competitive landscape, there can be the opportunity for higher return and differentiation by investors. Can this be done? It should be possible, but it will not be easy and requires some special skills as ranking different competitive characteristics. 

Managed futures - the "mystery" factor

 

In a CAIA post  "A Mystery Equity Factor", the author discusses a mystery factor. Look it is uncorrelated with the major factors, so it looks to be unique. It also has positive annualized returns versus other factors.

This mystery factor is revealed to be managed futures, specifically trend-following. This is an interesting way to portray trend-following. I don't really buy this depiction of trend-following as a unique risk factor or premium, but if you broaden your thinking, it is special. The CSAM trend-following index is a diverse portfolio of trend with a rather simple model that creates a unique return stream based on the behavior of investors to follow price action. At the least, it looks as though trend-following is a better alternative than some of the other well-defined factors such as value, size, momentum, quality and low volatility. 

The decay of hedge fund launches

This is a great chart on the rise and decline of entrepreneurial asset management. There was a great surge in hedge fund launches, but that is over. Regardless of the strategy, the launches are falling from the peak, and it looks like they will never return. 

Smart managers form pods and work for multi-strategy firms. The cost structure for start-ups is high. Fees are coming down while inflation has made all services more expensive. The compliance and regulatory costs are only going higher. Investors are smarter and conduct more due diligence. They are less likely to take risks on start-ups.

Is this good for investors and the markets? Perhaps there were too many launches at the peak. Everyone wanted to be a hedge fund manager and get incentive fees, yet the skill pool may have been much smaller. After accounting for factor analysis, there was likely less alpha than thought. 

Markets are competitive and efficient, yet it seems that we are losing something when new ideas and managers are not trying to beat the market. Nevertheless, industries mature. There are economics of scale and there is institutionalization of the process. Perhaps this alarm is just a longing for the old days of start-up zeal, but it is likely that investors are better served with a marketplace of larger firms that can control costs and better diversify. 

Campbell's law, Fed Policy, and 2% inflation

Campbell's Law - The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor 

Jerry Muller's corollary to Campbell's Law, "Anything that can be measured and rewarded will be gamed."

Goodhart's Law, "Any measure used for control is unreliable."

Let's think about the 2% inflation target. Why do we need to have a 2% target? What makes it so special? How close do we have to get to 2% to say the Fed is successful? What happened to an average inflation rate of 2%? If we want to average to a 2%, then should the Fed push to something below 2%?

Can you have deflation and economic growth? Is there something like good deflation and bad deflation? 

It is becoming increasingly clear that the focus on some arbitrary target can lead to more economic problem. If we control price inflation, we may just allow for greater asset price inflation. The goal is not some inflation number but stable purchasing power and effective growth. This may mean that the Fed intervenes in markets to provide financial stability but that is a last resort and not a policy of denying loses. We should not be data driven but goal driven. Let's be clear on the goals and why they are relevant. 

Managed futures and other hedge fund strategies

 

 

What is comparable to managed futures from the set of other hedge fund styles? I found this surprising, but there seems to be a close relationship between the managed futures index and market-neutral multi-factor fund index. See What Equity Factor Is Best Combined with Managed Futures?

On the surface, this does not seem to make much sense. The market-neutral effect means that the correlation with the stock index is gone, yet the correlation of managed futures and equities follows the moves with the multi-factor benchmark. Both have low correlation with the equity benchmark index, and both show negative correlation with the equity index at about the same time. Generally, it has been found that managed futures have a low correlation with many other risk premium - a low relationship with carry and with value but a stronger relationship with momentum. This relationship is capturing some of these other factor relationships. The closest substitute is still global macro, but it is worth exploring how managed futures fits with other risk premium indices. 

KuU - Known, unknown and Unknowable risks

 

One way to stop the needless noise associated with measuring risk is to develop frameworks on how to look at the risk problem. All risk situations are not the same. A conceptual framework can help with analyzing problems and improving the precision of our thinking. Within risk management, a good framework was developed by Deibold, Doherty, and Herring in their under-appreciated book The Known, the Unknown, and the Unknowable in Financial Risk Management. The KuU framework focuses on three types of risk, the known which is measurable or countable, the unknown which is what many have called uncertainty, and the unknowable, what we are not able to imagine or a function of our ignorance. All are focused on our knowledge which is either based on a measurement problem and theory issue. In KuU framework, we an look at risk in three dimensions. 

K, the known, refers to the probability distribution for an asset. This is the classic definition of risk. The outcomes and the probabilities for a situation are known. Knowable situations are well understood. There is a model, and the model has broad agreement among users.

u, the unknown, refers to a situation where the probabilities cannot be affixed to a set of outcomes. This is what Frank Knight would call uncertainty. If there is an unknown situation, there may be competing models which only offers conjectures and not clarity on what is possible.

U, the unknowable, would be any situation where future events cannot be identified. The events and probabilities are not known. Under this situation, there is no underlying model that can address or be associated with a market situation. 

The KuU framework can be associated with risk, uncertainty, and ignorance. By looking at any situation through this lens, we can better frame possible solutions. Is the issue a measurement problem? Is it a situation where we cannot get a count or measure? Is this a situation of ignorance?

We can solve or reduce ignorance through deeper research of the risk problem. We can also work at better measurement of risk, so that we can place bounds on the downside. If we can control risk and improve measurement, we can focus on the real problem of uncertainty. 

Unsupervised learning - Clustering and dimensionality reduction

 

Unsupervised learning can be a useful tool for finding relationships or grouping that may exist with large data sets. This can be extremely useful for finding deeper relationships than what may exist from just looking at correlation relationships. It can also be useful at finding links between a large set of assets and exogenous factors. More finance work has been done using PCA as a way of generating simple dimensional reductions. It is an east way to eliminate a primary common factor across stocks. 

I have been using unsupervised learning to help better gain diversification within a portfolio of futures markets especially within the commodity space. 

What is the right amount of investment staff?

 

The article "The unusual thing about Citadel versus other multi-strategy hedge funds", provides some interesting insights on the composition of investment staff associated with the largest multinational-strategy funds. The investment staff vary between 39% and 56% as a percentage of the total staff. These percentages tell us something about the firm strategy. A higher percentage of investment staff suggests that there is a greater focus on strategy pods while a lower number suggest that there is a more singularity of thinking about investments. It also tells us something about how first think they can create an edge. The lower investment staff percentage suggests that there is the view that an edge can be created by technology and not just investment acumen. There is no right answer, but the cost of running a multi-state is much higher than what some may think. There is a clear need for strong infrastructure to support all the trading and research that is being conducted.

Marty Zweig's rules - still useful

There is the assumption that new ideas are best. Follow what is the new thinking because ideas of the past just are not that valuable. I do not subscribe to this thinking. We can learn a lot from the best thinker of the past and in the investment area, Marty Zweig was a great technical equity trader. He developed a list of 17 investment rules, and I can say that most of these are still useful. The first two are classic trend-following along with numbers 5 and 12. The behavioral issues are embedded in rules 9, 10, 13, and 17. Fundamentals are associated with rules 3, 4, and 16. Macro investing is embedded in rule 6 and 15. Risk management is associated with 7, 8, 11, and 14. 

There are good take-aways from the Zweig list.

Know your moats to find value

You often hear about moats, but this chart provides a nice visual on the five types of moats that businesses may have. They are not the same, but the result is the same. There is a strong barrier that is not easy to scale. The moat argument does not mean that these stocks cannot be overvalued, but if there is an opportunity to buy cheap, they are always worth looking at. There can be a continuum of moats. Some are strong. Some are narrow, and some just do not exist.

The real value is finding moats that are being formed or in niche areas. This requires some heavy research.

There is a corporate life cycle which requires changing metrics

 

Professor Aswath Damodaran of NYU is one of the best practical minds in finance today. He has developed ideas on the life cycle of the corporation which I find very compelling. The corporation, while supposed to have infinite life, will behave like the rest of us with a life cycle. There are view corporation that age well. Corporation often do not have the capacity to change and thus they wither and age on an old idea. Even with a good idea, corporations will change and thus need to have an adjustment on the metric that work best for valuation. The chart above provides some insight on the changing metrics during the life of the corporation.

Strategy - there are trade-offs between agreement and certainty

The Stacey Matrix is and interesting way to compare certainty with agreement. This combination is often not considered in investment decisions, but a surprising amount of investment decisions are made as a group or committee decisions. There is a continuum on the certainty of the strategy or decision and there is a continuum associated with the level of agreement. When there is little certainty or agreement, there will be chaos. It does not happen often, yet we should expect that chaotic situations do exist. We move between simple, complicated, complex and finally chaotic. 

Realize that having agreement does not mean that you have the right strategy. I find the Stacey matrix had to fit with specific situations since certainty and agreement are hard to define, yet it is critical to think about the issues that will cause failure in strategic thinking and decisions.  

The great Rotation of July being upended in August

 

It is truly surprising how fast expectations and themes can change in equity markets. July was being called the Great Rotations from growth and momentum into smaller caps and value based on the view that inflation was solved, and rates would come down likely in September. The inflation problem was being licked and US economic growth was still considered reasonable. The result was interest sensitive sectors like real estate and utilities did well. Small caps did well. Value was doing better than those growth and momentum driven stocks. 

The story has now changed over the course of two days since the Fed meeting. Initial jobless claims have moved higher. The Sahm Rule may have been hit. The employment number moved lower relative to expectations. The unemployment rate moved higher, and the talk has been about Fed making a policy mistake and a 50 bps cut is on the table. 

All the facts are true; however, there is a sense of market over-reaction. The Mag Seven may come down to more reasonable levels and there should be a careful review of small cap names. The equal-weighted over market-cap trade looks more attractive at this time. Macro models will tilt to lower exposure to stocks and more to bonds, but it may be early to suggest that this is the beginning of major correction. Unfortunately, a correct is biased by the mega cap names and not the average name.