Hanke measures - Inflation is everywhere

The developed world is currently crazy about inflation but take a close look at some of the emerging and frontier market inflation numbers. Inflation is out of control as measured by free-market exchange rates from the Steve Hanke's website, Hanke's Inflation Satellite. 

Showing these numbers does not diminish the problem in the US or other DM markets, but it does show that prices can get out of control if there are not strong institutions and governments that have the desire to control inflation excesses.

China global financial stress elevated but not unusual

Implicit monetary policy is tied to financial stress along with growth and inflation. While it is not generally discussed in the central bank reaction function, there is a greater focus on macro-prudential policy and measurement. A good macro measure is to use some financial stress indicator index. These stress indicators will be correlated because stress is often global through a world-wide economic growth or financial market shock. 

China financial stress is elevated on a relative and absolute basis; however, it is still contained relative to the past and versus other countries as measured through a NYFED model. Generally, EM stress will be greater than in developed markets. 

The NYFED stress model includes equity returns, financial sector returns, equity volatility, short-term rates, the yield curve shape, interbank spreads, corporate bond spreads, sovereign bond spreads, and US bond convenience yields. It tracks closely with the Chicago Fed, KC Fed, ECB, and Bloomberg stress indices. 

Clearly, junk bond spreads have exploded in China and volatility has increased, but the combined stress measure is nowhere near March 2020 pandemic levels. Nevertheless, given the size of the China market, stress measures should be tracked closely to determine portfolio risk allocations.

Rates versus absolute change - Mistakes that investors make that matter

Behavioral biases exist and they really do matter for both the individual investor and markets overall. A provocative paper attacks one of the more obvious problem in finance that should have been explored much earlier. The paper, "Can the Market Multiply and Divide? Non-proportional Thinking in Financial Markets" studies the problem that investors don't seem to understand the difference between a $10 price change and 10% or proportional change. 

We may be so used to hearing financial data presented in a certain way that we don't even notice the problem. A commentator will say stock x is up $5, or the benchmark index is up Y points without saying the percentage change is contributing to the bias. 

This problem becomes obvious when you scale values by price, a $x change in a stock that has a low price will have a very different meaning from a $x change in a higher priced stock. Proportionality matters. Ineffective juggling between dollar price and percentage changes is a problem for the individual, but when explored at the market level it can explain some of the odd anomalies or puzzles seen in the stock market. 

Investors usually think about dollar not percentage units which leads to more extreme responses to news for lower priced stocks. Higher price stocks will be less volatile - a doubling in price will lead to an approximate 25% decline in volatility. Consequently, volatility jumps after a stock split. Lower price stocks will respond more strongly to firm-specific news. This non-proportional thinking can explain size-volatility/beta relationships, the leverage effect and return drift.

Guard your thinking through always thinking about the proportional impact of prices. 

The "extreme precariousness of the basis of knowledge"

"The state of confidence, as they term it, is a matter to which practical men always pay the closest and most anxious attention. But economists have not analyzed it carefully.... Our conclusions must mainly depend upon the actual observation of markets and business psychology.... The outstanding fact is the extreme precariousness of the basis of knowledge on which our estimates of prospective yield have to be made. Our knowledge of the factors which will govern the yield of an investment some years hence is usually very slight and often negligible." 

- Chapter 12 "The State of Long-Term Expectation" from The General Theory of Employment, Interest and Money"  John Maynard Keynes 

I like the term "precariousness of the basis of knowledge". I had to help with a private company valuation in a fast-changing industry. The difference in valuation given some simple assumptions was enormous, and I was using some very standard valuation techniques. 

The same uncertainty problem applies to any forward estimate of rates, inflation, or the dollar. Perhaps we can speak to trend or views in the short run, but the range of potential estimates out to a year or more is so wide to be almost useless. Our only savior is the range of past behavior over a year horizon, but in a highly uncertain macro environment that conditional restriction may also work against an effective forecast. 

Holding bitcoin ETFs given the futures contango - A difficult game

 

Bitcoin futures ETFs have started to be traded with the excitement associated with an easy method for investors to access bitcoin price activity; however, these instruments are not linked to the cash market but rather to bitcoin futures. This feature has significant implications for investors because these ETFs will be subject to roll risk. If the underlying futures market is in backwardation, long trades will gain from the roll-up the futures curve, but if the market is in contango, there is a negative cost from holding the long futures. 

So, what is the cost from holding bitcoin futures ETFs? The bitcoin futures market is in contango which creates a return drag. If the cash price does not move, the investor will lose on the roll cost.  

The cost of this contango effect is significant. The drop from second to first month bitcoin futures is over 11% on an annual basis on November 22. The futures are listed monthly. The cost is over 7% for third to second futures and 6% for fourth to third futures. Unfortunately, the liquidity for the back months is significantly lower than the front month, so trading is concentrated in the front two contracts. Volume in the front month is averaging a few thousand contracts while five months out the volume is less than 30 contracts. 

To make money, the ETF investor has to overcome management fees that are close to 100 basis points, pay the transaction costs associated with the trading, pay brokerage on their transaction, and pay the roll costs which means that the hurdle necessary to make a positive return is well over 10% for trading the most liquid futures. 

There have been similar high costs associated with trading crude oil ETFs associated with the futures contract when the market is in contango; however, more liquid back months have allowed trading along the crude oil futures curve. Investors need to be aware of the market's structural costs before entering into these investments. 

Are investors getting EM exposure or just China with some other EM risk in their equity benchmark?

Many equity investors will hold or benchmark their EM exposure with the MSCI emerging market equity index, but a close look will show that the index has changed radically through time. The top country exposure has switched several times through the decades, and we now have an index which is dominated by China. 

Given that China stocks have been hit hard from slower economic growth, geopolitical issues, changes in government regulation, and a growing real estate crisis starting with Evergrande, the EM benchmark has also been driven lower. In the last year, EEM has shown a decline but the EM index less China EMXC has gained 14 percent. 

A Goldman Sachs report shows the dominance of China in the MSCI index. China dominates in a way that has never been seen before and is the largest single country share in the history of the index. China is the second largest equity market globally and its weight in the MSCI EM index has doubled in the last five years. 

Not only is China a large weight in the index, but it has a low correlation with other EM stocks. The industry mix is different, and the drivers of return are different from other components of the EM equity index. This problem also exists for EM bond indices. 

China is an outlier from the rest of the EM market. It is an outlier with other developed markets, yet it cannot be ignored. Every investor must have a China opinion. Every investor must now think about EM investing with and without China. 

J Powell - The easy choice, but perhaps not the right choice

With Fed monetary policy at a crossroads, the conventional wisdom is that it is not good to change the chairman when there is policy choice uncertainty. Given the policy choices of the past few years and the choices ahead, it is not clear what is the value of conventional thinking other than a new choice may create even greater uncertainty.

Chairman Powell was the easy choice, but it may not have been the right choice. Taper speed will be an issue. Inflation is an issue. A rise in rates is an issue. Global finance is an issue. Bank regulation is an issue. Many of these issues are the making of the Fed. The argument will be made that the Fed did the best job possible given the events of the pandemic, and any criticism is just ex post sore grapes. We are not questioning the response in March 2020. The issue is the length and intensity of policy which now weighs on markets.

The tougher choice would provide some fresh perspective and admit there may have been mistakes, but that would have been in opposition of existing administrative thinking. The easiest choice is to accept that any failure could not have been avoided because the environment is out of the Fed's control, and they did the best it could. 

Should Lael Brainard been given the nod? She is smart and talented, but it will not matter if the core policies are unchanged. We will see her skills put to the test as vice-chairman. This appointment should be a positive.  

Both Powell and Brainard have commented on inflation being the top problem to be addressed in their thank you responses. This is a turn-around from the last few months. The market reaction was swift. The real question is how much the Fed is going to change course and become more aggressive addressing the inflation question now that the announcement has been made. Hearings are ahead, and both must now get in control of inflation.

Just-in-time strategy for an investment/trading portfolio

 

There is value from reading older work on strategic management and applying it to the money management industry. It gives a different perspective with needed structure for making better investment and business decisions. I found an old work "Just-in-time strategy for a turbulent world" by Lowell L Bryan useful for investment thinking. The core concept is that there should be diversification of projects - a diversification of timing for payback and risk as measured by familiarity.

In this just-in-time thinking, there are trade-offs between risk and timing horizon for an investment. Investor should think about having a mix of strategic trades and investments that may have different times to payoff with different types of risk. An investor should also think about the commitment of resources based on timing of pay-offs and the level of risk or familiarity of the project.

Risks can be classified according to relative knowledge or familiarity. There are low risks taken when you may have a high degree of distinctive knowledge that is unique to your organization. There are increased risks when others may have greater knowledge, and there is true uncertainty when there is difficulty with estimating payoffs. 

Your level of trading or commitment to investing should vary with your level of familiarity. Greater investments and risks should be taken in highly familiar areas while low amounts of capital should be given to truly uncertain projects where there is low familiarity. When others have greater knowledge, limited investments should be made as a test or as basis for gaining knowledge. Nevertheless, if you only invest in project and trades where there is great familiarity, there will be a limit on growth and opportunity. If you only invest in uncertain projects, time commitments before a payoff will often be great.  

The timing of resource investments can have an immediate payoff or will take time to provide a return. Firms should have a mix of projects to allow for long-term strategic growth. This thinking can be applied to research. There are short-term projects based on high familiarity, but those should be balanced against longer-term higher risk projects.

Trailing stops - the math says this is a complex decision

The math for trailing stops states that it may make good sense, but traders have known that for decades. However, the implementation of stop-loss is as difficult as the development of any trading rule. The core issue is determining how to optimally adjust those stops without losing potentially successful trades. Take three examples:

1. Fixed stops - Do not change the stop at all. Only question is determining where to put the initial stop. The probability of being stopped can be determined by the drift and volatility of the price series. The trader is willing to take more risk as the price moves away from the stop.

2. Variable stops - Change the stop with any gain in price. Question of keeping the probability of being stopped the same through time as reset by the price increase. Traders will still risk the same amount on price increases.

3. Trailing stops - Adjust the stop on a lagged basis as a percentage of the maximum value with some lag. More money will be risked as the trade increases in value.

This are not the only ways to describe stops, but it illustrates that the issue can be complex. It becomes even more complex if you think about the point of exit for a trade as an additional wrinkle to the problem. If you have a stop on the downside, then you should think about a stop or exit on the upside. The next higher level of complexity is determining when to enter in the first place. You don't need a stop if you don't put on a position, or more importantly, a stop is a form of error correction. The model has made a mistake. Hence, there is a need to stop-exit a position. Risk management cannot be detached from entry and exit decisions; however, many models perform worse once a stop-loss is added. Added to the stop-loss decision is the complex issue of when to re-enter a trade once a stop-loss is triggered.

This problem has been tackled by Tim Leung through his paper "Optimal Trading with a Trailing Stop" which is highly mathematical and in no way an easy read. I am still digesting the impact of his work, but I find that he has been able to provide structure to these higher levels of complexity.

Beyond first order thinking ... second and third order matter more

What separates the great analysts from the good analysts? It is simple, second order thinking. Levels of thinking may lead to reversals in price from what is expected or market responses that are counter intuitive. A shock to a market may not behave as expected because money is flowing based on more complex thinking.

First order thinking is the result of immediate thinking based on what has been expected from the past. It is associated with generalized thinking, based on the concept that all else is equal. It is our initial fast thinking. It would be system 1 Kahneman thinking based on simple intuition. For example, higher gasoline prices will lead to less driving. This immediate conclusion is the end of thinking and does not involve the implications of initial actions. It is reactionary and safe thinking and will be the answer that the majority will use.  

Second order thinking will extrapolate and think through the implications of what higher gasoline prices will have on other markets. It will question current assumptions and beliefs. This is system 2 thinking and is a deliberate approach to walk through the logical consequences of some action. It is hard focuses on uncertainty and complexity and my definition will not be conventional. 

Second order thinking will walk through what other industries will be affected by the rise in gas prices. It will have an effect on refiners. It will impact travel and entertainment. It will impact demand for electric cars. 

Third order effects will look at the implication of the second order effects to move to a third order. If there is higher demand for electric vehicles, there will be an impact on some industrial metals. Some of these higher order effects may prove to be illusionary; however, better analysts will think through events to form multiple hypotheses for opportunities.

Can a quant fund have second order thinking? This is very interesting question because a disciplined approach is often by definition literal. If "A" occurs, then do "B". The relationship between "A" and "B" has a sensitivity or coefficient of X, but the framework is very structured. Yet, second order thinking is critical for a good quant fund. A shock to one market may change the correlation among many assets. Second order thinking of a shock will look for correlation dislocations. 

Think beyond the immediate or obvious and realize that others may also be thinking beyond the immediate. It is a game of anticipating the higher order thinking of others.

Fed monetary accommodation abounds - look at real yields

It is the real rate that matters. There are several ways to measure it, but the 5-year TIPS yield provides a good market measure of longer-term real rates. The fed could not be more accommodative. The TIPS market yield is lowest on record. Raising rates two or even three times at 25 bps in 2022 with inflation break-evens falling to 2 percent will still leave real rates at best near zero. It is not a matter of tightening but reducing what is perhaps a level of excess accommodation. Short of a strong reversal in growth, the interest rate bias is tilted to higher levels. 

Financial stability not an issue as we enter the taper period

 

Financial stress and stability are not issues with the current economy. The foundation for the last round of quantitative easing was to solve an emergency liquidity problem. That problem has passed almost a year ago. The tapering should begin, and the Fed should move to the issue of rate increases. A cautious Fed has to deal with result of their policy prudence.

We don't know what the market impact of tapering will be given the size of the purchase program, the lower Treasury liquidity, growth prospects, and the ongoing government debt needs, but broad financial conditions and stress are fine. The Fed, nevertheless, should clarify its role in maintaining the integrity of financial markets. This is not the same as providing liquidity to relieve stress. 

Growth may slow, inflation may persist, and markets are still overvalued. All reasons for a correction, but it will not be driven by financial stress.

Meat and inflationary expectations - Key increases in goods prices impacts expectations

 

While markets focus on breakeven inflation expectations embedded in prices, the real economy is affected by consumer expectations of inflation. Consumers don't care about the survey of economists, and they don't care about inflation swaps or TIPS rates. 

Consumers do care about the price at the gas pump and the cost of groceries. These are not included in core inflation, but these numbers lead to spending adjustments and are real. Pay more for gas and there is less for something else. If the price of meat increases, a consumer may buy chicken or not go out.

 

Steak prices have increased more than 30% from pre-pandemic levels. Bacon and ground chuck are up more than 20%.

  

Of course, these are relative prices and not "inflation" or a general increase in prices. This distinction is important but if key relative prices are all rising, there is a perception of higher inflation. When prices are stable, inflation expectations are stable. If the cost of goods noticeably increases with some frequency, expectations rise and consumer behavior changes.

Enough increases in key products and there will be an increase in inflation expectations. The NY Fed consumer survey has one-year inflation over 5.5% and three-year inflation above 4%. These expectations will lead to demands for increases in wages. The spiral in prices begins.

Different levels of uncertainty require different thinking

Uncertainty surrounds every decision we make. You cannot get away from it. Investors should develop a best forecast for the expected return of an asset; however, there is still residual uncertainty. This would be the information or analysis that cannot nailed down or given a precise answer within our forecast. While Hugh Courtney from McKinsey discusses residual uncertainty for business strategy decisions, the framework can also be applied to thinking about investment decisions.  

If we analysis is done with a clear future, then single view thinking is workable. This is often used by most analysts. Incorporate best estimates and guesses, discount cash flow and form a view. It is easy but does not really account for uncertainty or the possibility that there are alternative solutions or futures. 

Level 2 uncertainty accepts that there are possible alternatives to our best guess, but they can be limited to specific unknown situations. The simple approach would be to account for an upside optimistic and downside negative case relative to our best guess. The good and bad scenario is a standard approach that does not focus on the core issue that specific factors or assumptions have more uncertainty than other factors. Limited focus on uncertainty is easier to deal with because specific uncertainty or unknown can be the focus of our attention. 

Level 3 uncertainty acknowledges that there is a broad range of possibilities. There several alternatives that cannot be defined or be associated with a few simple factors. While acknowledging many alternatives is helpful, the problem of dealing with multiple alternatives creates a difficult forecasting environment.

Level 4 uncertainty is not often faced, but this could be associated with new technology in a new industry. In this case, the range of outcomes may not be handicapped. Any forecast will only have a small chance of success, so extra compensation is necessary to engage in this type of investment.

Investors will benefit from trying to handicap the residual uncertainty faced after a best-efforts forecast is projected. The source and number of uncertain futures is necessary to handicap returns and place a true measure on risks taken.

Focus is on core inflation but global food prices matter

The focus is on core inflation for policymaking, but headline inflation still matters for global consumers. For many countries, food inflation is more important than in the US since it is a larger portion of their consumption basket. Food demand is inelastic. Hence, food increases are a drag on other spending. We can look at nominal prices, but the real price tells us whether there is something more going on in the agriculture sector that will not go away in the next quarter or two. 

Real prices are exploding to the upside similar to the last time we had global food riots. Oil prices have exceeded the maximum for the entire period of reporting by the FAO. Overall prices are moving to the same levels as the in the great commodity surge from over a decade ago. Congestion and logistics can explain some of these price increases given that futures prices have gone into backwardation.  

However, monetary policy cannot solve problems of real food prices. The same can be said for fiscal policy in the short run. In this case, micro structural and regulatory policies matter. Real food increases, like energy prices, adds to the complexity faced by policymakers.

 

Imprecise language - The big problem with investment analysis

 

Tracking news over the last year suggests that there is significant imprecision in language from both policymakers and analysts. This summer we learned the imprecision surrounded what was the likelihood of the Taliban overrunning Afghanistan. This fall we found that there was imprecision with the likelihood of key legislation in Congress. With the Fed, there has been imprecision in language concerning tapering and rate increases. There is spin with this imprecision. Policymakers don't want to be pinned to probability estimates. There is also imprecision from analysts who must discuss these issues. The talking heads must provide commentary, yet they do not want to be held to any precise estimates with their thoughts. Therefore, the meaning of words are so important if an analyst truly wants to provide a forecast and add value. 

We have talked about Sherman Kent's great work to solve the imprecise language problem at the CIA. He tried to bridge the disconnect between language and probability through forming a precise link between the two. Use common language; however, make sure that the audience knows what the words used mean.

The results graphed above are based on thousands of actual responses to an online survey created by Andrew Mauboussin, a data scientist at Twitter, and his father Michael, research director at BlueMountain Capital Management. The details of the survey can be found in "The perception of probabilistic value for different expressions",  and a drag tool can be found in the following article, "Here’s a handy tool to help you talk about probability."

For more on Sherman Kent and words of estimative probability, see:

Words of Estimative Probability (WEP) - Words matter and poor precision leads to decision failures

Sherman Kent - My guy for precision in forecasting language

Sherman Kent - the godfather of precision in forecasting language

Language, perception, and numbers - The translation problem

What does failed intelligence tell us about investing

"Likely" or "Probable" - there is a difference in language when talking about recommendations in the new year

We just don't know much about inflation and money

I thought I knew about the causes of inflation and the link with money. I don't, but then others don't either. The conventional story is that higher money growth through QE should lead to lead to higher economic activity and then higher inflation if economic slack is diminished. The link may exist, but the sensitivities between money, growth and inflation are unclear.  

We do have pre-COVID history from the BOJ, BOE, ECB, and the FED on massive QE programs with little evidence that inflation has greatly exceeded targets. We also have evidence that the money multiplier in all cases has fallen. The link between money and GDP has not been unstable rather it has been suggesting a desensitized relationship. See The International Experience of Central Bank Asset Purchases and Inflation by Gianluca Benigno and Paolo Pesenti.

Given this international evidence on QE around the world, what should we expect from tapering? We have less evidence of what will be happen, yet quantitative tapering will be the dominant theme with central bank policy over the next few quarters. In the case of the Fed, ending QE rounds and tapering have been associated with declining rates although these were periods of low inflation and lower debt financing.

The Fed has stated that tapering is not linked to rate increases, yet can we say with any certainty that tapering will be market neutral? Will tapering have only limited effect on fixed income and risky markets? Right now, the view is that reducing purchases are market impact neutral. We have yet to consider an actual reduction in the Fed's balance sheet. 

I am for a reversal of monetary excesses, yet my fear is that we are not clear on the market consequences. This tapering offers fixed income traders both opportunity and risk through betting against the status quo as we receive feedback on the cutback of purchases. Despite trying to delink tapering from rate moves, the two are naturally linked. Rate increases in the short to mid-maturities can be anticipated from fewer Fed purchases regardless of the Fed's forward guidance. 

Basics of data science - Machine learning is not econometrics

 

There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. - Leo Breiman 

Most analysts and investors who have gone to business school have taken at least one statistics class and perhaps an econometrics course. Business schools have integrated data science into the mix over the last five years, but finance has still been dominated by econometric thinking. With the econometric view, there is a proposed model for explaining markets. Data and statistics are used to test hypotheses and estimate parameters. Machine learning does not make any assumptions surrounding a model, rather the focus is on using data to make accurate predictions. If data is useful for predictions, then it has meaning. 

From a practical perspective, data science techniques like machine learning focuses on engineering solutions. The goal is solely to predict and be accurate. There is no attempt to fit a model that can explain, although there may be a desire for the inputs to be intuitive. 

The refocus on accuracy over causal reasoning should help with predictions; however, reasoning will be reversed. Inputs that provide an accurate forecast will now have to be assessed to understand their causal relationship with the variable to be predicted. Observational relationships obtained by machine learning will have to be given explanations. Nevertheless, data science should be embraced as a helpful investment tool. 

IQ or RQ - The quotient of rational ability may be more important

 

“You don’t need to be a rocket scientist. Investing is not a game where the guy with the 160 IQ beats the guy with a 130 IQ. Rationality is essential,” 

“Investing is not a game where the guy with the 160 IQ beats the guy with the 130 IQ. Once you have ordinary intelligence, what you need is the temperament to control the urges that get other people into trouble in investing.”

“If you have a 150 IQ, sell 30 points to someone else. You need to be smart, but not a genius,”

"Because you have all these smart people out there. The money doesn’t go to the people with the highest I.Q. There would be a very poor correlation between I.Q. and investing and results. And you say to yourself why does somebody with a 500-horsepower motor only get 100-horsepower out of it? And I would say that if you look at the intellect as being the horsepower that’s available, but you look at the output as reflecting the efficiency of that motor, it is rationality that causes the capacity to be translated in output."

-Warren Buffett

There is still a general mindset that IQ is a driver of success, yet the evidence points to a more nuanced view. There is a minimum intelligence needed for most jobs. That threshold may differ by profession, but it is not genius levels. Success is coupled with rationality which can be defined by several broad components —adaptive responding, good judgment, and good decision making. The smartest person in the room may not be successful if he cannot employ good decision-making. 

The measurement of IQ (Intelligence Quotient) handles abstract verbal and quantitative mechanics, while an assessment of someone's RQ (Rationality Quotient) focuses on the ability to lay out a problem's logic as well as alternative analytical approaches. We have moved away from standardized IQ tests given our assessment that individuals can have several different skills, yet there has not been a willingness to add RQ measurement or testing to capture rationality. 

Is rationality measurable? The answer is yes. While there are limitations like any testing format, questions have been derived to assess rationality. For more on this topic see The Rationality Quotient: Toward a Test of Rational Thinking by Keith E. Stanovich, Richard F. West and Maggie E. Toplak.

Investors should broaden their thinking on the skills necessary for success. Most have the minimum intellect, yet they need to assess and improve skills associated with rationality.

See:

Different components of rationality - Deeper thinking beyond behavioral biases

Smart does not mean rational - Need to think beyond SAT

You don't need intelligence; you need "mindware" to be successful

Liquidity down - risk up - A troubling sign for fixed-income

 

Government bonds are special because they provide liquidity when needed especially in a crisis. They are safe assets because you can buy what you want, when you want, at a price that is close to fair value and will not move when you execute size. Perhaps those days are over. 

A look at top of the book liquidity suggests that liquidity is not there. If you want to trade size, you will move the market. Dealers are not present for immediacy. Rates have been so stable for so long that the big liquidity providers may not exist. There are traders in these markets but not sizable dealers.

There may be massive flows as financial institutions decide that monetary policy is changing, and it is time to hedge or rebalance a loan book, yet there are few who may take the other side of these trades for short periods to make a market. Treasury and German bond markets are seeing the same problem as the short-end of the curve. Liquidity is present for longer maturities. The result of a less liquid market will be investor avoidance. Don't play in markets subject to liquidity shortfalls. This will create a new policy problem. Will central bank have to serve as continuous liquidity providers to ensure that government bonds are a safe asset?

What if there was a "Great Bond Reset" and equities did not notice?

 

The front-end of yield curves for several countries have gone through a massive repricing in October.  US 2-year Treasuries have doubled in yield during the month. Australian 2-years have increased by a factor five. There also have been significant moves in Sweden, Canada, and the UK. The great pandemic liquidity surge is over, or at least fixed income traders have said that the world has changed with higher inflation and policy will have to play catch-up. I don't want to say that bond vigilantes are back, long-end moves have been muted, but policy front-runners have made a statement. 

So what do risky assets like US stocks have to say about this repricing? Not much. October saw a 7 percent gain in the SPY, a gain of over 8 percent for the top 50 stocks, and an increase of over 9 percent for growth stocks. High beta stocks are up over 50 percent above the benchmark for 2021. 

Rates rises pushed forward in 2022, no problem. Slower third quarter GDP, no problem.  Taper likely to start soon, no issue. Temporary inflation through the first half of 2022, still no worries. Yes, funds are available, but does this look like an early recovery environment? This looks like a cusp point into a new monetary policy regime.