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Beauty Contests And Market Bottoms

Beauty Contests And Market Bottoms

By Nick Colas of DataTrek Research

Today we will discuss an early classic in the field of behavioral finance:…

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Beauty Contests And Market Bottoms

By Nick Colas of DataTrek Research

Today we will discuss an early classic in the field of behavioral finance: John Maynard Keynes’ “Beauty Contest”. Its lesson is that market prices are set by what investors think other investors think. At present, that dynamic is creating ever-lower stock prices because of the increasingly consensus idea that the S&P 500 will bottom somewhere between 3,000 and 3,400. Those levels come from expectations of lower earnings due to a recession. The bottom will come when investors think other investors believe it has arrived.

For Story Time Thursday this week we have a discussion of an early behavioral finance concept called the “Keynes Beauty Contest”. While distinctly out of step with modern values – the idea comes from John Maynard Keynes 1936 work “The General Theory of Employment, Interest and Money” - it is still a hugely useful paradigm today. Especially today, frankly …

Richard Thaler published a wonderful analysis of the Beauty Contest in 2015 (link below), which quotes from the 1936 Keynes work to describe how it works:

  • Imagine a newspaper contest “in which the competitors have to pick out the six prettiest faces from 100 photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole …”

  • “ … each competitor has to pick, not those faces that he himself finds prettiest, but those that he thinks likeliest to catch the fancy of other competitors, all of whom are looking at the problem from the same point of view …”

The analogy to equity markets:

  • Investors and traders look for investment ideas they think other market participants will find more attractive in the future.

  • The timeframe may be a day or a week for a trader and 6-12 months for an investor, but the idea is the same. Buy things that you expect other people will find more valuable at some future date. Any analysis worth pursuing must be in service to that goal.

The hard bit about the Beauty Contest as far as its application to investing is that it is iterative. It is not enough to pick faces you think the crowd will find attractive. Everyone else is doing that too. To win, you must run multiple cycles of “what will the crowd think?”

Thaler’s article updates Keynes’ idea with a numerical version which explains why this is so challenging:

  • “Guess a number from zero to 100, with the goal of making your guess as close as possible to two-thirds of the average guess of all those participating in the contest.”

  • “To help you think about this puzzle, suppose there are three players who guess 20, 30 and 40 respectively. The average guess would be 30, two-thirds of which is 20, so the person who guessed 20 would win.”

  • The naïve guess would be 50 – the midpoint between 1 and 100 – based on the assumption contestants are lazy and would just pick random numbers rather than latch on to the wrinkle of “two-thirds of the average guess”.

  • More educated guesses might be 33 (two thirds of that 50 naïve estimate) or 22 (on the assumption contestants have thought the problem through, but not iterated one level deeper).

Math nerds will think of this as a Nash equilibrium problem, and Thaler makes the point the only viable answer using this approach is zero. Iterate the last point’s math ad infinitum and you get zero. Yes, this assumes only math Ph.D.s are playing the game. But it is a logical conclusion nonetheless.

We can use this idea to estimate what market participants think fair value on the S&P 500 is today:

The naïve guess is today’s close: 3785. We’ve had a horrible first half of 2022, and maybe all the bad news is finally baked into stock prices.

The second order guess might be 3,386, if we assume investors will think other market participants will key off either pre-pandemic highs and/or discount a modest earnings recession:

  • This was the last S&P 500 high before the Pandemic Recession (February 19th, 2020).

  • It is also 18x S&P earnings of $188/share, which is roughly 15 percent (14.5 pct, to be exact) below current earnings power of $220/share.

  • While earnings typically decline 25 percent in a recession, perhaps any upcoming economic downturn will be milder than most. The 18x multiple is slightly richer than the 10-year average of 17x, but fair since investors tend to pay more for trough earnings as they anticipate higher earnings in a recovery.

The third order guess could be around 3,000, if investors believe markets must discount a full-blown recession before there is enough general interest in stocks to make for a durable low:

  • Assume an average hit (25 pct decline) to S&P earnings from a recession and you get $165/share versus the current $220/share earnings power.

  • Put an 18x multiple on that $166/share and you get an S&P of 2,970.

Takeaway: fair value on the S&P – or any other stock market index – is a function of what investors think other investors think. In bull markets those beliefs are iteratively revised upwards. In bear markets, such as now, those revisions trend lower until specific catalysts change investor perceptions. Then, the whole cycle starts all over again. At the end of a very difficult 6 months for stock prices, it is worth remembering that there is always a low and a next bull market. The goal now is to play defense until those arrive.

Source: Thaler article: https://www.chicagobooth.edu/review/keyness-beauty-contest

Tyler Durden Mon, 07/04/2022 - 14:30

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Economics

Growing Surgical Revenue and Automating OR Processes a Top Priority for Health Systems

Growing Surgical Revenue and Automating OR Processes a Top Priority for Health Systems
PR Newswire
MOUNTAIN VIEW, Calif., Oct. 5, 2022

Survey finds 95% of health system executives desire more automation and less reliance on manual OR processes
MOUN…

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Growing Surgical Revenue and Automating OR Processes a Top Priority for Health Systems

PR Newswire

Survey finds 95% of health system executives desire more automation and less reliance on manual OR processes

MOUNTAIN VIEW, Calif., Oct. 5, 2022 /PRNewswire/ -- Increasing surgical services revenue is a top priority for healthcare systems, with automation seen as a way to accomplish it, according to a new survey of healthcare executives conducted by The Health Management Academy.

Seventy-six percent of respondents named increasing surgical services revenue as a top priority, while half the health systems represented said they plan to increase investments across their surgical services in the next two years.

The survey, which was conducted in August 2022 in partnership with Qventus, the leading provider of AI-based software for care operations automation, was completed by 21 executives whose titles include chief medical officer, chief operating officer, VP of perioperative services, VP of operations, VP of surgical specialties, surgical chair, clinical enterprise lead and business operations director for surgical services. The responding executives represent 19 health systems with an average total operating revenue of $6.3 billion.

Key findings include:

  • Increasing surgical services revenue is a top priority for the majority (76%) of executives. About half (52%) of health systems are planning to increase investments across the surgical service line in the next two years.

  • Health system executives are focused on end-to-end growth strategies. Top strategies to increase surgical revenue growth include: improving operating room (OR) scheduling and access (81%), growing case volumes (71%), and increasing surgical referrals to reduce patient leakage (57%).

  • The majority (71%) of executives report 11% to 30% of their health system's OR time is not optimally used.

  • Nearly all (95%) of surveyed healthcare systems are looking to automate OR scheduling more and rely less on manual processes.

  • All (100%) executives agree there is opportunity to improve surgeon satisfaction rates. Their strategies for improving satisfaction include addressing burnout, streamlining internal processes and using technology to augment manual tasks.

"This data confirms what we hear from our leading health system members: executives know their financial recovery from the pandemic depends on growing surgical revenue, and that requires driving integrated strategies that optimize access, case volumes and mix, as well as market share. Leaders recognize that manual processes are holding them back, and they view automation as an essential capability to grow their surgical services revenue," said Brian Contos, SVP of Research & Member Insights at The Health Management Academy.

The crisis in surgical revenue has been aggravated by the COVID-19 pandemic and staffing shortages, which have cut into hospital operating margins. As a result, healthcare systems are looking for technology that will allow them to maximize their existing capacity without adding resources.

"The survey findings validate what we've been hearing from our health system partners," said Mudit Garg, Co-founder and CEO of Qventus. "Hospitals are focused on making their perioperative services more productive and efficient, but their existing tools and EHRs are incapable of doing it. To gain a new competitive advantage, they need a new approach and are turning to automation software."

The Qventus Perioperative Solution is the only solution that automates strategic growth of surgical services. By combining AI & machine learning, behavioral science, and comprehensive data, the solution creates new white space on OR and surgical robot calendars, automatically fills open times with strategic cases, and identifies referral and outmigration improvement opportunities — while also giving visibility into OR & surgeon performance. As a result, health systems can unlock over 50% of blocks otherwise unused, increase robotic cases by 33%, and add over 2 cases per OR per month using existing resources.

To view the full report, click here.

About Qventus

Qventus is the leading provider of AI-based software for care operations automation. Integrating with EHRs, the Qventus platform uses AI, machine learning, and behavioral science to power best-practice solutions for inpatient, perioperative, emergency department, and command center settings. As a partner to leading health systems and hospitals across the country, including Boston Medical Center, HonorHealth, M Health Fairview, Saint Luke's Health System, and ThedaCare, Qventus delivers proven outcomes, including over 2 new surgical cases added per operating room per month, 30-50% fewer excess days, and 1 full day reduction in length of stay. For more, visit https://qventus.com/.

Media Contact:

Jim Sweeney
Amendola Communications on behalf of Qventus
(216) 650-3376
jsweeney@acmarketingpr.com

View original content to download multimedia:https://www.prnewswire.com/news-releases/growing-surgical-revenue-and-automating-or-processes-a-top-priority-for-health-systems-301640744.html

SOURCE Qventus

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Government

JOLTs jolted: Did the Fed break the labour market?

In the Bureau of Labor Statistics (BLS) August release of the Job Openings and Labor Turnover Survey (JOLTS) report, the number of job openings, a measure…

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In the Bureau of Labor Statistics (BLS) August release of the Job Openings and Labor Turnover Survey (JOLTS) report, the number of job openings, a measure of demand for labour, fell to 10.1 million. This was short of market estimates of 11 million and lower than last month’s level of 11.2 million.

It also marked the fifth consecutive month of decreases in job openings this year, while the August unemployment rate had ticked higher to 3.7%, near a five-decade low.

In the latest numbers, the total job openings were the lowest reported since June 2021, while incredibly, the decline in vacancies of 1.1 million was the sharpest in two decades save for the extraordinary circumstances in April 2020. 

Healthcare services, other services and retail saw the deepest declines in job openings of 236,000, 183,000, and 143,000, respectively.

With total jobs in some of these sectors settling below pre-pandemic levels, the Fed’s push for higher borrowing costs may finally be restricting demand for workers in these areas.

The levels of hires, quits and layoffs (collectively known as separations) were little changed from July.

The quits rate (a percentage of total employment in the month), a proxy for confidence in the market was steady at 2.8%.

Source: US BLS

From a bird’s eye view, 1.7 openings were available for each unemployed person, cooling from 2.0 in the month prior but still above the historic average. 

The market still appears favourable for workers but seems to have begun showing signs of fatigue.

Ian Shepherdson, Economist at Pantheon Macroeconomics noted that it was too soon to suggest if a new trend had started to emerge, and said,

…this is the first official indicator to point unambiguously, if not necessarily reliably, to a clear slowing in labour demand.

Nick Bunker, Head of Economic Research at Indeed, also stated,

The heat of the labour market is slowly coming down to a slow boil as demand for hiring new workers fades.

Ironically, equities surged as investors pinned their hopes on weakness in headline jobs numbers being the sign of breakage the Fed needed to pull back on its tightening.

Kristen Bitterly, Citi Global Wealth’s head of North American investments added,

(In the past, in) 8 out of the 10 bear markets, we have seen bounces off the lows of 10%…and not just one but several, this is very common in this type of environment.

The worst may be yet to come

As for the health of the economy, after much seesawing in its projections, which swung between 0.3% as recently as September 27 and as high as 2.7% just a couple of weeks earlier, the Atlanta Fed GDPNow estimate was finalized at a sharply rebounding 2.3% for Q3, earlier in the week.

Rod Von Lipsey, Managing Director, UBS Private Wealth Management was optimistic and stated,

…looking for a stronger fourth quarter, and traditionally, the fourth quarter is a good part of the year for stocks.

As I reported in a piece last week, a crucial consideration that has been brought up many a time is the unknown around policy lags.

Cathie Wood, Ark Invest CEO and CIO noted that the Fed has increased rates an incredible 13-fold in a span of just a few months, which is in stark contrast to the rate doubling engineered by Governor Volcker over the span of a decade.

Pedro da Costa, a veteran Fed reporter and previously a fellow at the Peterson Institute for International Economics, emphasized that once the Fed tightens policy, there is no way to know when this may be fully transmitted to the economy, which could lie anywhere between 6 to 18 months.

The JOLTs report reflects August data while the Fed has continued to tighten. This raises the probability that the Fed may have already done too much, and the environment may be primed to send the jobs market into a tailspin.

Several recent indicators suggest that the labour market is getting ready for a significant deceleration.

For instance, new orders contracted aggressively to 47.1. Although still expansionary, ISM manufacturing data fell sharply to 50.9 global, factory employment plummeted to 48.7, global PMI receded into contractionary territory at 49.8, its lowest level since June 2020 while durable goods declined 0.2%.

Moreover, transpacific shipping rates, a leading indicator absolutely crashed, falling 75% Y-o-Y on weaker demand and overbought inventories.

Steven van Metre, a certified financial planner and frequent collaborator at Eurodollar University, argued

“…the next thing to go is the job market.“

A recent study by KPMG which collated opinions of over 400 CEOs and business leaders at top US companies, found that a startling 91% of respondents expect a recession within the next 12 months. Only 34% of these think that it would be “mild and short.”

More than half of the CEOs interviewed are looking to slash jobs and cut headcount.

Similarly, a report by Marcum LLP in collaboration with Hofstra University found that 90% of surveyed CEOs were fearful of a recession in the near future.

It also found that over a quarter of company heads had already begun layoffs or planned to do so in the next twelve months.

Simply put, American enterprises are not buying the Fed’s soft-landing plans.

A slew of mass layoffs amid overwhelming inventories and a weak consumer impulse will result in a rapid decline in price pressures, exacerbating the threat of too much tightening.

Upcoming data

On Friday, the markets will be focused on the BLS’s non-farm payrolls data. Economists anticipate a comparatively small addition of jobs, likely to be near 250,000, which would mark the smallest monthly increase this year.

In a world where interest rates are still rising, demand is giving way, the prevailing sentiment is weak and companies are burdened by excessive inventories, can job cuts be far behind?

The post JOLTs jolted: Did the Fed break the labour market? appeared first on Invezz.

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Spread & Containment

Measuring the Ampleness of Reserves

Over the past fifteen years, reserves in the banking system have grown from tens of billions of dollars to several trillion dollars. This extraordinary…

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Over the past fifteen years, reserves in the banking system have grown from tens of billions of dollars to several trillion dollars. This extraordinary rise poses a natural question: Are the rates paid in the market for reserves still sensitive to changes in the quantity of reserves when aggregate reserve holdings are so large? In today’s post, we answer this question by estimating the slope of the reserve demand curve from 2010 to 2022, when reserves ranged from $1 trillion to $4 trillion.

What Are Reserves? And Why Do They Matter?

Banks hold accounts at the Federal Reserve where they keep cash balances called “reserves.” Reserves meet banks’ various needs, including making payments to other financial institutions and meeting regulatory requirements. Over the past fifteen years, reserves have grown enormously, from tens of billions of dollars in 2007 to $3 trillion today. The chart below shows the evolution of reserves in the U.S. banking system as a share of banks’ total assets from January 2010 through September 2022. The supply of reserves depends importantly on the actions of the Federal Reserve, which can increase or decrease the quantity of reserves by changing its securities holdings, as it did in response to the global financial crisis and the COVID-19 crisis.

Reserves Have Ranged from 8 to 19 Percent of Bank Assets from 2010 to 2022

Sources: Federal Reserve Bank of New York; Federal Reserve Economic Data, FRED (“TLAACBW027SBOG”); authors’ calculations.

Why does the quantity of reserves matter? Because the “price” at which banks trade their reserve balances, which in turn depends importantly on the total amount of reserves in the system, is the federal funds rate, which is the interest rate targeted by the Federal Open Market Committee (FOMC) in the implementation of monetary policy. In 2022, the FOMC stated that “over time, the Committee intends to maintain securities holdings in amounts needed to implement monetary policy efficiently and effectively in its ample reserves regime.” In this ample reserves regime, the Federal Reserve controls short-term interest rates mainly through the setting of administered rates, rather than by adjusting the supply of reserves each day as it did prior to 2008 (as discussed in this post). In today’s post, we describe a method to measure the sensitivity of interest rates to changes in the quantity of reserves that can serve as a useful indicator of whether the level of reserves is ample.

The Demand for Reserves Informs Us about Rate Sensitivity to Reserve Shocks

To assess whether the level of reserves is ample, one needs to first understand the demand for reserves. Banks borrow and lend in the market for reserves, typically overnight. The reserve demand curve describes the price at which these institutions are willing to trade their balances as a function of aggregate reserves. Its slope measures the price sensitivity to changes in the level of reserves. Importantly, banks earn interest on their reserve balances (IORB), set by the Federal Reserve. Because the IORB rate directly affects the willingness of banks to lend reserves, it is useful to describe the reserve demand curve in terms of the spread between the federal funds rate and the IORB rate. In addition, we control for the overall growth of the U.S. banking sector by specifying reserve demand in terms of the level of reserves relative to commercial banks’ assets.

There is a clear nonlinear downward-sloping relationship between prices and quantities of reserves, consistent with economic theory. The chart below plots the spread between the federal funds rate and the IORB against total reserves as a share of commercial banks’ total assets.  When reserves are very low, the demand curve has a steep negative slope, reflecting the willingness of borrowers to pay high rates because reserves are scarce. At the other extreme, when reserves are very high, the curve becomes flat because banks are awash with reserves and the supply is abundant. Between these two regions, an intermediate regime–that we refer to as “ample”–emerges, where the demand curve exhibits a modest downward slope. The color coding of the chart reflects the shifts in the reserve demand curve over time. In particular, the curve appears to have moved to the right and upward around 2015 and then moved upward after March 2020, at the onset of the COVID pandemic.

Reserve Demand Has Shifted over Time

Sources: Federal Reserve Bank of New York; Federal Reserve Economic Data, FRED (“TLAACBW027SBOG,” “IOER,” and “IORB”); authors’ calculations.

This chart highlights two of the main challenges in estimating the slope of the reserve demand curve. First, the curve is highly nonlinear, which means that a standard linear estimation approach is not appropriate. Second, various long-lasting changes in the regulation and supervision of banks, in their internal risk-management frameworks, and in the structure of the reserve market itself have resulted in shifts in the reserve demand curve. A third challenge is that the quantity of reserves may be endogenous to banks’ demand for them. Therefore, to properly measure the reserve demand curve, one must disentangle shocks to supply from those to demand. As we explain in detail in a recent paper, our estimation strategy addresses all three of these challenges.

Estimating the Slope of the Reserve Demand Curve

Our approach provides time-varying estimates of the price sensitivity of the demand for reserves that can be used to distinguish between periods in which reserves are relatively scarce, ample, or abundant. The chart below presents our daily estimates of the slope of the demand curve, as measured by the rate sensitivity to changes in reserves. Although we do not have a precise criterion for when reserves are scarce versus ample, during two episodes in our sample, the estimated rate sensitivity is well away from zero. The first episode occurs early in our sample, in 2010, and the second emerges almost ten years later, in mid-2019. In two other periods—during 2013-2017 and from mid-2020 through early September 2022—the estimated slope is very close to zero, indicating an abundance of reserves. The remaining periods are characterized by a modest negative slope of the reserve demand curve, consistent with ample (but short of abundant) reserves. The overall pattern of these estimates is robust to changes in the model specification, such as including spillovers from the repo and Treasury markets or measuring reserves as a share of gross domestic product or bank deposits (instead of as a share of banks’ assets).

Rate Sensitivity Changed over Time, Following the Path of Reserves

Sources: Federal Reserve Bank of New York; Federal Reserve Economic Data, FRED (“TLAACBW027SBOG,” “IOER,” and “IORB”); authors’ calculations.

Interest Rate Spreads Alone Are Not Reliable Indicators of Reserve Scarcity

As we discuss in our paper, the time variation in the estimated price sensitivity in the demand for reserves is based on observations of small movements along the demand curve due to exogenous supply shocks. The location of the curve itself, however, also changes over time. That is, there is not a constant relationship between the level of reserves and the slope of the reserve demand curve.  

In our paper, we find evidence of both horizontal and vertical shifts in the reserve demand curve, with vertical upward shifts being particularly important since 2015. This finding implies that the level of the federal funds-IORB spread may not be a reliable summary statistic for the sensitivity of interest rates to reserve shocks, and that estimates of the price sensitivity in the demand for reserves provide additional useful information.

In summary, we have developed a method to estimate the time-varying interest rate sensitivity of the demand for reserves that accounts for the nonlinear nature of reserve demand and allows for structural shifts over time. A key advantage of our methodology is that it provides a flexible and readily implementable approach that can be used to monitor the market for reserves in real time, allowing one to assess the “ampleness” of the reserve supply as market conditions evolve.

Gara Afonso is the head of Banking Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.

Gabriele La Spada is a financial research economist in Money and Payments Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.   

John C. Williams is the president and chief executive officer of the Federal Reserve Bank of New York.  

How to cite this post:
Gara Afonso, Gabriele La Spada, and John C. Williams, “Measuring the Ampleness of Reserves,” Federal Reserve Bank of New York Liberty Street Economics, October 5, 2022, https://libertystreeteconomics.newyorkfed.org/2022/10/measuring-the-ampleness-of-reserves/.


Disclaimer
The views expressed in this post are those of the author(s) and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author(s).

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