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China Yuan Swaps Soar Amid Fears Evergrande Default Will Lead To Liquidity Crisis

China Yuan Swaps Soar Amid Fears Evergrande Default Will Lead To Liquidity Crisis

The initial contagion from the upcoming default of Evergrande,…

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This article was originally published by Zero Hedge
China Yuan Swaps Soar Amid Fears Evergrande Default Will Lead To Liquidity Crisis

The initial contagion from the upcoming default of Evergrande, which after the company's hiring of bankruptcy advisor Houlihan Lokey is just a matter of days, is starting to emerge.

China’s one-year onshore swap curves surged to the highest in almost four years, signaling market worries over liquidity shortage on potential default by a key property developer Evergrande. Interbank borrowing costs also rise ahead of the central bank’s medium-term lending facility operation on Wednesday.

As Bloomberg notes the 1-year dollar-yuan onshore swap - a gauge of funding costs for the Chinese currency via the foreign exchange market - surged as high as 1,843 pips Tuesday, the highest in almost four years.

"Considering huge uncertainties over the key developer’s bond default and the possible spillover to the property sector, market participants might intend to swap more CNH and CNY liquidity in the FX swap market (sell/buy USD against yuan),” said Ken Cheung, Chief Asian FX Strategist at Mizuho.

While one would be hard-pressed top find any fears in US assets, Cheung notes that traders might be preparing for “the liquidity squeeze in crisis mode” adding that a full-blown bankruptcy would trigger a domino effect of defaults in its bonds and wealth management products, or as he put it in terms so simple even those who were in diapers when Lehamn filed, “the collapse of credit would lead to liquidity squeeze in financial markets."

While funding markets are only now starting to reflect Evergrande default fears, the contagion across China's credit market has been visible for weeks, with local junk bond yields surging to the highest since the covid crash.

Not helping market liquidity is traders confusion over how much of the 600BN yuan in medium term loans maturing on Wednesday will be rolled over by the PBOC, any liquidity drains by the central bank will lead to even tighter funding conditions and could accelerate the collapse in one or more Chinese companies.

“A partial rollover looks likely given that the 7-day repo rate remains pretty stable and the PBOC will only act when the 7-day moves,” said Hao Zhou senior emerging economist at Commerzbank in Singapore, adding that “the central bank will need more weakening signals to move on rates so maybe next month is a better time window with the Q3 GDP report due.”

His conclusion: “Evergrande hasn’t had a big impact on interbank market yet.” That will change very fast once the company officially files.

 

 

Tyler Durden Tue, 09/14/2021 - 12:00

Economics

Investors’ Cash Balances Struggling to Swallow Smart Money Supply

There are near-record amounts of cash ready to be deployed into markets…and corporations are doing their best to drain it.Investors have a near-record amount of cash ready to invest in stocks (or whatever else), a bullish indication of “cash on the s…

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There are near-record amounts of cash ready to be deployed into markets...and corporations are doing their best to drain it.

Investors have a near-record amount of cash ready to invest in stocks (or whatever else), a bullish indication of "cash on the sidelines" as deceptive as that clichè is. According to the Investment Company Institute, investors hold more than $4.5 trillion (with a "t") in money market funds.

And yet corporations are issuing a record amount of stock, a bearish indication of supply and smart-money selling pressure. Bloomberg data shows that U.S. corporations have issued more than $450 billion in stock via IPOs, secondary, and additional offerings over the past 52 weeks.

US corporate stock issuance

Bullish investors will give more credence to the former; bearish investors the latter. There is little question that both are factual, and it's a relatively unusual situation. Usually, when corporations are issuing boatloads of stock, investors have small cash reserves and vice-versa; when corporations can't issue shares due to lack of demand, investors are usually hoarding cash at the time.

It's rare to see such high levels at the same time. If we look at a ratio of the two, then things become a bit clearer.

During the pandemic panic, the ratio neared 30 and was the highest in 30 years. In other words, there was 28 times more cash available than shares offered in supply. There are ways to quibble with the technicals, but it's simply meant as a reflection of sentiment.

Over the past year, the ratio has declined steadily as supply ramped up. Corporations are "feeding the ducks," as the saying goes. Even though money market assets haven't been drained much, the skyrocketing supply has caused the ratio to drop below 10 for the first time since the year 2000. 


What else we're looking at

  • A deeper look at money market assets and the ratio to corporate stock issuance
  • What it means when individual investors become bearish with stocks near their highs
  • A detailed look at the surge in natural gas prices and the futures curve
  • Small-cap stocks are entering a seasonal soft spot

Stat box

Natural gas futures prices have skyrocketed by 110% over the past 6 months. That's the most since 2004 and ranks as the 5th-largest 6-month return in 30 years.

Etcetera

Less shiny. The Optimism Index on the GLD gold fund plunged below 11.5% on Thursday, one of its lowest levels in a year. Our Backtest Engine shows that GLD rallied over the next week after 13 out of 16 prior signals.

gold gld sentiment optimism index

Go big or go home. Over the past 3 sessions, the IWM small-cap ETF has lost an average of more than $500 million in assets per day. That's the 2nd-largest amount since small-caps entered their trading range in February.

iwm small cap fund flow

A mostly pessimistic world. Our Optimism Index Geo-Map shows that investors in most parts of the world are showing pessimism (the deeper the green color, the more pessimism). Pockets of optimism are seen in Asia, including India and Japan.

optimism index geo map

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Economics

Research Review | 17 Sep 2021 | Financial Shocks And Crises

Banking-Crisis Interventions, 1257 – 2019 Andrew Metrick and Paul Schmelzing (Yale) September 7, 2021 We present a new database of banking-crisis interventions…

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Banking-Crisis Interventions, 1257 – 2019
Andrew Metrick and Paul Schmelzing (Yale)
September 7, 2021
We present a new database of banking-crisis interventions since the 13th century. The database includes 1886 interventions in 20 categories across 138 countries, covering interventions during all of the crises identified in the main banking-crisis chronologies, while also cataloguing a large number of interventions outside of those crises. The data show a gradual shift over the past centuries from the traditional interventions of a lender-of-last-resort, suspensions of convertibility, and bank holidays, towards a much more prominent role for capital injections and sweeping guarantees of bank liabilities. Furthermore, intervention frequencies and sizes suggest that the crisis problem in the financial sector has indeed reached an apex during the post-Bretton Woods era – but that such trends are part of a more deeply entrenched development that saw global intervention frequencies and sizes gradually rise since at least the late 17th century.

Can Financial Soundness Indicators Help Predict Financial Sector Distress?
Marcin Pietrzak (IMF)
July 23, 2021
This paper shows how the role of Financial Soundness Indicators (FSIs) in financial surveillance can be usefully enhanced. Drawing from different statistical techniques, the paper illustrates that FSIs generate signals that can accurately detect, with 4 to 12 quarters lead, emerging financial distress—as measured by tight financial conditions.

Financial Crises: A Survey
Amir Sufi (U. of Chicago) and Alan M. Taylor (U. of California)
August 17, 2021
Financial crises have large deleterious effects on economic activity, and as such have been the focus of a large body of research. This study surveys the existing literature on financial crises, exploring how crises are measured, whether they are predictable, and why they are associated with economic contractions. Historical narrative techniques continue to form the backbone for measuring crises, but there have been exciting developments in using quantitative data as well. Crises are predictable with growth in credit and elevated asset prices playing an especially important role; recent research points convincingly to the importance of behavioral biases in explaining such predictability. The negative consequences of a crisis are due to both the crisis itself but also to the imbalances that precede a crisis. Crises do not occur randomly, and, as a result, an understanding of financial crises requires an investigation into the booms that precede them.

Macroeconomic and Financial Risks: A Tale of Mean and Volatility
Dario Caldara (Federal Reserve), et al.
August 2021
We study the joint conditional distribution of GDP growth and corporate credit spreads using a stochastic volatility VAR. Our estimates display significant cyclical co-movement in uncertainty (the volatility implied by the conditional distributions), and risk (the probability of tail events) between the two variables. We also find that the interaction between two shocks–a main business cycle shock as in Angeletos et al. (2020) and a main financial shock–is crucial to account for the variation in uncertainty and risk, especially around crises. Our results highlight the importance of using multivariate nonlinear models to understand the determinants of uncertainty and risk.

Pre-crisis conditions and financial crisis duration
Thanh Cong Nguyen (Phenikaa University)
July 3, 2021
This paper examines how pre-crisis conditions affect the duration of different types of financial crises using a data sample of 244 financial crises in 89 countries over the period 1985-2017. Results from our parametric survival analysis show that the duration of any type of financial crisis is longer for countries having higher levels of public debt prior to financial crises, whereas it is shorter for countries characterised by higher pre-crisis levels of (i) current account balance, (ii) international reserves, and (iii) institutional quality. Similarly, while pegged exchange rate regimes are associated with a longer duration of financial crises, majority governments help countries emerge faster from crises. Moreover, banking and currency crises tend to be more prolonged when preceded by higher credit growth. We also find a positive effect of pre-crisis fiscal balance on the probability of crisis ending, and it is noteworthy that this effect is strengthened under majority governments and a stronger institutional environment. Finally, our duration dependence analysis suggests that banking, currency, and twin and triple crises are more likely to end when they grow older.

Monetary policy, financial shocks and economic activity
Anastasios Evgenidis (U. of Newcastle) and A.G. Malliaris (Loyola U. Chicago)
March 1, 2021
This paper contributes to a deeper understanding of macroeconomic outcomes to financial market disturbances and the central bank’s role in financial stability, by using Bayesian VAR (BVAR) models. We document that a shock that increases credit to non-financial sector leads to a persistent decline in economic activity. In addition, we examine whether the behavior of financial variables is useful in signaling the 2008 recession. The answer is positive as our medium-scale BVAR generates early warning signals pointing to a sustained slowdown in growth. Finally, we suggest that the expansion phase of the business cycle can be subdivided into an early and a late expansion. Based on this distinction, we show that if the Fed had raised the policy rate when the economy moved from the early to late expansion, it could have mitigated the severity of the last recession.

Stress Testing the Financial Macrocosm
J. Doyne Farmer (University of Oxford), et al.
August 30, 2021
What kind of models do we need to guide us through the next crisis? If past crises are any indication, we need to explore new approaches. During the Great Financial Crisis, the models that existed at the time were of little value because they focused on firm-level interactions and did not capture the system-wide dynamics that fueled the crisis. In this paper, we sketch a vision for a new approach to understanding and mitigating financial and economic crises. We argue that next-generation stress test models must take a comprehensive a view of the financial macrocosm to enable the regulator to effectively regulate and supervise the macro-financial dynamics of the global economy.


Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return

By James Picerno


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Economics

Technical Value Scorecard Report For The Week of 9-17-21

Relative Value Graphs

This week’s results are interesting as the divergences between growth/low beta and value/cyclical sectors are not as evident as…

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Relative Value Graphs

  • This week’s results are interesting as the divergences between growth/low beta and value/cyclical sectors are not as evident as over the last few months.
  • Transports are the most overbought sector, albeit not at a very high score. Energy has moved up as well. That said, materials and industrials, two other sectors affiliated with cyclical sectors, are the most oversold sectors.   
  • Energy stocks had a great week, beating the S&P by over 3.5%. Over the last four weeks, it has been the best performing sector with an excess return of 7.42%.
  • Most factors/indexes remain oversold, with small and mid-cap stocks the most oversold. Inflation, worker shortages, and higher wages have a more significant adverse effect on these companies than many larger S&P 500 companies.

Absolute Value Graphs

  • Materials and Industrials are the only sectors oversold on the absolute graphs. Like small and mid-caps, higher wages and input costs are weighing on those sectors. Discretionary is the most overbought sector, but with a score just north of 50%, it has room to strengthen before we offer caution. Energy, trading better due to higher crude and natural gas prices, had the largest increase in its absolute score. It is overbought but not terribly so.
  • The S&P 500, bottom-right in the second set of graphs, is overbought as well, but within the year’s range. Its low scores earlier in the week almost brought it to fair value. For now, fair value seems to mark the lows for any local sell-off.  
  • There are no sectors more than two standard deviations from its 50 or 200 dma. The only close one is Technology at 1.75 standard deviations above its 200 dma.
  • Broadly speaking, there is little in this report to offer a warning that the recent sell-off could worsen. The new trend worth consideration is the bifurcation of the cyclical sectors due to inflationary concerns on profit margins.

Users Guide

The technical value scorecard report is one of many tools we use to manage our portfolios. This report may send a strong buy or sell signal, but we may not take any action if other research and models do not affirm it.

The score is a percentage of the maximum score based on a series of weighted technical indicators for the last 200 trading days. Assets with scores over or under +/-70% are likely to either consolidate or change the trend. When the scatter plot in the sector graphs has an R-squared greater than .60 the signals are more reliable.

The first set of four graphs below are relative value-based, meaning the technical analysis is based on the ratio of the asset to its benchmark. The second set of graphs is computed solely on the price of the asset. At times we present “Sector spaghetti graphs” which compare momentum and our score over time to provide further current and historical indications of strength or weakness. The square at the end of each squiggle is the current reading. The top right corner is the most bullish, while the bottom left corner is the most bearish.

The ETFs used in the model are as follows:

  • Staples XLP
  • Utilities XLU
  • Health Care XLV
  • Real Estate XLRE
  • Materials XLB
  • Industrials XLI
  • Communications XLC
  • Banking XLF
  • Transportation XTN
  • Energy XLE
  • Discretionary XLY
  • S&P 500 SPY
  • Value IVE
  • Growth IVW
  • Small Cap SLY
  • Mid Cap MDY
  • Momentum MTUM
  • Equal Weighted S&P 500 RSP
  • NASDAQ QQQ
  • Dow Jones DIA
  • Emerg. Markets EEM
  • Foreign Markets EFA
  • IG Corp Bonds LQD
  • High Yield Bonds HYG
  • Long Tsy Bonds TLT
  • Med Term Tsy IEI
  • Mortgages MBB
  • Inflation TIP
  • Inflation Index- XLB, XLE, XLF, and Value (IVE)
  • Deflation Index- XLP, XLU, XLK, and Growth (IWE)

The post Technical Value Scorecard Report For The Week of 9-17-21 appeared first on RIA.

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