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In March 2020, the Federal Reserve launched the Secondary Market Corporate Credit Facility (SMCCF) to stabilize the $10 trillion U.S. corporate bond market, which faced falling prices and rising credit spreads due to the COVID-19 pandemic. By purchasing corporate bonds in the secondary market, the Fed aimed to support credit markets, marking its first direct intervention in corporate debt. Bin Wei assesses the SMCCF’s effectiveness and examines how it influenced corporate bond pricing.

Image courtesy of interviewee. October 3, 2024

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This video presents a study investigating the impact of the COVID-19 pandemic on the U.S. corporate bond markets, particularly in early 2020. As the pandemic began, there was significant strain on these markets, characterized by a rush for cash leading to widespread sell-offs across various financial sectors. Notably, in March 2020, bond prices fell dramatically, and an unusual inversion of the credit curve occurred, reversing the typical trend where long-term bonds yield higher prices than short-term ones.

In response to this financial turmoil, the Federal Reserve implemented the Secondary Market Corporate Credit Facility (SMC-CF) on March 23, 2020, marking the first time the Fed directly supported corporate credit markets by signaling its willingness to purchase outstanding corporate debt. The study highlights how this program aimed to stabilize the bond market, ensuring companies could still access credit during economic disruptions.

The research focuses on the effects of these Fed programs, identifying significant improvements in corporate bond market conditions following the announcements. The study utilizes a matched sample methodology to analyze eligible and ineligible bonds, employing difference-in-differences regressions to evaluate the effectiveness of the SMC-CF program. Findings indicate that the program successfully reduced credit spreads, improved investor confidence, and restored the upward-sloping term structure of credit prices, thus facilitating easier borrowing for companies post-announcement.

The analysis also addresses how the Fed's actual bond purchases further impacted market prices, emphasizing a notable differential effect of such purchases on eligible bonds. Overall, the study suggests that the Fed's rapid response through these measures significantly influenced market conditions and helped in recovering from the pandemic-induced financial strain. Future research directions proposed include a deeper exploration of the transmission mechanisms of the SMC-CF and broader monetary policy effects.

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Here are five key points from the video:

1. **Impact of COVID-19 on Corporate Bond Market**: The COVID-19 pandemic strained the US corporate bond market in early 2020, leading to a significant sell-off and a "dash for cash," where investors rushed to liquidate their short-term, high-quality investment-grade bonds, resulting in an inversion of the credit curve.

2. **Federal Reserve Intervention**: In response to the financial crisis, the Federal Reserve implemented two major programs—the Primary Market Corporate Credit Facility (PMCCF) and the Secondary Market Corporate Credit Facility (SMCCF) on March 23, 2020. These programs marked the first time the Fed directly supported corporate credit markets by purchasing corporate debt to stabilize the bond market.

3. **Effectiveness and Eligibility Criteria of SMCCF**: The SMCCF was aimed at purchasing corporate bonds from US investment-grade companies with maturities of five years or less. It was extended to include certain foreign bonds that were downgraded after March 22, 2020. The program's objective was to stabilize the corporate bond market and ensure that businesses could continue to operate during the pandemic.

4. **Methodology and Analysis**: The study utilized a matched sample methodology to assess the SMCCF program's efficacy by comparing eligible and ineligible bonds issued by the same companies. A difference-in-differences approach was used to analyze the effect of the program announcements on credit prices, finding that the announcements not only lowered credit prices but also helped restore the upward-sloping credit curve.

5. **Mechanisms of Market Recovery**: The study identified two main factors contributing to the recovery of the corporate bond market: a "dash for cash," which pressured short-term credit, and the growing unwillingness of broker-dealers to absorb inventory during the crisis. The Fed's actions helped to calm the market and improved dealers' willingness to participate, leading to a steepening of the credit curve and improved overall market sentiment.

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Here are key quotes extracted from the video regarding the effects of the COVID-19 pandemic on the US corporate bond markets and the response of the Federal Reserve:

1. **Impact of COVID-19**: "When COVID-19 hit in early 2020, it puts a lot of strain on the US corporate bond market... panic spread through the markets."

2. **Market Behavior**: "We observed this sudden debt for cash that led to a big sell off, not just in bonds, but also across different markets."

3. **Credit Curve Dynamics**: "In early to mid March, 2020... the credit curve actually got inverted... the longer-term credit spread were actually smaller than the short-term spread."

4. **Federal Reserve Intervention**: "The Fed made a major move on March 23rd, 2020, launching two big programs... this is the first time that the Fed directly supported corporate credit markets."

5. **Program Objectives**: "Through these programs, the Fed was committed to buying a substantial amount of corporate debt... to stabilize the corporate bond market and ensure businesses could continue."

6. **Program Extensions**: "The SMC SAFE was extended to include certain foreign angels... companies which were downgraded but previously had investment-grade ratings."

7. **Research Connection**: "Our paper is most closely related to... study the effects of the SMC SAFE... the authors analyze the reaction of the corporate bond credit price."

8. **Methodological Innovation**: "Our paper controls for the credit curve and we also point out the broader mechanism through which the SMC SAFE announcements affected the corporate bond market."

9. **Findings on Credit Prices**: "The announcements on March 23 and April 9 not only significantly lowered the average level of credit price for investment-grade bonds, they also led to a persistence and economically significant narrowing of credit spreads on eligible bonds."

10. **Credit Curve Restoration**: "The announcements helped restore the upward slope term structure of credit spreads... this ultimately restored the credit curve to its pre-pandemic level and shape."

11. **Effects of Actual Purchases**: "We find evidence that the actual bond purchases in the sector market actually had a differential effect of about three basis points on the purchase bonds relative to their ineligible counterparts."

12. **Transmission Mechanism**: "The fast announcements of the SMC SAFE really helps calm the market by reducing the upcharge reserves... the credit curve is restored to its pre-pandemic shape."

These quotes encapsulate the main points regarding the effects of the pandemic on the bond market, Federal Reserve interventions, and the subsequent financial analysis conducted in relation to these events.

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

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Our study is about, what happens,

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to the US corporate bond markets during the pandemic,

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especially in early 2000, 20.

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So as we can somehow recall,

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when COVID-19 hit in early 2020, it puts a lot

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of strain on the US corporate bond market.

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So we observed this sudden debt for cash, that led

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to a big sell off, not just in bonds,

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but also across different markets.

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So this income mutual funds experienced large outflows

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and the panic spread through the markets.

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In March, 2020, COVID bonds prices dropped

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and the crisis price widened fast.

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So, and then

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we actually observed a very interesting phenomenon

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during March, 2020.

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Uh, you know, normally the relationship between credit price

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and the bond maturity implies an upward slope credit curve,

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meaning that the longer term credit price

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are typically larger.

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But what happens in early

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to meet March, 2020 is that

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the credit curve actually got inverted.

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Meaning that the longer term credit spread are actually,

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will actually lower smaller than the short term spread.

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And then the gap between this long

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and the short term spread once sharply negative.

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So this inversion was most

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noticeable in the safest part of investment grade market,

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where this panicked investors rushed

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to sell off their most liquid assets,

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particularly this short term,

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high quality investment grade bonds.

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And then the Fed reserve quickly stepped in when the

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financial market started to get rocky,

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and they rolled off a bunch of measures

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to cushion the economic blow from the pandemic.

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While the actions helped avoid a bigger market crash,

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the corporate bond market still struggled

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with liquidity issues and the credit express kept widening.

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So to tackle these growing problems,

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the Fed made a major move on March 23rd, 2020,

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launching two big programs.

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One is what you mentioned,

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the primary market corporate credit facility,

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long S-P-M-C-C-F,

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and the second one is the secondary market corporate credit

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facility loan, S-A-M-C-C-F.

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So our paper is for the second one.

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So this is the first time that the Fed, the Federal Reserve

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directly supported corporate credit markets

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by signaling a willingness

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to purchase outstanding corporate debt

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and then potentially take a material amount

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of credit risk on its balance sheet.

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What are these programs, right?

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And then what was the stated objective of the SMC safe?

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So here, both programs were this,

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emergency landing programs introduced by the Fed,

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right in response to this, financial turmoil caused

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by the COVID-19 pandemic in 2020 through these programs,

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the Fed was committed to buying a substantial amount

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of corporate debt in both the primary

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and the sector markets.

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So by design, these programs aim to stabilize

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the corporate bond market

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and ensure businesses, businesses could continue

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to access credit despite the economic disruptions.

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So if we want to talk about separately, so

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the P-M-C-C-F was created to provide credits directly

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to large corporations by purchasing new bonds

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or loans issued by eligible companies.

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And then in contrast, the A-C-M-C-C-F was set up to buy

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existing corporate bonds

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that were already issued on the sector market, right?

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This program also purchased shares in ETFs, right?

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Exchange traded funds that held corporate bonds.

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So let me talk a little bit more about SMC safe,

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which is the subject started in our paper.

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So this program

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was initially announced on March 23rd, 2020,

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and then the eligible bonds were required

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to have been issued by US investment grade companies.

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And then this bonds, to be eligible had

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to have a remaining maturity of five years or less, right?

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So there is this eligibility criteria.

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And then on April nine, this program,

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SMC safe was extended to include certain foreign angels.

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This basically means that the companies which were used

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to have the investment grade ratings,

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but somehow downgraded.

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Uh, after March 22, there are several papers

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that studied the market turmoil of mid-March 2020.

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So, harder at all 2021 paper,

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they document these, copay bonds traded at a discount

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compared to layer corresponding credit default swap

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contracts during this, market turmoil in early

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to mid March, 2020.

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This gap is evidenced for the so-called dash for cash

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phenomenon, meaning that investors, they need to cash out.

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They primarily sold safer and more liquid corporate bonds,

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and then some other papers like papers by O'Hara.

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And so 2021

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and the car guard at all 2021 papers in these papers,

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the also documents the UN willingness of broker dealers

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to absorb the signing pressure at the height of the crisis.

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So these papers tell us about what happened, you know,

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what was the,

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what were the dislocations in this co bond market?

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And our paper is most closely related

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to the following papers.

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Uh, let's study the effects of the SMC safe.

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So there's a paper by,

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KO at all 2020 in their paper.

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Um, the author document a significant positive effect

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of the announcements on both March 23

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and April nine on the corporate bond ETFs

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and a second paper, by AWA and the CHO 2021.

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In their paper, the authors analyze the reaction

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of the corporate bond credit price

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to the fast announcements on both states.

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And the layer main findings stress

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the heterogeneous response of credit price

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across credit ratings.

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And then in another paper by Chenko

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and her co-authors in 2022 GFE paper,

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the authors document, significant

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improvements in both primary and sector market conditions

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after the program announcements,

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and they attribute the improvement

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to the increased willingness of dealers

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to underwrite issuances and inter

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and intermediates in sector markets.

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So these are the re related papers.

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So our paper,

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differ from these papers along the following dimensions.

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So compared to these papers, our paper controls

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for the confounding factor due to the inversion

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of the credit curve.

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And we also point out the broader mechanism

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through which the SMC safe announcements

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affected the corporate bond market.

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Specifically, our empirical analysis takes into account the

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announcements in induced rotations of the credit curve,

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which is absent in the affirmations papers.

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And furthermore, we use a preferred habitat theoretical

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model to illustrate the broader based mechanism of

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how such program affects market prices

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at the announcement date,

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and also how, you know, what are the effects

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of the actual purchases.

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This theoretical exercise highlights the importance

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of this broad-based reduction in risk aversion

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as the main channel through which the SMC safe influenced

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the corporate credit curve.

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The trace dataset is the, one of the,

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most important dataset used in our paper.

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Um, so this trace dataset is a database,

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containing information about individual corporate bonds

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transactions in the sector market.

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So from this, from this database, we obtain information such

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as the bonds, identity like qip,

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and we also observe the purchase dates and also time.

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And we also observe the transaction price and the quantity.

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And also we observe the type of the transactions, meaning

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that whether it is a dealer to dealer transactions

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or dealer to customer transactions.

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And we use this database

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and we actually, we are able to identify almost all

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the first actual purchases

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of individual bonds when the Fed implemented the SMC

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safe starting in June.

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So we are able to match almost all the, you know,

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we can identify almost all the feds bond purchases.

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So this is about the trace dataset.

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Um, and we use these triggers, we use this dataset,

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to construct this, matched sample.

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So that's one novelty of our study

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because, for each issuer, we can actually find

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a matched sample of eligible and ineligible bonds.

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As I mentioned earlier, right?

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There is, eligibility criter

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that requires the maturity of, eligible bonds

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to be five years or less.

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Therefore, each issuer we have identify eligible bonds

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that have maturity, less than or equal to five years,

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and also ineligible bonds

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that have maturity greater than five years.

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And then for each issuer, we try to find a pair

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of such eligible and ineligible bonds.

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And at the same time, we try to, you know,

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make the maturities of this pair of bonds to be

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as close as possible.

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So that's what we call the matched sample.

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So this matched sample would be a very, useful

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in identifying,

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and assessing the efficacy of the program

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because in this way, right, we can, control

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for the credit risk of the issuer

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because these bonds are issued by the same issuer, right?

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So that's one advantage, for having this matched sample.

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So, methodology wise, we use this,

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difference in differences.

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Socalled, DID, regressions to

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assess the efficacy of the program.

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So specifically,

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our regressions right include this issue of face effects,

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and we also include controls

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for other bonds characteristics.

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And then most importantly, to implement this,

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DID regressions, we include this, interaction term

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between a date dummy and the bond eligibility dummy.

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So this date dummy will be equal to one if this states is

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after the announcement states,

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and then this bond eligibility

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dummy will be one if this bond is actually eligible, meaning

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that this bond has remaining maturity less

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than or equal to five years.

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So the coefficient of this interaction term,

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would actually, measure, the differential response

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of credit, price of eligible

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and ineligible bonds in response to the announcements

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of the program, right?

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So in this way, we can somehow, we can judge

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and, measure the efficacy of the program.

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Um, so this is the empirical analysis and part of our paper.

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We also have some theoretical model, based on the,

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preferred heide framework.

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The main purpose of that exercise is to capture

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and calibrate the D for cash, which

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is an an adverse demand shock, right?

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Devices don't want, to hold bonds.

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They want to sell their holdings to get cash.

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So that's one factor.

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And the theoretical model captures another factor,

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which is the sharp increase in the abstracters risk version.

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And then we demonstrate that both factors are needed

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in order to account for the observed shifts

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or inversion of the credit curve.

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Although baseline results indicate that the,

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the announcements on both March 23

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and April nine,

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not only significantly lowered the average level

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of credit price for mass grade bonds, they also led

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to a persistence

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and economically significant narrowing

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of credit scores on eligible bonds quantitatively.

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We show that across these two announcements,

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within our 10 day event.

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Window of estimate suggests that, layer will a total

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decline of about 90 basis points in credit price

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for eligible bonds relative, relative

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to layer in eligible counterparts.

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So that shows significant effect of the program.

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And then, so this, in this baseline analysis,

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we only look at the effect of the program

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or the level of the credit price,

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and then we extend this baseline analysis by considering,

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the, so-called slope effects.

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We want to, to measure how the two announcements

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affected the slope of the term structure of credit price.

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That's the credit curve at the end.

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Our results suggests that, this March 23 announcements

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had a significantly stronger slope effect on the eligible

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segments of the credit curve and end.

15:14.015 --> 15:15.225
This really helped

15:15.805 --> 15:18.505
to restore the upward slope term structure

15:18.525 --> 15:19.705
of credit express,

15:20.115 --> 15:22.385
especially at the short end of the credit curve.

15:23.085 --> 15:27.065
On the other hand, the April nine announcement in contrast

15:27.595 --> 15:31.105
right, it led to a uniform downshift

15:31.445 --> 15:34.185
and steepening of the entire term structure

15:34.365 --> 15:35.425
of credit express.

15:36.085 --> 15:39.505
So this ultimately restored the credit curve

15:39.765 --> 15:42.345
to its pre pandemic label and shape.

15:42.365 --> 15:44.865
In the baseline analysis, we focus on the label effects,

15:45.325 --> 15:48.265
and then in our extended analysis,

15:48.325 --> 15:50.105
we further look at the slope effects,

15:50.405 --> 15:53.105
and then we find both announcements, help

15:53.325 --> 15:55.145
to steepen the credit curve.

15:55.765 --> 15:59.785
And then not only that, we also look at the,

15:59.925 --> 16:04.385
we also quantify the price impact of the Fed reserves actual

16:04.985 --> 16:07.745
purchases, meaning that when the Fed started

16:07.845 --> 16:12.065
to implement this S-M-C-C-F in mid June, 2020.

16:12.605 --> 16:14.945
And we want to know, right,

16:15.165 --> 16:17.385
did this actual purchases have an

16:17.445 --> 16:19.145
effect on the corporate bond market?

16:19.765 --> 16:21.585
And, we find evidence

16:21.585 --> 16:25.385
that the actual bond purchases in the sector market

16:25.985 --> 16:27.785
actually had a differential effect

16:27.925 --> 16:32.065
of about three basic points on the purchase bonds relative

16:32.065 --> 16:34.545
to layer in eligible counterparts.

16:35.165 --> 16:37.625
So these three basic points may seem to be small,

16:37.965 --> 16:42.945
but actually if we take into account the modest scale

16:43.605 --> 16:44.985
of these purchases, right,

16:44.985 --> 16:46.465
just a few hundred billion dollars.

16:47.125 --> 16:51.025
So compared to the qe, purchases amount.

16:51.685 --> 16:55.145
So you know, this three basic points, differential effect

16:55.765 --> 16:57.465
is still accessible effect.

16:57.965 --> 17:02.185
So this further confirm our main result of the overall

17:02.785 --> 17:03.785
efficacy of the program.

17:04.805 --> 17:08.045
So besides what I mentioned,

17:08.555 --> 17:12.205
this empiric analysis on the, announcements

17:12.665 --> 17:16.165
and the purchase effects, we also develop

17:16.765 --> 17:21.445
a theoretical preferred type type framework based on anos

17:21.445 --> 17:23.085
and VLA 2021 page.

17:23.085 --> 17:25.645
The purpose of this, theoretical exercise is

17:25.645 --> 17:29.525
that we want to shed light on the mechanism of the SMC safe.

17:30.185 --> 17:34.485
So what we did is that, we first stands layer model,

17:35.305 --> 17:37.165
in original model.

17:37.785 --> 17:40.165
The model is about the treasury bond market.

17:40.865 --> 17:41.885
We extend their model

17:41.905 --> 17:44.125
to include not only the treasury bond market,

17:44.345 --> 17:48.785
but also includes, copay bond market and end.

17:49.795 --> 17:53.175
We calibrate of extended's preferred habitat model,

17:53.555 --> 17:56.935
and then using the pre the ca the calibrated model,

17:57.635 --> 17:59.335
we explain the role

17:59.675 --> 18:03.375
of two factors in driving the inversion of the credit curve.

18:03.755 --> 18:07.735
So the first factor is this, dash for cash, right?

18:08.155 --> 18:11.615
In other words, we observed this surge in the demand

18:11.675 --> 18:13.455
for cash in mid-March.

18:14.155 --> 18:16.615
And then this, so-called dash for cash

18:17.155 --> 18:21.295
had a disproportionately large effect on the short end

18:21.355 --> 18:22.695
of the credit curve, right?

18:22.845 --> 18:27.455
Because investors, they wanted to sell, they want

18:27.455 --> 18:29.775
to liquidate the more liquid short term

18:29.925 --> 18:31.055
corporate bonds first.

18:32.975 --> 18:36.235
So, and the second factor is that the,

18:36.235 --> 18:40.515
broker dealers became increasingly unwilling

18:40.575 --> 18:42.555
to take on inventory when they face

18:42.905 --> 18:46.675
with this substantial sell off across fixed income markets.

18:46.895 --> 18:50.195
We are able to capture both factors in our model.

18:50.975 --> 18:54.725
And then, so from the lens of our model,

18:55.185 --> 18:57.365
we shed the light on the mechanism of the program.

18:58.025 --> 19:01.765
So specifically we show that the fast announcements

19:01.905 --> 19:06.765
of the SMC safe really helps calm the market

19:07.345 --> 19:09.725
by reducing the upcharge reservers.

19:10.625 --> 19:14.925
So as a result, when the upcharge verion is reduced,

19:15.535 --> 19:18.805
right, they are more waiting to take a large positions

19:19.145 --> 19:23.245
and then they can really help dampen the transmission

19:23.465 --> 19:26.325
of a negative demand shock arising from

19:26.355 --> 19:27.925
this dash for cash.

19:28.235 --> 19:29.685
This, big sell off.

19:30.225 --> 19:33.805
So as a result, the credit curve is restored

19:34.265 --> 19:36.565
to its pre pandemic shape and arrival.

19:36.865 --> 19:40.565
In this paper, we found that the announcements on March 23,

19:40.935 --> 19:42.765
April 9th, 2020,

19:43.355 --> 19:47.845
they both had a big impact on reducing investment grade

19:47.845 --> 19:50.725
credit spread across all maturities.

19:51.265 --> 19:52.565
And specifically, we show

19:52.565 --> 19:55.645
that this announcements gradually lowered

19:55.825 --> 19:57.765
and steepened the credit curve.

19:58.605 --> 20:00.705
And then eventually the

20:01.305 --> 20:05.065
announcements helped bring back this upper slope

20:05.065 --> 20:07.745
infrastructure of credit price,

20:07.965 --> 20:10.225
in the investment grade markets, just like

20:10.335 --> 20:12.185
what it was before the pandemic.

20:13.245 --> 20:17.585
So all total of results imply that the primary effects

20:17.925 --> 20:22.025
of the fast announcements was to restore investor confidence

20:22.245 --> 20:24.345
and improve market sentiments.

20:24.695 --> 20:28.665
This process, it makes it substantially easier

20:28.845 --> 20:31.385
for companies to borrow in the corporate bonds market

20:31.565 --> 20:33.305
and also in other markets as well.

20:34.005 --> 20:38.065
So, for your question about the potential,

20:38.705 --> 20:42.305
interesting areas of feature research, we think it would be

20:42.825 --> 20:45.305
interesting to have a deeper understanding

20:45.445 --> 20:46.825
of the transmission mechanism

20:47.065 --> 20:48.285
Of the S-M-C-C-A

20:48.745 --> 20:51.605
or even transmission mechanism of the monetary policy.

20:51.785 --> 20:54.045
In general. I think this is,

20:54.045 --> 20:57.725
this has been a very promising, research direction

20:58.105 --> 21:01.005
and we have already seen some more recent papers in

21:01.005 --> 21:01.485
that area.

Impact of COVID-19 on US Corporate Bond Markets

00:00:00 - Our study is about, what happens, to the US corporate bond markets during the pandemic, especially in early 2000, 20. So as we can somehow recall, when COVID-19 hit in early 2020, it puts a lot of strain on the US corporate bond market. So we observed this sudden debt for cash, that led to a big sell off, not just in bonds, but also across different markets.

00:00:38 - and the panic spread through the markets. In March, 2020, COVID bonds prices dropped and the crisis price widened fast. So, and then we actually observed a very interesting phenomenon during March, 2020. you know, normally the relationship between credit price and the bond maturity implies an upward slope credit curve,

00:01:09 - are typically larger. But what happens in early to meet March, 2020 is that the credit curve actually got inverted. Meaning that the longer term credit spread are actually, will actually lower smaller than the short term spread. And then the gap between this long and the short term spread once sharply negative. So this inversion was most

Federal Reserve's Response to Pandemic-Induced Market Turmoil

00:01:42 - where this panicked investors rushed to sell off their most liquid assets, particularly this short term, high quality investment grade bonds. And then the Fed reserve quickly stepped in when the financial market started to get rocky, and they rolled off a bunch of measures to cushion the economic blow from the pandemic. While the actions helped avoid a bigger market crash,

00:02:14 - with liquidity issues and the credit express kept widening. So to tackle these growing problems, the Fed made a major move on March 23rd, 2020, launching two big programs. One is what you mentioned, the primary market corporate credit facility, long S-P-M-C-C-F, and the second one is the secondary market corporate credit facility loan, S-A-M-C-C-F.

00:02:44 - So this is the first time that the Fed, the Federal Reserve directly supported corporate credit markets by signaling a willingness to purchase outstanding corporate debt and then potentially take a material amount of credit risk on its balance sheet. What are these programs, right? And then what was the stated objective of the SMC safe? So here, both programs were this,

Federal Reserve's Corporate Debt Stabilization Programs

00:03:19 - right in response to this, financial turmoil caused by the COVID-19 pandemic in 2020 through these programs, the Fed was committed to buying a substantial amount of corporate debt in both the primary and the sector markets. So by design, these programs aim to stabilize the corporate bond market and ensure businesses, businesses could continue

00:03:51 - So if we want to talk about separately, so the P-M-C-C-F was created to provide credits directly to large corporations by purchasing new bonds or loans issued by eligible companies. And then in contrast, the A-C-M-C-C-F was set up to buy existing corporate bonds that were already issued on the sector market, right?

00:04:21 - Exchange traded funds that held corporate bonds. So let me talk a little bit more about SMC safe, which is the subject started in our paper. So this program was initially announced on March 23rd, 2020, and then the eligible bonds were required to have been issued by US investment grade companies.

Eligibility Criteria and Market Reactions in Corporate Bond Programs

00:04:52 - to have a remaining maturity of five years or less, right? So there is this eligibility criteria. And then on April nine, this program, SMC safe was extended to include certain foreign angels. This basically means that the companies which were used to have the investment grade ratings, but somehow downgraded. after March 22, there are several papers

00:05:26 - So, harder at all 2021 paper, they document these, copay bonds traded at a discount compared to layer corresponding credit default swap contracts during this, market turmoil in early to mid March, 2020. This gap is evidenced for the so-called dash for cash phenomenon, meaning that investors, they need to cash out.

00:06:00 - and then some other papers like papers by O'Hara. And so 2021 and the car guard at all 2021 papers in these papers, the also documents the UN willingness of broker dealers to absorb the signing pressure at the height of the crisis. So these papers tell us about what happened, you know, what was the,

Analyzing Related Research on SMC Safe Effects

00:06:28 - And our paper is most closely related to the following papers. let's study the effects of the SMC safe. So there's a paper by, KO at all 2020 in their paper. the author document a significant positive effect of the announcements on both March 23 and April nine on the corporate bond ETFs

00:07:00 - In their paper, the authors analyze the reaction of the corporate bond credit price to the fast announcements on both states. And the layer main findings stress the heterogeneous response of credit price across credit ratings. And then in another paper by Chenko and her co-authors in 2022 GFE paper, the authors document, significant

00:07:33 - after the program announcements, and they attribute the improvement to the increased willingness of dealers to underwrite issuances and inter and intermediates in sector markets. So these are the re related papers. So our paper, differ from these papers along the following dimensions. So compared to these papers, our paper controls

Analyzing SMC Safe's Impact on the Corporate Credit Curve

00:08:02 - of the credit curve. And we also point out the broader mechanism through which the SMC safe announcements affected the corporate bond market. Specifically, our empirical analysis takes into account the announcements in induced rotations of the credit curve, which is absent in the affirmations papers. And furthermore, we use a preferred habitat theoretical

00:08:35 - how such program affects market prices at the announcement date, and also how, you know, what are the effects of the actual purchases. This theoretical exercise highlights the importance of this broad-based reduction in risk aversion as the main channel through which the SMC safe influenced the corporate credit curve. The trace dataset is the, one of the,

00:09:06 - so this trace dataset is a database, containing information about individual corporate bonds transactions in the sector market. So from this, from this database, we obtain information such as the bonds, identity like qip, and we also observe the purchase dates and also time. And we also observe the transaction price and the quantity.

Methodology for Analyzing Bond Transactions

00:09:37 - that whether it is a dealer to dealer transactions or dealer to customer transactions. And we use this database and we actually, we are able to identify almost all the first actual purchases of individual bonds when the Fed implemented the SMC safe starting in June. So we are able to match almost all the, you know, we can identify almost all the feds bond purchases.

00:10:10 - and we use these triggers, we use this dataset, to construct this, matched sample. So that's one novelty of our study because, for each issuer, we can actually find a matched sample of eligible and ineligible bonds. As I mentioned earlier, right? There is, eligibility criter that requires the maturity of, eligible bonds

00:10:42 - Therefore, each issuer we have identify eligible bonds that have maturity, less than or equal to five years, and also ineligible bonds that have maturity greater than five years. And then for each issuer, we try to find a pair of such eligible and ineligible bonds. And at the same time, we try to, you know, make the maturities of this pair of bonds to be as close as possible. So that's what we call the matched sample.

Methodological Framework for Evaluating Program Efficacy

00:11:16 - in identifying, and assessing the efficacy of the program because in this way, right, we can, control for the credit risk of the issuer because these bonds are issued by the same issuer, right? So that's one advantage, for having this matched sample. So, methodology wise, we use this, difference in differences.

00:11:48 - assess the efficacy of the program. So specifically, our regressions right include this issue of face effects, and we also include controls for other bonds characteristics. And then most importantly, to implement this, DID regressions, we include this, interaction term between a date dummy and the bond eligibility dummy.

00:12:19 - after the announcement states, and then this bond eligibility dummy will be one if this bond is actually eligible, meaning that this bond has remaining maturity less than or equal to five years. So the coefficient of this interaction term, would actually, measure, the differential response of credit, price of eligible

Efficacy Analysis of the Corporate Credit Program

00:12:50 - of the program, right? So in this way, we can somehow, we can judge and, measure the efficacy of the program. so this is the empirical analysis and part of our paper. We also have some theoretical model, based on the, preferred heide framework. The main purpose of that exercise is to capture and calibrate the D for cash, which

00:13:22 - Devices don't want, to hold bonds. They want to sell their holdings to get cash. So that's one factor. And the theoretical model captures another factor, which is the sharp increase in the abstracters risk version. And then we demonstrate that both factors are needed in order to account for the observed shifts or inversion of the credit curve. Although baseline results indicate that the,

00:13:53 - and April nine, not only significantly lowered the average level of credit price for mass grade bonds, they also led to a persistence and economically significant narrowing of credit scores on eligible bonds quantitatively. We show that across these two announcements, within our 10 day event. Window of estimate suggests that, layer will a total decline of about 90 basis points in credit price

Impact of Fed Announcements on Credit Curve Dynamics

00:14:27 - to layer in eligible counterparts. So that shows significant effect of the program. And then, so this, in this baseline analysis, we only look at the effect of the program or the level of the credit price, and then we extend this baseline analysis by considering, the, so-called slope effects. We want to, to measure how the two announcements affected the slope of the term structure of credit price.

00:15:01 - Our results suggests that, this March 23 announcements had a significantly stronger slope effect on the eligible segments of the credit curve and end. This really helped to restore the upward slope term structure of credit express, especially at the short end of the credit curve. On the other hand, the April nine announcement in contrast right, it led to a uniform downshift

00:15:34 - of credit express. So this ultimately restored the credit curve to its pre pandemic label and shape. In the baseline analysis, we focus on the label effects, and then in our extended analysis, we further look at the slope effects, and then we find both announcements, help to steepen the credit curve. And then not only that, we also look at the, we also quantify the price impact of the Fed reserves actual

Impact of SMC-CF Purchases on Corporate Bond Market

00:16:07 - to implement this S-M-C-C-F in mid June, 2020. And we want to know, right, did this actual purchases have an effect on the corporate bond market? And, we find evidence that the actual bond purchases in the sector market actually had a differential effect of about three basic points on the purchase bonds relative to layer in eligible counterparts.

00:16:37 - but actually if we take into account the modest scale of these purchases, right, just a few hundred billion dollars. So compared to the qe, purchases amount. So you know, this three basic points, differential effect is still accessible effect. So this further confirm our main result of the overall efficacy of the program. So besides what I mentioned,

00:17:12 - and the purchase effects, we also develop a theoretical preferred type type framework based on anos and VLA 2021 page. The purpose of this, theoretical exercise is that we want to shed light on the mechanism of the SMC safe. So what we did is that, we first stands layer model, in original model. The model is about the treasury bond market.

Analyzing Credit Curve Inversion Factors

00:17:41 - to include not only the treasury bond market, but also includes, copay bond market and end. We calibrate of extended's preferred habitat model, and then using the pre the ca the calibrated model, we explain the role of two factors in driving the inversion of the credit curve. So the first factor is this, dash for cash, right? In other words, we observed this surge in the demand

00:18:14 - And then this, so-called dash for cash had a disproportionately large effect on the short end of the credit curve, right? Because investors, they wanted to sell, they want to liquidate the more liquid short term corporate bonds first. So, and the second factor is that the, broker dealers became increasingly unwilling to take on inventory when they face

00:18:46 - We are able to capture both factors in our model. And then, so from the lens of our model, we shed the light on the mechanism of the program. So specifically we show that the fast announcements of the SMC safe really helps calm the market by reducing the upcharge reservers. So as a result, when the upcharge verion is reduced,

Restoring the Credit Curve: Impact of Key Announcements during Pandemic

00:19:19 - and then they can really help dampen the transmission of a negative demand shock arising from this dash for cash. This, big sell off. So as a result, the credit curve is restored to its pre pandemic shape and arrival. In this paper, we found that the announcements on March 23, April 9th, 2020, they both had a big impact on reducing investment grade

00:19:51 - And specifically, we show that this announcements gradually lowered and steepened the credit curve. And then eventually the announcements helped bring back this upper slope infrastructure of credit price, in the investment grade markets, just like what it was before the pandemic. So all total of results imply that the primary effects

00:20:22 - and improve market sentiments. This process, it makes it substantially easier for companies to borrow in the corporate bonds market and also in other markets as well. So, for your question about the potential, interesting areas of feature research, we think it would be interesting to have a deeper understanding of the transmission mechanism Of the S-M-C-C-A

Promising Research Directions in Corporate Bond Markets

00:21:01 - In general. I think this is, this has been a very promising, research direction and we have already seen some more recent papers in that area.

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