12.1 cds indices
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This document discusses credit default swap (CDS) indices, which are used as proxies to represent the systematic credit quality of segments in the credit markets. It describes the two main families of CDS indices - the CDX family covering North America and emerging markets, and the iTraxx family covering Europe, Asia, and countries. The indices are composed of liquidly traded single-name CDS contracts from representative debt issuers with common characteristics, and track the average CDS spreads across the component contracts. The two most popular indices are CDX and iTraxx.
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This document provides a summary of key points from Chapter 7 of the textbook "Managing Credit Risk Under The Basel III Framework, 3rd ed". It discusses credit ratings and FICO scores as methods of assessing credit risk. Credit ratings are issued by major agencies and indicate the likelihood of default on a scale. FICO scores similarly assess individuals' credit risk based on payment history, credit utilization, credit history, experience, and inquiries. The document also outlines average default rates associated with different rating levels and scoring bands.
06.2 credit risk controls
This document provides an outline and overview of credit risk controls under the Basel III framework. It discusses controls for both single debts and debt portfolios. For single debts, it describes controls like bilateral netting, principal amortization, collateral, margining, credit guarantees, credit default swaps, downgrade triggers, and call provisions. For debt portfolios, it discusses reducing concentration and dependency through diversification, as well as credit securitization and credit limits. The appendix provides mathematical formulas for concepts like instant LGD, hazard rate, and average LGD.
03.2 homogeneous debt portfolios
This document discusses credit risk modeling for a homogeneous debt portfolio. It covers modeling approaches for independent, finite, and infinite homogeneous portfolios using concepts like the binomial distribution, Gaussian copula, and correlation coefficient (CCC). Key credit risk factors like probability of default, loss given default, exposure at default, and number of borrowers are accounted for in the portfolio modeling. Diversification effects from varying the number of borrowers and their default dependency are also examined.
02.2 credit products
This document provides an overview of various credit products including term loans, credit cards, mortgages, and corporate bonds. For each product, it discusses the purpose from the perspective of borrowers and lenders, key cash flows, risk factors such as exposure at default and loss given default, interest rates, and examples of typical structures. It also covers topics such as accrued interest calculation, seniority of corporate debts, and loss given default assumptions.
01.2 credit risk factors and measures
This document provides an introduction to credit risk factors and measures. It discusses key concepts like exposure at default, loss given default, probability of default, expected loss, and one-year expected loss. It also provides an example of calculating these measures for a simple loan with a principal of $10,000, loss given default of 90%, probability of default of 3%, and residual maturity of 3 years. The expected loss is calculated as $786 and one-year expected loss is $270 for this loan.
05.3 credit quality monitoring
This document contains two examples from a textbook on managing credit risk under the Basel III framework. The first example shows a table with debt exposure data including exposure at default, loss given default, probability of default, expected loss and other risk metrics for 30 exposures. The second example shows a global markets monitoring table with currency exchange rates, market volatility levels and equity index alerts. It also includes a chart showing commodity price and equity index trends over three months in 2008.
03.3 homogeneous debt portfolios
This document provides examples of credit risk modeling techniques using an Excel workbook. It includes examples of calculating expected loss for individual and multiple borrowers, modeling default correlation using copulas, and simulating defaults in a homogeneous loan portfolio. The workbook is intended to demonstrate concepts from the textbook "Managing Credit Risk Under The Basel III Framework" by Dr. Lam Yat-fai.
20.3 regulatory credit exposures
This Excel workbook contains 7 examples demonstrating different approaches to calculating capital requirements for credit risk under the Basel III framework. The examples include the standardized approach, ratings-based approach, internal ratings-based approach for equity exposure, underlying debt portfolio calculations for the supervisory formula approach, and calculations using the supervisory formula approach with the largest EAD, Q largest EADs, and all EADs given. The document was prepared according to the textbook "Managing Credit Risk Under The Basel III Framework" and contains calculations of capital charges, expected loss, and risk-weighted assets.
20.1 regulatory credit exposures
This document discusses different types of regulatory credit exposures under the Basel III framework, including debt exposures, securitization exposures, and specialized lending. It provides details on various types of debt exposures such as loans, bonds, credit lines, and credit derivatives. It defines securitization exposures as financial instruments constructed through credit structuring using underlying debt portfolios or combinations of credit default swaps and high quality assets. The document also briefly outlines capital charge calculation requirements for securitization exposures under Basel III.
19.3 regulatory irb validation
This document contains 3 examples of credit risk analysis techniques from a textbook on managing credit risk under Basel III. It includes binomial tests with formulas to calculate confidence levels and default rates for a portfolio with a BBB credit rating and 10,000 loans. It also shows a chi-square test comparing expected and observed default counts across 10 rating categories.
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招聘代理：本公司诚聘英国加拿大澳洲新西兰美国法国德国新加坡各地代理人员如果你有业余时间有兴趣就请联系我们咨询顾问：+微信:95270640田里逡巡一番抱起一只硕大的西瓜用石刀劈开抑或用拳头砸开每人抱起一大块就啃啃得满嘴满脸猴屁股般的红艳大家一个劲地指着对方吃吃地笑瓜裂得古怪奇形怪状却丝毫不影响瓜味甜丝丝的满嘴生津遍地都是瓜横七竖八的活像掷满了一地的大石块摘走二三只爷爷是断然发现不了的即便发现爷爷也不恼反而教山娃辨认孰熟孰嫩孰甜孰淡名义上是护瓜往往在瓜棚里坐上一刻饱吃一顿后山娃就领着阿黑漫山遍野地跑阿黑是一条黑色的大猎狗挺机灵的是山室
Independent Study - College of Wooster Research (2023-2024)
"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.
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Seminar: Gender Board Diversity through Ownership Networks
12.1 cds indices
- 1. Managing Credit Risk Under The Basel III Framework 175 Copyright 2018 CapitaLogic Limited CDS Indices 12 KEY CONCEPTS • CDX index • iTraxx index • On-the-run series • CDS index contract 12 CDS indices 12.1 CDX and iTraxx indices ★★★★★★★★★★★★ Similar to other financial risks, the credit risk of a debt comprises the systematic risk driven by macro factors common to many debts and specific risk driven by idiosyncratic factors impacting only that particular debt. For internationally active banks, their debt investments are largely diversified due to the huge number of debts issued by many different issuers in the debt portfolio, leaving the systematic risk as the dominating component. Since systematic risk is not observable directly, effort has been made to discover this systematic risk. This drives the development of the CDS indices. Region Credit quality/theme No. of compo -nents Index North America Investment grade 125 CDX.NA.IG Investment grade and high volatility 30 CDX.NA.IG.HVOL High yield grade 100 CDX.NA.HY BB 37 CDX.NA.HY.BB B 46 CDX.NA.HY.B Crossover 35 CDX.NA.XO First lien leveraged loans 100 LCDX Emerging markets 14 CDX.EM Diversified 40 CDX.EM Diversified Table 12.1 CDX indices A CDS index is the arithmetic average of the updated CDS spreads of a group of liquidly traded and standardized single name CDSs (from three to 125 components) that are originated on specific days in March and September to protect the reference debts issued by a number of different and representative debt issuers with certain common characteristics. After the origination, the CDS spreads of this group of single name CDSs are calculated with respect to the revised premium, subject to the assumption that a new zero value single name CDS is originated for the original reference debt, having the same principal, issuer and maturity day but updated LGD, updated PD and reduced protection period. A CDS index serves as a proxy to represent the systematic credit quality of a particular segment in the credit market.
- 2. 176 Managing Credit Risk Under The Basel III Framework Copyright 2018 CapitaLogic Limited Region Theme No. of CDSs Index Europe 125 iTraxx Europe High volatility 30 iTraxx Europe HiVol Crossover 75 iTraxx Europe Crossover First lien loan 40 iTraxx LEVX Non-financial 100 iTraxx Non-financials Senior subordination financial 25 iTraxx Financials Senior Junior subordination financial 25 iTraxx Financials Sub Telecommunications, media and technology 20 iTraxx TMT Industrial 20 iTraxx Industrials Energy industry 20 iTraxx Energy Manufacturers of consumer products 30 iTraxx Consumers Automobile industry 10 iTraxx Autos Asia Ex-Japan investment grade 50 iTraxx Asia Ex-Japan high yield 20 iTraxx Asia HY Japan 50 iTraxx Japan Australia 25 iTraxx Australia Country West Europe 15 iTraxx SOVX West Europe Central/East Europe, Middle East and Africa 15 iTraxx SOVX CEEMEA Asia Pacific 10 iTraxx SOVX Asia Pacific Latin America 8 iTraxx SOVX Latin America Global liquid investment grade iTraxx SOVX IG G7 iTraxx SOVX G7 Brazil, Russia, India, China iTraxx SOVX BRIC Table 12.2 iTraxx indices The major CDS indices are operated and published on a daily basis by Mark-it.31 These CDS indices come in two families: • The CDX family covers the CDS indices for North America and emerging markets; and • The iTraxx family covers the CDS indices for Europe, Asia and countries. In addition to geographical area, CDS indices are also classified by type of debt issuers, credit quality and standard tenor.32 As such, a number of CDS indices are created to serve the needs of a broad range of investors. The two most popular CDS indices are: 31 The CDS indices are published by Mark-it on its website with the URL http://www.markit.com/markit.jsp?jsppage=indices.jsp 32 Standard tenors include one, three, five, seven and ten years.