Interest rate risk management for banks under Basel II, presentation by Christine Brown, Department of Finance , The University of Melbourne, Shanghai, December 8-12, 2008
This presentation provides complete study ofcredit risk management,how it was performed in yester years ,how it is taken care nowadays and what is the road ahead in future
Interest rate risk management for banks under Basel II, presentation by Christine Brown, Department of Finance , The University of Melbourne, Shanghai, December 8-12, 2008
This presentation provides complete study ofcredit risk management,how it was performed in yester years ,how it is taken care nowadays and what is the road ahead in future
Credit risks are calculated based on the borrowers’ overall ability to repay. Our objective was to use optimization in order to create a tool that approves or rejects loans to borrowers. We also used optimization to establish how much interest rate/credit will be extended to borrowers who were approved for a loan.
Credit risk refers to the risk that a borrower will default on any type of debt by failing to make payments which it is obligated to do. The risk is primarily that of the lender and includes lost principal and interest, disruption to cash flows, and increased collection costs. The loss may be complete or partial and can arise in a number of circumstances. For example:
• A consumer may fail to make a payment due on a mortgage loan, credit card, line of credit, or other loan
• A company is unable to repay amounts secured by a fixed or floating charge over the assets of the company
• A business or consumer does not pay a trade invoice when due
• A business does not pay an employee's earned wages when due
• A business or government bond issuer does not make a payment on a coupon or principal payment when due
• An insolvent insurance company does not pay a policy obligation
• An insolvent bank won't return funds to a depositor
• A government grants bankruptcy protection to an insolvent consumer or business.
To reduce the lender's credit risk, the lender may perform a credit check on the prospective borrower, may require the borrower to take out appropriate insurance, such as mortgage insurance or seek security or guarantees of third parties, besides other possible strategies. In general, the higher the risk, the higher will be the interest rate that the debtor will be asked to pay on the debt.
This presentations chalks out in detail information about ALM in Indian Bank. It starts with the basics of Balance sheet; applicability of ALM in real life; Evolution and then starts with main topics of ALM like structured statement; Liquidity risk, its management; currency risk and finally ends with Interest Risk management.
Links to Video’s in the ppt
Balance Sheet
http://www.investopedia.com/terms/b/balancesheet.asp
NII/NIM
http://www.investopedia.com/terms/n/netinterestmargin.asp
www.abhijeetdeshmukh.com
Counterparty Credit Risk and CVA under Basel IIIHäner Consulting
Financial institutions which apply for an IMM waiver under Basel III need to fullfill a broad set of requirements. We present the quantitative, organizational and operational implications and provide some hand-on guidance how to fulfill the regulatory requirements.
Credit risks are calculated based on the borrowers’ overall ability to repay. Our objective was to use optimization in order to create a tool that approves or rejects loans to borrowers. We also used optimization to establish how much interest rate/credit will be extended to borrowers who were approved for a loan.
Credit risk refers to the risk that a borrower will default on any type of debt by failing to make payments which it is obligated to do. The risk is primarily that of the lender and includes lost principal and interest, disruption to cash flows, and increased collection costs. The loss may be complete or partial and can arise in a number of circumstances. For example:
• A consumer may fail to make a payment due on a mortgage loan, credit card, line of credit, or other loan
• A company is unable to repay amounts secured by a fixed or floating charge over the assets of the company
• A business or consumer does not pay a trade invoice when due
• A business does not pay an employee's earned wages when due
• A business or government bond issuer does not make a payment on a coupon or principal payment when due
• An insolvent insurance company does not pay a policy obligation
• An insolvent bank won't return funds to a depositor
• A government grants bankruptcy protection to an insolvent consumer or business.
To reduce the lender's credit risk, the lender may perform a credit check on the prospective borrower, may require the borrower to take out appropriate insurance, such as mortgage insurance or seek security or guarantees of third parties, besides other possible strategies. In general, the higher the risk, the higher will be the interest rate that the debtor will be asked to pay on the debt.
This presentations chalks out in detail information about ALM in Indian Bank. It starts with the basics of Balance sheet; applicability of ALM in real life; Evolution and then starts with main topics of ALM like structured statement; Liquidity risk, its management; currency risk and finally ends with Interest Risk management.
Links to Video’s in the ppt
Balance Sheet
http://www.investopedia.com/terms/b/balancesheet.asp
NII/NIM
http://www.investopedia.com/terms/n/netinterestmargin.asp
www.abhijeetdeshmukh.com
Counterparty Credit Risk and CVA under Basel IIIHäner Consulting
Financial institutions which apply for an IMM waiver under Basel III need to fullfill a broad set of requirements. We present the quantitative, organizational and operational implications and provide some hand-on guidance how to fulfill the regulatory requirements.
Credit risk management for industrial corporatesMarco Berizzi
Presentation of a credit risk management model to be used for industrial corporates exploiting Nobel prize Merton theoretical credit risk approach and Basel Committee framework for financial institutions.
The above model calculates credit lines, capital absorption, expected loss and un-expected loss for each industrial corporate customer as functions of average exposition and rating assignation.
More specifically average exposition coincides with customer commercial account receivable stock along a certain elapsed time and rating measures customer merit worthiness / solvability leveraging financial statement indicators, payment delay ratios and country risk variables.
This is a partial preview of the document found here:
https://flevy.com/browse/business-document/financial-derivatives-103
Description:
Along with the basics of various financial derivatives required for risk management, it also covers various hedging strategies, comparisons, option valuation and brief on forward rate agreements.
International journal of engineering and mathematical modelling vol1 no1_2015_2IJEMM
Default risk has always been a matter of importance for financial managers and scholars. In this paper we apply an intensity-based approach for default estimation with a software simulation of the Cox-Ingersoll-Ross model. We analyze the possibilities and effects of a non-linear dependence between economic and financial state variables and the default density, as specified by the theoretical model. Then we perform a test for verifying how simulation techniques can improve the analysis of such complex relations when closed-form solutions are either not available or hard to come by.
In this paper, we construct a Credit Default Swap pricing model for default recovery rates under
distributional uncertainty based on a structured pricing model and distributional uncertainty theory. The model
is algorithmically transformed into a solvable semi-definite programming problem using the Lagrangian dual
method, and the solution of the model is given using the projection interior point method. Finally, an empirical
analysis is conducted, and the results show that the model constructed in this paper is reasonable and efficient
It is not difficult to find situations of marked change in variables and with unpredictable event risk implies estimation problems. E.g.,
Credit spreads in 2008 rise to levels that could never have been forecast based upon previous history. The subprime crisis of 2007/8: credit spreads & volatility rise to unseen levels & shift in debtor behavior (delinquency patterns)
E.g., estimating the volatility from data in a calm (turbulent) period implies under (over) estimation of future realized volatility
Due to the limited size of the insurance market, insurance companies usually purchase insurance
from a few reinsurance companies with large differences. At this time, using the Vasicek model to describe the
counterparty credit risk will be inaccurate; besides, the insurance company’s understanding of the counterparty
default threshold distribution is incomplete, which makes it difficult to effectively determine the counterparty
default probability.
IFRS 9 Implementation : Using the Z-score approach as a KRI to identify adverse credit deterioration for Stage Transition from 1 to stages 2/3 in IFRS 9 Modeling
Using Cross Asset Information To Improve Portfolio Risk Estimationyamanote
There are obvious relationships between the various securities of a given firm that impact our expectations of risk. For example, if fixed income investors expect a corporate bond of a company to default, there must be a related bankruptcy event that would negatively impact shareholders in that firm. In this presentation, Nick will describe how to use data from bond and option markets to improve risk estimation for equity portfolios, and how to use information from the equity markets to improve estimation of credit risk in fixed income securities. The goal of the process is to create holistic risk estimation where all expectations of risk are mutually consistent across the entire capital structure of a firm, and related derivatives.
Using a Survival Model for Credit Risk Scoring and Loan Pricing Instead of XG...CFO Pro+Analytics
In the consumer lending space, fintech companies have innovated many aspects of the consumer experience. One of the biggest innovations has been the real-time approval of consumers for installment loans with borrowed cash hitting consumer bank accounts in an expedited and highly satisfying way.
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Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
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US Economic Outlook - Being Decided - M Capital Group August 2021.pdfpchutichetpong
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
“In order for the U.S. economy to continue growing, whether there is another wave or not, the U.S. needs to focus on diversifying supply chains, supporting business investment, and maintaining consumer spending,” says Grace Feeley, a research analyst at M Capital Group.
While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
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Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
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3. Three main approaches to modeling credit risk
in the finance literature
•
•
•
Structural approach: Assumptions are made about the dynamics
of a firm’s assets, its capital structure, and its debt and share
holders. A firm defaults if the assets are insufficient according to
some measure. A liability is characterized as an option on the firm’s
assets.
Reduced form approach: No assumptions are made concerning
why a default occurs. Rather, the dynamics of default are
exogenously given by the default rate (or intensity). Prices of credit
sensitive securities can be calculated as if they were default free
using the risk free rate adjusted by the level of intensity.
Incomplete information approach: Combines the structural and
reduced form approaches.
5. 1. We want to use the structural approach to
incorporate bond default risk in bond valuation
The value of the firm’s assets are assumed to follow the process,
where μ is the instantaneous expected rate of return on assets, and
σ is the standard deviation of the return on assets.
Let D(t,T) be the date t market value of debt with promised payment B
at date t.
The second line in (18.2) says that the payoff to the creditors equals
the promised payment (B) minus the payoff on a European put
option written on the firm’s assets with exercise price B.
6. Market value of firm debt, D(t)
Let P(t,T) represent the current date t price of a default-free, zerocoupon bond that pays $1 at date T, where the bond conforms with
the Vasicek model in Ch. 9.
Pennacchi asserts that using results for pricing options (Ch. 9.3)
when interest rates are random (as in 9.58), we can write
7. Market value of firm equity, E(t)
Shareholder equity is similar to a call option on the firm’s assets, since
at maturity the payoff to equity holders is max [A(t) – B, 0].
However, shareholder equity is different from a European option if the
firm pay dividends to shareholders prior to maturity as reflected in
the first term of the last line in (18.4) where δ denotes the dividend
rate.
8. Critique of the Merton model
The Merton model assumption is that the firm has a single issue of zero-coupon
debt. That is unrealistic. Modeling multiple issues with different maturities
and seniorities complicates default.
In response some models have suggested that default occurs when the firm’s
assets hit a lower boundary. That boundary has a monotonic relation to the
firm’s total outstanding debt. The first passage time is when the value of the
firm’s assets crosses through the lower boundary.
First passage model - - bond indenture provisions often include safety
covenants that give bond holders the right to reorganize the firm if the value
falls below a given barrier.
The first passage model defines the survival probability as p(t,T) that the
distance to default does not reach zero at any date τ between t and T. The
distance to default is often measured in terms of standard deviations.
10. 2. We want to use the reduced form approach to
incorporate bond default risk in bond valuation
The reduced form model was developed to overcome the
nontradeability and nonobservability of the firm’s asset value
process (Jarrow &Turnbull, 1992).
Default is not tied to the dynamics of asset prices and this breaks the
link between the firm’s balance sheet and the likelihood of default.
Rather, default is based on an exogenous Poisson process, so it may
be better able to capture the effects of default due to additional
unobserved factors.
Reduced form models can also be used to value defaultable bonds
using the techniques used for default-free bonds.
In the reduced form framework, we assume that the default event
depends on a “reduced form process,” that may depend on the
firm’s assets and capital structure, but also on other macroeconomic
factors that influence default.
11. The default event for a firm’s bond is modeled as a Poisson process
with a time-varying “default intensity.”
Conditional on no default occurring up to date t, the instantaneous
probability of default at (t, t+dt) is denoted as λ(t) dt, where λ(t) is the
physical default intensity, or “hazard rate,” where it is assumed that
λ(t) ≥ 0. Since λ(t) is time-varying, it may be linked to changes in
underlying state variables.
We can compute the physical probability that a bond will not default
from date t to date τ where t ≤ τ ≤ T. This physical survival
probability is written
12. Zero recovery bond
(bond holders receive nothing in the event of a default)
With zero recovery the bondholder payoff at date T is either D(T,T) = B
if no default occurs, or D(T,T) = 0 if default occurred during (t,T).
If we apply risk-neutral pricing, the date t value of a zero-recovery bond
can be written
where r is the instantaneous “default-free” interest rate, which gives
us the risk-neutral default intensity rather than the physical default
intensity in (18.5).
The risk-neutral default intensity accounts for the market price of risk
due to the Poisson arrival of the default event.
13. Value of the zero-recovery defaultable bond
Using the calculated survival probability in (18.5) we get
So, (18.9) indicates that valuing a zero-recovery defaultable bond is
similar to valuing a default-free bond, except that we use the
discount rate, r(u) + λ(t), rather than just r(u).
20. Default depends on both Brownian motion vector (dz) for
the state variables and the Poisson process (dq) for arrival
of default) - - the default process is “doubly stochastic”
21. 3. We want to extend the structural and reduced
form models for bonds to the case of bank loans
The link between loans and optionality can be illustrated by a payoff
function to a bank lender. Here repayment of the loan requires
amount 0B. But the market value of project assets can be AL or AH.
At AL the borrow would have an incentive to default on the loan
contract by forfeiting the assets to the bank. Above 0B the bank
earns a fixed return on the loan.
This is analogous to the payoff to a put option writer on a stock with
exercise price B.
22. Structural model (KMV)
The value of a put option on a stock can be written as,
F(S, X, r, σ, T)
The value of a default option on a loan can be written as,
G(A, B, r, σA, T)
where A is the value of the firm’s assets and B is the repayment at
maturity. We note that the values for A and σA are not directly
observable.
The KMV Credit Monitor Model turns the bank’s lending problem
around and considers it from the perspective of the borrower.
To solve for the two unknowns, A and σA , the model uses
•
•
the structural relationship between market value of equity and
market value of assets, and
the relationship between volatility of assets and volatility of equity.
23. Loan repayment from the perspective of the
borrower (equity holder)
The payoff function of the equity holder is a call option on the assets of
the firm, H(A, σA, r, B, T).
KMV solves the unobservables problem by assuming that σE = g(σA)
where σE is the observable volatility of firm equity and with two
equations in two unknowns, we can solve for A and σA . Once these
values are derived, KMV calculates the expected default frequency
(EDF).
24. Calculating the theoretical EDF
If A = 100, σA = 10, and B = 80, the distance to default = (A-B)/σA =
2 standard deviations. The value of assets would have to decline by
2 standard deviations in order to enter default.
25. Based on a sufficiently large sample of firms, we
can map the distance to default into EDF
26. Critique of the KMV model
It is difficult to construct the theoretical EDF curves without the
assumption of normality of asset returns
Private firm EDFs can only be constructed by using accounting data
and other observable characteristics of the borrower
The KMV approach does not distinguish between different types of
debt (bonds that vary by seniority, collateral, covenants,
convertibility, etc.)
The KMV model is static - - once the debt is in place the firm does not
change it. The default behavior of firms that manage their leverage
positions is not captured.
27. Reduced-form model (CreditRisk+)
The Credit Risk+ model is based on an insurance approach where
default is an event that resembles other insurable events (casualty
losses, death, injury, etc.). These are generally referred to as
mortality models which involve actuarial estimate of the events
occurring.
• Default is modeled as a continuous variable with an underlying
probability distribution.
• Default uncertainty is one type of uncertainty, there is also
uncertainty surrounding the size or severity of the loss.
• Loss severities are distributed into “bands,” and the number of
bands is adjusted to get greater accuracy in the estimation.
• The frequency of losses and the severity of losses produce a
distribution of losses for each band. Summing across these bands
we construct the loss distribution for a portfolio of loans.
28. Constructing the loss distribution in the
CreditRisk+ model
Using the formula for the Poisson distribution
31. The loss distribution for a single loan portfolio
(severity rate = $20,000 per $100,000 of loan)
32. Critique of the CreditRisk+ model
The observed distribution of losses may have a larger variance than
the model shows. This would tend to underestimate the true
economic capital requirement.
• This may be due to an assumption that the mean default rate is
constant within each band. So, increase the number of bands for
more accuracy.
• Default rates across bands may be correlated due to underlying
state variables that have broader impact on borrowers.
• The predictive usefulness of the approach depends on the size of
the sample of loans.
• The model is not a “full VaR model” because it concentrates on loss
rates, not on loan value changes. It is a default model, not a markto-market model.