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Rutter Associates
Rutter Associates

... Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan ORIGINATORS: What is the bank’s perception regarding large corporate and middle market loans? a) Loans generate sufficient profit that they add shareholder value b) Loans do not add shareholder value by them ...
Credit Risk – Introduction
Credit Risk – Introduction

... measures of default probability Moody’s long-term ratings are opinions of the relative credit risk of financial obligations with an original maturity of one year or more. They address the possibility that a financial obligation will not be honored as promised. Such ratings use Moody’s Global Scale a ...
Assessing the risk-return trade-off in loans
Assessing the risk-return trade-off in loans

... loans returns from interest rates and historical loan default rates. Since this information is generally available for banks and supervisors, my model can be readily applied either as a risk management or as an off-site supervisory tool. I consider a general structure in which defaults are driven by ...
Uncertainty, Default and Risk
Uncertainty, Default and Risk

... With uncertainty, the quoted return may differ from the expected return. • The quoted return is also called the stated or promised return. ...
Evaluation Cultures? On Invoking `Culture` in the Analysis of
Evaluation Cultures? On Invoking `Culture` in the Analysis of

... There are two reasons for shifting the focus from science to the financial markets. First, evaluation in financial markets is of enormous importance yet very poorly understood. For example, a crucial role of financial markets is to channel investment capital to some activities and not to others, and ...
Incorporating Strategy Risk of Active Managers into Portfolio Risk and Optimization
Incorporating Strategy Risk of Active Managers into Portfolio Risk and Optimization

... performance is typically expressed by measures such as “tracking error”, which describes the expectation of times-series standard deviation of benchmark relative returns. This is useful for index fund management, where the expectation of the mean for benchmark relative return is fixed at zero. The a ...
The joint distribution of the time to ruin and the number of claims
The joint distribution of the time to ruin and the number of claims

... where u ≥ 0 is the initial surplus, c is the rate of premium income per unit time, and {S(t)}t≥0 is the aggregate claims process. We have S(t) = PM(t) i=1 Xi , where {M(t)}t≥0 is a Poisson process with Poisson parameter λ, Xi denotes the amount of the ith claim, and {Xi }∞ i=1 is a sequence of indep ...
Strategy RIsk and the Central Paradox for Active Management
Strategy RIsk and the Central Paradox for Active Management

... Requires estimating covariance matrix of forecasting errors which will always be undetermined for large numbers of assets If we understood our future errors well enough to reliably forecast their covariance, we would change our strategy and not make the errors ...
an approach to determining the probability of default
an approach to determining the probability of default

... However, in recent decades, analysts have generally opted for the logit and probit multivariate models. In this respect, the first to use these types of technique applied to business prediction was Ohlso (1980). Numerous studies have appeared in the financial literature in which these models are uti ...
Stephen Millard
Stephen Millard

... difference between the deadweight loss and the ‘entrepreneurs share’ distortion; I’d appreciate some intuition as to whether or not this is a separate distortion (I think not) and why it adds to the existing deadweight loss ...
Modeling Credit Risk with Partial Information
Modeling Credit Risk with Partial Information

... simplify the presentation we assume that x = 0 and σ = 1, as well. Under the martingale measure, cash balances have no drift term. Under the empirical measure, however, one would expect that the cash balances should drift at the spot rate of interest. This is consistent with the firm holding its cas ...
Major Currencies And Capitalization
Major Currencies And Capitalization

... The analysis above suggests no systematic excess correlation exists across major currencies and time for the Russell 1000. At best there is a series of anecdotes applicable for individual currencies and over individual market environments; several of these anecdotes are sector specific. The inspirat ...
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Document

... Instead of looking across the different measures of risk we look deeper within one, beta. We dissect beta into its component parts. A stock’s beta can be broken down into correlation with the market portfolio times the stock’s own volatility, divided by overall market volatility. When comparing stoc ...
Portfolio Value-at-Risk Using Regular Vine Copulas
Portfolio Value-at-Risk Using Regular Vine Copulas

... of them are using linear correlation. However, linear correlation can be misleading and it is important to know a dependence structure between the assets of interest. In this case copulas can be a very useful concept, due to the fact that they reveal dependence structure on a quantile scale and ther ...
Contemporary Logistics The Research on Credit Risk of Manufacturing Listed Companies
Contemporary Logistics The Research on Credit Risk of Manufacturing Listed Companies

... In logistic model, the dependent variable is a binary variable, which can take only two values, 0 and 1, stands for a thing happens or not. Independent variable can be continuous variable, discrete variable or dummy variable. When logistic model is applied to research in company’s credit risk, the p ...
Chapter 5 Credit risk - Department of Applied Mathematics and
Chapter 5 Credit risk - Department of Applied Mathematics and

... determine that a loan which has not been repaid for some time period is indeed nonperforming, implying that the loss should be recognized by the bank. For example, if the client is past due 10 days, this may already indicate that he or she has some troubles with repaying the loan, but it may be only ...
ASYMPTOTIC FORMULAS FOR THE IMPLIED VOLATILITY AT
ASYMPTOTIC FORMULAS FOR THE IMPLIED VOLATILITY AT

... the Black-Scholes model. For a general model of call option prices, the implied volatility can be obtained by inverting the Black-Scholes call pricing function with respect to the volatility variable and composing the resulting inverse function with the original call pricing function. ...
Dynamic analysis of bankruptcy and economic waves
Dynamic analysis of bankruptcy and economic waves

... the Russian government postponed decisions of restructuring the industrial sector after the privatisations in earlier 1990. It did not force insolvent firms into bankruptcy, even when it was their largest creditor. The government, particularly at the regional level, often interferes in bankruptcy pr ...
1 Modelling borrowing constraints in Bewley models
1 Modelling borrowing constraints in Bewley models

... act competitively as price takers. The interest rate on savings is risk-free and equal to 1̄, i.e., the saver deposits ̄ units of consumption this period into the bank and next period receives one unit of consumption for sure. Borrowers can subscribe loan contracts through the same banking interm ...
C15.0021 Money, Banking, and Financial Markets
C15.0021 Money, Banking, and Financial Markets

... premium. But NOTICE that the key variables are A, market value of assets, and asset risk  2 Neither of which are directly observable. An Option Model Example is given on page 237. The KMV model uses the OPM to extract the implied market value of assets (A), and the asset volatility of a given firm. ...
- ePrints Soton
- ePrints Soton

... Survival analysis, Cox Proportional Hazards, default risk Introduction In this case study we describe a pricing model that was built for a leading UK mortgage lender. Our model combines survival analysis and Monte Carlo simulation, allowing the company to experiment with different portfolios, pricin ...
DC after the Budget: is your default dangerous?
DC after the Budget: is your default dangerous?

... David Heathcock, DC Product and Distribution Manager at Schroders ...
Confidence Intervals for Value at Risk
Confidence Intervals for Value at Risk

... called VaR or Value at Risk. It is built around statistical topics and probability concepts that have been around for decades. Value at Risk was established and disseminated in the early 1990s by a handful of scientists and mathematicians called “quants.” These were the mathematicians who went to wo ...
Advanced Calculus with Financial Engineering
Advanced Calculus with Financial Engineering

... Simpson’s rules. • Convergence of numerical algorithms – practical considerations. Approximation errors and the order of convergence of a numerical algorithm. • The order of convergence of the midpoint, trapezoidal, and Simpson’s rules. Financial Applications: • Discount factors and discount curve. ...
Credit Market Frictions and the Productivity Slowdown
Credit Market Frictions and the Productivity Slowdown

... Frictionless economy: marginal product of capital = funding rate ρ Equilibrium PD falls, ceteris paribus, if Firm is more productive and has more collateral There is greater competition among banks Bank funding costs are lower ...
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Financial correlation

Financial correlations measure the relationship between the changes of two or more financial variables in time. For example, the prices of equity stocks and fixed interest bonds often move in opposite directions: when investors sell stocks, they often use the proceeds to buy bonds and vice versa. In this case, stocks and bonds are negatively correlated.Financial correlations play a key role in modern finance. Under the capital asset pricing model, CAPM (a model recognised by a Nobel prize), an increase in diversification increases the return/risk ratio. Diversification is synonymous with inverse correlation: the lower the correlation between the constituent holdings, (preferably negative), the lower the risk of holding the combined portfolio. Measures of risk include value at risk VAR, expected shortfall ES, and enterprise risk management ERM.
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