want 2 know.

[seajnaaz]

salam 2 all,
i want 2 know if any1 can answer my question..wht is financial modelling ?is main kiya hota hai kitnay arsay ki hoti hai n etc
etc .if any 1 answer my question i ll be thankful.

[derivativetrader]

Financial Modelling is very naive term. It doesn't quite have a precise meaning. Exmaples of FM includes valuation of stocks etc., or carrying out Asset and Liaibility management modelling.

Hope it suffice.

DT

[maani]

Hi,
Projecting the financial position of a company is termed as financial modelling...Statistical methods and ratio analysis are normally used for financial forecasting...trend analysis can also be used for projecting the figures...trends are usually projected for five to ten years...because the forecasts are estimates only and making estimates for a period which is far away might be useless...excel spreadsheets can also be use for financial modelling...
In modelling a relationship between two or more variables is formed and then by inserting different values of one variable the value of other variable can be found...(this method is termed as trend analysis in statistics)...
The variables in accounting can be receivables, payables, sales, purchases, investments, shares and stock, debentures etc...
You can form a relationship in these variables...that relationship will be the model for projecting the future figures and with the help of the resulted projected figures u can estimate the financial position of the company in future years...


Ace

[seajnaaz]

thanz alot respected maani n derivativetrader.it ll be very helpful.
especially maani sir.ur detailed note is very helpful.

[Desert Sleet]

<BLOCKQUOTE id=quote><font size=1 face="Verdana, Tahoma, Arial" id=quote>quote<hr height=1 noshade id=quote>
Hi,
Projecting the financial position of a company is termed as financial modelling...Statistical methods and ratio analysis are normally used for financial forecasting...trend analysis can also be used for projecting the figures...trends are usually projected for five to ten years...because the forecasts are estimates only and making estimates for a period which is far away might be useless...excel spreadsheets can also be use for financial modelling...
In modelling a relationship between two or more variables is formed and then by inserting different values of one variable the value of other variable can be found...(this method is termed as trend analysis in statistics)...
The variables in accounting can be receivables, payables, sales, purchases, investments, shares and stock, debentures etc...
You can form a relationship in these variables...that relationship will be the model for projecting the future figures and with the help of the resulted projected figures u can estimate the financial position of the company in future years...


Ace
<hr height=1 noshade id=quote></BLOCKQUOTE id=quote></font id=quote><font face="Verdana, Tahoma, Arial" size=2 id=quote>

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If I could... Then I would... Turn back time!!

[Desert Sleet]

In this talk i can give an overview of the statistical approaches to modelling dependence that underlie the most important industry credit risk models, including RiskMetrics, CreditRisk+, KMV and CreditPortfolioView. Assumptions concerning the nature of dependence between defaults and credit downgrades crucially affect the tail of the portfolio loss distribution and thus the determination of a credit risk VaR.
In the existing models two general approaches to modelling dependence may be identified latent variable models and mixture models. In latent variable models default (or downgrade) occurs if a latent variable, usually interpreted as company asset value, falls below a threshold, usually interpreted as liabilities. In the major industry models the latent variables for a portfolio of obligors are invariably taken to be multivariate normal. To understand the nature of dependence in such models, as well as possible deficiencies of the approach, we introduce the important concepts of copulas and tail dependence.
There are certain branches of financial Modeling. some of them are follows.
Modelling Dependent Credit Risks
the theory of exchangeable sequences and martingale convergence to justify the Dirichlet-binomial distribution for modelling the number of defaults in a credit portfolio. The portfolio consists of homogeneous groups characterized by their credit ratings. The random default probabilities for members of the different groups preserve the strict monotonicity according to the credit rating; this induces a hierarchical dependence structure. A special feature of the model is the fact that it can be fitted easily to Standard & Poors's data, for example. Iterated urn schemes and extensions to random credit rating transition matrices are discussed.
Decentralized Risk Management Using Coherent Measures of Risk
We begin with a review of coherent risk measures for regulation of risk. We then consider a more general class of risk measures suitable for managing risk to satisfy a shareholder, and discuss the relationship of these measures to utility theory. We then apply these risk measures to the problem of firm-wide risk management; specifically we introduce a structure for allowing desks in a firm to trade risk limits in an internal market among themselves. Assuming that desks seek to maximize expected return subject to constraints imposed by these risk limits, we show that the internal market for changes in risk limits has an equilibrium which produces optimal firm behavior.
Real Option Valuation in Investment Planning Models
the financial community has used option valuation models for many years to price contingent claims or derivatives of underlying financial assets. Many firms have now also used these general ideas to value real options, investment decisions involving real assets. In this context, the investment may represent the exercise of an option to build or purchase capacity, develop a product, or license intellectual property. After exercising the option, cash flows result as in the financial context, allowing the application of similar valuation techniques.
This talk will describe the valuation of real options and their use for practical investment decisions. The presentation will also highlight advantages of real option approaches over traditional net present value analyses, in particular for investments where delay or adding flexibility may increase value. Discussion will include how optimization models can incorporate real options into an overall strategic investment framework, what differences exist between financial options and real options, and what key factors to include in using real option models in practice.
Scenario Optimisation Asset and Liability Modelling for Endowments with Minimum Guarantees
Endowments with a minimum guaranteed rate of return appear in insurance policies, pension plans and social security plans. In several cases, especially in the insurance industry, such endowments also participate in the business and receive bonuses from the firm's asset portfolio. In this talk we develop a scenario based optimization model for asset and liability management of participating insurance policies with minimum guarantees. The model allows the analysis of the tradeoffs facing an insurance firm in structuring its policies as well as the choices in covering their cost. The model is applied to the analysis of policies offered by Italian insurance firms. While the optimized model results are in general agreement with current industry practices, inefficiencies are still identified and potential improvements are suggested.
The modeling tools developed for the management of insurance policies are also used to develop a web-based system for individual investors. Investor's goals and risk profiles are addressed in an integrated fashion. The requirements for real-time modeling by the average investor must be reflected in the model



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If I could... Then I would... Turn back time!!


Edited by - desert sleet on Jan 26 2005 110150 PM

[maani]

You are welcome seajnaaz...

Ace