This document summarizes a webinar on calculating Value at Risk (VaR). It introduces VaR as a standard measure of quantifying market risk. Simple VaR can be calculated based on an asset's volatility and value. Portfolio VaR incorporates correlations between assets. Several examples demonstrate calculating VaR for single assets, portfolios, and incorporating variances, correlations, and confidence levels. Non-linear assets require different VaR approaches as deltas are not constant.
Using Mean-Variance Optimization in the Real World: Black-Litterman vs. Resam...SSA KPI
油
The document compares two techniques for making mean-variance optimization (MVO) more usable in real-world asset allocation: Black-Litterman and resampling. Both techniques help address limitations of MVO, such as unintuitive portfolios caused by estimation error. The experiment found that while both techniques led to more diversified portfolios than historical inputs alone, Black-Litterman created the most intuitive portfolios for practical use.
1) The document discusses option-based portfolio management strategies that can enhance returns while reducing drawdown risks compared to traditional long-only equity strategies.
2) It analyzes several option-based indices from the CBOE that implement strategies like buy-writes, put-writes, and collars on the S&P 500.
3) Historical analysis shows these option strategies had higher returns, lower volatility, and stronger risk-adjusted returns than the S&P 500 and fixed income over the past 20+ years.
1. Value at Risk (VaR) is a measure of the maximum potential loss of a portfolio over a given period of time and at a given confidence level.
2. VaR was introduced in the 1990s as a tool to measure risk in financial portfolios and determine adequate capital levels. It has since become widely used by financial institutions.
3. VaR estimates the loss of a portfolio that will not be exceeded with a given probability, usually 95%, over a specific time period like one day. For example, a one day, 95% VaR of $1 million means there is a 5% probability of losing more than $1 million on a given day.
VaR is a risk measurement that estimates the maximum potential loss over a given period of time with a certain confidence level. Regulators require banks to calculate VaR using a 10-day horizon and 99% confidence level to determine market risk capital. Expected shortfall is an alternative measure that is considered more risk-sensitive than VaR. Back-testing involves comparing VaR estimates to actual portfolio returns to evaluate the accuracy of VaR calculations.
The document discusses hedge accounting strategies for credit unions, presenting case studies of two credit unions - ABC Credit Union and 123 Credit Union - that were seeking to hedge their portfolios of CDs against interest rate risk using cash flow hedges, and the different solutions for qualifying for hedge accounting based on the historical correlation of their balances to the hedge instrument benchmark rate. Key takeaways include using an advisor to properly plan and execute hedging strategies that qualify for hedge accounting, obtaining auditor approval, and ensuring hedge effectiveness is quantitatively assessed.
Risk management in banking involves four main steps: identifying risks, measuring them both qualitatively and quantitatively, managing the risks, and monitoring and reviewing risks on an ongoing basis. There are three main categories of risk for banks: credit risk, market risk, and operational risk. Basel II aimed to make capital requirements more risk-sensitive by directly linking capital to the risk levels of counterparties and businesses. It introduced three pillars: minimum capital requirements, supervisory review, and market discipline through disclosure.
This document discusses Value at Risk (VaR), a risk measurement technique used in finance. There are three main methods to calculate VaR: the historical method, variance-covariance method, and Monte Carlo simulation. The historical method looks at past losses and assumes history will repeat. The variance-covariance method assumes returns are normally distributed. Monte Carlo simulation models future returns through hypothetical trials. All methods make assumptions that may not reflect reality and have limitations around changing distributions over time. VaR is widely used but also faces criticism for relying on untested models and giving a false sense of confidence.
Liquidity risk refers to the potential inability of an individual, business, or financial institution to meet short-term financial obligations due to insufficient cash or liquid assets. It arises when assets cannot be quickly sold or converted into cash without significant loss in value, potentially leading to operational or financial disruptions.
Page 1 of 9 This material is only for the use of stud.docxkarlhennesey
油
Page 1 of 9
This material is only for the use of students enrolled in FIN 740 for purposes associated with the course and may not be
retained or further disseminated. All information in this material is proprietary to Dr. Sung Ik Kim. Scanning, copying,
posting to a website or reproducing and sharing in any form is strictly prohibited.
Chapter 10. Quantitative Risk Management in R
In this chapter, I explore how we can describe the risk of a single security or a portfolio (a set of assets).
Especially, I introduce the concept of value at risk (VaR) and expected shortfall (ES) here.
1. What is value at risk (VaR)?
Value at risk is one of the most widely used risk measure in finance. VaR was popularized by J.P. Morgan
in the 1990s. The executive at J.P. Morgan wanted their risk managers to generate one statistic that
summarized the risk of the firms entire portfolio at the end of each day. What they came up with was VaR,
which is now widely used by corporate treasurers and fund managers as well as by financial institutions.
VaR is a one-tailed confidence interval. If the 5-day 95% VaR of a portfolio is $1,000, then we expect the
portfolio will lose $1,000 or less in 95% of the scenarios and lose more than $1,000 in 5% of the scenarios
in 5 days. For example, we are interested in making a statement of the following form when using the VaR:
We are 95 percent certain that we will not lose more than $1,000 in 5 days.
It is a function of two parameters: the time horizon (e.g. 5-day in the example above) and the confidence
level (e.g. 95% in the example above). We can define VaR for any confidence level, but 95% has become an
extremely popular choice at many financial firms. The time horizon also needs to be specified for VaR. On
trading desks with liquid portfolios, it is common to measure the one-day 95% VaR.
The following figure provides a graphical representation of VaR at the 95% confidence level. The figure
shows the probability density function for the returns of a portfolio. Because VaR is measured at the 95%
confidence level, 5% of the distribution is to the left of the VaR level, and 95% is to the right.
Page 2 of 9
This material is only for the use of students enrolled in FIN 740 for purposes associated with the course and may not be
retained or further disseminated. All information in this material is proprietary to Dr. Sung Ik Kim. Scanning, copying,
posting to a website or reproducing and sharing in any form is strictly prohibited.
We now formally define VaR. Let L be a random variable, which represents the loss to our portfolio. L is
simply the opposite of the return to our portfolio. For example, if the return of our portfolio is -$1,000, the
loss, L, is +$1,000. For given confidence level 留, VaR is defined as
P(L VaR) = 1
We can also define VaR directly in terms of returns. If we multiply both sides of the inequality above by -1,
and replace .
Discounted Cash Flow Methodology for Banks and Credit UnionsLibby Bierman
油
As institutions prepare for the CECL or current expected credit loss model for the allowance for loan and lease losses (ALLL), institutions are prudently learning the various methodologies available to them. Discounted Cash Flow or DCF is one proposed methodology. This session presents best practices and use cases for the ALLL methodology. See the recording: http://web.sageworks.com/dcf-webinar/
Fixed Income Derived Analytics Powered By BlackRock SolutionsConor Coughlan
油
This is an overview of the new Thomson Reuters Fixed Income Derived Analytics powered by BlackRock Solutions.
For more information visit www.prdcommunity.com
(R)isk Revolution - Current trends and challenges in Credit & Operational RiskMarkus Krebsz
油
This was presented as part of a Senior Australian Bankers' Master Class held at GCU London on 19 Sept 2012. Dr. Robert Webb was co-presenting on the UK & European Banking system.
A comprehensive presentation on the financial risks involved in businesses in general & specifically in banks.
What is Risk?
Generally - Danger, Hazard, Adverse impact, Fear of loss.
Financially-Loss of earnings/capital
May result in incapability of financial institution to meet business goals
Basically there are 4 main risks:
1. Credit Risk
2. Market Risk
3. Liquidity Risk
4. Operational Risk
Risk management is amongst the most overlooked yet very critical aspects of systematic trading. In this webinar, youll get to learn risk management techniques to overcome the most common challenges. This session will explain you the concepts of optimal leverage, hedging and risk indicators.
- Risk Management and the real challenge
- Optimal leverage: Kelly formula, Maximum drawdown
- Market risk: Stop Losses, volatility targeting, value-at-risk
- Hedging techniques
- Risk indicators
Learn more about our EPAT course here: https://www.quantinsti.com/epat/
Most Useful links:
Visit us at: https://www.quantinsti.com/
Like us on Facebook: https://www.facebook.com/quantinsti/
Follow us on LinkedIn: https://www.linkedin.com/company/quantinsti
Follow us on Twitter: https://twitter.com/QuantInsti
Value at Risk (VaR) is a statistical technique used to measure and quantify the level of financial risk within a firm, portfolio, or position over a specific time frame. It aims to quantify, with a single number, the maximum potential loss that could occur over a given time period at a given confidence level. There are different approaches to calculating VaR such as variance-covariance, historical simulation, and Monte Carlo simulation. VaR is widely used by banks and other financial institutions to monitor and control their risk exposure and capital adequacy. However, it does have some weaknesses as the results can vary depending on the underlying assumptions and there are costs associated with maintaining a VaR system.
The Imperatives of Investment Suitabilityfinametrica
油
Presentation given by Paul Resnik (Co-Founder, FinaMetrica) at the National Institute of Securities Markets (NISM) in Mumbai, India. It emphasizes on the importance of measuring risk tolerance of investors in the process of matching investment products to an individual's needs. Visit www.riskprofiling.com to know more.
This document compares two downside risk measures - Value at Risk (VaR) and Expected Shortfall (ES or CVaR) - for portfolio optimization. It defines each measure, discusses how to optimize portfolios to minimize each risk, and lists advantages and disadvantages. The document also presents numerical implementations comparing frontiers, portfolio weights, and out-of-sample performances when optimizing for VaR versus CVaR. It concludes there is no definitive answer on which measure is better, as it depends on factors like data availability and model accuracy.
This document discusses various risks faced by banks, including CAMEL risks relating to capital adequacy, asset quality, management, earnings, and liquidity. It also discusses asset liability management (ALM), which involves planning, organizing, and controlling a bank's assets and liabilities to maintain liquidity and net interest income. Other topics covered include liquidity management, types of liquidity risk, interest rate risk management, and sources of interest rate risk.
The document outlines a roadmap to transform a property and casualty insurer's direct marketing strategy from a mass mailing approach focused on call center volume to a more data-driven and targeted strategy. It details challenges around expertise, data access, and key performance indicators. The proposed strategy focuses on building analytics capabilities, testing creative concepts, and optimizing mailings based on customer value. Key metrics like response rates, revenue, and cost per acquisition are improved. The client is able to grow their direct business significantly while lowering marketing costs over a two year period.
The document discusses Orc Software's risk management tools for trading firms and banks. It describes how Orc Trading for Risk Management gives firms the ability to understand their total risk exposure through features like accurate market views, exposure to risk sensitivities, scenario analysis, and profit and loss projections. The tool is used by leading trading firms and banks to provide real-time risk insights on exchange traded derivatives. It also provides success stories of how heads of trading and risk at different financial institutions have used Orc Trading for Risk Management to improve their risk management and control.
1) The presentation discusses Equitas Micro Finance's model of fair and transparent pricing. It focuses on responsible pricing by having investors bear the cost of growth while keeping steady state costs low for borrowers.
2) Equitas aims for high operating efficiency through best technology and processes, benchmarks delinquency assumptions to national MFI levels, and caps return on equity at 20% to determine fair lending rates.
3) The model provides transparency through clear communication of reducing balance interest rates and publishing administrative fees in borrowers' passbooks.
This document provides a summary of key concepts in corporate finance, including:
1) Sources of corporate funding and capital structure, capital expenditures, and tools used for allocating funds. Key goals are investing and financing.
2) Investing involves forgoing current consumption for future returns. Financing examines return ratios like ROCE, ROE, and ROIC from different perspectives.
3) Tools used in corporate finance include NPV, IRR, payback period, and leverage. Equity valuation methods include free cash flow, NPV, IRR, relative valuation, and payback period. Modern portfolio theory examines efficient diversification of risk.
Risky business: Guide to Risk ManagementMichael Le
油
This document provides an introduction to risk management. It defines risk as the probability of an undesired event multiplied by its consequences. There are various types of risk, including market risk, credit risk, and operational risk. Risk is measured using techniques like value at risk and profit and loss. Credit ratings are important but not always reliable indicators of risk. Effective risk management requires understanding potential risks from diverse sources, quantifying exposures, and implementing systems to monitor and report on risk.
The document discusses the capital charge for credit risk under Basel 2. It outlines the three pillars of Basel 2 - minimum capital requirements, supervisory review, and market discipline. It then describes the standardized approach and internal ratings-based approach to computing capital charge for credit risk. The standardized approach uses external ratings and risk weights. The internal ratings-based approach has a foundation and advanced option where banks model PD, LGD, and EAD with regulatory oversight.
This document provides an overview of financial management. It discusses key topics such as the role of financial management in businesses, the scope and elements of financial management including investment, financial, and dividend decisions. It also covers related topics such as finance vs financing, careers in finance, financial institutions and capital markets, and financial management issues in the new millennium.
The document discusses various approaches to asset and liability management (ALM), with a focus on liquidity risk management. It proposes using multiple metrics to measure liquidity risk, including the loan-to-deposit ratio, 1-week and 1-month liquidity ratios, a cumulative liquidity model, an intercompany lending report, and a liquidity risk factor. These metrics provide different insights into a bank's self-sufficiency, exposure to roll risk, potential stress points, and daily funding needs from both structural and forward-looking perspectives. The document emphasizes examining liquidity risk at the country, legal entity, and group levels with appropriate limits and assumptions.
The document discusses corporate-bank relationships since the 2008 financial crisis. It presents the results of a survey that found most corporations believe the crisis highlighted the value of their treasury functions but few received extra resources. While corporations prefer long-term strategic relationships with banks, most believe banks prefer short-term transactional approaches. It also lists political, economic, social and technological trends that will impact future corporate-bank relationships and stresses the importance of risk management and distinguishing service quality over price.
1. The document provides background information on Renuka Consumer Products Limited (RCPL), a company that manufactures and sells soaps, hair color, and detergents. It discusses RCPL's historical financial performance and key assumptions about future volume, price, cost, and expense trends.
2. Akshay, the owner of RCPL, is considering how to prepare the company for increasing competition. The document reviews RCPL's sales, costs, expenses, and profitability over time to help Akshay identify areas to focus on.
3. Inputs are provided from various department heads on expected trends in volumes, prices, costs, wages, and other expenses to help Akshay develop financial
This document provides an agenda for a seminar on financial reporting and analysis for the CFA Level I exam in June 2011. It lists topics that will be covered, including an introduction, the balance sheet, advanced concepts, and contact information. It also provides information about Pristine, the organization providing the seminar materials and training. Pristine was founded by professionals to create world-class finance professionals through innovative content delivery and training methodologies. Pristine is an authorized training provider for several financial certifications.
Liquidity risk refers to the potential inability of an individual, business, or financial institution to meet short-term financial obligations due to insufficient cash or liquid assets. It arises when assets cannot be quickly sold or converted into cash without significant loss in value, potentially leading to operational or financial disruptions.
Page 1 of 9 This material is only for the use of stud.docxkarlhennesey
油
Page 1 of 9
This material is only for the use of students enrolled in FIN 740 for purposes associated with the course and may not be
retained or further disseminated. All information in this material is proprietary to Dr. Sung Ik Kim. Scanning, copying,
posting to a website or reproducing and sharing in any form is strictly prohibited.
Chapter 10. Quantitative Risk Management in R
In this chapter, I explore how we can describe the risk of a single security or a portfolio (a set of assets).
Especially, I introduce the concept of value at risk (VaR) and expected shortfall (ES) here.
1. What is value at risk (VaR)?
Value at risk is one of the most widely used risk measure in finance. VaR was popularized by J.P. Morgan
in the 1990s. The executive at J.P. Morgan wanted their risk managers to generate one statistic that
summarized the risk of the firms entire portfolio at the end of each day. What they came up with was VaR,
which is now widely used by corporate treasurers and fund managers as well as by financial institutions.
VaR is a one-tailed confidence interval. If the 5-day 95% VaR of a portfolio is $1,000, then we expect the
portfolio will lose $1,000 or less in 95% of the scenarios and lose more than $1,000 in 5% of the scenarios
in 5 days. For example, we are interested in making a statement of the following form when using the VaR:
We are 95 percent certain that we will not lose more than $1,000 in 5 days.
It is a function of two parameters: the time horizon (e.g. 5-day in the example above) and the confidence
level (e.g. 95% in the example above). We can define VaR for any confidence level, but 95% has become an
extremely popular choice at many financial firms. The time horizon also needs to be specified for VaR. On
trading desks with liquid portfolios, it is common to measure the one-day 95% VaR.
The following figure provides a graphical representation of VaR at the 95% confidence level. The figure
shows the probability density function for the returns of a portfolio. Because VaR is measured at the 95%
confidence level, 5% of the distribution is to the left of the VaR level, and 95% is to the right.
Page 2 of 9
This material is only for the use of students enrolled in FIN 740 for purposes associated with the course and may not be
retained or further disseminated. All information in this material is proprietary to Dr. Sung Ik Kim. Scanning, copying,
posting to a website or reproducing and sharing in any form is strictly prohibited.
We now formally define VaR. Let L be a random variable, which represents the loss to our portfolio. L is
simply the opposite of the return to our portfolio. For example, if the return of our portfolio is -$1,000, the
loss, L, is +$1,000. For given confidence level 留, VaR is defined as
P(L VaR) = 1
We can also define VaR directly in terms of returns. If we multiply both sides of the inequality above by -1,
and replace .
Discounted Cash Flow Methodology for Banks and Credit UnionsLibby Bierman
油
As institutions prepare for the CECL or current expected credit loss model for the allowance for loan and lease losses (ALLL), institutions are prudently learning the various methodologies available to them. Discounted Cash Flow or DCF is one proposed methodology. This session presents best practices and use cases for the ALLL methodology. See the recording: http://web.sageworks.com/dcf-webinar/
Fixed Income Derived Analytics Powered By BlackRock SolutionsConor Coughlan
油
This is an overview of the new Thomson Reuters Fixed Income Derived Analytics powered by BlackRock Solutions.
For more information visit www.prdcommunity.com
(R)isk Revolution - Current trends and challenges in Credit & Operational RiskMarkus Krebsz
油
This was presented as part of a Senior Australian Bankers' Master Class held at GCU London on 19 Sept 2012. Dr. Robert Webb was co-presenting on the UK & European Banking system.
A comprehensive presentation on the financial risks involved in businesses in general & specifically in banks.
What is Risk?
Generally - Danger, Hazard, Adverse impact, Fear of loss.
Financially-Loss of earnings/capital
May result in incapability of financial institution to meet business goals
Basically there are 4 main risks:
1. Credit Risk
2. Market Risk
3. Liquidity Risk
4. Operational Risk
Risk management is amongst the most overlooked yet very critical aspects of systematic trading. In this webinar, youll get to learn risk management techniques to overcome the most common challenges. This session will explain you the concepts of optimal leverage, hedging and risk indicators.
- Risk Management and the real challenge
- Optimal leverage: Kelly formula, Maximum drawdown
- Market risk: Stop Losses, volatility targeting, value-at-risk
- Hedging techniques
- Risk indicators
Learn more about our EPAT course here: https://www.quantinsti.com/epat/
Most Useful links:
Visit us at: https://www.quantinsti.com/
Like us on Facebook: https://www.facebook.com/quantinsti/
Follow us on LinkedIn: https://www.linkedin.com/company/quantinsti
Follow us on Twitter: https://twitter.com/QuantInsti
Value at Risk (VaR) is a statistical technique used to measure and quantify the level of financial risk within a firm, portfolio, or position over a specific time frame. It aims to quantify, with a single number, the maximum potential loss that could occur over a given time period at a given confidence level. There are different approaches to calculating VaR such as variance-covariance, historical simulation, and Monte Carlo simulation. VaR is widely used by banks and other financial institutions to monitor and control their risk exposure and capital adequacy. However, it does have some weaknesses as the results can vary depending on the underlying assumptions and there are costs associated with maintaining a VaR system.
The Imperatives of Investment Suitabilityfinametrica
油
Presentation given by Paul Resnik (Co-Founder, FinaMetrica) at the National Institute of Securities Markets (NISM) in Mumbai, India. It emphasizes on the importance of measuring risk tolerance of investors in the process of matching investment products to an individual's needs. Visit www.riskprofiling.com to know more.
This document compares two downside risk measures - Value at Risk (VaR) and Expected Shortfall (ES or CVaR) - for portfolio optimization. It defines each measure, discusses how to optimize portfolios to minimize each risk, and lists advantages and disadvantages. The document also presents numerical implementations comparing frontiers, portfolio weights, and out-of-sample performances when optimizing for VaR versus CVaR. It concludes there is no definitive answer on which measure is better, as it depends on factors like data availability and model accuracy.
This document discusses various risks faced by banks, including CAMEL risks relating to capital adequacy, asset quality, management, earnings, and liquidity. It also discusses asset liability management (ALM), which involves planning, organizing, and controlling a bank's assets and liabilities to maintain liquidity and net interest income. Other topics covered include liquidity management, types of liquidity risk, interest rate risk management, and sources of interest rate risk.
The document outlines a roadmap to transform a property and casualty insurer's direct marketing strategy from a mass mailing approach focused on call center volume to a more data-driven and targeted strategy. It details challenges around expertise, data access, and key performance indicators. The proposed strategy focuses on building analytics capabilities, testing creative concepts, and optimizing mailings based on customer value. Key metrics like response rates, revenue, and cost per acquisition are improved. The client is able to grow their direct business significantly while lowering marketing costs over a two year period.
The document discusses Orc Software's risk management tools for trading firms and banks. It describes how Orc Trading for Risk Management gives firms the ability to understand their total risk exposure through features like accurate market views, exposure to risk sensitivities, scenario analysis, and profit and loss projections. The tool is used by leading trading firms and banks to provide real-time risk insights on exchange traded derivatives. It also provides success stories of how heads of trading and risk at different financial institutions have used Orc Trading for Risk Management to improve their risk management and control.
1) The presentation discusses Equitas Micro Finance's model of fair and transparent pricing. It focuses on responsible pricing by having investors bear the cost of growth while keeping steady state costs low for borrowers.
2) Equitas aims for high operating efficiency through best technology and processes, benchmarks delinquency assumptions to national MFI levels, and caps return on equity at 20% to determine fair lending rates.
3) The model provides transparency through clear communication of reducing balance interest rates and publishing administrative fees in borrowers' passbooks.
This document provides a summary of key concepts in corporate finance, including:
1) Sources of corporate funding and capital structure, capital expenditures, and tools used for allocating funds. Key goals are investing and financing.
2) Investing involves forgoing current consumption for future returns. Financing examines return ratios like ROCE, ROE, and ROIC from different perspectives.
3) Tools used in corporate finance include NPV, IRR, payback period, and leverage. Equity valuation methods include free cash flow, NPV, IRR, relative valuation, and payback period. Modern portfolio theory examines efficient diversification of risk.
Risky business: Guide to Risk ManagementMichael Le
油
This document provides an introduction to risk management. It defines risk as the probability of an undesired event multiplied by its consequences. There are various types of risk, including market risk, credit risk, and operational risk. Risk is measured using techniques like value at risk and profit and loss. Credit ratings are important but not always reliable indicators of risk. Effective risk management requires understanding potential risks from diverse sources, quantifying exposures, and implementing systems to monitor and report on risk.
The document discusses the capital charge for credit risk under Basel 2. It outlines the three pillars of Basel 2 - minimum capital requirements, supervisory review, and market discipline. It then describes the standardized approach and internal ratings-based approach to computing capital charge for credit risk. The standardized approach uses external ratings and risk weights. The internal ratings-based approach has a foundation and advanced option where banks model PD, LGD, and EAD with regulatory oversight.
This document provides an overview of financial management. It discusses key topics such as the role of financial management in businesses, the scope and elements of financial management including investment, financial, and dividend decisions. It also covers related topics such as finance vs financing, careers in finance, financial institutions and capital markets, and financial management issues in the new millennium.
The document discusses various approaches to asset and liability management (ALM), with a focus on liquidity risk management. It proposes using multiple metrics to measure liquidity risk, including the loan-to-deposit ratio, 1-week and 1-month liquidity ratios, a cumulative liquidity model, an intercompany lending report, and a liquidity risk factor. These metrics provide different insights into a bank's self-sufficiency, exposure to roll risk, potential stress points, and daily funding needs from both structural and forward-looking perspectives. The document emphasizes examining liquidity risk at the country, legal entity, and group levels with appropriate limits and assumptions.
The document discusses corporate-bank relationships since the 2008 financial crisis. It presents the results of a survey that found most corporations believe the crisis highlighted the value of their treasury functions but few received extra resources. While corporations prefer long-term strategic relationships with banks, most believe banks prefer short-term transactional approaches. It also lists political, economic, social and technological trends that will impact future corporate-bank relationships and stresses the importance of risk management and distinguishing service quality over price.
1. The document provides background information on Renuka Consumer Products Limited (RCPL), a company that manufactures and sells soaps, hair color, and detergents. It discusses RCPL's historical financial performance and key assumptions about future volume, price, cost, and expense trends.
2. Akshay, the owner of RCPL, is considering how to prepare the company for increasing competition. The document reviews RCPL's sales, costs, expenses, and profitability over time to help Akshay identify areas to focus on.
3. Inputs are provided from various department heads on expected trends in volumes, prices, costs, wages, and other expenses to help Akshay develop financial
This document provides an agenda for a seminar on financial reporting and analysis for the CFA Level I exam in June 2011. It lists topics that will be covered, including an introduction, the balance sheet, advanced concepts, and contact information. It also provides information about Pristine, the organization providing the seminar materials and training. Pristine was founded by professionals to create world-class finance professionals through innovative content delivery and training methodologies. Pristine is an authorized training provider for several financial certifications.
The document is an agenda for a seminar on CFA Level II Equity Investments held in June 2011. The agenda covers an introduction, understanding the CFA exam structure, an introduction to equity investments including valuation concepts and calculations of free cash flow to the firm (FCFF) and weighted average cost of capital (WACC). It also lists the presenter's contact information.
The document provides an agenda for a seminar on Value-at-Risk (VaR) trainings by Pristine Careers. The agenda includes an introduction to Pristine Careers, an overview of the FRM examination structure, an introduction to VaR including calculating simple VaR and VaR for linear and non-linear assets, registration information, and details on the next seminar. Pristine Careers is an authorized training provider for financial risk certification exams and programs.
This document provides an agenda for a seminar on quantitative analysis for the FRM exam. It lists topics that will be covered including probability distributions and key concept checkers. It also discusses Pristine, the company providing the seminar, which was founded by professionals to create world-class risk management professionals. Pristine is an authorized training provider for several certifications and has trained over 1000 students. It utilizes topic experts and both classroom and online delivery methods to improve learning.
This document provides an agenda for a seminar on quantitative analysis for the FRM exam. It lists topics that will be covered including probability distributions and key concept checkers. It also discusses Pristine, the company providing the seminar, which was founded by professionals to create world-class risk management professionals. Pristine is an authorized training provider for several certifications and has trained over 1000 students. It utilizes topic experts and both classroom and online delivery methods to improve learning.
The document defines various free cash flow metrics:
1) FCFF (free cash flow to firm) is calculated from net income, depreciation, interest, taxes, capital expenditures, and working capital investments.
2) FCFE (free cash flow to equity) is calculated from FCFF adjusted for interest and net borrowing.
3) Examples are provided to calculate FCFF given inputs for net income, depreciation, interest, taxes, capital expenditures, and working capital changes. FCFE is then calculated from FCFF using an additional input for net borrowing.
4) FCFF is most appropriate when a firm lacks a stable dividend policy or the policy is unrelated to earnings, as it reflects
Free cash flow (FCF) represents the cash a company generates after maintaining and growing its assets, and is important because it allows companies to enhance shareholder value through opportunities. FCF can be calculated by taking operating cash flow and subtracting capital expenditures, and while negative FCF is not inherently bad, it could signify large investments that have the potential to earn high returns in the long run.
This document discusses various quantitative analysis techniques for time series data, including regression analysis, trend models, seasonality models, autoregressive models, and techniques for addressing autocorrelation. It provides an overview of simple and multiple linear regression, assumptions of regression models, and methods for model specification testing including analysis of variance.
FSA tips for CFA Preparation by Pristine (Annotated)Pristine Careers
油
The answer is C. An income statement measures a company's financial performance over a specified period of time.
An income statement summarizes a company's revenues and expenses over a period of time, such as monthly, quarterly, or annually. It shows whether the company made a profit or loss over that period.
The matching principle states that expenses should be recognized in the same period as the revenues to which they relate. This ensures that net income is not overstated or understated in any given period.
The two steps of the matching principle are:
1) Revenues are recognized (reported) when earned, not when cash is received. This matches current revenues with current expenses.
2) Expenses are recognized (reported) when incurred, not when cash is paid out. This matches current expenses with current revenues.
Following the matching principle helps provide useful information to investors and other financial statement users about a company's profitability and performance in a given period. It helps ensure expenses are properly allocated to the revenues of the period in
2. System Requirements for Webinar
Operating System: Windows速 2000, XP, 2003 Server or Vista
Processor: Minimum of Pentium速 class 1GHz CPU with 512 MB of RAM (Recommended) (2
GB of RAM for Windows速 Vista)
Connectivity: Cable modem, DSL or better Internet connection
Plug-ins : Internet Explorer速 6.0 or newer, Mozilla速 Firefox速 2.0 or newer (JavaScriptTM and
JavaTM enabled)
Other HARDWARE: Good Quality Microphone, speakers/headphones, Participants wishing to
connect to audio using VoIP will need a fast Internet connection, a microphone and speakers (a
USB headset is recommended).
www.pristinecareers.com
3. Agenda
About Pristine
Introduction to VaR
Calculating Simple VaR
VaR for Linear & Non-Linear Assets
Marginal VaR
Our Contact
www.pristinecareers.com
4. About Pristine
An institution started by graduates from premiere institutes like IIM/IITs with
diversified experience in financial sector
An authorized "Course Provider" for the FRM Exam and provides trainings for
preparation of the FRM & CFA Exam.
The faculty members are drawn from IIT/IIM's having relevant experience in risk
management & Investment banking.
Pristine has developed relationships with various Investment Banks, Commercial
Banks, Asset Management Firms, Insurance Companies, Securities Regulators,
Hedge Funds, Large Corporations, Multinationals and Credit Rating Firms and is a
source to these companies for FRM and CFA candidates.
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5. Agenda
About Pristine
Introduction to VaR
Calculating Simple VaR
VaR for Linear & Non-Linear Assets
Marginal VaR
Our Contact
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6. Introduction To Various Risks
Risk can be broadly defined as the degree of uncertainty about future net returns
Credit risk relates to the potential loss due to the inability of a counterpart to meet its
obligations
Operational risk takes into account the errors that can be made in instructing payments
or settling transactions
Liquidity risk is caused by an unexpected large and stressful negative cash flow over a
short period
Market risk estimates the uncertainty of future earnings, due to the changes in market
conditions
Current Focus of Study is Market Risk
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7. What is VaR ?
Value at Risk (VaR) has become the standard measure that financial analysts use to
quantify this risk
VAR represents maximum potential loss in value of a portfolio of financial instruments
with a given probability over a certain horizon
In simpler words, it is a number that indicates how much a financial institution can lose
with probability 慮 over a given time horizon
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8. VAR Benefits
Aggregates all of the risks in a portfolio into a single number
Suitable for use in the boardroom, reporting to regulators, or disclosure in annual
report
Provides an approach to arrive at economical capital.
Relates capital with the expected losses
Scaled to time
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9. VaR Measurement
Mark-to-market the portfolio
Estimate the distribution of portfolio returns
VAR : a very challenging statistical problem
Compute the VaR of the portfolio
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10. Distribution of returns : Three broad categories
Parametric
RiskMetrics
GARCH
Nonparametric
Historical Simulation
the Hybrid model
Semiparametric
Extreme Value Theory
CAViaR
quasi-maximum likelihood GARCH
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11. Financial markets: empirical facts
Financial return distributions are leptokurtotic,
that is they have heavier tails
a higher peak than a normal distribution
Equity returns are typically negatively skewed
Squared returns have significant autocorrelation
volatilities of market factors tend to cluster
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12. Agenda
About Pristine
Introduction to VaR
Calculating Simple VaR
VaR for Linear & Non-Linear Assets
Marginal VaR
Our Contact
www.pristinecareers.com
13. Visualizing VAR
V a lu e a t R is k
.0 2 2 433
.0 1 6 3 2 4 .7
.0 1 1 2 1 6 .5
.0 0 5 1 0 8 .2
.0 0 0 0
1 .5 2 .9 4 .3 5 .6 7 .0
C e rta inty is 9 5 .0 0 % f ro m 2 .6 to + In finity
Confidence (x%) ZX%
90% 1.28
95% 1.65
The area under the normal curve for
confidence value is: 97.5% 1.96
99% 2.32
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14. VAR : Representations
A portfolio having a current value of say Rs.500,000- can be described to have
a daily value at risk of US$ 5000- at a 99% confidence level,
which means there is a 1/100 chance of the loss exceeding US$ 5000/-
considering no great paradigm shifts in the underlying factors.
A one day VAR of $10mm using a probability of 5% means that there is a 5%
chance that the portfolio could lose more than $10mm in the next trading day.
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15. How To Measure ?
VaR (daily VaR) (in %) = ZX% *
ZX% : the normal distribution value for the given probability (x%) (normal
distribution has mean as 0 and standard deviation as 1)
: standard deviation (volatility) of the asset (or portfolio)
VaR (daily VaR) = VaR (in %) * asset value
Or, VaR (daily VaR) = ZX% * * asset value
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16. How To Measure ?
VaR (n days) (in %) = VaR(daily VaR) (in %) * n
VaR (n days) = ZX% * * asset value * n
port = wa2 a2 + wb2 b2+2wawb* a* b* ab
VaRport (daily VaR) (in %) =
wa2 (%VaRa)2 + wb2 (%VaRb)2+2wawb* (%VaRa)* (%VaRb)* ab
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17. Basic Problem #1
Asset daily standard deviation is 1.6%
Market Value is US $ 10 Mn
What is VaR (%) at 99% confidence?
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18. Basic Problem #2:
What is the VaR value for 10 day VaR in the earlier case?
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19. Basic Problem #3:
What is the daily portfolio VaR at 97.5% confidence level?
Investment in asset A is US$ 40 Mn
Investment in asset B is US$ 60 Mn
Volatility of asset A is 5.5% and asset B is 4.25%
Portfolio VaR if correlation between A and B is 20% ?
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20. Extended Problem #3.1
Portfolio VaR if correlation between A and B is Zero?
What if correlation is 1 ?
Or -1 ?
What are the implications ?
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21. Basic Problem #4:
Market Value of asset US$ 10 Mn
Daily variance is 0.0005
What is the annual VaR at 95% confidence with 250 trading days in a year?
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22. Basic Problem #5:
For an uncorrelated portfolio what is the VaR if:
VaR asset A is US$ 10 Mn
VaR asset B is US$ 20 Mn
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23. Agenda
About Pristine
Introduction to VaR
Calculating Simple VaR
VaR for Linear & Non-Linear Assets
Marginal VaR
Our Contact
www.pristinecareers.com
24. VaR for Linear and Non-Linear Assets
When the value of the delta is constant for all changes in the underlying.
Primarily in the case of fixed income securities we have linear assets
When the value of the delta keeps on changing with the change in the underlying
asset. It is seen in options
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25. VaR for Linear Assets
Linear Derivatives: Payoff diagrams that are linear or almost linear
Forwards, futures
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26. VaR for Linear Derivatives
Delta of Derivative
Change in price of Derivative to change in underlying asset
For example,
The permitted lot size of S&P CNX Nifty futures contracts is 200 and multiples thereof. If
So VaR of Nifty Futures contract is 200 * VaR of Nifty
VaRLinear Derivative = VaR Underlying Risk Factor
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27. VaR for Non-Linear Assets
Non-Linear Derivatives: Payoff diagrams
that are highly non-linear
Non-linearity is due to the derivative either
being an option or having an option
embedded in its structure
Options, Credit Derivatives, Swaps
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28. VaR for Non-Linear Derivatives
Main reason for difference is the shape of the payoff curve
Option
For Delta Normal VaR price
A linear approximation is created
Approximation is an imperfect proxy for the portfolio
Slope =
Computationally easy but may be less accurate. B
The delta-normal approach (generally) does not work for
portfolios of nonlinear securities. A Stock price
Options Var = Delta of Option * (VaR at Zx%)
f ( x ) f ( x0 ) + f ( x0 )( x x0 ) + 1 2 f 霞( x0 )( x x0 )2
Consider a portfolio of options dependent on a single stock price,
S. Define P
隆 =
S
S
Approximately: x =
S
For Many Underlying variables: P = 隆 S = S隆 x
P = S i 隆i xi
i
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29. Problem #6 (Linear Assets)
If the daily VaR at 5%of Nikkie is 0.8 crores and you have 100 lots of Nikkie contract,
Calculate annual VaR at 95% confidence for your portfolio assuming 250 days?
= 0.8*200*sqrt(250)
= 1264.911 crores
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30. Problem #7 (Non-Linear Assets) :
If the value of stock is 100 and the value of the put option at 110 is 20. 10 units change
in the underlying brings in change of 4 units change in the option premium. If the annual
volatility is 0.25. Calculate daily VaR at 97.5% assuming 250 days?
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31. Agenda
About Pristine
Introduction to VaR
Calculating Simple VaR
VaR for Linear & Non-Linear Assets
Marginal VaR
Our Contact
www.pristinecareers.com
32. What is the Total Risk?
Bonds
Stocks
Options
Credit
Forex
Total Risk??
32 www.pristinecareers.com
33. Marginal VaR
Suppose a portfolio has assets a, b and c. The Marginal VaR is the VaR of the
portfolio VaR of the respective asset.
Marginal VaR is for each unit and is the change in VaR of the portfolio with one
unit change in the components
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34. Problem #8 (Marginal VAR) :
Bank portfolio of stock has Reliance and Tata Steel with beta of 1.20 and 0.85. The VaR
of the portfolio is Rs. 3,00,000 with the position of Reliance being Rs. 10,00,000 and
Tata Steel as Rs, 5,00,000.
What is the Marginal VaR for each?
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36. Agenda
About Pristine
Introduction to VaR
Calculating Simple VaR
VaR for Linear & Non-Linear Assets
Marginal VaR
Our Contact
www.pristinecareers.com
37. Contact
Contact Phone Email
Atul Kumar +91 93221 94932 atul@eneev.com
Pawan Prabhat +91 98676 25422 pawan@eneev.com
Paramdeep Singh +91 93118 45000 paramdeep@eneev.com
Sarita Chand +91 93427 34627 sarita@eneev.com
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Pristine Careers is an official course provider of FRM Exam preparation
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