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Financial Strategies for Value Creation

This course is designed for students who have limited experience and knowledge about the U. Students will learn about the U. Topics Covered: Banks Insurance companies, pension funds, mutual funds, and hedge funds Financial instruments How traders manage risk, interest rate risk Value at risk Volatility Correlation, copulas Market risk VaR, historical simulation and model building approach Credit risk, estimating default probabilities Credit risk losses and credit VaR The credit crisis, stress testing, liquidity risk, model risk Economic capital and RAROC, career-ending mistakes.

This course reviews the accounting requirements associated with asset valuation and income recognition of complex portfolios that utilize advanced hedging techniques.

The course analyzes an organization's control environment and processes within COSO and SOX frameworks and examines the control practices that organizations use to help ensure the integrity of information provided by its accounting systems. Finally, tax related issues and Basel II are also discussed.

This course will serve as a review of the entire program. Capstone projects are graded pass-fail as part of this course. Capstone projects may begin prior to the start of this course, but they must be completed by its conclusion. In addition it will review the accounting requirements associated with asset valuation and income recognition of complex portfolios that utilize advanced hedging techniques. Experiential Learning. For more information, visit Experiential Learning. The course trains students with advanced knowledge of financial risk management to build risk measurement and management tools by using Excel VBA.

It assumes prior knowledge of the VBA language. It provides an advanced learning forum for students to develop specific applications on their own. Widoczny [Schowaj] Abstrakt. Adres strony. Prace Naukowe Politechniki Warszawskiej. Operational risk management. Strzelczak, S. The overview of up-to-date issues of operational risk management begins from a discussion of basic concepts.

Different types of risks and relations between them have been carefully analyzed. It was underlined that the practice and research of risk management have been dominated by the experience of financial services, and particularly by banking and insurance. However, this sector faces rather unique business risk profiles, comparing to e. Finally, the trade-offs between risks and risk-adjusted performance measures have been discussed, The second part of the paper focuses evaluation of operational risks. It begins from an overview of basic approaches to operational risk measurement, i. The latest combine judgment by managers and loss experience and the most representative among them are: historical loss mapping and key risk indicators KRI.

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Mastering Interest Rate Risk Strategy: A practical guide to managing corporate financial risk

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Interest rate risk management (1) Part 5 - ACCA (AFM) lectures

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Video Editing. Mastering R for Quantitative Finance. Use R to optimize your trading strategy and build up your own risk management system. Skip to the end of the images gallery. Skip to the beginning of the images gallery.

Read Now Look inside. More Information Learn Analyze high frequency financial data Build, calibrate, test, and implement theoretical models such as cointegration, VAR, GARCH, APT, Black-Scholes, Margrabe, logoptimal portfolios, core-periphery, and contagion Solve practical, real-world financial problems in R related to big data, discrete hedging, transaction costs, and more.

Discover simulation techniques and apply them to situations where analytical formulas are not available Create a winning arbitrage, speculation, or hedging strategy customized to your risk preferences Understand relationships between market factors and their impact on your portfolio Assess the trade-off between accuracy and the cost of your trading strategy About R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages.

Features Learn to manipulate, visualize, and analyze a wide range of financial data with the help of built-in functions and programming in R Understand the concepts of financial engineering and create trading strategies for complex financial instruments Explore R for asset and liability management and capital adequacy modeling Page Count Course Length 10 hours 51 minutes ISBN Date Of Publication 10 Mar Table of contents.

Multivariate time series analysis Volatility modeling Summary References and reading list. Arbitrage pricing theory Modeling in R Summary References. Getting data from open sources Introduction to big data analysis in R K-means clustering on big data Big data linear regression analysis Summary References.

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A general pricing approach The role of dynamic hedging How R can help a lot A glance beyond vanillas Greeks — the link back to the vanilla world Pricing the Double-no-touch option Another way to price the Double-no-touch option The life of a Double-no-touch option — a simulation Exotic options embedded in structured products Summary References.

Hedging of derivatives Hedging in the presence of transaction costs Further extensions Summary References. The basics of fundamental analysis Collecting data Revealing connections Including multiple variables Separating investment targets Setting classification rules Backtesting Industry-specific investment Summary References.

Data preparation Interest rate risk measurement Liquidity risk measurement Modeling non-maturity deposits Summary References. Systemic risk in a nutshell The dataset used in our examples Core-periphery decomposition The simulation method Possible interpretations and suggestions Summary References. Add to Cart. What do I get with a Packt subscription? Exclusive monthly discount - no contract Unlimited access to entire Packt library of over eBooks and Videos new titles added every month on new and emerging tech. What do I get with a Video? Download this Video course in MP4 format DRM FREE - read and interact with your content when you want, where you want, and how you want Immediately access your video course for viewing or download through your Packt account.

What do I get with an eBook? Add To Cart. Start a FREE day trial. Analyze high frequency financial data Build, calibrate, test, and implement theoretical models such as cointegration, VAR, GARCH, APT, Black-Scholes, Margrabe, logoptimal portfolios, core-periphery, and contagion Solve practical, real-world financial problems in R related to big data, discrete hedging, transaction costs, and more.

https://podbestgratalab.ml Discover simulation techniques and apply them to situations where analytical formulas are not available Create a winning arbitrage, speculation, or hedging strategy customized to your risk preferences Understand relationships between market factors and their impact on your portfolio Assess the trade-off between accuracy and the cost of your trading strategy.

Learn to manipulate, visualize, and analyze a wide range of financial data with the help of built-in functions and programming in R Understand the concepts of financial engineering and create trading strategies for complex financial instruments Explore R for asset and liability management and capital adequacy modeling. Multivariate time series analysis. Volatility modeling. References and reading list. Arbitrage pricing theory. Modeling in R.

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The intensity of trading. The volume forecasting model. Implementation in R. Getting data from open sources. Introduction to big data analysis in R. K-means clustering on big data. Big data linear regression analysis. Terminology and notations. Currency options. Exchange options.

Quanto options. The Black model. The Vasicek model. The Cox-Ingersoll-Ross model. Parameter estimation of interest rate models. Using the SMFI5 package. A general pricing approach. The role of dynamic hedging. How R can help a lot. A glance beyond vanillas.