Optimal portfolios

Lecture Financial modeling  Topic 4: Portfolio riskreturn optimization. In this chapter students will compute optimal portfolio weights that combine risky portfolios and risk free assets, compute efficient (max return/min risk) and optimal risky portfolios, compute optimal complete portfolios that combine a risk free asset or borrowing.
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Chapter 5  Portfolio risk and return (Part I). In this chapter, we will explore the process of examining the risk and return characteristics of individual assets, creating all possible portfolios, selecting the most efficient portfolios, and ultimately choosing the optimal portfolio tailored to the individual in question.
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In Chapter 8 we discussed optimal risky portfolios. That decision governs how an investor chooses between riskfree assets and “the” optimal portfolio of risky assets. This chapter explains how to construct that optimal risky portfolio. We begin with a discussion of how diversification can reduce the variability of portfolio returns. After establishing this basic point, we examine efficient diversification strategies at the asset allocation and security selection levels.
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Single period market models are the most elementary market models. Only a single period is considered. The beginning of the period is usually denoted by the time t = 0 and the end of the period by time t = 1. At time t = 0 stock prices, bond prices,possibly prices of other financial assets or specific financial values are recorded and the financial agent can choose his investment, often a portfolio of stocks and bond. At time t = 1 prices are recorded again and the financial agent obtains a payoff corresponding to the value of his portfolio at time t = 1....
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Chapter 6  Portfolio risk and return (Part II). The topics discussed in this chapter are: Portfolio risk and return, optimal risky portfolio and the capital market line (CML), returngenerating models and the market model, systematic and nonsystematic risk, capital asset pricing model (CAPM) and the security market line (SML), performance measures, arbitrage pricing theory (APT) and factor models.
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Expected asset risk measures are needed to construct optimal portfolios, plan for retirement, value equities and options, and forecast corporate cash flow distributions. In this lecture, students will: Compute asset return variance and standard deviation, scale standard deviations across time, compute moving average volatility, compute volatility using EWMA models, compute implied volatility using the blackscholes option pricing model.
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Topic 11  Fixed income portfolio optimization. After completing this topic, you should be able to: Manage the interest rate risk of fixed income portfolios; compute portfolio value, income, duration, convexity compute effective duration; optimize liabilities funding (pension) using duration and convexity; optimize fixed income portfolios using duration and convexity.
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Topic 4  Modeling portfolio risk, return, and VaR. In this chapter, the learning objectives are: Compute portfolio return, risk, var using excel and matrix operations; compute optimal portfolios; computing VaRs and Confidence Intervals using @Risk.
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In this chapter, students understand and can recall the process of portfolio construction and optimization; students can compute nasset portfolio mean, volatility, and sharpe ratios; optimal combined portfolios that combine risky and riskfree assets.
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Strategic Corporate Finance provides a ‘‘realworld’’ application of the principles of modern corporate finance, with a practical, investment banking advisory perspective. Building on 15 years of corporate finance advisory experience, this book serves to bridge the chronic gap between corporate finance theory and practice. Topics range from weighted average cost of capital, valuebased management and M&A, to optimal capital structure, risk management and dividend/buyback policy.
307p vigro23 28082012 97 60 Download

The favorable reception of Portfolio Management Formulas exceeded even the greatest expectation I ever had for the book. I had written it to promote the concept of optimal f and begin to immerse readers in portfolio theory and its missing relationship with optimal f. Besides finding friends out there, Portfolio Management Formulas was surprisingly met by quite an appetite for the math concerning money management. Hence this book. I am indebted to Karl Weber, Wendy Grau, and others at John Wiley & Sons who allowed me the necessary latitude this book required....
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Strategic Corporate Finance provides a ‘‘realworld’’ application of the principles of modern corporate finance, with a practical, investment banking advisory perspective. Building on 15 years of corporate finance advisory experience, this book serves to bridge the chronic gap between corporate finance theory and practice. Topics range from weighted average cost of capital, valuebased management and M&A, to optimal capital structure, risk management and dividend/buyback policy.
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In everyday life we are often forced to make decisions involving risks and perceived opportunities. The consequences of our decisions are affected by the outcomes of random variables that are to various degrees beyond our control. Such decision problems arise, for instance, in financial and insurance markets.
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This book presents and develops major numerical methods currently used for solving problems arising in quantitative finance. Our presentation splits into two parts. Part I is methodological, and offers a comprehensive toolkit on numerical methods and algorithms. This includes Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transformbased methods and quadrature techniques. Part II is practical, and features a number of selfcontained cases.
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Chris Adcock is Professor of Financial Econometrics in the University of Sheffield. His career includes several years working in quantitative investment management in the City and, prior to that, a decade in management science consultancy. His research interests are in the development of robust and nonstandard methods for modelling expected returns, portfolio selection methods and the properties of optimized portfolios. He has acted as an advisor to a number of asset management firms. He is the founding editor of the European Journal of Finance. George A.
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If successful, this book will change your idea about what an optimal investment portfolio is. It is intended to be a guide both to understanding irrational investor behavior and to creating individual investors’ portfolios that account for these irrational behaviors. In this book, an optimal portfolio lies on the efficient frontier, but it may move up or down that frontier depending on the individual needs and preferences of each investor.
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Evaluating mutual fund performance is a topic of longstanding interest in the academic literature, but few if any studies have addressed the selection of an optimal portfolio of funds. Instead of using the historical data to estimate performance measures or produce fund rank ings, this study uses the data to explore the mutualfund investment decision.
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Asset allocation investigates the optimal division of a portfolio among different asset classes. Standard theory involves the optimal mix of risky stocks, bonds, and cash together with various subdivisions of these asset classes. Underlying this is the insight that diversification allows for achieving a balance between risk and return: by using different types of investment, losses may be limited and returns are made less volatile without losing too much potential gain.
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Interest income is the most important source of revenue for most of the banks. The aim of this paper is to assess the impact of dierent interest rate scenarios on the banks' interest income. As we do not know the interest rate sensitivity of real banks, we construct for each bank a portfolio with a similar composition of its assets and liabilities, called 'tracking bank'. We evaluate the eect of 260 historical interest rate shocks on the tracking banks of German savings banks and cooperative banks.
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In recent years, the credit derivatives market has become extremely active. Especially credit default swaps (CDSs) and collateralized debt obligations (CDOs) have contributed to what has been an amazing development. The most important benefit of credit derivatives is their ability to transfer the credit risk of an arbitrary number of obligors in a simple, efficient, and standardized way, giving rise to a liquid market for credit risk that can be easily accessed by many market participants.
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