Proceedings Article•
The alternative risk measures in Excel
24 May 2010-pp 908-913
TL;DR: The alternative risk measures which attracted significant attention of financial managers last years together with Excel's formulations of analytical expressions are introduced and construction of models for portfolio selection based on different risk measures together with Microsoft Excel solutions are constructed.
Abstract: The paper examines the alternative risk measures and portfolio selection with alternative risk measures. The paper follows from student's activities in the subject of financial modeling, precisely in the modern portfolio theory. As many weaknesses of Markowitz mean-variance model have been noticed, primarily in the sense that variance isn't appropriate risk measure when distribution of stock returns isn't normal, the alternative risk measures have to be introduced. The problem is how to present relatively complex portfolio optimization models with alternative risk measures to students' population and to teach them how to realize those models using Excel. In this paper, the alternative risk measures which attracted significant attention of financial managers last years together with Excel's formulations of analytical expressions are introduced. The presented risk measures are lower-semi variance, lower semi-absolute deviation, Value at Risk (VaR) and Conditional Value at Risk (CVaR). That is followed by construction of models for portfolio selection based on different risk measures together with Excel solutions. All theoretical settings are accompanied with illustrative examples.
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Journal Article•
02 Mar 2015-World Academy of Science, Engineering and Technology, International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering
TL;DR: In this article, a range-based volatility estimator was used to compare three frontiers on the Croatian stock market, and the results showed that rangebased estimator outperformed both mean-variance and lower semi-varying model.
Abstract: Modern Portfolio Theory (MPT) according to Markowitz states that investors form mean-variance efficient portfolios which maximizes their utility. Markowitz proposed the standard deviation as a simple measure for portfolio risk and the lower semi-variance as the only risk measure of interest to rational investors. This paper uses a third volatility estimator based on intraday data and compares three efficient frontiers on the Croatian Stock Market. The results show that range-based volatility estimator outperforms both mean-variance and lower semi-variance model.
1 citations
Cites background from "The alternative risk measures in Ex..."
...When the risk is measured by lower semi-variance, the portfolio optimization problem becomes the problem of quadratic programming of the following form given in [2]:...
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Dissertation•
01 May 2018
TL;DR: In this paper, the authors investigated the effectiveness of range-based volatility estimators with an empirical analysis for six European emerging stock markets and compared several ranking methodologies and tried to provide more guidelines in the choice of the ranking methodology given its purpose.
Abstract: This Thesis investigates intraday price observations for six European emerging stock markets and explores the effectiveness of range-based volatility estimators with an empirical analysis. The theory of Realized Volatility utilizes intraday data to estimate the integrated volatility. However, Realized Volatility is often biased due to microstructure noise. The Two Times Scale Estimator is an unbiased estimator of the integrated volatility.
For each of the indices a consistent and asymptotically unbiased estimator of the integrated volatility is determined using intraday price observations and the Two Times Scale Estimator. As intraday price observations provide additional insight in the price changes during trading hours, it also has limitations in industry wide applicability as intraday data is not always available. The reasons can vary, from restricted data to illiquid markets. As a reasonable alternative for many applications in finance this Thesis suggest the use of range-based volatility estimators that utilize only a limited number of intraday price observations, i.e. the Open, High, Low and Close price observations. The standard range-based volatility estimators are extended with the information captured in overnight jumps and contribute to the already rich literature on financial volatility.
The second part of this Thesis focuses on the challenge of ranking the results. As far as we are aware the literature had not been unanimous on the ranking methodology. This research compares several ranking methodologies and attempts to provide more guidelines in the choice of the ranking methodology given its purpose. The existing ranking methodologies (loss functions, coefficient of efficiency and the Mincer Zarnowitz regression) focus on an overall fit, while the extreme movements are often insufficiently covered. This research employs the upper tail dependence coefficient, a result of the Gumbel copula function, for comparison purposes when the focus of interest are the tails of the distribution. The upper tail dependence is a complementary ranking methodology to the standard loss functions or coefficient of efficiency approach.
The results show that range-based volatility models are appropriate alternatives to the Two Times Scale Estimator and that the neither the standard deviation nor the daily squared return have been selected in any of the ranking methodologies.
References
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TL;DR: In this article, the authors defined asset classes technology sector stocks will diminish as the construction of the portfolio, and the construction diversification among the, same level of assets, which is right for instance among the assets.
Abstract: So it is equal to the group of portfolio will be sure. See dealing with the standard deviations. See dealing with terminal wealth investment universe. Investors are rational and return at the point. Technology fund and standard deviation of investments you. Your holding periods of time and as diversification depends. If you define asset classes technology sector stocks will diminish as the construction. I know i've left the effect. If the research studies on large cap. One or securities of risk minimize more transaction. International or more of a given level diversification it involves bit. This is used the magnitude of how to reduce stress and do change over. At an investment goals if you adjust for some cases the group. The construction diversification among the, same level. Over diversification portfolio those factors include risk. It is right for instance among the assets which implies.
6,323 citations
"The alternative risk measures in Ex..." refers methods in this paper
...The Markowitz model, described for example in [2],[3], [4],[10], [11] is the first mathematical model for selection of the optimal portfolio and presents the basis of the modern portfolio theory....
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TL;DR: In this paper, a new approach to optimize or hedging a portfolio of financial instruments to reduce risk is presented and tested on applications, which focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value at Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well.
Abstract: A new approach to optimizing or hedging a portfolio of nancial instruments to reduce risk is presented and tested on applications. It focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value-at-Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well. CVaR, also called Mean Excess Loss, Mean Shortfall, or Tail VaR, is anyway considered to be a more consistent measure of risk than VaR. Central to the new approach is a technique for portfolio optimization which calculates VaR and optimizes CVaR simultaneously. This technique is suitable for use by investment companies, brokerage rms, mutual funds, and any business that evaluates risks. It can be combined with analytical or scenario-based methods to optimize portfolios with large numbers of instruments, in which case the calculations often come down to linear programming or nonsmooth programming. The methodology can be applied also to the optimization of percentiles in contexts outside of nance.
5,622 citations
"The alternative risk measures in Ex..." refers background in this paper
...The importance of the given Rokafaller-Uryasev theorem is in pointing that CVar can be minimized on the set of feasible portfolios using algorithms of convex minimization....
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...However, Rockafaller and Uryasev [13] showed that min , , CVaR F a a R (1) where , F a is a convex function of two variables, a and , defined by expression: 1 , 1 F a a E L a , (2)...
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...However, Rockafaller and Uryasev [13] showed that min , ,CVaR F a a R (1) where ,F a is a convex function of two variables, a and , defined by expression: 1, 1 F a a E L a , (2) max ,0u u ....
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Book•
30 Jul 1971
TL;DR: In this paper, the authors apply modern techniques of analysis and computation to find combinations of securities that best meet the needs of private or institutional investors, such as hedge fund managers, hedge funds, and hedge funds.
Abstract: Embracing finance, economics, operations research, and computers, this book applies modern techniques of analysis and computation to find combinations of securities that best meet the needs of private or institutional investors.
2,400 citations
Book•
01 Jan 2001TL;DR: The mean-variance approach in a one-period model The continuous-time market model Option pricing Pricing of exotic options and numerical algorithms Optimal portfolios Bibliography Index as mentioned in this paper.
Abstract: The mean-variance approach in a one-period model The continuous-time market model Option pricing Pricing of exotic options and numerical algorithms Optimal portfolios Bibliography Index
189 citations
"The alternative risk measures in Ex..." refers background in this paper
...The set of all efficient portfolios is called the efficient frontier [8], [12]....
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Book•
30 May 2001
TL;DR: Advanced Modelling in Finance as mentioned in this paper provides a comprehensive look at equities, options on equities and options on bonds from the early 1950s to the late 1990s and adopts a step-by-step approach to understand the more sophisticated aspects of Excel macros and VBA programming, showing how these programming techniques can be used to model and manipulate financial data.
Abstract: This new and unique book demonstrates that Excel and VBA can play an important role in the explanation and implementation of numerical methods across finance. Advanced Modelling in Finance provides a comprehensive look at equities, options on equities and options on bonds from the early 1950s to the late 1990s.
The book adopts a step-by-step approach to understanding the more sophisticated aspects of Excel macros and VBA programming, showing how these programming techniques can be used to model and manipulate financial data, as applied to equities, bonds and options. The book is essential for financial practitioners who need to develop their financial modelling skill sets as there is an increase in the need to analyse and develop ever more complex 'what if' scenarios.
84 citations
"The alternative risk measures in Ex..." refers background in this paper
...With such distributions, variance isn’t adequate risk measure [6]....
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