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tactical timing of low volatility equity strategies
tactical timing of low volatility equity strategies

... the low volatility strategy was still above 9%. Moreover, in terms of risk-adjusted returns as measured by the Sharpe Ratio the two were even closer (0.09 difference). Though the expectation of interest rates increasing further might be widespread, generally central banks have indicated that this wi ...
A bank is a place that will lend you money if you can prove
A bank is a place that will lend you money if you can prove

... Using Option Valuation Models to Value Loans • Figure 4.1 loan payoff = Figure 4.2 payoff to the writer of a put option on a stock. • Value of put option on stock = equation (4.1) = f(S, X, r, , ) where S=stock price, X=exercise price, r=risk-free rate, =equity volatility,=time to maturity. Val ...
Value at Risk - Binus Repository
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...  Value portfolio today  Sample once from the multivariate distributions of the xi  Use the xi to determine market variables at end of one day  Revalue the portfolio at the end of day Options, Futures, and Other Derivatives 6th Edition, Copyright © John C. Hull 2005 ...
NBER WORKING PAPER SERIES INTERNATIONAL CONSUMPTION RISK IS SHARED AFTER ALL:
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Taste, information, and asset prices: Implications for the valuation of
Taste, information, and asset prices: Implications for the valuation of

... Our analysis starts with a model of a pure exchange economy with a single risky asset and perfectly competitive, risk-averse investors. We assume that there are two types of investors who we label type 1 and type 2. The risky asset represents shares in a …rm that generates cash and engages in CSR ac ...
Cumulative Prospect Theory, Option Prices, and the Variance
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... According to asset pricing theory, assets earn risk premiums when they are exposed to underlying systematic risk factors. It is however still an unanswered question what these risk factors are. The research around this topic can be split into two groups. First, there are theoretical approaches tryin ...
Backtesting Value-at-Risk based on Tail Losses Woon K. Wong
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... rightly decided the frequency-of-exceptions method that is simple and straightforward to implement. Though size-based backtests of ES have recently been proposed by Berkowitz (2001) and Kerkhof and Melenberg (2004), they rely on large sample to converge to the required limiting distribution. The bac ...
Options on Energy Portfolios in an HJM Framework
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... nature of spot prices, currency exchange rates and convenience yields. Interest rate risk is also mentioned, but is not included in the numerical implementation. The analytic framework is heavily inspired by Miltersen and Schwartz (1998); however, while they allow the interest rate to be stochastic ...
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... to equity prices in the estimation leads to significantly different estimates. Including bond price data in the estimation also seems to reduce the equity pricing errors of the models, sometimes quite dramatically. This in turn means that whatever the merit of structural models, if they are estimate ...
Mathematical modeling and analysis of options with jump
Mathematical modeling and analysis of options with jump

... one with exponential and the second with an absolute value function). All of these researchers assumed that the price of the underlying asset and its volatility are uncorrelated. Heston (1993) releases this assumption when offered a model that uses a square-root volatility function and a volatility ...
Sensitivity, Hedging, and the "Greeks" (PDF)
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... (c) For a particular scripting language of your choice, modify the script to draw a graph of Γ versus t for a call option on an at-themoney stock, with K = 50, r = 0.10, σ = 0.25, T − t = 0.25. (d) For a particular scripting language of your choice, modify the script to draw the graph of Γ versus S ...
CTAs: Shedding light on the black box
CTAs: Shedding light on the black box

... CTA allocation. 6. CTAs can disappoint on a standalone basis (calendar annual or short term in general) but make a lot of sense in a portfolio context. They broadly de-risk traditional assets while re-risking hedge fund portfolios. This may not be the consensus view but we believe it was the source ...
THE EVOLVING RESIDENTIAL GROUND RENT MARKET
THE EVOLVING RESIDENTIAL GROUND RENT MARKET

... over a longer period of time directly from housebuilders or existing investors. The advantages of such an approach include the avoidance of having to bid overly aggressively to secure stock. However, such a strategy takes a significant amount of time to employ and build scale. Larger investors have ...
Expected Returns on Major Asset Classes
Expected Returns on Major Asset Classes

... DDM-based expected return on stocks. According to this way of thinking, the equity risk premium is an artifact, a derived quantity that depends on the time and place for which it is being estimated. Other premia, or differences of asset class expected returns, have the same characteristic. Ibbotson ...
Credit Ratings and The Cross
Credit Ratings and The Cross

... significant only during periods of credit rating downgrades. During such periods, low quality firms experience substantial deterioration in their operating and financial performance, and are sold by institutional investors leading to considerable price drops. The deteriorating fundamental performance i ...
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Modern portfolio theory

Modern portfolio theory (MPT) is a theory of finance that attempts to maximize portfolio expected return for a given amount of portfolio risk, or equivalently minimize risk for a given level of expected return, by carefully choosing the proportions of various assets. Although MPT is widely used in practice in the financial industry and several of its creators won a Nobel memorial prize for the theory, in recent years the basic assumptions of MPT have been widely challenged by fields such as behavioral economics.MPT is a mathematical formulation of the concept of diversification in investing, with the aim of selecting a collection of investment assets that has lower overall risk than any other combination of assets with the same expected return. This is possible, intuitively speaking, because different types of assets sometimes change in value in opposite directions. For example, to the extent prices in the stock market move differently from prices in the bond market, a combination of both types of assets can in theory generate lower overall risk than either individually. Diversification can lower risk even if assets' returns are positively correlated.More technically, MPT models an asset's return as a normally or elliptically distributed random variable, defines risk as the standard deviation of return, and models a portfolio as a weighted combination of assets, so that the return of a portfolio is the weighted combination of the assets' returns. By combining different assets whose returns are not perfectly positively correlated, MPT seeks to reduce the total variance of the portfolio return. MPT also assumes that investors are rational and markets are efficient.MPT was developed in the 1950s through the early 1970s and was considered an important advance in the mathematical modeling of finance. Since then, some theoretical and practical criticisms have been leveled against it. These include evidence that financial returns do not follow a normal distribution or indeed any symmetric distribution, and that correlations between asset classes are not fixed but can vary depending on external events (especially in crises). Further, there remains evidence that investors are not rational and markets may not be efficient. Finally, the low volatility anomaly conflicts with CAPM's trade-off assumption of higher risk for higher return. It states that a portfolio consisting of low volatility equities (like blue chip stocks) reaps higher risk-adjusted returns than a portfolio with high volatility equities (like illiquid penny stocks). A study conducted by Myron Scholes, Michael Jensen, and Fischer Black in 1972 suggests that the relationship between return and beta might be flat or even negatively correlated.
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