Results 1  10
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23
An exploration of the forward premium puzzle in currency markets
 Review of Financial Studies
, 1997
"... A standard empirical finding is that expected changes in exchange rates and interest rate differentials across countries are negatively related, implying that uncovered interest rate parity is violated in the data. This article provides new empirical evidence that suggests that violations of uncover ..."
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Cited by 39 (2 self)
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A standard empirical finding is that expected changes in exchange rates and interest rate differentials across countries are negatively related, implying that uncovered interest rate parity is violated in the data. This article provides new empirical evidence that suggests that violations of uncovered interest rate parity, and its economic implications, depend on the sign of the interest rate differential. A framework related to term structure models is developed to account for the puzzling relationship between expected changes in exchange rates and interest rate differentials. Estimation results suggest that a particular term structure model can account for the puzzling empirical evidence. According to the hypothesis of uncovered interest rate parity, expected changes in the nominal exchange rate should be positively related to the difference in the nominal interest rate across countries. In particular, this hypothesis implies that the slope coefficient from the regression of the change in exchange rate on the interest rate differential should be one. The forward premium puzzle refers to the welldocumented empirical finding that the slope coefficient from this regression is significantly negative [see Bilson (1981),
Optimal Dynamic Portfolio Selection: MultiPeriod MeanVariance Formulation
 Math. Finance
, 1998
"... The meanvariance formulation by Markowitz in 1950s and its analytical solution by Merton in 1972 paved a foundation for modern portfolio selection analysis in single period. This paper considers an analytical optimal solution to the meanvariance formulation in multiperiod portfolio selection. Spec ..."
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Cited by 37 (1 self)
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The meanvariance formulation by Markowitz in 1950s and its analytical solution by Merton in 1972 paved a foundation for modern portfolio selection analysis in single period. This paper considers an analytical optimal solution to the meanvariance formulation in multiperiod portfolio selection. Specifically, analytical optimal portfolio policy and analytical expression of the meanvariance efficient frontier are derived in this paper for the multiperiod meanvariance formulation. An efficient algorithm is also proposed in this paper in finding an optimal portfolio policy to maximize a utility function of the expected value and the variance of the terminal wealth. Key Words: Multiperiod portfolio selection, multiperiod meanvariance formulation, utility function. This research was partially supported by the Research Grants Council of Hong Kong, grant no. CUHK 4130/97E. The authors very much appreciate the constructive comments from Professor Stanley R. Pliska. y Author to whom a...
Markowitz revisited: meanvariance models in financial portfolio analysis
 SIAM Rev
, 2001
"... Abstract. Meanvariance portfolio analysis provided the first quantitative treatment of the tradeoff between profit and risk. We describe in detail the interplay between objective and constraints in a number of singleperiod variants, including semivariance models. Particular emphasis is laid on avo ..."
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Cited by 24 (1 self)
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Abstract. Meanvariance portfolio analysis provided the first quantitative treatment of the tradeoff between profit and risk. We describe in detail the interplay between objective and constraints in a number of singleperiod variants, including semivariance models. Particular emphasis is laid on avoiding the penalization of overperformance. The results are then used as building blocks in the development and theoretical analysis of multiperiod models based on scenario trees. A key property is the possibility of removing surplus money in future decisions, yielding approximate downside risk minimization.
Markowitz’s meanvariance portfolio selection with regime switching: A continuoustime model
 SIAM Journal on Control and Optimization
"... ..."
The Evolution of Portfolio Rules and the Capital Asset Pricing Model
, 1998
"... The aim of this paper is to test the performance of the standard version of CAPM in an evolutionary framework. We imagine a heterogeneous population of longlived agents who invest their wealth according to dierent portfolio rules and we ask what is the fate of those who happen to behave as prescrib ..."
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Cited by 14 (3 self)
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The aim of this paper is to test the performance of the standard version of CAPM in an evolutionary framework. We imagine a heterogeneous population of longlived agents who invest their wealth according to dierent portfolio rules and we ask what is the fate of those who happen to behave as prescribed by CAPM. In a complete securities market with aggregate uncertainty, we prove that traders who either believe in CAPM and use it as a rule of thumb, or are endowed with genuine meanvariance preferences, under some very weak conditions, vanish in the long run. We show that a sucient condition to drive CAPM or mean variance traders wealth shares to zero is that an investor endowed with a logarithmic utility function enters the market. We nally check the robustness of our results allowing for dierent kinds of heterogeneity among traders.
2002b). “MeanSemivariance Behavior: An Alternative Behavioral Model.” Working paper
 IESE Business School
"... Abstract: The most widelyused measure of an asset’s risk, beta, stems from an equilibrium in which investors display meanvariance behavior. This behavioral criterion assumes that portfolio risk is measured by the variance (or standard deviation) of returns, which is a questionable measure of risk. ..."
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Cited by 4 (2 self)
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Abstract: The most widelyused measure of an asset’s risk, beta, stems from an equilibrium in which investors display meanvariance behavior. This behavioral criterion assumes that portfolio risk is measured by the variance (or standard deviation) of returns, which is a questionable measure of risk. The semivariance of returns is a more plausible measure of risk (as Markowitz himself admits) and is backed by theoretical, empirical, and practical considerations. It can also be used to implement an alternative behavioral criterion, meansemivariance behavior, that is almost perfectly correlated to both expected utility and the utility of mean compound return. Although the analytical framework and results are general, they are particularly relevant for emerging markets.
Growth Optimal Investment Strategy Efficacy: An application on long run Australian equity data
, 2002
"... A number of investment strategies designed to maximise portfolio growth are tested on a long run Australian equity data set. The application of these growth optimal portfolio techniques produces impressive rates of growth, despite the fact that the assumptions of normality and stability that underli ..."
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Cited by 3 (0 self)
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A number of investment strategies designed to maximise portfolio growth are tested on a long run Australian equity data set. The application of these growth optimal portfolio techniques produces impressive rates of growth, despite the fact that the assumptions of normality and stability that underlie the growth optimal model are shown to be inconsistent with the data. Growth optimal portfolios are constructed by rebalancing the portfolio weights of 25 Australian listed companies each month with the aim of maximising portfolio growth. These portfolios are shown to produce growth rates that are up to twice those of the benchmark, equally weighted, minimum variance and 15% drift portfolios. The key to the success of the classic, no shortsales, growth optimal portfolio strategy lies in its ability to select for portfolio inclusion a small number of Australian stocks during their high growth periods. The study introduces a variant of ridge regression to form the basis of one of the growth focussed investment strategies. The ridge growth optimal technique overcomes the problem of numerically unstable portfolio weights that dogs the formation of shortsales allowed growth portfolios. For the short sales not allowed growth portfolio, the use of the ridge estimator produces increased asset diversification in the growth portfolio, while at the same time reducing the amount of portfolio adjustment required in rebalancing the growth portfolio from period to period. B.F.Hunt Graduate School of Business University of Technology Sydney Ben.hunt@uts.edu.au
On the history of the Growth Optimal Portfolio
, 2005
"... The growth optimal portfolio (GOP) is a portfolio which has a maximal expected growth rate over any time horizon. As a consequence, this portfolio is sure to outperform any other significantly different strategy as the time horizon increases. This property in particular has fascinated many researche ..."
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Cited by 3 (0 self)
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The growth optimal portfolio (GOP) is a portfolio which has a maximal expected growth rate over any time horizon. As a consequence, this portfolio is sure to outperform any other significantly different strategy as the time horizon increases. This property in particular has fascinated many researchers in finance and mathematics created a huge and exciting literature on growth optimal investment. This paper attempts to provide a comprehensive survey of the literature and applications of the GOP. In particular, the heated debate of whether the GOP has a special place among portfolios in the asset allocation decision is reviewed as this still seem to be an area where some misconceptions exists. The survey also provides an extensive review of the recent use of the GOP as a pricing tool, in for instance the socalled “benchmark approach”. This approach builds on the numéraire property of the GOP, that is, the fact that any other asset denominated in units of the GOP become a supermartingale
Optimal Hedging Strategy For A Portfolio Investment Problem With Additional Constraints
, 1999
"... . Consider a portfolio investment problem in a multistock diffusion stochastic financial market model with random appreciation rates, where additional constraints are required to be satisfied with probability 1. A general performance index is introduced. It covers many practically important perform ..."
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Cited by 2 (2 self)
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. Consider a portfolio investment problem in a multistock diffusion stochastic financial market model with random appreciation rates, where additional constraints are required to be satisfied with probability 1. A general performance index is introduced. It covers many practically important performance indeces as special cases. Admissible strategies are assumed to use only observations of market prices. The appreciation rates are not assumed to be available. An optimal hedging strategy independent of current observation of the appreciation rates is obtained. AMS(MOS) subject classification: 49K45, 60G15, 93E20 1 Introduction The paper investigates an investment problem in a stochastic diffusion model of a securities market which consists of a risk free bond or bank account and a finite number of risky stocks. It is assumed that the prices of the stocks On leave from The Institute of Mathematics and Mechanics, St.Petersburg State University 1 OPTIMAL STRATEGY FOR INVESTMENT PROBL...
Geometric Mean Maximization: An Overlooked Portfolio Approach?
"... Academics and practitioners usually optimize portfolios on the basis of mean and variance. They set the goal of maximizing riskadjusted returns measured by the Sharpe ratio and thus determine their optimal exposures to the assets considered. However, there is an alternative criterion that has an eq ..."
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Cited by 1 (0 self)
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Academics and practitioners usually optimize portfolios on the basis of mean and variance. They set the goal of maximizing riskadjusted returns measured by the Sharpe ratio and thus determine their optimal exposures to the assets considered. However, there is an alternative criterion that has an equally plausible underlying idea; geometric mean maximization aims to maximize the growth of the capital invested, thus seeking to maximize terminal wealth. This criterion has several attractive properties and is easy to implement, and yet it does not seem to be very widely used by practitioners. The ultimate goal of this article is to explore potential empirical reasons that may explain why this is the case. The data, however, does not seem to suggest any clear answer, and, therefore, the question posed in the title remains largely unanswered: Are practitioners overlooking a useful criterion?