نتایج جستجو برای: downside risk

تعداد نتایج: 944273  

Journal: :Operations Research 2005
Arjen Siegmann André Lucas

We consider a dynamic asset allocation problem formulated as a mean-shortfall model in discrete time. A characterization of the solution is derived analytically under general distributional assumptions for serially independent risky returns. The solution displays risk taking under shortfall, as well as a specific form of time diversification. Also, for a representative stock-return distribution...

2002
Haiqin Yang Irwin King Laiwan Chan

Recently, Support Vector Regression (SVR) has been applied to financial time series prediction. Typical characteristics of financial time series are non-stationary and noisy in nature. The volatility, usually time-varying, of the time series is therefore some valuable information about the series. Previously, we had proposed to use the volatility to adaptively change the width of the margin of ...

2003
Arjen Siegmann

This paper analyzes optimal investment policies for pension funds of a defined benefit (DB) type. The nature of a DB fund induces a natural modeling of preferences being of the mean-downside risk type. With compensation for inflation as an explicit goal of a pension fund, a natural reference point for the risk measure is the future (indexed) value of the liabilities. Results are presented for d...

2015
Benoît Sévi

a r t i c l e i n f o Keywords: Risk-return tradeoff Downside-risk MIDAS regressions HAR model Intraday data This paper considers the downside-risk aversion of investors as an explanation for the risk-return trade-off. We test empirically this hypothesis using intraday data along with the recent measure of downside-risk called realized semivariance developed in Barndorff-Nielsen et al. (2010). ...

2001
Andre Lucas Cees L. Dert

Portfolio insurance strategies based on options typically treat the investment in the risky asset, e.g., stock, as fixed. We show in a mean/downside-risk framework that such a strategy is inefficient. Using at the money put options, expected returns can be increased by more than 250 basis points without taking on more risk. Gains can become arbitrarily large when one uses options with extremely...

2008
Anil Khuman Dietmar Maringer Nick Constantinou

Constant Proportion Portfolio Insurance (CPPI) is a dynamic portfolio management strategy that is currently of popular interest in both industry and academic research. The CPPI methodology is designed to guarantee, to the buyer, a minimum payoff at maturity using a portfolio comprised only of one risky asset and one riskless asset. The goal is to allow an amount of participation in capital mark...

Journal: :Fuzzy Sets and Systems 2007
Enriqueta Vercher José D. Bermúdez José Vicente Segura

This paper presents two fuzzy portfolio selection models where the objective is to minimize the downside risk constrained so that a given expected return should be achieved. We assume that the rates of returns on securities are approximated as LR-fuzzy numbers of the same shape, and that the expected return and risk are evaluated by interval-valued means. We establish the relationship between t...

2015
W. V. Harlow Keith C. Brown Jeffrey Brown Dan Cassidy Jeremy Crean

Despite its clear importance, there is no consensus on the optimal asset allocation strategy for retirement investors of varying age, gender, and risk tolerance. This study analyzes the allocation question by focusing on the downside risks that result from the joint uncertainty over investment returns and life expectancy. Using a new analytical approach, we show that concentrating on the severi...

2014
Andriy Bodnaruk Andrei Simonov

Using survey-based measures of loss aversion of mutual fund managers, we study the effects of institutional investor preferences on their investment decisions, performance, and career outcomes. Funds managed by managers with higher aversion to losses take on less downside risk and have lower risk-adjusted returns. More loss averse managers are more likely to have their contracts terminated. Our...

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