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The Valuation of Structured
Products: Empirical Findings for the Swiss Market
by Andreas
Grunbichler & Hanspeter Wohlwend
University of Zurich
Abstract
This article analyses the valuation of 192 structured products
without a capital guarantee. In contrast to similar studies,
this investigation takes in both the primary and the secondary
market. Its central element is a comparison of the implied
volatilities of the options contained in the structured products
with those of comparable EUREX options...
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Value-at-Risk Based Risk
Management: Optimal Policies and Asset Prices
by Suleyman Basak & Alex Shapiro
London Business School & New York University
February, 2001
Abstract
This article analyzes optimal, dynamic portfolio and
wealth/consumption policies of utility maximizing investors who
must also manage market-risk exposure using Value-at-Risk (VaR).
We find that VaR risk managers often optimally choose a larger
exposure to risky assets than non risk managers, and
consequently incur larger losses, when losses occur. We suggest
an alternative risk-management model, based on the expectation
of a loss, to remedy the shortcomings of VaR...
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Value at Risk Calculations,
Extreme Events, and Tail Estimation
by Salih N. Neftci
Department of Mathematics ETHZ, CH-8092 Zurich, Switzerland
Abstract
The notion of extreme movements in asset prices is implicit in
current risk management practices. Capital adequacy assumes a
threshold that classifies
observed changes in market risk factors either as extreme or
ordinary. A probability is first chosen to measure the
“extremeness” of events that may affect a particular portfolio.
This probability then determines the proper threshold...
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Value–at–Risk and Extreme Returns
by Jon Danielsson & Casper G. de Vries
London School of Economics & Tinbergen Institute
January, 2000
Abstract
Accurate prediction of the frequency of extreme events is of
primary importance in many financial applications such as
Value–at–Risk (VaR) analysis. We propose a semi–parametric
method for VaR evaluation. The largest risks are modelled
parametrically, while smaller risks are captured by the
non–parametric empirical distribution function...
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VALUE AT RISK WHEN DAILY CHANGES
IN MARKET VARIABLES ARE NOT NORMALLY DISTRIBUTED
by John Hull & Alan White
November, 1997
Abstract
This paper proposes a new model for calculating VaR where the
user is free to choose any probability distributions for daily
changes in the market variables and parameters of the
probability distributions are subject to updating schemes such
as GARCH. Transformations of the probability distributions are
assumed to be multivariate normal. The model is appealing in
that the calculation of VaR is relatively straightforward and
can make use of the RiskMetrics or a similar database...
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Volatility and Cross Correlation
Across Major Stock Markets
by Latha Ramchand & Raul Susmel
University of Houston - Department of Finance
December 4, 1997
Abstract
Several papers have documented the fact that correlations across
major stock markets are higher when markets are more volatile -
this is done by comparing unconditional correlations over
sub-periods or by using conditional correlations that are time
varying. In this paper we examine the relation between
correlation and variance in a conditional time and state varying
framework. We use a switching ARCH (SWARCH) technique that does
two things.
One, it enables us to model variance as state varying. Two, a
bivariate SWARCH model allows us to go from conditional variance
to state varying covariances and correlations and hence test for
differences in correlations across variance regimes. We find
that the correlations between the U.S. and other world markets
are on average 2 to 3.5 times higher when the U.S. market is in
a high variance state as compared to a low variance regime. We
also find that, compared to a GARCH framework, the portfolio
choices resulting from our SWARCH model lead to higher Sharpe
ratios.
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| HEDGE FUND RISK AND OTHER
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as mutual funds, including mutual fund requirements to provide
certain periodic and standardized pricing and valuation information
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ability, sophistication/experience and willingness to bear the
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place undue reliance on hypothetical or pro forma performance.
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risk.
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higher risk.
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regardless of any positive return- will offset the Hedge Fund’s
trading profits. In a fund of funds or similar structure, fees are
generally charged at the fund as well as the sub-fund levels;
therefore fees charged investors will be higher that those charged
if the investor invested directly in the sub-fund(s).
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investment in the Hedge Fund is suitable for the investor in light
of the investor’s investment objectives, financial circumstances and
tax situation.
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representation is made that any fund will or is likely to achieve
its objectives or that any investor will or is likely to achieve
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Before making any investment, you should thoroughly review the
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Indices also may contain securities or types of securities that are
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