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@ARTICLE{Acerbi2002,
author = {Acerbi, Carlo and Tasche, Dirk},
title = {Expected Shortfall: A Natural Coherent Alternative to Value at Risk},
journal = {Economic Notes},
year = {2002},
volume = {31},
pages = {379-388},
number = {2},
abstract = {We discuss the coherence properties of expected shortfall (ES) as
a financial risk measure. This statistic arises in a natural way
from the estimation of the ‘average of the 100% worst losses’
in a sample of returns to a portfolio. Here p is some fixed confidence
level. We also compare several alternative representations of ES
which turn out to be more appropriate for certain purposes.},
owner = {brian},
timestamp = {2007.09.08}
}
@ARTICLE{Acerbi2002a,
author = {Acerbi, Carlo and Tasche, Dirk},
title = {On the Coherence of Expected Shortfall},
journal = {Journal of Banking and Finance},
year = {2002},
volume = {26},
pages = {1487-1503},
number = {7},
abstract = {Expected Shortfall (ES) in several variants has been proposed as remedy
for the defi-ciencies of Value-at-Risk (VaR) which in general is
not a coherent risk measure. In fact, most definitions of ES lead
to the same results when applied to continuous loss distributions.
Differences may appear when the underlying loss distributions have
discontinuities. In this case even the coherence property of ES can
get lost unless one took care of the details in its definition. We
compare some of the definitions of Expected Shortfall, pointing out
that there is one which is robust in the sense of yielding a coherent
risk measure regardless of the underlying distributions. Moreover,
this Expected Shortfall can be estimated effectively even in cases
where the usual estimators for VaR fail.
Key words: Expected Shortfall; Risk measure; worst conditional expectation;
tail con-ditional expectation; value-at-risk (VaR); conditional value-at-risk
(CVaR); tail mean; co-herence; quantile; sub-additivity.},
owner = {brian},
timestamp = {2007.09.08}
}
@ARTICLE{Agarwal2004,
author = {Agarwal, Vikas and Naik, Narayan},
title = {Risks and portfolio decisions involving hedge funds},
journal = {Review of Financial Studies},
year = {2004},
volume = {17},
pages = {63-98},
number = {1},
owner = {peter},
timestamp = {2008.02.11}
}
@ARTICLE{Agarwal2002,
author = {Agarwal, Vikas and Naik, Narayan},
title = {Characterizing Systematic Risk of Hedge Funds with Buy-and-Hold and
Option-based Strategies},
journal = {Working Paper. London Business School},
year = {2002},
owner = {brian},
timestamp = {2008.05.07}
}
@ARTICLE{Agarwal2000,
author = {Agarwal, Vikas and Naik, Narayan},
title = {Generalized Style Analysis of Hedge Funds},
journal = {Journal of Asset Management},
year = {2000},
volume = {1},
pages = {93-109},
number = {1},
owner = {brian},
timestamp = {2008.05.07}
}
@ARTICLE{Agarwal1999,
author = {Agarwal, Vikas and Naik, Narayan},
title = {Multi-period Performance Persistence Analysis of Hedge Funds},
journal = {Journal of Financial and Quantitative Analysis},
year = {1999},
volume = {35},
pages = {337-342},
number = {3},
owner = {brian},
timestamp = {2008.05.07}
}
@BOOK{AmencLeSourd2003,
title = {Portfolio Theory and Performance Analysis},
publisher = {Wiley Finance},
year = {2003},
author = {Amenc, No\"{e}l and Le Sourd, V\'{e}ronique},
owner = {peter},
timestamp = {2007.11.16}
}
@TECHREPORT{Amenc2005,
author = {Amenc, No\"{e}l and Malaise, Philippe and Vaissi\'{e}, Mathieu},
title = {Edhec Funds of Hedge Funds Reporting Survey : A Return-Based Approach
to Funds of Hedge Funds Reporting},
institution = {Edhec Risk and Asset Management Research Centre},
year = {2005},
month = {January},
file = {Edhec Funds of Hedge Funds Reporting Survey.pdf:/home/brian/docs/Research/Edhec Funds of Hedge Funds Reporting Survey.pdf:PDF},
owner = {brian},
timestamp = {2007.09.01}
}
@ARTICLE{Amenc2002,
author = {Amenc, No\"{e}l and Martellini, Lionel},
title = {Portfolio optimization and Hedge Fund Style Allocation Decisions},
journal = {Journal of Alternative Investment},
year = {2002},
volume = {5},
pages = {7-20},
number = {2},
abstract = {This article attempts to evaluate the out-of-sample performance of
an improved estimator of the covariance structure of hedge fund index
returns, focusing on its use for optimal portfolio selection. Using
data from CSFB/Tremont hedge fund indices, we find that ex-post volatility
of minimum variance portfolios generated using implicit factor-based
estimation techniques is between 1.5 and 6 times lower than that
of a value-weighted benchmark, such differences being both economically
and statistically significant. This strongly indicates that optimal
inclusion of hedge funds in an investor portfolio can potentially
generate a dramatic decrease in the portfolio volatility on an out-of-sample
basis. Differences in mean returns, on the other hand, are not statistically
significant, suggesting that the improvement in terms of risk control
does not necessarily come at the cost of lower expected returns.},
file = {:/home/brian/Portfolio_Optimization_and_Hedge_Fund_Style_Allocation_Decisions_2002_Amenc_Martellini_SSRN-id305006.pdf:PDF},
owner = {brian},
timestamp = {2007.08.19},
url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=305006}
}
@ARTICLE{Amenc2003,
author = {Amenc, No\"{e}l and Martellini, Lionel and Vaiss\'{e}, Mathieu},
title = {Benefits and Risks of Alternative Investment Strategies},
journal = {Journal of Asset Management},
year = {2003},
volume = {4},
pages = {96-118},
number = {2},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{Ardia2010,
author = {Ardia, David and Boudt, Kris and Carl, Peter and Mullen, Katharine
and Peterson, Brian},
title = {Differential evolution (DEoptim) for non-convex portfolio optimization},
journal = {R Journal, forthcoming},
year = {2011},
owner = {Administrator},
timestamp = {2010.05.30}
}
@BOOK{Aronson2007,
title = {Evidence-Based Technical Analysis},
publisher = {Wiley},
year = {2007},
author = {David Aronson},
owner = {peter},
timestamp = {2007.11.04}
}
@ARTICLE{Artzner1999,
author = {Artzner, Philippe and Delbaen, Freddy and Eber, Jean-Marc and Heath,
David},
title = {Coherent Measures of Risk},
journal = {Mathematical Finance},
year = {1999},
volume = {9},
pages = {203-228},
number = {3},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Artzner1997,
author = {Artzner, Philippe and Delbaen, Freddy and Eber, Jean-Marc and Heath,
David},
title = {Thinking Coherently},
journal = {RISK},
year = {1997},
volume = {10},
pages = {68-71},
number = {10},
owner = {brian},
timestamp = {2007.11.06}
}
@MISC{Artzner2002,
author = {Philippe Artzner and Freddy Delbaen and Jean-Marc Eber and David
Heath and Heyjin Ku},
title = {Coherent Multiperiod Risk Measurement},
howpublished = {working paper, Department of Mathematics, ETH-Z\"{u}rich.},
month = {February},
year = {2002},
abstract = {We explain why and how to deal with the definition, acceptability,
computation and management of risk in a genuinely multitemporal way.
Coherence axioms provide a representation of a risk-adjusted valuation.
Some special cases of practical interest allowing for easy recursive
computations are presented. The multiperiod extension of Tail VaR
is discussed.},
citeseerurl = {http://citeseer.ist.psu.edu/artzner02coherent.html},
file = {Coherent_Multiperiod_Risk_Measurement_2002_Artzner.pdf:/home/brian/docs/Research/Coherent_Multiperiod_Risk_Measurement_2002_Artzner.pdf:PDF},
owner = {brian},
text = {Artzner, P, Delbaen, F., Eber, J.-M., Heath, D. & Ku, H. (2002) Coherent
multiperiod risk measurement, working paper, Department of Mathematics,
ETH-Z\"{u}rich.},
timestamp = {2007.08.22},
url = {http://citeseer.ist.psu.edu/artzner02coherent.html}
}
@ARTICLE{Asness2001,
author = {Asness, Cliff S. and Krail, Robert and Liew, John M.},
title = {Do Hedge Funds Hedge?},
journal = {SSRN eLibrary},
year = {2001},
doi = {10.2139/ssrn.252810},
language = {English},
location = {http://ssrn.com/paper=252810},
owner = {peter},
publisher = {SSRN},
timestamp = {2007.11.17},
type = {Working Paper Series}
}
@MISC{AthaydeFlores2004,
author = {Athayde, Gustavo M. and Flores Jr, Renat\^{o} G.},
title = {Do Higher Moments Really Matter in Portfolio Choice?},
howpublished = {Graduate School of Economics, Getulio Vargas Foundation (Brazil)
in its series Economics Working Papers (Ensaios Economicos da EPGE)
with number 574},
month = {December},
year = {2004},
number = {574},
owner = {peter},
timestamp = {2007.11.03}
}
@BOOK{Bacon2004,
title = {Practical Portfolio Performance Measurement and Attribution},
publisher = {Wiley},
year = {2004},
author = {Bacon, Carl},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Baillie1992,
author = {Baillie, Richard T. and Bollerslev, Tim},
title = {Prediction in Dynamic Models with Time-Dependent Conditional Variances},
journal = {Journal of Econometrics},
year = {1992},
volume = {52},
pages = {91-113},
number = {1-2},
owner = {brian},
timestamp = {2007.10.30}
}
@INBOOK{Bali2004,
chapter = {Alternative Approaches to Estimating VaR for Hedge Fund Portfolios},
pages = {253-277},
title = {Intelligent Hedge Fund Investing},
publisher = {RiskBooks},
year = {2004},
editor = {Barry Schachter},
author = {Bali, Turan G. and Gokcan, Suleyman},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Bali2007,
author = {Bali, Turan G. and Gokcan, Suleyman and Liang, Bing},
title = {Value at Risk and the Cross-Section of Hedge Fund Returns},
journal = {Journal of Banking and Finance},
year = {2007},
volume = {31},
pages = {1135-1166},
number = {4},
abstract = {Using two large hedge fund databases, this paper empirically tests
the presence and significance of a cross-sectional relation between
hedge fund returns and value at risk (VaR). The univariate and bivariate
portfolio-level analyses as well as the fund-level regression results
indicate a significantly positive relation between VaR and the cross-section
of expected returns on live funds. During the period of January 1995
to December 2003, the live funds with high VaR outperform those with
low VaR by an annual return difference of 9%. This risk-return tradeoff
holds even after controlling for age, size, and liquidity factors.
Furthermore, the risk profile of defunct funds is found to be different
from that of live funds. The relation between downside risk and expected
return is found to be negative for defunct funds because taking high
risk by these funds can wipe out fund capital, and hence they become
defunct. Meanwhile, voluntary closure makes some well performed funds
with large assets and low risk fall into the defunct category. Hence,
the risk-return relation for defunct funds is more complicated than
what implies by survival. We demonstrate how to distinguish live
funds from defunct funds on an ex ante basis. A trading rule based
on buying the expected to live funds and selling the expected to
disappear funds provides an annual profit of 8–10% depending on
the investment horizons.},
keywords = {Hedge fund; Value at risk; Cross-section of expected returns; Liquidity;
Voluntary closure},
owner = {brian},
timestamp = {2007.08.19},
url = {http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VCY-4MG6P7X-3&_user=10&_coverDate=04%2F30%2F2007&_rdoc=1&_fmt=summary&_orig=browse&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=aa98941c82f67e4f1d0dabad4a769c62}
}
@BOOK{Becker1988,
title = {The New {S} Language},
publisher = {Chapman \& Hall},
year = {1988},
author = {Richard A. Becker and John M. Chambers and Allan R. Wilks},
address = {London},
abstract = {This book is often called the ``\emph{Blue Book}'', and introduced
what is now known as S version 2.},
owner = {brian},
timestamp = {2008.04.27}
}
@BOOK{Bernstein1996,
title = {Against the Gods: The Remarkable Story of Risk},
publisher = {John Wiley {\&} Sons},
year = {1996},
author = {Peter L. Bernstein},
isbn = {471121045},
owner = {peter}
}
@ARTICLE{Bertsimas2004,
author = {Dimitris Bertsimas and Geoffrey J. Lauprete and Alexander Samarov},
title = {Shortfall as a Risk Measure: Properties, Optimization and Applications},
journal = {Journal of Economic Dynamics and Control},
year = {2004},
volume = {28},
pages = {1353-1381},
number = {7},
abstract = {Motivated from second-order stochastic dominance, we introduce a risk
measure that we call shortfall. We examine shortfall’s properties
and discuss its relation to such commonly used risk measures as standard
deviation, VaR, lower partial moments, and coherent risk measures.
We show that the mean-shortfall optimization problem, unlike mean-VaR,
can be solved efficiently as a convex optimization problem, while
the sample mean-shortfall portfolio optimization problem can be solved
very efficiently as a linear optimization problem. We provide empirical
evidence (a) in asset allocation, and (b) in a problem of tracking
an index using only a limited number of assets that the mean-shortfall
approach might have advantages over mean-variance.},
file = {:/home/brian/docs/Research/Shortfall_as_a_risk_measure_Bertsimas2004.pdf:PDF},
owner = {brian},
timestamp = {2008.01.02}
}
@BOOK{Bodie1995,
title = {Investments},
publisher = {Irwin},
year = {1995},
author = {Bodie, Z., and Kane, A., and Marcus, A.},
owner = {brian},
timestamp = {2007.08.19}
}
@MISC{PortfolioAnalytics,
author = {Kris Boudt and Peter Carl and Brian G. Peterson},
title = {{PortfolioAnalytics}: Portfolio Analysis, including numeric methods
for optimization of portfolios},
year = {2010},
note = {R package version 0.0.6},
owner = {brian},
timestamp = {2008.02.01},
url = {http://braverock.com/R/}
}
@INCOLLECTION{BoudtPetersonCarl2008,
author = {Boudt, Kris and Peterson, Brian G. and Carl, Peter},
title = {Hedge fund portfolio selection with modified expected shortfall},
booktitle = {Computational Finance and its Applications III},
publisher = {WIT, Southampton},
year = {2008},
editor = {Brebbia, C.A. and Constantino, M. and Larran, M.},
series = {WIT Transactions on Modelling and Simulation},
owner = {n06054},
timestamp = {2008.05.14}
}
@ARTICLE{Boudt2007,
author = {Boudt, Kris and Peterson, Brian G. and Croux, Christophe},
title = {Estimation and Decomposition of Downside Risk for Portfolios with
Non-Normal Returns},
journal = {Journal of Risk},
year = {2008},
pages = {Winter 2008, 79-103},
owner = {brian},
timestamp = {2007.09.12}
}
@TECHREPORT{Burns2005,
author = {Burns, Patrick},
title = {A Guide for the Unwilling S User},
institution = {Burns Statistics},
year = {2005},
owner = {brian},
timestamp = {2008.05.07},
url = {http://www.burns-stat.com/pages/Tutor/unwilling_S.pdf}
}
@BOOK{CampbellLoMackinlay1997,
title = {The Econometrics of Financial Markets},
publisher = {Princeton University Press},
year = {1997},
author = {John Y. Campbell and Andrew Lo and Craig MacKinlay},
address = {Princeton},
owner = {peter},
timestamp = {2007.09.20}
}
@ARTICLE{Campbell2001,
author = {Rachel Campbell and Ronald Huisman and Kees Koedijk},
title = {Optimal Portfolio Selection in a Value at Risk Framework},
journal = {Journal of Banking and Finance},
year = {2001},
volume = {25},
pages = {1789-1804},
number = {9},
abstract = {In this paper, we develop a portfolio selection model which allocates
financial assets by maximising expected return subject to the constraint
that the expected maximum loss should meet the Value-at-Risk limits
set by the risk manager. Similar to the mean±variance approach a
performance index like the Sharpe index is constructed.Furthermore
when expected returns are assumed to be normally distributedwe show
that the model provides almost identical results to the mean±variance
approach.We provide an empirical analysis using two risky assets:
US stocks and bonds. The results highlight the influence of both
non-normal characteristics of the expected return distribution and
the length of investment time horizon on the optimal portfolio selection.},
file = {Optimal portfolio selection in a Value-at-Risk framework 2001 Campbell Huisman Koedijk JBF01.pdf":"/home/brian/docs/Research/Optimal portfolio selection in a Value-at-Risk framework 2001 Campbell Huisman Koedijk JBF01.pdf":PDF},
owner = {brian},
timestamp = {2007.11.19}
}
@ARTICLE{Capocci2004,
author = {Capocci, Daniel P.J. and H\"{u}bner, Georges},
title = {An Analysis of Hedge Fund Performance},
journal = {Journal of Empirical Finance},
year = {2004},
volume = {11},
pages = {55-89},
number = {1},
month = {January},
owner = {peter},
timestamp = {2008.02.11}
}
@MISC{PerformanceAnalytics,
author = {Peter Carl and Brian G. Peterson},
title = {{PerformanceAnalytics}: Econometric Tools for Performance and Risk
Analysis},
year = {2010},
note = {R package version 1.0.2.1},
owner = {brian},
timestamp = {2008.02.01},
url = {http://braverock.com/R/}
}
@BOOK{Carmona2004,
title = {Statistical Analysis of Financial Data in S-Plus},
publisher = {Springer},
year = {2004},
author = {Ren\'{e} A. Carmona},
series = {Springer Texts in Statistics},
owner = {peter},
timestamp = {2007.11.04}
}
@INBOOK{Chambers1992,
chapter = {4},
pages = {95-144},
title = {Statistical Models in S},
publisher = {Chapman \& Hall/CRC},
year = {1992},
editor = {John M. Chambers and Trevor J. Hastie},
author = {John M. Chambers},
owner = {peter},
timestamp = {2008.02.13}
}
@BOOK{Chambers1998,
title = {Programming with Data},
publisher = {Springer},
year = {1998},
author = {John M. Chambers},
address = {New York},
note = {ISBN 0-387-98503-4},
abstract = {This ``\emph{Green Book}'' describes version 4 of S, a major revision
of S designed by John Chambers to improve its usefulness at every
stage of the programming process.},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-22-2008951-0,00.html},
timestamp = {2008.04.27},
url = {http://cm.bell-labs.com/cm/ms/departments/sia/Sbook/}
}
@BOOK{Chambers1992a,
title = {Statistical Models in {S}},
publisher = {Chapman \& Hall},
year = {1992},
author = {John M. Chambers and Trevor J. Hastie},
address = {London},
abstract = {This is also called the ``\emph{White Book}'', and introduced S version
3, which added structures to facilitate statistical modeling in S.},
owner = {brian},
publisherurl = {http://www.crcpress.com/shopping_cart/products/product_detail.asp?sku=C3040&parent_id=&pc=},
timestamp = {2008.04.27}
}
@ARTICLE{ChanGetmanskyetal2005,
author = {Nicholas Chan and Mila Getmansky and Shane M. Haas and Andrew W.
Lo},
title = {Systemic Risk and Hedge Funds},
journal = {NBER Working Paper Series},
year = {2005},
number = {11200},
month = {March},
institution = {National Bureau of Economic Research},
owner = {peter},
series = {Working Paper Series},
timestamp = {2007.11.03},
type = {Working Paper},
url = {http://www.nber.org/papers/w11200}
}
@ARTICLE{Chow2001,
author = {Chow, George and Kritzman, Mark},
title = {Risk budgets},
journal = {Journal of Portfolio Management},
year = {2001},
pages = {Winter 2001, 56-60},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Christoffersen2005,
author = {Christoffersen, Peter and Gon\c{c}alves, S\'{i}lvia},
title = {Estimation Risk in Financial Risk Management},
journal = {Journal of Risk},
year = {2005},
volume = {7},
pages = {1-28},
number = {3},
owner = {brian},
timestamp = {2007.10.30}
}
@TECHREPORT{Basel2006,
author = {Basel~II~Committee},
title = {Basel II: International Convergence of Capital Measurement and Capital
Standards: A Revised Framework - Comprehensive Version},
institution = {Bank of International Settlements},
year = {2006},
month = {June},
note = {available at: \url{http://www.bis.org/publ/bcbs128.htm}},
file = {bcbs128.pdf:http\://www.bis.org/publ/bcbs128.pdf:PDF},
owner = {brian},
timestamp = {2007.09.15},
url = {http://www.bis.org/publ/bcbs128.htm}
}
@TECHREPORT{Compliance2007,
author = {LLC Compliance},
title = {Basel II Training},
institution = {Complaince, LLC},
year = {2007},
note = {available at: \url{http://www.basel-ii-accord.com/BaselText/Basel525to537.htm}},
owner = {brian},
timestamp = {2007.09.15},
url = {http://www.basel-ii-accord.com/BaselText/Basel525to537.htm}
}
@ARTICLE{Cont2001,
author = {Cont, Rama},
title = {Empirical Properties of Asset Returns: Stylized Facts and Statistical
Issues},
journal = {Quantitative Finance},
year = {2001},
volume = {1},
pages = {223-236},
owner = {brian},
timestamp = {2008.01.02}
}
@ARTICLE{Cornish1937,
author = {Cornish, Edmund A. and Fisher, Ronald A.},
title = {Moments and Cumulants in the Specification of Distributions},
journal = {Revue de l'Institut International de Statistique},
year = {1937},
volume = {5},
pages = {307-320},
number = {4},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Creal2007,
author = {Drew Creal and Ying Gu and Eric Zivot},
title = {Evaluating Structural Models for the U.S. Short Rate Using EMM and
Particle Filters},
year = {2007},
month = aug,
abstract = {We combine the efficient method of moments with appropriate algorithms
from the optimal filtering literature to study a collection of models
for the U.S. short rate. Our models include two continuous-time stochastic
volatility models and two regime switching models, which provided
the best fit in previous work that examined a large collection of
models. The continuous-time stochastic volatility models fall into
the class of nonlinear, non-Gaussian state space models for which
we apply particle filtering and smoothing algorithms. Our results
demonstrate the effectiveness of the particle filter for continuous-time
processes. Our analysis also provides an alternative and complementary
approach to the reprojection technique of Gallant and Tauchen (1998)
for studying the dynamics of volatility.},
publisher = {University of Washington, Department of Economics},
url = {http://ideas.repec.org/p/udb/wpaper/uwec-2006-18.html}
}
@ARTICLE{Cribari-Neto1999,
author = {Francisco Cribari-Neto and Spyros G. Zarkos},
title = {{R}: Yet another econometric programming environment},
journal = {Journal of Applied Econometrics},
year = {1999},
volume = {14},
pages = {319-329},
file = {Cribari-Neto+Zarkos\:1999.pdf:http\://www.R-project.org/nosvn/papers/Cribari-Neto+Zarkos\:1999.pdf:PDF},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.interscience.wiley.com/jpages/0883-7252/}
}
@BOOK{Dalgaard2002,
title = {Introductory Statistics with R},
publisher = {Springer-Verlag},
year = {2002},
author = {Dalgaard, Peter},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Dalgaard2002a,
title = {Introductory Statistics with {R}},
publisher = {Springer},
year = {2002},
author = {Peter Dalgaard},
pages = {288},
note = {ISBN 0-387-95475-9},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-10130-22-2287329-0,00.html?changeHeader=true},
timestamp = {2008.04.27},
url = {http://www.biostat.ku.dk/~pd/ISwR.html}
}
@ARTICLE{DaviesKatLu2006,
author = {Davies, Ryan J. and Kat, Harry M. and Lu, Sa},
title = {Fund of Hedge Funds Portfolio Selection: A Multiple-Objective Approach},
year = {2006},
keywords = {Hedge funds, asset allocation, diversification, skewness, kurtosis,
optimisation},
language = {English},
location = {http://faculty.babson.edu/rdavies/pgp_final17.pdf},
owner = {peter},
timestamp = {2007.11.03},
type = {Working Paper Series}
}
@ARTICLE{DeMiguel2009,
author = {DeMiguel, Victor and Garlappi, Lorenzo and Uppal, Raman},
title = {Optimal versus na\"{\i}ve diversification: how inefficient is the
{1/N} portfolio strategy?},
journal = {Review of Financial Studies},
year = {2009},
volume = {22},
pages = {1915-1953},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Denault2001,
author = {Denault, Michel},
title = {Coherent allocation of risk capital},
journal = {Journal of Risk},
year = {2001},
pages = {Fall 2001, 1-33},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Denton2004,
author = {Denton, M., and Jayaraman, J.D.},
title = {Incremental, Marginal, and Component {VaR}},
journal = {Sunguard},
year = {2004},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{DiClemente2003,
author = {Di Clemente, Annalisa and Romano, Claudio},
title = {Beyond Markowitz: Building Optimal Portfolio Using Non-Elliptical
Asset Return Distributions},
journal = {Working paper},
year = {2003},
abstract = {The Modern Portfolio Theory (MPT) assumes that the asset return distribution
is
multivariate normal. However, statistical data show fat-tailed and
asymmetric asset return
distributions. Consequently, the minimum-variance portfolios are not
efficient with respect
to their effective risk profile (in particular, with refer to their
tail risk). We know that only
whether the asset return distribution is elliptical (for example,
in the case of multi-normal
distribution) the mean-variance criterion is correct. Hence, for non-elliptical
distributions,
the minimum-variance portfolios may be far from the efficient ones
with respect to relevant
and tractable risk measures as, in particular, the Conditional VaR
(CVaR).
The aim of this paper is therefore to underline how the optimal portfolio
composition
with respect to CVaR may change, assuming different hypotheses for
generating the asset
return scenarios. In order to achieve this purpose, primarily we generate
scenarios for
portfolio asset returns assuming the traditional hypothesis of multivariate
conditional normal
distribution. Successively, we generate the scenarios from the empirical
distribution using
Filtered Historical Simulation (FHS). Finally, we generate Monte Carlo
(MC) asset return
scenarios by using Extreme Value Theory (EVT) and copula function.
These latter scenarios
are generated from a non-elliptical multivariate distribution constructed
by a Student’s tcopula
with ten degrees of freedom and assuming marginal distributions Gaussian
in the
center and EVT distributed in the tail. Finally, we apply the whole
methodology described to
a portfolio of Italian equities.},
file = {Beyond_Markowitz\:_Building_Optimal_Portfolio_Using_Non-Elliptical_Asset_Return_Distributions_2003_Di-Clemente_Romano.pdf:/home/brian/My Documents/Research/Beyond_Markowitz\:_Building_Optimal_Portfolio_Using_Non-Elliptical_Asset_Return_Distributions_2003_Di-Clemente_Romano.pdf:PDF},
keywords = {Extreme Value Theory, Copula Function, Filtered Historical Simulation,
Exponentially Weighted Moving Average, Conditional Value-at-Risk,
Portfolio Optimization},
owner = {brian},
timestamp = {2007.09.11},
url = {http://www.gloriamundi.org/detailpopup.asp?ID=453056362}
}
@ARTICLE{Draper1973,
author = {Draper, Norman R. and Tierney, David E.},
title = {Exact Formulas for Additional Terms in Some Important Expansions},
journal = {Communications in Statistics-Theory and Methods},
year = {1973},
volume = {1},
pages = {495-524},
number = {6},
owner = {brian},
timestamp = {2007.10.30}
}
@BOOK{Ellis2005,
title = {Ahead of the curve: a commonsense guide to forecasting business and
market cycles},
publisher = {Harvard Business Press},
year = {2005},
author = {Ellis, J.H.},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Ellner2001,
author = {Stephen P. Ellner},
title = {Review of {R}, Version 1.1.1},
journal = {Bulletin of the Ecological Society of America},
year = {2001},
volume = {82},
pages = {127--128},
number = {2},
month = {April},
owner = {brian},
timestamp = {2008.04.27}
}
@ARTICLE{Embrechts2000,
author = {Embrechts, Paul},
title = {Extreme Value Theory: Potential and Limitations as an Integrated
Risk Management Tool},
journal = {Derivatives Use, Trading \& Regulation},
year = {2000},
volume = {6},
pages = {449-456},
file = {Extreme Value Theory\: Potential and Limitations as an Integrated Risk Management Tool_2000_Embrechts.pdf:/home/brian/My Documents/Research/Extreme Value Theory\: Potential and Limitations as an Integrated Risk Management Tool_2000_Embrechts.pdf:PDF},
owner = {brian},
timestamp = {2007.09.08},
url = {http://www.math.ethz.ch/~baltes/ftp/evtpot.pdf}
}
@BOOK{Embrechts1999,
title = {Modelling Extremal Events for Insurance and Finance. Application
of Mathematics.},
publisher = {Springer-Verlag},
year = {1999},
author = {Embrechts, Paul and Kl\"{u}pelberg, Claudia, and Mikosch, Thomas},
owner = {brian},
timestamp = {2007.08.19}
}
@INCOLLECTION{Embrechts2001,
author = {Embrechts, Paul and McNeil, Alexander and Straumann, Daniel},
title = {Correlation and Dependence in Risk Management: Properties and Pitfalls},
booktitle = {Risk Management: Value at Risk and Beyond},
publisher = {Cambridge University Press},
year = {2001},
editor = {Dempster, M.A.H.},
chapter = {7},
pages = {176-273},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{EngleDCC02,
author = {Engle, R.F.},
title = {Dynamic Conditional Correlation - a Simple Class of Multivariate
{GARCH} Models},
journal = {Journal of Business and Economic Statistics},
year = {2002},
volume = {20},
pages = {339-350},
owner = {Administrator},
timestamp = {2011.05.27}
}
@ARTICLE{Faber2007,
author = {Faber, Mebane T},
title = {A Quantitative Approach to Tactical Asset Allocation},
journal = {Journal of Wealth Management},
year = {2007},
volume = {16},
pages = {69-79},
owner = {Administrator},
timestamp = {2011.06.09}
}
@BOOK{Faraway2004,
title = {Linear Models with R},
publisher = {Chapman \& Hall/CRC},
year = {2004},
author = {Julian J. Faraway},
address = {Boca Raton, FL},
note = {ISBN 1-584-88425-8},
abstract = {The first book that directly uses R to teach data analysis, Linear
Models with R focuses on the practice of regression and analysis
of variance. It clearly demonstrates the different methods available
and in which situations each one applies. It covers all of the standard
topics, from the basics of estimation to missing data, factorial
designs, and block designs, but it also includes discussion of topics,
such as model uncertainty, rarely addressed in books of this type.
The presentation incorporates an abundance of examples that clarify
both the use of each technique and the conclusions one can draw from
the results.},
owner = {brian},
publisherurl = {http://www.crcpress.com/shopping_cart/products/product_detail.asp?sku=C4258&parent_id=&pc=},
timestamp = {2008.04.27},
url = {http://www.stat.lsa.umich.edu/~faraway/LMR/}
}
@TECHREPORT{Farnsworth2006,
author = {Farnsworth, Grant V.},
title = {Econometrics in R},
institution = {Northwestern University},
year = {2006},
owner = {brian},
timestamp = {2008.05.07},
url = {http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf}
}
@ARTICLE{Favre2002,
author = {Favre, Laurent and Galeano, Jose-Antonio},
title = {Mean-Modified Value-at-Risk Optimization with Hedge Funds},
journal = {Journal of Alternative Investment},
year = {2002},
volume = {5},
pages = {2-21},
number = {2},
abstract = {Based on the normal value-at-risk, we develop a new value-at-risk
method called modified value-at-risk. This modified value-at-risk
has the property to adjust the risk, measured by volatility alone,
with the skewness and the kurtosis of the distribution of returns.
The modified value-at-risk allows us to measure the risk of a portfolio
with non-normally distributed assets like hedge funds or technology
stocks and to solve for optimal portfolio by minimizing the modified
value-at-risk at a given confidence level.},
file = {Mean-modified_VaR_optimization_with_Hedge_Funds_EDHEC_Favre_2002.pdf:/home/brian/docs/Research/Mean-modified_VaR_optimization_with_Hedge_Funds_EDHEC_Favre_2002.pdf:PDF},
owner = {brian},
timestamp = {2007.07.25},
url = {http://www.gloriamundi.org/picsresources/lfjg1.pdf}
}
@ARTICLE{Favre2003,
author = {Favre, Laurent, and Renaldo, A.},
title = {How to Price Hedge Funds: From Two- to Four-Moment CAPM},
journal = {UBS and EDHEC Business School},
year = {2003},
volume = {October},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Fernandez1998,
author = {Fern\'{a}ndez, Carmen and Steel, Mark F.J.},
title = {On Bayesian Modelling of Fat Tails and Skewness},
journal = {Journal of the American Statistical Association},
year = {1998},
volume = {93},
pages = {359-371},
number = {441},
owner = {brian},
timestamp = {2007.10.30}
}
@BOOK{Fox2002,
title = {An {R} and {S-Plus} Companion to Applied Regression},
publisher = {Sage Publications},
year = {2002},
author = {John Fox},
address = {Thousand Oaks, CA, USA},
note = {ISBN 0761922792},
abstract = {A companion book to a text or course on applied regression (such as
``Applied Regression, Linear Models, and Related Methods'' by the
same author). It introduces S, and concentrates on how to use linear
and generalized-linear models in S while assuming familiarity with
the statistical methodology.},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.socsci.mcmaster.ca/jfox/Books/Companion/}
}
@ARTICLE{Fung2002,
author = {Fung, W.K. and Hsieh, D. A.},
title = {Asset-based Style Factors for Hedge Funds},
journal = {Financial Analysts Journal},
year = {2002},
volume = {58},
pages = {16-27},
number = {5},
owner = {brian},
timestamp = {2008.05.07}
}
@ARTICLE{FungHsieh1999,
author = {Fung, William K.H. and Hsieh, David A.},
title = {Is Mean-Variance Analysis Applicable to Hedge Funds?},
journal = {Economics Letters},
year = {1999},
volume = {62},
pages = {53-58},
abstract = {This paper shows that the mean-variance analysis of hedge funds approximately
preserves the ranking of preferences in
standard utility functions. This extends the results of Levy and Markowitz
(1979) [Levy, H., Markowitz, H.M., 1979.
Approximating expected utility by a function of mean and variance.
American Economic Review 69, 308–317] and
Hlawitschka (1994) [Hlawitschka, W., 1994. The empirical nature of
Taylor-series approximations to expected utility.
American Economic Review 84, 713–719] for individual stocks and
portfolios of stocks.},
keywords = {Hedge funds; Mean-variance analysis; Taylor-series approximation;
risk version},
owner = {peter},
timestamp = {2007.11.03},
url = {http://faculty.fuqua.duke.edu/~dah7/PDFofPublishedPapers/EconLett1999.pdf}
}
@ARTICLE{Furrer2001,
author = {Reinhard Furrer and Diego Kuonen},
title = {{GRASS GIS et R}: main dans la main dans un monde libre},
journal = {Flash Informatique Sp{\'e}cial {\'E}t{\'e}},
year = {2001},
pages = {51-56},
month = {sep},
owner = {brian},
timestamp = {2008.04.27},
url = {http://sawww.epfl.ch/SIC/SA/publications/FI01/fi-sp-1/sp-1-page51.html}
}
@ARTICLE{Gehin2006,
author = {G\'{e}hin, Walter},
title = {The Challenge of Hedge Fund Performance Measurement: a Toolbox Rather
Than a Pandora's Box},
journal = {Working paper},
year = {2006},
owner = {peter},
timestamp = {2007.11.03}
}
@ARTICLE{Garman1997,
author = {Garman, Mark B.},
title = {Taking VaR to pieces},
journal = {RISK},
year = {1997},
volume = {10},
pages = {70-71},
number = {10},
owner = {brian},
timestamp = {2007.09.09},
url = {http://www.fea.com/resources/pdf/a_taking_var_to_pieces.pdf}
}
@ARTICLE{Garman1997a,
author = {Garman, Mark B.},
title = {Ending the Search for Component {VaR}},
journal = {Working paper},
year = {1997},
owner = {brian},
timestamp = {2007.09.09},
url = {http://www.fea.com/resources/pdf/a_endsearchvar.pdf}
}
@ARTICLE{Gaussel2001,
author = {Gaussel, N. and Legras, J. and Longin, F. and Rabemananjara, R.},
title = {Beyond the {VaR} Horizon},
journal = {Quants Review},
year = {2001},
volume = {No. 37.},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Geltner1993,
author = {Geltner, David},
title = {Estimating Market Values from Appraised Values without Assuming an
Efficient Market},
journal = {Journal of Real Estate Research},
year = {1993},
volume = {8},
pages = {325-345},
owner = {brian},
timestamp = {2007.09.01}
}
@ARTICLE{Geltner1991,
author = {Geltner, David},
title = {Smoothing in Appraisal-Based Returns},
journal = {Journal of Real Estate Finance and Economics},
year = {1991},
volume = {4},
pages = {327-345},
owner = {brian},
timestamp = {2007.09.01}
}
@ARTICLE{Gentleman2000,
author = {Robert Gentleman and Ross Ihaka},
title = {Lexical Scope and Statistical Computing},
journal = {Journal of Computational and Graphical Statistics},
year = {2000},
volume = {9},
pages = {491--508},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.amstat.org/publications/jcgs/}
}
@ARTICLE{GetmanskyLoEtAl2004,
author = {Mila Getmansky and Andrew W. Lo and Igor Makarov},
title = {An Econometric Model of Serial Correlation and Illiquidity in Hedge
Fund Returns},
journal = {Journal of Financial Economics},
year = {2004},
pages = {529-609},
number = {74},
month = {March},
abstract = {The returns to hedge funds and other alternative investments are often
highly serially cor-
related, in sharp contrast to the returns of more traditional investment
vehicles such as
long-only equity portfolios and mutual funds. In this paper, we explore
several sources of
such serial correlation and show that the most likely explanation
is illiquidity exposure,
i.e., investments in securities that are not actively traded and for
which market prices are
not always readily available. For portfolios of illiquid securities,
reported returns will tend
to be smoother than true economic returns, which will understate volatility
and increase
risk-adjusted performance measures such as the Sharpe ratio. We propose
an economet-
ric model of illiquidity exposure and develop estimators for the smoothing
profile as well
as a smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds
drawn from the
TASS database, we show that our estimated smoothing coefficients vary
considerably across
hedge-fund style categories and may be a useful proxy for quantifying
illiquidity exposure.},
keywords = {Hedge Funds; Serial Correlation; Performance Smoothing; Liquidity;
Market Efficiency.},
owner = {peter},
timestamp = {2007.11.03}
}
@ARTICLE{Giot2003,
author = {Giot, Pierre and Laurent, S\'{e}bastien},
title = {Value-at-Risk for Long and Short Trading Positions},
journal = {Journal of Applied Econometrics},
year = {2003},
volume = {18},
pages = {641-664},
number = {6},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{Gourieroux2000,
author = {Gouri\'{e}roux, Christian and Laurent, Jean-Paul and Scaillet, Olivier},
title = {Sensitivity Analysis of Value at Risk},
journal = {Journal of Empirical Finance},
year = {2000},
volume = {7},
pages = {225-245},
number = {3-4},
owner = {brian},
timestamp = {2007.10.30}
}
@MANUAL{FinTS,
title = {FinTS: Companion to Tsay (2005) Analysis of Financial Time Series},
author = {Spencer Graves},
year = {2008},
note = {R package version 0.2-6},
owner = {brian},
timestamp = {2008.02.11},
url = {http://cran.r-project.org/src/contrib/Descriptions/FinTS.html}
}
@ARTICLE{Guegan2004,
author = {Guegan, Dominique and Cyril, Caillault},
title = {Forecasting {VaR} and Expected Shortfall using Dynamical Systems:
A Risk Management Strategy},
journal = {Working paper},
year = {2004},
month = {June 27},
abstract = {Using copulas' approach and parametric models, we show that the bivariate
distribution of an Asian portfolio is not stable all along the period
under study. Thus, we develop several dynamical models to compute
two market risk's measures: the Value at Risk and the Expected Shortfall.
The methods considered are the RiskMetric methodology, the Multivariate
GARCH models, the Multivariate Markov-Switching models, the empirical
histogram and the dynamical copulas. We discuss the choice of the
best method with respect to the policy management of banks supervisors.
The copula approach seems to be a good compromise between all these
models. It permits to take into account financial crises and to obtain
a low capital requirement during the most important crises.},
file = {Forecasting_VaR_and_Expected_Shortfall_using_Dynamical_Systems\:_A_Risk_Management_Strategy_2004_Guegan_Cyril_SSRN-id898828.pdf:/home/brian/My Documents/Research/Forecasting_VaR_and_Expected_Shortfall_using_Dynamical_Systems\:_A_Risk_Management_Strategy_2004_Guegan_Cyril_SSRN-id898828.pdf:PDF},
keywords = {Value at Risk, Expected Shortfall, Copula, RiskMetrics, Risk management},
owner = {brian},
timestamp = {2007.09.11},
url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=898828}
}
@ARTICLE{Gueyie2006,
author = {Gueyi\'{e}, Jean-Pierre and Amvella, Serge Patrick},
title = {Optimal Portfolio Allocation Using Funds of Hedge Funds},
journal = {Journal of Wealth Management},
year = {2006},
volume = {9},
pages = {85-95},
number = {2},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{Hallerbach2002,
author = {Hallerbach, Winfried G.},
title = {Decomposing Portfolio Value-at-Risk: A General Analysis},
journal = {Journal of Risk},
year = {2002},
volume = {5},
pages = {1-18},
number = {2},
abstract = {An intensive and still growing body of research focuses on estimating
a portfolio’s Valueat-
Risk. Depending on both the degree of non-linearity of the instruments
comprised in
the portfolio and the willingness to make restrictive assumptions
on the underlying
statistical distributions, a variety of analytical methods and simulation-based
methods are
available. Aside from the total portfolio’s VaR, there is a growing
need for information
about (i) the marginal contribution of the individual portfolio components
to the
diversified portfolio VaR, (ii) the proportion of the diversified
portfolio VaR that can be
attributed to each of the individual components consituting the portfolio,
and (iii) the
incremental effect on VaR of adding a new instrument to the existing
portfolio.
Expressions for these marginal, component and incremental VaR metrics
have
been derived by Garman [1996a, 1997a] under the assumption that returns
are drawn
from a multivariate normal distribution. For many portfolios, however,
the assumption
of normally distributed returns is too stringent. Whenever these deviations
from
normality are expected to cause serious distortions in VaR calculations,
one has to resort
to either alternative distribution specifications or historical and
Monte Carlo simulation
methods. Although these approaches to overall VaR estimation have
received substantial
interest in the literature, there exist to the best of our knowledge
no procedures for
estimating marginal VaR, component VaR and incremental VaR in either
a non-normal
analytical setting or a Monte Carlo / historical simulation context.
This paper tries to fill this gap by investigating these VaR concepts
in a general
distribution-free setting. We derive a general expression for the
marginal contribution of
an instrument to the diversified portfolio VaR - whether this instrument
is already
included in the portfolio or not. We show how in a most general way,
the total portfolio
VaR can be decomposed in partial VaRs that can be attributed to the
individual
instruments comprised in the portfolio. These component VaRs have
the appealing
property that they aggregate linearly into the diversified portfolio
VaR. We not only
show how the standard results under normality can be generalized to
non-normal
analytical VaR approaches but also present an explicit procedure for
estimating marginal
VaRs in a simulation framework. Given the marginal VaR estimate, component
VaR and
incremental VaR readily follow. The proposed estimation approach pairs
intuitive appeal
with computational efficiency. We evaluate various alternative estimation
methods in an
application example and conclude that the proposed approach displays
an astounding
accuracy and a promising outperformance.},
keywords = {Value-at-Risk, marginal VaR, component VaR, incremental VaR, nonnormality,
non-linearity, estimation, simulation},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{HarveyLiechtyetal2004,
author = {Harvey, Campbell R. and Liechty, John C. and Liechty, Merrill W.
and M\"{u}ller, Peter},
title = {Portfolio Selection with Higher Moments},
journal = {Working paper},
year = {2004},
month = {May},
abstract = {We build on the Markowitz portfolio selection process by incorporating
higher order
moments of the assets, as well as utility functions based on predictive
asset returns.
We propose the use of the skew normal distribution as a characterization
of the asset
returns. We show that this distribution has many attractive features
when it comes
to modeling multivariate returns. Preference over portfolios is framed
in terms of ex-
pected utility maximization. We discuss estimation and optimal portfolio
selection
using Bayesian methods. These methods allow for a comparison to other
optimiza-
tion approaches where parameter uncertainty is either ignored or accommodated
in an
ad hoc manner. Our results suggest that it is important to incorporate
higher order
moments in portfolio selection. Further, we show that our approach
leads to higher
expected utility than the resampling methods common in the practice
of finance.},
keywords = {Bayesian statistics, multivariate skewness, parameter uncertainty,
portfolio selection, utility function maximization.},
owner = {peter},
timestamp = {2007.11.03},
url = {http://faculty.fuqua.duke.eduzSz%7EcharveyzSzResearchzSzWorking_PaperszSzW70_Portfolio_selection_with.pdf/harvey04portfolio.pdf}
}
@BOOK{Heiberger2004,
title = {Statistical Analysis and Data Display: An Intermediate Course with
Examples in {S-Plus}, {R}, and {SAS}},
publisher = {Springer},
year = {2004},
author = {Richard M. Heiberger and Burt Holland},
series = {Springer Texts in Statistics},
note = {ISBN 0-387-40270-5},
abstract = {A contemporary presentation of statistical methods featuring 200 graphical
displays for exploring data and displaying analyses. Many of the
displays appear here for the first time. Discusses construction and
interpretation of graphs, principles of graphical design, and relation
between graphs and traditional tabular results. Can serve as a graduate-level
standalone statistics text and as a reference book for researchers.
In-depth discussions of regression analysis, analysis of variance,
and design of experiments are followed by introductions to analysis
of discrete bivariate data, nonparametrics, logistic regression,
and ARIMA time series modeling. Concepts and techniques are illustrated
with a variety of case studies. S-Plus, R, and SAS executable functions
are provided and discussed. S functions are provided for each new
graphical display format. All code, transcript and figure files are
provided for readers to use as templates for their own analyses.},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-10129-22-28904982-0,00.html?changeHeader=true},
timestamp = {2008.04.27},
url = {http://astro.temple.edu/~rmh/HH}
}
@BOOK{Huet2003,
title = {Statistical Tools for Nonlinear Regression},
publisher = {Springer},
year = {2003},
author = {Sylvie Huet and Annie Bouvier and Marie-Anne Gruet and Emmanuel Jolivet},
address = {New York},
note = {ISBN 0-387-40081-8},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-22-7107970-0,00.html},
timestamp = {2008.04.27}
}
@BOOK{Iacus2003,
title = {Laboratorio di statistica con {R}},
publisher = {McGraw-Hill},
year = {2003},
author = {Stefano Iacus and Guido Masarotto},
pages = {384},
address = {Milano},
note = {ISBN 88-386-6084-0},
owner = {brian},
publisherurl = {http://www.ateneonline.it/LibroAteneo.asp?item_id=1436},
timestamp = {2008.04.27}
}
@ARTICLE{Ihaka1996,
author = {Ross Ihaka and Robert Gentleman},
title = {R: A Language for Data Analysis and Graphics},
journal = {Journal of Computational and Graphical Statistics},
year = {1996},
volume = {5},
pages = {299--314},
number = {3},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.amstat.org/publications/jcgs/}
}
@TECHREPORT{RiskMetrics1996,
author = {J.P.Morgan/Reuters},
title = {RiskMetrics Technical Document},
institution = {J.P. Morgan/Reuters},
year = {1996},
number = {Fourth Edition},
address = {New York},
owner = {brian},
timestamp = {2007.09.09}
}
@ARTICLE{Jaschke2002,
author = {Jaschke, Stefan R.},
title = {The Cornish-Fisher-Expansion in the Context of Delta-Gamma-Normal
Approximations},
journal = {Journal of Risk},
year = {2002},
volume = {4},
pages = {33-52},
number = {4},
month = {December},
citeseerurl = {http://citeseer.ist.psu.edu/608652.html},
file = {Cornish_fisher_Expansion_in _the_Context_of_Delta_Gamma_Normal_Approximations-Jaschke-2001.pdf:/home/brian/docs/Research/Cornish_fisher_Expansion_in _the_Context_of_Delta_Gamma_Normal_Approximations-Jaschke-2001.pdf:PDF},
institution = {Journal of Risk},
owner = {brian},
timestamp = {2007.08.25},
type = {Sonderforschungsbereich 373},
url = {http://ideas.repec.org/p/wop/humbsf/2001-54.html}
}
@ARTICLE{Jin2006,
author = {Jin, Hanqing and Markowitz, Harry and Zhou, Xunyu},
title = {A Note on Semivariance},
journal = {Mathematical Finance},
year = {2006},
volume = {Vol. 16, No. 1, January},
pages = {53-61},
abstract = {In a recent paper (Jin, Yan, and Zhou 2005), it is proved that efficient
strategies of the continuous-time mean-semivariance portfolio selection
model are in general never achieved save for a trivial case. In this
note, we show that the mean-semivariance efficient strategies in
a single period are always attained irrespective of the market condition
or the security return distribution. Further, for the below-target
semivariance model the attainability is established under the arbitrage-free
condition. Finally, we extend the results to problems with general
downside risk measures.},
owner = {brian},
timestamp = {2007.08.19},
url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=910640}
}
@ARTICLE{JobsonKorkie1981,
author = {Jobson, J.D. and Korkie, B.M.},
title = {Performance Hypothesis Testing with the Sharpe and Treynor Measures},
journal = {Journal of Finance},
year = {1981},
volume = {36},
pages = {889-908},
owner = {Administrator},
timestamp = {2011.06.12}
}
@ARTICLE{Jondeau2006,
author = {Jondeau, Eric and Rockinger, Michael},
title = {Optimal Portfolio Allocation Under Higher Moments},
journal = {European Financial Management},
year = {2006},
volume = {12},
pages = {29-55},
number = {1},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Jorion2007,
title = {Value at Risk: the New Benchmark for Managing Financial Risk, 3rd
edition},
publisher = {McGraw Hill},
year = {2007},
author = {Jorion, Phillippe},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Kalkbrener2005,
author = {Kalkbrener, Michael},
title = {An Axiomatic Approach to Capital Allocation},
journal = {Mathematical Finance},
year = {2005},
volume = {15},
pages = {425-437},
number = {3},
month = {July},
abstract = {Capital allocation techniques are of central importance in portfolio
management and risk-based performance measurement. In this paper
we propose an axiom system for capital allocation and analyze its
satisfiability and completeness: it is shown that for a given risk
measure rho there exists a capital allocation lambda that satisfies
the main axioms if and only if rho is subadditive and positively
homogeneous. Furthermore, it is proved that the axiom system uniquely
specifies lambda. We apply the axiomatization to the most popular
risk measures in the finance industry in order to derive explicit
capital allocation formulae for these measures.},
doi = {doi:10.1111/j.1467-9965.2005.00227.x},
file = {:/home/brian/docs/Research/axiomatic_approach_to_capital_allocation_2005_Kalkbrener.pdf:PDF},
keywords = {capital allocation, risk measure, expected shortfall, value-at-risk,
Hahn-Banach theorem},
owner = {brian},
timestamp = {2008.04.27}
}
@ARTICLE{Kalman1960,
author = {Kalman, Rudolf Emil},
title = {A New Approach to Linear Filtering and Prediction Problems},
journal = {Transactions of the ASME -- Journal of Basic Engineering},
year = {1960},
volume = {82},
pages = {35-45},
number = {Series D},
month = {March},
comment = {this is a transcription of the original paper for readability and
referenceability. transcription notes are at the url},
file = {:/home/brian/docs/Research/Kalman1960.pdf:PDF},
keywords = {linear filter, Kalman filter},
owner = {brian},
timestamp = {2008.02.09},
url = {http://www.cs.unc.edu/~welch/kalman/kalmanPaper.html}
}
@TECHREPORT{Kaufmann2005,
author = {Roger Kaufmann},
title = {Long Term Risk Management},
institution = {Swiss Life},
year = {2005},
abstract = {In this paper financial risks for long time horizons are investigated.
As measures for these risks, value-at-risk and expected shortfall
are considered.
In a first part, questions concerning a two-week horizon are addressed.
For
GARCH-type processes and stochastic volatility models with jumps,
methods
to estimate quantiles of financial risks for two-week periods are
introduced, and
compared with the widely used square-root-of-time rule, which scales
one-day
risk measures by $\sqrt{10}$ to get ten-day risk measures.
In the second part of the paper, a framework for the measurement of
one-year
risks is developed. Several models for financial time series are introduced,
and
compared with each other. The various models are tested for their
appropriateness
for estimating one-year expected shortfall and value-at-risk on 95\%
and
99\% confidence levels.},
file = {Long_Term_Risk_Management_2004_Kaufmann.pdf:/home/brian/docs/Research/Long_Term_Risk_Management_2004_Kaufmann.pdf:PDF},
owner = {brian},
school = {Department of Mathematics, ETH-Z\"{u}rich},
timestamp = {2007.11.19}
}
@PHDTHESIS{Kaufmann2004,
author = {Roger Kaufmann},
title = {Long Term Risk Management},
school = {Department of Mathematics, ETH-Z\"{u}rich},
year = {2004},
file = {Long_Term_Risk_Management_2004_thesis_Kaufmann.pdf:/home/brian/docs/Research/Long_Term_Risk_Management_2004_thesis_Kaufmann.pdf:PDF},
owner = {brian},
timestamp = {2007.11.19}
}
@ARTICLE{Kazemi2003,
author = {Kazemi and Schneeweis and Gupta},
title = {Omega as a Performance Measure},
journal = {Working paper},
year = {2003},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Keating2002,
author = {Keating, J. and Shadwick, W.F.},
title = {The Omega Function},
journal = {Finance Development Center, London},
year = {2002},
volume = {working paper},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Keel2010,
author = {Keel, Simon and Ardia, Simon},
title = {Generalized Marginal Risk},
journal = {Journal of Asset Management},
year = {2011},
volume = {12},
pages = {123-131},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Khan2007,
author = {Khan, Jafar A. and Van Aelst, Stefan and Zamar, Ruben H.},
title = {Robust Linear Model Selection Based on Least Angle Regression},
journal = {Journal of the American Statistical Association},
year = {2007},
volume = {102},
pages = {1289-1299},
number = {1289-1299},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{Kooli2005,
author = {Maher Kooli and Serge Patrick Amvella and Jean-Pierre Gueyi\'{e}},
title = {Hedge Funds in a Portfolio Context: a Mean-Modified Value at Risk
Framework},
journal = {Derivative Use, Trading and Regulation},
year = {2005},
volume = {10},
pages = {373-383},
number = {4},
abstract = {Practical Implications: This paper finds that the modified Sharpe
ratio, which uses the value at risk (VaR) as a risk measure, is more
accurate than the traditional Sharpe ratio. Also, the VaR adjusted
to the Cornish–Fisher expansion is a good compromise between the
normal VaR (based on the standard deviation of returns) and the historical
VaR (which uses past returns to proxy future returns). With the VaR
adjusted to the Cornish–Fisher expansion, the paper examines the
behaviour of a Canadian institutional investor’s portfolio which
includes hedge funds (HFs). It is confirmed that including HFs in
a portfolio improves its risk-adjusted performance. The findings
are relevant for investors who invest in different traditional and
alternative assets as well as in HFs. It should be noted, however,
that if an investment offers a superior risk-return profile, it does
not automatically mean that investors should buy it, as it may not
fit their preferences and/or fit in with other available alternatives.
Abstract: Hedge funds (HFs) are attracting growing interest from investors.
Their persistent high returns, combined with their low correlation
with traditional assets such as equities and bonds, have certainly
acted in their favour. This attraction is, however, accompanied by
a price to pay. Hedge funds’ returns generally have negative skewness
and excess kurtosis, which force their distribution to deviate from
normality. The purpose of this paper is to determine an acceptable
risk measure, which allows one to analyse correctly the behaviour
of these funds in a Canadian institutional investor portfolio. It
is shown that the modified Sharpe ratio, which uses the value at
risk (VaR) as a risk measure, is more accurate. Furthermore, among
various measures of VaR, the VaR adjusted to the Cornish–Fisher
expansion is more conservative. Overall, the paper confirms that
including HFs in a portfolio improves its risk-adjusted performance.},
owner = {brian},
timestamp = {2008.01.02}
}
@ARTICLE{Kosowski2007,
author = {Kosowski, Robert and Naik, Narayan Y. and Teo, Melvyn },
title = {Do Hedge Funds Deliver Alpha? A Bayesian and Bootstrap Analysis},
journal = {Journal of Financial Economics},
year = {2007},
volume = {84},
pages = {229-264},
month = {April},
abstract = {Using a robust bootstrap procedure, we find that top hedge fund performance
cannot be explained by luck, and hedge fund performance persists
at annual horizons. Moreover, we show that Bayesian measures, which
help overcome the short-sample problem inherent in hedge fund returns,
lead to superior performance predictability. Sorting on Bayesian
alphas, relative to OLS alphas, yields a 5.5% per year increase in
the alpha of the spread between the top and bottom hedge fund deciles.
Our results are robust and relevant to investors as they are neither
confined to small funds, nor driven by incubation bias, backfill
bias, or serial correlation.},
file = {Do_Hedge_unds_Deliver_Alpha_A_Bayesian_and_Bootstap_Analoysis_2005-2007_Kosowski.pdf:/home/brian/docs/Research/Do_Hedge_unds_Deliver_Alpha_A_Bayesian_and_Bootstap_Analoysis_2005-2007_Kosowski.pdf:PDF},
keywords = {hedge fund, persistence, Bayesian, alpha, backfill, incubation, bootstrap},
language = {English},
location = {http://ssrn.com/paper=829025},
owner = {brian},
publisher = {SSRN},
timestamp = {2007.09.01},
type = {Working Paper Series}
}
@ARTICLE{Kuester2006,
author = {Kuester, Keith and Mittnik, Stefan and Paolella, Marc S.},
title = {Value-at-Risk Prediction: A Comparison of Alternative Strategies},
journal = {Journal of Financial Econometrics},
year = {2006},
volume = {4},
pages = {53-89},
number = {1},
abstract = {Given the growing need for managing financial risk, risk prediction
plays an increasing role in banking and finance. In this study we
compare the out-of-sample performance of existing methods and some
new models for predicting value-at-risk (VaR) in a univariate context.
Using more than 30 years of the daily return data on the NASDAQ Composite
Index, we find that most approaches perform inadequately, although
several models are acceptable under current regulatory assessment
rules for model adequacy. A hybrid method, combining a heavy-tailed
generalized autoregressive conditionally heteroskedastic (GARCH)
filter with an extreme value theory-based approach, performs best
overall, closely followed by a variant on a filtered historical simulation,
and a new model based on heteroskedastic mixture distributions. Conditional
autoregressive VaR (CAVaR) models perform inadequately, though an
extension to a particular CAVaR model is shown to outperform the
others.},
keywords = {empirical finance, extreme value theory, fat tails, GARCH, quantile
regression},
location = {http://ssrn.com/paper=922912},
owner = {brian},
publisher = {SSRN},
timestamp = {2007.08.19}
}
@ARTICLE{Kuonen2001b,
author = {Diego Kuonen},
title = {Introduction au data mining avec {R} : vers la reconqu{\^e}te du
`knowledge discovery in databases' par les statisticiens},
journal = {Bulletin of the Swiss Statistical Society},
year = {2001},
volume = {40},
pages = {3-7},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.statoo.com/en/publications/2001.R.SSS.40/}
}
@ARTICLE{Kuonen2001,
author = {Diego Kuonen and Valerie Chavez},
title = {{R} - un exemple du succ{\`e}s des mod{\`e}les libres},
journal = {Flash Informatique},
year = {2001},
volume = {2},
pages = {3-7},
owner = {brian},
timestamp = {2008.04.27},
url = {http://sawww.epfl.ch/SIC/SA/publications/FI01/fi-2-1/2-1-page3.html}
}
@ARTICLE{Kuonen2001a,
author = {Diego Kuonen and Reinhard Furrer},
title = {Data mining avec {R} dans un monde libre},
journal = {Flash Informatique Sp{\'e}cial {\'E}t{\'e}},
year = {2001},
pages = {45-50},
month = {sep},
owner = {brian},
timestamp = {2008.04.27},
url = {http://sawww.epfl.ch/SIC/SA/publications/FI01/fi-sp-1/sp-1-page45.html}
}
@MISC{Lambert2001,
author = {Lambert, Philippe and Laurent, S\'{e}bastien},
title = {Modelling Financial Time Series Using {GARCH}-type Models and a Skewed
{Student} Density},
howpublished = {Working paper},
year = {2001},
note = {Universit\'{e} de Li\`{e}ge},
owner = {brian},
timestamp = {2007.10.30},
volume = {working paper}
}
@BOOK{Lhabitant2004,
title = {Hedge Funds: Quantitative Insights},
publisher = {Wiley},
year = {2004},
author = {Lhabitant, Francois-Sergei},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Liang1999,
author = {Liang, Bing},
title = {On the Performance of Hedge Funds},
journal = {Financial Analysts Journal},
year = {1999},
volume = {55},
pages = {72-85},
number = {4},
month = {July/August},
owner = {brian},
timestamp = {2008.05.07}
}
@BOOK{Limas2001,
title = {Control de Calidad. Metodologia para el analisis previo a la modelizaci{\'o}n
de datos en procesos industriales. Fundamentos te{\'o}ricos y aplicaciones
con R.},
publisher = {Servicio de Publicaciones de la Universidad de La Rioja},
year = {2001},
author = {Manuel Castej{\'o}n Limas and Joaqu{\'\i}n Ordieres Mer{\'e} and
Fco. Javier de Cos Juez and Fco. Javier Mart{\'\i}nez de Pis{\'o}n
Ascacibar},
note = {ISBN 84-95301-48-2},
abstract = {This book, written in Spanish, is oriented to researchers interested
in applying multivariate analysis techniques to real processes. It
combines the theoretical basis with applied examples coded in R.},
owner = {brian},
timestamp = {2008.04.27}
}
@BOOK{Litterman1998,
title = {The Practice of Risk Management: Implementing Processes for Managing
Firm-Wide Market Risk},
publisher = {Euromoney},
year = {1998},
author = {Litterman, R. and Gumerlock, R. and et. al.},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Litterman1996,
author = {Litterman, Robert B},
title = {Hot Spots$^{TM}$ and hedges},
journal = {Journal of Portfolio Management},
year = {1996},
pages = {Special issue 1996, 52-75},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Lo2001,
author = {Lo, Andrew W. },
title = {Risk Management for Hedge Funds: Introduction and Overview},
journal = {SSRN eLibrary},
year = {2001},
doi = {10.2139/ssrn.283308},
keywords = {Risk management, hedge funds, risk transparency, risk budgeting, fund
of funds},
language = {English},
location = {http://ssrn.com/paper=283308},
owner = {peter},
publisher = {SSRN},
timestamp = {2007.11.03},
type = {Working Paper Series}
}
@ARTICLE{Maillard2010,
author = {Maillard, Sebastien and Roncalli, Thierry and Teiletche, Jerome},
title = {On the properties of equally-weighted risk contributions portfolios},
journal = {Journal of Portfolio Management},
year = {2010},
pages = {Summer 2010, 60-70},
owner = {Administrator},
timestamp = {2010.09.02}
}
@BOOK{Maindonald2003,
title = {Data Analysis and Graphics Using R: An Example-Based Approach},
publisher = {Cambridge University Press},
year = {2003},
author = {Maindonald, J. and Braun, J.},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Maindonald2003a,
title = {Data Analysis and Graphics Using R},
publisher = {Cambridge University Press},
year = {2003},
author = {John Maindonald and John Braun},
pages = {362},
address = {Cambridge},
note = {ISBN 0-521-81336-0},
owner = {brian},
publisherurl = {http://www.cup.org/},
timestamp = {2008.04.27},
url = {http://wwwmaths.anu.edu.au/~johnm/r-book.html}
}
@BOOK{Marin2007,
title = {Bayesian Core: A Practical Approach to Computational Bayesian Statistics},
publisher = {Springer},
year = {2007},
author = {Jean-Michel Marin and Christian P. Robert},
pages = {258},
edition = {First},
month = feb,
abstract = {This Bayesian modeling book is intended for practitioners and applied
statisticians looking for a self-contained entry to computational
Bayesian statistics. Focusing on standard statistical models and
backed up by discussed real datasets available from the book website,
it provides an operational methodology for conducting Bayesian inference,
rather than focusing on its theoretical justifications. Special attention
is paid to the derivation of prior distributions in each case and
specific reference solutions are given for each of the models. Similarly,
computational details are worked out to lead the reader towards an
effective programming of the methods given in the book. While R programs
are provided on the book website and R hints are given in the computational
sections of the book, The Bayesian Core requires no knowledge of
the R language and it can be read and used with any other programming
language.
The Bayesian Core can be used as a textbook at both undergraduate
and graduate levels, as exemplified by courses given at Universit{\'e}
Paris Dauphine (France), University of Canterbury (New Zealand),
and University of British Columbia (Canada). It serves as a unique
textbook for a service course for scientists aiming at analyzing
data the Bayesian way as well as an introductory course on Bayesian
statistics. The prerequisites for the book are a basic knowledge
of probability theory and of statistics. Methodological and data-based
exercises are included within the main text and students are expected
to solve them as they read the book. Those exercises can obviously
serve as assignments, as was done in the above courses. Datasets,
R codes and course slides all are available on the book website.},
isbn = {0387389792},
owner = {brian},
timestamp = {2008.02.02}
}
@ARTICLE{Markowitz1952,
author = {Harry Markowitz},
title = {Portfolio Selection},
journal = {Journal of Finance},
year = {1952},
volume = {7},
pages = {77-91},
number = {1},
owner = {brian},
timestamp = {2008.01.02}
}
@BOOK{Maronna2006,
title = {Robust Statistics: Theory and Methods},
publisher = {Wiley},
year = {2006},
author = {Maronna, Ricardo A. and Martin, Douglas R. and Yohai, Victor J.},
owner = {brian},
timestamp = {2007.10.30}
}
@ARTICLE{Martellini2005,
author = {Martellini, Lionel and Vaissi\'{e}, Mathieu and Ziemann, Volker},
title = {Investing in Hedge Funds: Adding Value through Active Style Allocation
Decisions},
journal = {EDHEC Risk and Asset Management Research Centre},
year = {2005},
volume = {October},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{MartelliniZiemann2010,
author = {Martellini, Lionel and Ziemann, Volker},
title = {Improved Forecasts of Higher-Order Comoments and Implications for
Portfolio Selection},
journal = {Review of Financial Studies},
year = {2010},
volume = {23},
pages = {1467-1502},
owner = {peter},
timestamp = {2007.11.03}
}
@ARTICLE{MartelliniZiemann2005,
author = {Martellini, Lionel and Ziemann, Volker},
title = {Marginal Impacts on Portfolio Distributions},
journal = {EDHEC Risk and Asset Management Research Centre},
year = {2005},
volume = {working paper},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Martin2001,
author = {Martin, Richard and Thompson, Kevin and Browne, Christopher},
title = {{VaR}: Who Contributes and How Much?},
journal = {RISK},
year = {2001},
volume = {14},
pages = {99-102},
number = {8},
owner = {brian},
timestamp = {2007.10.30}
}
@BOOK{Mase2004,
title = {Introduction to Data Science for engineers--- Data analysis using
free statistical software R (in Japanese)},
publisher = {Suuri-Kogaku-sha, Tokyo},
year = {2004},
author = {S. Mase and T. Kamakura and M. Jimbo and K. Kanefuji},
pages = {254},
month = {April},
note = {ISBN 4901683128},
owner = {brian},
timestamp = {2008.04.27}
}
@BOOK{McNeil2005,
title = {Quantitative Risk Management: Concepts, Techniques, Tools},
publisher = {Princton University Press},
year = {2005},
author = {McNeil, Alexander J. and Frey, R\"{u}dinger and Embrechts, Paul},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Memmel2003,
author = {Memmel, C},
title = {Performance hypothesis testing with the {Sharpe} Ratio},
journal = {Finance Letters},
year = {2003},
volume = {1},
pages = {21-23},
owner = {Administrator},
timestamp = {2011.06.12}
}
@BOOK{Michaud1998,
title = {Efficient Asset Management: A Practical Guide to Stock Portfolio
Optimization and Asset Allocation},
publisher = {Harvard Business School Press},
year = {1998},
author = {Michaud, Richard O.},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Murrell2006,
title = {R Graphics},
publisher = {Chapman \& Hall/CRC},
year = {2006},
author = {Paul Murrell},
series = {Computer Science and Data Analysis Series},
owner = {peter},
timestamp = {2007.11.04}
}
@ARTICLE{Murrell2000,
author = {Paul Murrell and Ross Ihaka},
title = {An Approach to Providing Mathematical Annotation in Plots},
journal = {Journal of Computational and Graphical Statistics},
year = {2000},
volume = {9},
pages = {582--599},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.amstat.org/publications/jcgs/}
}
@BOOK{Nolan2000,
title = {Stat Labs: Mathematical Statistics Through Applications},
publisher = {Springer},
year = {2000},
author = {Deborah Nolan and Terry Speed},
series = {Springer Texts in Statistics},
note = {ISBN 0-387-98974-9},
abstract = {Integrates theory of statistics with the practice of statistics through
a collection of case studies (``labs''), and uses R to analyze the
data.},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40106-22-2104508-0,00.html?changeHeader=true},
timestamp = {2008.04.27},
url = {http://www.stat.Berkeley.EDU/users/statlabs/}
}
@ARTICLE{Okunev2003,
author = {Okunev, John and White, Derek},
title = {Hedge Fund Risk Factors and Value at Risk of Credit Trading Strategies},
journal = {SSRN eLibrary},
year = {2003},
abstract = {This paper analyzes the risk characteristics for various hedge fund
strategies specializing in fixed income instruments. Because fixed
income hedge fund strategies have exceptionally high autocorrelations
in reported returns and this is taken as evidence of return smoothing,
we first develop a method to completely eliminate any order of autocorrelation
process across a wide array of time series processes. Once this is
complete, we determine the underlying risk factors to the "true"
hedge fund returns and examine the incremental benefit attained from
using nonlinear payoffs relative to the more traditional linear factors.
For a great many of the hedge fund indices we find the strongest
risk factor to be equivalent to a short put position on high-yield
debt. In general, we find a moderate benefit to using the nonlinear
risk factors in terms of the ability to explain reported returns.
However, in some cases this fit is not stable even over the in-sample
period. Finally, we examine the benefit to using various factor structures
for estimating the value-at-risk of the hedge funds. We find, in
general, that using nonlinear factors slightly increases the estimated
downside risk levels of the hedge funds due to their option-like
payoff structures.},
doi = {10.2139/ssrn.460641},
keywords = {Hedge Funds, Value at Risk},
language = {English},
location = {http://ssrn.com/paper=460641},
owner = {brian},
publisher = {SSRN},
timestamp = {2007.09.01},
type = {Working Paper Series}
}
@ARTICLE{Okunev2005,
author = {Okunev, John and White, Derek, and Lewis, Nigel},
title = {Using a Value at Risk Approach to Enhance Tactical Asset Allocation},
journal = {SSRN eLibrary},
year = {2005},
keywords = {Tactical Asset Allocation, Value at Risk},
language = {English},
location = {http://ssrn.com/paper=879522},
owner = {brian},
publisher = {SSRN},
timestamp = {2007.09.02},
type = {Working Paper Series},
url = {http://ssrn.com/paper=879522}
}
@ARTICLE{Parello2007,
author = {Parello, Joseph},
title = {Downside Risk Analysis Applied to Hedge Funds Universe},
year = {2007},
abstract = {Hedge Funds are considered as one of the portfolio management sectors
which shows a fastest growing for the past decade. An optimal Hedge
Fund management requires an appropriate risk metrics. The classic
CAPM theory and its Ratio Sharpe fail to capture some crucial aspects
due to the strong non-Gaussian character of Hedge Funds statistics.
A possible way out to this problem while keeping the CAPM simplicity
is the so-called Downside Risk analysis. One important benefit lies
in distinguishing between good and bad returns, that is: returns
greater or lower than investor's goal. We revisit most popular Downside
Risk indicators and provide new analytical results on them. We compute
these measures by taking the Credit Suisse/Tremont Investable Hedge
Fund Index Data and with the Gaussian case as a benchmark. In this
way an unusual transversal lecture of the existing Downside Risk
measures is provided.},
doi = {10.1016/j.physa.2007.04.079},
owner = {brian},
timestamp = {2007.08.19},
url = {http://arxiv.org/abs/physics/0610162}
}
@BOOK{Parmigiani2003,
title = {The Analysis of Gene Expression Data},
publisher = {Springer},
year = {2003},
author = {Giovanni Parmigiani and Elizabeth S. Garrett and Rafael A. Irizarry
and Scott L. Zeger},
address = {New York},
note = {ISBN 0-387-95577-1},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-22-2292983-0,00.html},
timestamp = {2008.04.27}
}
@BOOK{Pearson2002,
title = {Risk Budgeting: Portfolio Problem Solving with Value-at-Risk},
publisher = {Wiley},
year = {2002},
author = {Neil D. Pearson},
pages = {256},
edition = {1},
isbn = {0471405566},
owner = {brian},
timestamp = {2007.12.08}
}
@ARTICLE{Peterson2008,
author = {Peterson, Brian G. and Kris Boudt},
title = {Component {VaR} for a non-normal world},
journal = {{RISK}},
year = {2008},
pages = {November 2008, 78-81},
owner = {Administrator},
timestamp = {2010.12.19}
}
@INPROCEEDINGS{Pflug2000,
author = {Pflug, G. Ch.},
title = {Some remarks on the value-at-risk and the conditional value-at-risk},
booktitle = {Probabilistic constrained optimization: methodology and applications},
year = {2000},
editor = {Uryasev, S.},
pages = {272-281},
publisher = {Dordrecht: Kluwer},
owner = {Administrator},
timestamp = {2010.12.19}
}
@BOOK{Pinheiro2000,
title = {Mixed-Effects Models in S and {S-Plus}},
publisher = {Springer},
year = {2000},
author = {Jose C. Pinheiro and Douglas M. Bates},
note = {ISBN 0-387-98957-0},
abstract = {A comprehensive guide to the use of the `nlme' package for linear
and nonlinear mixed-effects models.},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-10129-22-2102822-0,00.html?changeHeader=true},
timestamp = {2008.04.27}
}
@ARTICLE{Plantinga2001,
author = {Plantinga, Auke and van der Meer, Robert and Sortino, Frank},
title = {The Impact of Downside Risk on Risk-Adjusted Performance of Mutual
Funds in the Euronext Markets.},
journal = {Working paper},
year = {2001},
abstract = {Many performance measures, such as the classic Sharpe ratio have difficulty
in evaluating the performance of mutual funds with skewed return
distributions. Common causes for skewness are the use of options
in the portfolio or superior market timing skills of the portfolio
manager. In this article we examine to what extent downside risk
and the upside potential ratio can be used to evaluate skewed return
distributions. In order to accomplish this goal, we first show the
relation between the risk preferences of the investor and the risk-adjusted
performance measure. We conclude that it is difficult to interpret
differences in the outcomes of risk-adjusted performance measures
exclusively as differences in forecasting skills of portfolio managers.
We illustrate this with an example of a simulation study of a protective
put strategy. We show that the Sharpe ratio leads to incorrect conclusions
in the case of protective put strategies. On the other hand, the
upside potential ratio leads to correct conclusions. Finally, we
apply downside risk and the upside potential ratio in the process
of selecting a mutual fund from a sample of mutual funds in the Euronext
stock markets. The rankings appear similar, which can be attributed
to the absence of significant skewness in the sample. However, find
that the remaining differences can be quite significant for individual
fund managers, and that these differences can be attributed to skewness.
Therefore, we prefer to use the UPR as an alternative to the Sharpe
ratio, as it accounts better for the use of options and forecasting
skills.},
keywords = {Performance measurement, mutual funds, skewness, Sharpe ratio, market
efficiency},
owner = {brian},
timestamp = {2007.08.19},
url = {http://ssrn.com/abstract=277352}
}
@ARTICLE{Pownall99,
author = {R. Pownall and R. Huisman and K. Koedijk},
title = {Asset Allocation in a Value-at-Risk Framework},
year = {1999},
owner = {brian},
text = {R. A.J. Pownall, R. Huisman, and Kees G. Koedijk. Asset allocation
in a value-at-risk framework. In Proceedings of the European Finance
Association Conference, Helsinki, Finland, 1999.},
timestamp = {2007.11.19},
url = {citeseer.ist.psu.edu/huisman99asset.html}
}
@BOOK{Price2005,
title = {Differential Evolution - A practical approach to global optimization},
publisher = {Springer-Verlag},
year = {2005},
author = {Price, K.V. and Storn, R.M. and Lampinen, J.A.},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{Qian2006,
author = {Qian, Edward},
title = {On the Financial Interpretation of Risk Contribution: Risk Budgets
Do
Add Up},
journal = {Journal of Investment Management},
year = {2006},
volume = {4},
pages = {1-11},
number = {4},
owner = {brian},
timestamp = {2007.10.16}
}
@ARTICLE{Qian2005,
author = {Qian, Edward},
title = {Risk parity portfolios: efficient portfolios through true diversification
of risk},
journal = {Panagora Asset Management},
year = {2005},
volume = {September},
owner = {Administrator},
timestamp = {2010.12.19}
}
@ARTICLE{RanaldoFavre2005,
author = {Ranaldo, Angelo and Favre Sr., Laurent},
title = {{How to Price Hedge Funds: From Two- to Four-Moment CAPM}},
journal = {SSRN eLibrary},
year = {2005},
keywords = {Hedge funds, CAPM, higher moments, skewness, kurtosis, required rate
of return},
language = {English},
location = {http://ssrn.com/paper=474561},
owner = {peter},
publisher = {SSRN},
timestamp = {2007.11.03},
type = {Working Paper Series}
}
@ARTICLE{Ribeiro2001,
author = {Ribeiro, Jr., Paulo J. and Patrick E. Brown},
title = {Some words on the R project},
journal = {The ISBA Bulletin},
year = {2001},
volume = {8},
pages = {12--16},
number = {1},
month = {March},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.iami.mi.cnr.it/isba/index.html}
}
@MISC{Ricci2005,
author = {Vito Ricci},
title = {Fitting Distributions with R},
howpublished = {Working paper},
month = {February},
year = {2005},
file = {Ricci-distributions-en.pdf:http\://cran.r-project.org/doc/contrib/Ricci-distributions-en.pdf:PDF},
owner = {peter},
timestamp = {2007.11.03}
}
@ARTICLE{Ricci2004,
author = {Vito Ricci},
title = {{R} : un ambiente opensource per l'analisi statistica dei dati},
journal = {Economia e Commercio},
year = {2004},
volume = {1},
pages = {69--82},
abstract = {This paper would be a short introduction and overview about the language
and environment for statistical analysis R, without entering in specific
details too much computational. I give a look about this opensource
software pointing out its main features, its functionalities, its
pros and cons describing some libraries and the kind of analysis
they support. I supply a summary, with a short description, about
many resources concerning R that can be found in the Web: the most
are in English language, but there are also some in the Italian language.
The aim of this work is to contribute in increasing of the use of
the R environment in Italy among statistical researchers trying to
``advertise'' this software and its opensource philosophy.},
owner = {brian},
timestamp = {2008.04.27}
}
@ARTICLE{Ripley2001,
author = {Brian D. Ripley},
title = {The {R} Project in Statistical Computing},
journal = {MSOR Connections. The newsletter of the LTSN Maths, Stats \& OR Network.},
year = {2001},
volume = {1},
pages = {23--25},
number = {1},
month = {February},
owner = {brian},
timestamp = {2008.04.27},
url = {http://ltsn.mathstore.ac.uk/newsletter/feb2001/pdf/rproject.pdf}
}
@BOOK{Robert2005,
title = {Monte Carlo Statistical Methods (Springer Texts in Statistics)},
publisher = {Springer},
year = {2005},
author = {Robert, Christian P. and Casella, George },
month = {July},
abstract = {{<P>Monte Carlo statistical methods, particularly those based on Markov
chains, are now an essential component of the standard set of techniques
used by statisticians. This new edition has been revised towards
a coherent and flowing coverage of these simulation techniques, with
incorporation of the most recent developments in the field. In particular,
the introductory coverage of random variable generation has been
totally revised, with many concepts being unified through a fundamental
theorem of simulation</P> <P></P> <P>There are five completely new
chapters that cover Monte Carlo control, reversible jump, slice sampling,
sequential Monte Carlo, and perfect sampling. There is a more in-depth
coverage of Gibbs sampling, which is now contained in three consecutive
chapters. The development of Gibbs sampling starts with slice sampling
and its connection with the fundamental theorem of simulation, and
builds up to two-stage Gibbs sampling and its theoretical properties.
A third chapter covers the multi-stage Gibbs sampler and its variety
of applications. Lastly, chapters from the previous edition have
been revised towards easier access, with the examples getting more
detailed coverage.</P> <P></P> <P>This textbook is intended for a
second year graduate course, but will also be useful to someone who
either wants to apply simulation techniques for the resolution of
practical problems or wishes to grasp the fundamental principles
behind those methods. The authors do not assume familiarity with
Monte Carlo techniques (such as random variable generation), with
computer programming, or with any Markov chain theory (the necessary
concepts are developed in Chapter 6). A solutions manual, which covers
approximately 40\% of the problems, is available for instructors
who require the book for a course.</P> <P></P> <P>Christian P. Robert
is Professor of Statistics in the Applied Mathematics Department
at Universit\'{e} Paris Dauphine, France. He is also Head of the
Statistics Laboratory at the Center for Research in Economics and
Statistics (CREST) of the National Institute for Statistics and Economic
Studies (INSEE) in Paris, and Adjunct Professor at Ecole Polytechnique.
He has written three other books, including The Bayesian Choice,
Second Edition, Springer 2001. He also edited Discretization and
MCMC Convergence Assessment, Springer 1998. He has served as associate
editor for the Annals of Statistics and the Journal of the American
Statistical Association. He is a fellow of the Institute of Mathematical
Statistics, and a winner of the Young Statistician Award of the Societi\'{e}
de Statistique de Paris in 1995.</P> <P></P> <P>George Casella is
Distinguished Professor and Chair, Department of Statistics, University
of Florida. He has served as the Theory and Methods Editor of the
Journal of the American Statistical Association and Executive Editor
of Statistical Science. He has authored three other textbooks: Statistical
Inference, Second Edition, 2001, with Roger L. Berger; Theory of
Point Estimation, 1998, with Erich Lehmann; and Variance Components,
1992, with Shayle R. Searle and Charles E. McCulloch. He is a fellow
of the Institute of Mathematical Statistics and the American Statistical
Association, and an elected fellow of the International Statistical
Institute.</P> <P></P> <P> </P> <P> </P> <P> </P> <P> </P>}},
citeulike-article-id = {1839984},
comment = {p373, Chapter 10 "The Multi-Stage Gibbs Sampler"
""" Although the Gibbs sampler is, formally, a special case of the
Metropolic-Hastings algorithm (or rather a combination of Metropolis-Hastings
algorithms applied to different components; see Theorem 10.13), the
Gibbs sampling algorithm has a number of distinct features:
+ The acceptance rate of the Gibbs sampler is uniformly equal to 1.
Therefore, every simulated value is accepted and the suggestions
of Section 7.6.1 on the optimal acceptance rates do not apply in
this setting. This also means that convergence assessment for this
algorithm should be treated differently than for Metropolis-Hastings
techniques.
+ The use of the Gibbs sampler implies limitations on the choice of
instrumental distributions an requires a prior knowledge of some
analytical or probabilistic properties of f.
+ The Gibbs sampler is, by construction, multidimensional. Even though
some components of the simulated vector may be artificial for the
problem of interest, or unnecessary for the required inference, the
construction is still at least two-dimensional.
+ The Gibbs sampler does not apply to problems where the number of
parameters varies, as in Chapter 11, because of the obvious lack
of irreducibility of the resultung chain.
"""},
howpublished = {Hardcover},
isbn = {0387212396},
keywords = {gibbs, mcmctheory},
priority = {0},
url = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&path=ASIN/0387212396}
}
@ARTICLE{Rockafellar2000,
author = {Rockafellar, Ralph T and Uryasev, Stanislav},
title = {Optimization of Conditional Value-at-Risk},
journal = {Journal of Risk},
year = {2000},
pages = {Spring 2000, 21-41},
owner = {Administrator},
timestamp = {2010.12.19}
}
@INCOLLECTION{Rousseeuw1985,
author = {Rousseeuw, Peter J.},
title = {Multivariate Estimation with High Breakdown Point},
booktitle = {Mathematical Statistics and Its Applications},
publisher = {Dordrecht-Reidel},
year = {1985},
editor = {Grossmann, W. and Pflug, G. and Vincze, I. and Wertz, W.},
volume = {B},
pages = {283-297},
owner = {brian},
timestamp = {2007.10.30}
}
@BOOK{Ruppert2004,
title = {Statistics and Finance, an Introduction},
publisher = {Springer-Verlag},
year = {2004},
author = {Ruppert, David},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Scaillet2002,
author = {Scaillet, Olivier},
title = {Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall},
journal = {Mathematical Finance},
year = {2002},
volume = {14},
pages = {74-86},
number = {1},
owner = {brian},
timestamp = {2007.10.30}
}
@BOOK{Scherer2007,
title = {Portfolio Construction and Risk Budgeting},
publisher = {London: Risk Books},
year = {2007},
author = {Scherer, Bernd},
edition = {3rd},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Scherer2005,
title = {Modern Portfolio Optimization},
publisher = {Springer},
year = {2005},
author = {Scherer, Bernd. and Martin, Douglas},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{ScottHorvath1980,
author = {Scott, Robert C. and Horvath, Philip A.},
title = {On the Direction of Preference for Moments of Higher Order than the
Variance},
journal = {Journal of Finance},
year = {1980},
volume = {35},
pages = {915-919},
number = {4},
month = {September},
owner = {peter},
timestamp = {2007.11.03}
}
@ARTICLE{Sharpe1992,
author = {Sharpe, William},
title = {Asset Allocation: Management Style and Performance Measurement},
journal = {Journal of Portfolio Management},
year = {1992},
pages = {7-19},
number = {Winter},
owner = {brian},
timestamp = {2008.05.07}
}
@ARTICLE{Sharpe1991,
author = {Sharpe, William},
title = {Capital Asset Prices with and without Negative Holdings},
journal = {Journal of Finance},
year = {1991},
volume = {46},
pages = {489-509},
number = {2},
month = {June},
abstract = {My Nobel lecture in 1990. Includes a concise version of the original
CAPM with extensions to cover cases in which negative holdings are
not allowed.},
doi = {10.2307/2328833},
owner = {brian},
timestamp = {2007.11.19},
url = {http://nobelprize.org/economics/laureates/1990/sharpe-lecture.pdf}
}
@ARTICLE{Sharpe1988,
author = {William Sharpe},
title = {Determining a Fund's Effective Asset Mix},
journal = {Investment Management Review},
year = {1988},
month = {December},
owner = {peter},
timestamp = {2008.02.11}
}
@ARTICLE{Sharpe2002,
author = {Sharpe, William F.},
title = {Budgeting and Monitoring Pension Fund Risk},
journal = {Financial Analysts Journal},
year = {2002},
volume = {58},
pages = {74-86},
number = {5},
owner = {brian},
timestamp = {2007.10.16}
}
@ARTICLE{Sharpe1994,
author = {Sharpe, William F.},
title = {The Sharpe Ratio},
journal = {Journal of Portfolio Management},
year = {1994},
volume = {Fall},
pages = {49-58},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Sharpe1964,
author = {Sharpe, William F.},
title = {Capital Asset Prices - A Theory of Market Equilibrium Under Conditions
of Risk},
journal = {Journal of Finance},
year = {1964},
volume = {September},
pages = {425-442},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Sharpe1963,
author = {Sharpe, William F.},
title = {A Simplified Model for Portfolio Analysis},
journal = {Management Science},
year = {1963},
volume = {January},
pages = {277-293},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Shumway2006,
title = {Time Series Analysis and its Applications with R examples: second
edition},
publisher = {Springer},
year = {2006},
author = {Shumway, Robert H. and Stoffer, David S.},
owner = {brian},
timestamp = {2007.08.19}
}
@MISC{Sortino1999,
author = {Sortino, Frank},
title = {The Sortino Ratio},
howpublished = {http://www.sortino.com/htm/Sortino%20Ratio.htm},
owner = {brian},
timestamp = {2007.08.19},
url = {http://www.sortino.com/htm/Sortino%20Ratio.htm}
}
@ARTICLE{Sortino1994,
author = {Sortino, Frank A. and Price, Lee N.},
title = {Performance Measurement in a Downside Risk Framework},
journal = {Journal of Investing},
year = {1994},
volume = {Fall},
pages = {59-65},
owner = {brian},
timestamp = {2007.08.19},
url = {http://www.sortino.com/htm/performance.htm}
}
@TECHREPORT{NIST2006,
author = {National Institute of Standards and Technology},
title = {Engineering Statistics Handbook},
institution = {NIST/Sematech},
year = {2006},
owner = {brian},
timestamp = {2007.08.28},
url = {http://www.itl.nist.gov/div898/handbook/toolaids/pff/ehb-chapters-1-8.pdf}
}
@ARTICLE{Stoyanov2009,
author = {Stoyanov, Stoyan and Rachev, Svetlozar T and Fabozzi, Frank J},
title = {Sensitivity of portfolio {VaR} and {CVaR} to portfolio return characteristics},
journal = {Universit\"{a}t Karlsruhe working paper},
year = {2009},
owner = {Administrator},
timestamp = {2010.12.19}
}
@INBOOK{Tasche2004,
chapter = {Allocating Portfolio Economic Capital to Sub-Portfolios},
pages = {275-302},
title = {Economic Capital: A Practitioners Guide},
publisher = {Risk Books},
year = {2004},
editor = {Ashish Dev},
author = {Tasche, Dirk},
owner = {brian},
review = {Tasche's Theorem 1 references a proof in Kalkbrener 2002 which Tasche
characterizes as stating that "in the case of sub-additive and one
homogeneous risk measures only derivatives yield risk contributions
that do not exceed the corresponding stand-alone risks"(p.286).
Tasche also says "if a risk measure is smooth, we should use its partial
derivatives as risk contributions of the assets in the portfolio.
Otherwise we run the risk of receiving misleading information about
the profitability of the assets."(p.286)
Another point he makes in the conclusion to the chapter is:
"the allocation procedure has to be based on the derivatives of the
applied risk measure with respect to the weights of the sub-portfolios
or assets."(p. 299)
If you search the book for "Theorem I", you can read the Theorem itself
on pages 284 and 285 and read most of the proof as well.},
timestamp = {2008.04.29}
}
@ARTICLE{Thorp1997,
author = {Thorp, Edward O.},
title = {The Kelly Criterion in Blackjack, Sports Betting, and the Stock Market},
year = {1997, revised 1998},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Treynor1973,
author = {Treynor, Jack L. and Black, Fischer},
title = {How to Use Security Analysis to Improve Portfolio Selection},
journal = {Journal of Business},
year = {1973},
volume = {46},
pages = {66-86},
number = {1},
month = {January},
note = {available at http://ideas.repec.org/a/ucp/jnlbus/v46y1973i1p66-86.html},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Tsay2005,
title = {Analysis of Financial Time Series},
publisher = {Wiley},
year = {2005},
author = {Tsay, Ruey},
edition = {2},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Uryasev1999,
author = {Uryasev, S. and Rockafellar, R.},
title = {Optimization of Conditional Value-at-Risk},
journal = {Journal of Risk},
year = {2000},
volume = {2},
pages = {21-41},
number = {3},
owner = {brian},
timestamp = {2007.07.25}
}
@ARTICLE{Vaissie2003,
author = {Vaissie, Mathieu},
title = {A Detailed Analysis of the Construction Methods and Management Principles
of Hedge Fund Indices},
journal = {EDHEC Risk and Asset Management Research Centre},
year = {2003},
volume = {October},
owner = {brian},
timestamp = {2007.08.19}
}
@BOOK{Venables2002,
title = {Modern Applied Statistics with {S}. Fourth Edition},
publisher = {Springer},
year = {2002},
author = {William N. Venables and Brian D. Ripley},
note = {ISBN 0-387-95457-0},
abstract = {A highly recommended book on how to do statistical data analysis using
R or S-Plus. In the first chapters it gives an introduction to the
S language. Then it covers a wide range of statistical methodology,
including linear and generalized linear models, non-linear and smooth
regression, tree-based methods, random and mixed effects, exploratory
multivariate analysis, classification, survival analysis, time series
analysis, spatial statistics, and optimization. The `on-line complements'
available at the books homepage provide updates of the book, as well
as further details of technical material. },
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-22-1542120-0,00.html},
timestamp = {2008.04.27},
url = {http://www.stats.ox.ac.uk/pub/MASS4/}
}
@BOOK{VenablesRipley2002,
title = {Moderen Applied Statistics with S},
publisher = {Springer},
year = {2002},
author = {Venables, William N. and Ripley, Brian D.},
edition = {4},
owner = {peter},
timestamp = {2007.11.04}
}
@BOOK{Venables2000,
title = {S Programming},
publisher = {Springer},
year = {2000},
author = {William N. Venables and Brian D. Ripley},
note = {ISBN 0-387-98966-8},
abstract = {This provides an in-depth guide to writing software in the S language
which forms the basis of both the commercial S-Plus and the Open
Source R data analysis software systems.},
owner = {brian},
publisherurl = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-22-2104231-0,00.html},
timestamp = {2008.04.27},
url = {http://www.stats.ox.ac.uk/pub/MASS3/Sprog/}
}
@BOOK{Verzani2005,
title = {Using R for Introductory Statistics},
publisher = {Chapman \& Hall/CRC},
year = {2005},
author = {John Verzani},
address = {Boca Raton, FL},
note = {ISBN 1-584-88450-9},
abstract = {There are few books covering introductory statistics using R, and
this book fills a gap as a true ``beginner'' book. With emphasis
on data analysis and practical examples, `Using R for Introductory
Statistics' encourages understanding rather than focusing on learning
the underlying theory. It includes a large collection of exercises
and numerous practical examples from a broad range of scientific
disciplines. It comes complete with an online resource containing
datasets, R functions, selected solutions to exercises, and updates
to the latest features. A full solutions manual is available from
Chapman \& Hall/CRC.},
owner = {brian},
publisherurl = {http://www.crcpress.com/shopping_cart/products/product_detail.asp?sku=C4509&parent_id=&pc=},
timestamp = {2008.04.27},
url = {http://wiener.math.csi.cuny.edu/UsingR/}
}
@ARTICLE{White2006,
author = {White, Derek and Okunev, John },
title = {Moment Matching for the Masses},
journal = {SSRN eLibrary},
year = {2006},
abstract = {It is well known that Cholesky decomposition will compress the tails
in a multivariate probability mass. With significantly skewed or
highly kurtotic distributions, this tail compression can be quite
severe. In this paper, a simple methodology is presented to generate
multivariate systems matching the first four moments, a desired correlation
structure, and any number of tail points.},
keywords = {Value at Risk, Simulation, Cholesky decomposition, Risk Management,
multivariate moments},
language = {English},
location = {http://ssrn.com/paper=921451},
owner = {brian},
publisher = {SSRN},
timestamp = {2007.09.03},
type = {Working Paper Series},
url = {http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=921451}
}
@ARTICLE{Zangari1996,
author = {Zangari, Peter},
title = {A {VaR} Methodology for Portfolios that include Options},
journal = {RiskMetrics Monitor},
year = {1996},
volume = {First Quarter},
pages = {4-12},
owner = {brian},
timestamp = {2007.08.19}
}
@ARTICLE{Zhu2010,
author = {Zhu, Shushang and Li, Duan and Sun, Xiaoling},
title = {Portfolio selection with marginal risk control},
journal = {Journal of Computational Finance},
year = {2010},
pages = {Fall 2010, 1-26},
owner = {Administrator},
timestamp = {2010.12.19}
}
@BOOK{Zivot2006,
title = {Modeling Financial Time Series with S-Plus: second edition},
publisher = {Springer},
year = {2006},
author = {Zivot, Eric and Wang, Jiahui},
owner = {brian},
timestamp = {2007.08.19}
}
@PROCEEDINGS{Hornik2001,
title = {Proceedings of the 2nd International Workshop on Distributed Statistical
Computing (DSC 2001)},
year = {2001},
editor = {Kurt Hornik and Friedrich Leisch},
address = {Technische Universit{\"a}t Wien, Vienna, Austria},
note = {ISSN 1609-395X},
owner = {brian},
timestamp = {2008.04.27},
url = {http://www.ci.tuwien.ac.at/Conferences/DSC.html}
}
@BOOK{Matz2006,
title = {Liquidity Risk Measurement and Management: A Practitioner's Guide
to Global Best Practices},
publisher = {Wiley Finance},
year = {2006},
editor = {Matz, Leonard and Nue, Peter},
owner = {brian},
timestamp = {2007.09.02}
}
@MISC{EDHEC2003,
title = {About EDHEC Alternative Indexes},
howpublished = {\url{http://www.edhec-risk.com/indexes/pure_style/about}},
month = {December},
year = {2003},
journal = {EDHEC Risk and Asset Management Research Centre},
owner = {brian},
url = {http://www.edhec-risk.com/indexes/pure_style/about},
volume = {December 16}
}