TY - JOUR
TI - Properties of the Margrabe Best-of-Two strategy to tactical asset allocation
UR - http://dx.doi.org/10.2139/ssrn.3081036
KW - Best-of-Two, Bond-Equity, Margrabe, Tactical Asset Allocation, Upside Potential, Downside Protection
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Hartmann, S.
AU - Nguyen, G.
PY - 2019
DA - .
T2 - International Review of Financial Analysis, Forthcoming
IS - 00
VL - 00
SP - 01
EP - 01
ER -
TY - JOUR
TI - Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values
UR - http://dx.doi.org/10.2139/ssrn.2976084
KW - elastic-net, US industrial production, sentiment analysis, time-series aggregation, topic-sentiment, sentometrics
LA - en
AU - Ardia, D.
AU - Bluteau, K.
AU - Boudt, K.
PY - 2019
DA - .
T2 - International Journal of Forecasting, Forthcoming
IS - 0
VL - 0
SP - 01
EP - 01
ER -
TY - JOUR
TI - Generalized autoregressive score models in R: The GAS package
UR - http://dx.doi.org/10.18637/jss.v088.i06
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Catania, L.
PY - 2019
DA - 1.1
T2 - Journal of Statistical Software, Forthcoming
IS - 6
VL - 88
SP - 1
EP - 28
ER -
TY - JOUR
TI - Markov-switching GARCH models in R: The MSGARCH package
UR - http://dx.doi.org/10.2139/ssrn.2845809
LA - en
AU - Ardia, D.
AU - Bluteau, K.
AU - Boudt, K.
AU - Catania, L.
AU - Trottier, D. A.
PY - 2019
DA - .
T2 - Journal of Statistical Software, Forthcoming
IS - 0
VL - 0
SP - 01
EP - 01
ER -
TY - JOUR
TI - Regime changes in Bitcoin GARCH volatility dynamics
UR - https://doi.org/10.1016/j.frl.2018.08.009
LA - en
AU - Ardia, D.
AU - Bluteau, K.
AU - Ruede, M.
PY - 2019
DA - .
T2 - Finance Research Letters, Forthcoming
IS - 0
VL - 0
SP - 01
EP - 01
ER -
TY - JOUR
TI - Downside risk evaluation with the R package GAS
UR - http://dx.doi.org/10.32614/RJ-2018-064
KW - GAS, Time Series Models, Score Models, Dynamic Conditional Score, Risk Management, VaR, R Software
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Catania, L.
PY - 2018
DA - .
T2 - R Journal
IS - 2
VL - 10
SP - 410
EP - 421
ER -
TY - JOUR
TI - Forecasting risk with Markov-switching GARCH models: A large-scale performance study
UR - https://doi.org/10.1016/j.ijforecast.2018.05.004
LA - en
AU - Ardia, D.
AU - Bluteau, K.
AU - Boudt, K.
AU - Catania, L.
PY - 2018
DA - .
T2 - International Journal of Forecasting
IS - 4
VL - 34
SP - 733
EP - 747
ER -
TY - JOUR
TI - Methods for computing numerical standard errors: Review and application to Value-at-Risk estimation
UR - https://doi.org/10.1515/jtse-2017-0011
LA - en
AU - Ardia, D.
AU - Bluteau, K.
AU - Hoogerheide, L.
PY - 2018
DA - .7
T2 - Journal of Time Series Econometrics
IS - 2
VL - 10
SP - 1
EP - 9
ER -
TY - JOUR
TI - Beyond risk-based portfolios: Balancing performance and risk contributions in asset allocation
UR - https://doi.org/10.1080/14697688.2018.1424349
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Nguyen, G.
PY - 2018
DA - .
T2 - Quantitative Finance
IS - 8
VL - 18
SP - 1249
EP - 1259
ER -
TY - JOUR
TI - The peer performance ratios of hedge funds
UR - https://doi.org/10.1016/j.jbankfin.2017.10.014
LA - en
AU - Ardia, D.
AU - Boudt, K.
PY - 2018
DA - .
T2 - Journal of Banking and Finance
VL - 87
SP - 351
EP - 368
ER -
TY - JOUR
TI - The impact of parameter and model uncertainty on market risk predictions from GARCH-type models
UR - http://onlinelibrary.wiley.com/doi/10.1002/for.2472/full
KW - GARCH models; Bayesian and frequentist estimation; predictive density combination; beta linear pool; censored optimal pooling; backtesting
LA - en
AU - Ardia, D.
AU - Kolly, J.
AU - Trottier, D. A.
PY - 2017
DA - .11
T2 - Journal of Forecasting
IS - 7
VL - 36
SP - 808
EP - 823
ER -
TY - JOUR
TI - The impact of covariance misspecification in risk-based portfolios
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Bolliger, G.
AU - Gagnon-Fleury, P.
PY - 2017
DA - .3
AB - The equal-risk-contribution, inverse-volatility weighted, maximum-diversification and minimum-variance portfolio weights are all direct functions of the estimated covariance matrix. We perform a Monte Carlo study to assess the impact of covariance matrix misspecification to these risk-based portfolios at the daily, weekly and monthly forecasting horizon. Our results show that the equal-risk-contribution and inverse-volatility weighted portfolio weights are relatively robust to covariance misspecification. In contrast, the minimum-variance portfolio weights are highly sensitive to errors in both the estimated variances and correlations, while errors in the estimated correlations can have a large effect on the weights of the maximum-diversification portfolio.
T2 - Annals of Operations Research
VL - 0
SP - 1
EP - 5
ER -
TY - JOUR
TI - A new bootstrap test for multiple assets joint risk testing
UR - https://www.risk.net/journal-of-risk/4562496/a-new-bootstrap-test-for-multiple-assets-joint-risk-testing
LA - en
AU - Ardia, D.
AU - Gatarek, L.
AU - Hoogerheide, L.
PY - 2017
DA - .4
T2 - Journal of Risk
IS - 4
VL - 19
SP - 1
EP - 22
ER -
TY - JOUR
TI - nse: Computation of numerical standard errors in R
UR - http://dx.doi.org/10.21105/joss.00172
KW - Bootstrap, GARCH, HAC kernel, numerical standard error (NSE), spectral density
LA - en
AU - Ardia, D.
AU - Bluteau, K.
PY - 2017
DA - .2
AB - nse is an R package (R Core Team (2016)) for computing the numerical standard error (NSE), an estimate of the standard deviation of a simulation result if the simulation experiment were to be repeated many times. The package provides a set of wrappers around several R packages, which give access to more than thirty estimators, including batch means estimators (Geyer (1992 Section 3.2)), initial sequence estimators (Geyer (1992 Equation 3.3)), spectrum at zero estimators (Heidelberger and Welch (1981),Flegal and Jones (2010)), heteroskedasticity and autocorrelation consistent (HAC) kernel estimators (Newey and West (1987),Andrews (1991),Andrews and Monahan (1992),Newey and West (1994),Hirukawa (2010)), and bootstrap estimators Politis and Romano (1992),Politis and Romano (1994),Politis and White (2004)).
T2 - Journal of Open Source Software
IS - 2
VL - 10
SP - 1
EP - 1
ER -
TY - JOUR
TI - RiskPortfolios: Computation of risk-based portfolios in R
UR - http://dx.doi.org/10.21105/joss.00171
KW - Risk-based portfolios, optimization, R software
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Gagnon-Fleury, P.
PY - 2017
DA - .2
AB - RiskPortfolios is an R package for constructing risk-based portfolios. It provides a set of functionalities to build mean-variance, minimum variance, inverse-volatility weighted (Leote De Carvalho, Lu, and Moulin (2012)), equal-risk-contribution (Maillard, Roncalli, and Teïletche (2010)), maximum diversification (Choueifaty and Coignard (2008)), and risk-efficient (Amenc et al. (2011)) portfolios. Optimization is achieved with the R packages quadprog (Weingessel (2013)) and nloptr (Ypma (2014)). Long or gross constraints can be added to the optimizer. As risk-based portfolios are mainly based on covariances, the package also provides a large set of covariance matrix estimators.
T2 - Journal of Open Source Software
IS - 2
VL - 10
SP - 1
EP - 1
ER -
TY - JOUR
TI - Stress-testing with parametric models and Fully Flexible Probabilities
UR - http://onlinelibrary.wiley.com/doi/10.1002/wilm.10565/full
KW - Fully flexible probabilities, GARCH, Stress-testing
LA - en
AU - Ardia, D.
AU - Bluteau, K.
PY - 2017
DA - .1
AB - We propose a simple methodology to simulate scenarios from a parametric risk model while accounting for stress-test views via fully flexible probabilities (Meucci, 2010, 2013).
T2 - Wilmott Magazine
VL - 87
SP - 52
EP - 55
ER -
TY - JOUR
TI - Smart beta and CPPI performance
UR - http://www.en.affi.asso.fr/151-finance-journal.htm
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Wauters, M.
PY - 2016
DA - .
T2 - Finance
IS - 3
VL - 37
SP - 32
EP - 65
ER -
TY - JOUR
TI - Macroeconomic stress-testing of mortgage default rate using a vector error correction model and entropy pooling
UR - http://www.revueassurances.ca/en/
KW - mortgage default probability, entropy pooling, macroeconomic variables, stress-testing, VECM
LA - en
AU - Ardia, D.
AU - Guerrouaz, A.
AU - Rey, J.
PY - 2016
DA - .
AB - We propose a methodology to perform macroeconomic stress-testing on the probability of default of a given borrowers’ population (i.e., aggregate probability of default) through simulation from a vector error correction model and entropy pooling (Meucci, 2008).
T2 - Insurance and Risk Management
IS - 3-4
VL - 83
SP - 115
EP - 133
ER -
TY - JOUR
TI - Moments of standardized Fernandez–Steel skewed distributions: Applications to the estimation of GARCH-type models
UR - http://www.sciencedirect.com/science/article/pii/S1544612316300836
KW - Asymmetric GARCH, Backtesting, Bayesian, Maximum likelihood, Skewness
LA - en
AU - Trottier, D. A.
AU - Ardia, D.
PY - 2016
DA - .8
AB - We provide general expressions for obtaining raw, absolute and conditional moments for a standardized version of the class of skewed distributions proposed by Fernandez and Steel (1998). We show that these expressions are readily programmable in addition of greatly reducing the computational cost. We discuss several applications that are relevant for the purpose of estimating asymmetric conditional volatility models under skewed distributions.
T2 - Finance Research Letters
VL - 18
SP - 311
EP - 316
ER -
TY - JOUR
TI - A Note on Jointly Backtesting Models for Multiple Assets and Horizons
UR - http://onlinelibrary.wiley.com/doi/10.1002/wilm.10509/abstract
KW - bootstrap test;GARCH;dependent time series;multiple testing;value-at-risk
LA - en
AU - Ardia, D.
AU - Guerrouaz, A.
AU - Hoogerheide, L.
PY - 2016
DA - .5
AB - We propose a simulation-based methodology, which allows us to test the performance of multi-level and/or multi-horizon value-at-risk forecasts.
T2 - Wilmott Magazine
VL - 83
SP - 46
EP - 49
ER -
TY - JOUR
TI - Predicting market risk with density combination: An introduction
UR - http://onlinelibrary.wiley.com/doi/10.1002/wilm.10473/abstract
KW - Density forecast combination, censoring, incomplete model set, risk model contribution, skew Student-t distribution, pool risk forecasts
LA - en
AU - Ardia, D.
AU - Kolly, J.
PY - 2016
DA - .
AB - Density forecast combination is a useful tool for risk managers to reduce model risk. We present up-to-date methodologies in the field, discuss key issues and provide some illustrations.
T2 - Wilmott Magazine
VL - 81
SP - 52
EP - 57
ER -
TY - JOUR
TI - Return and risk of pairs trading using a simulation-based Bayesian procedure for predicting stable ratios of stock prices
UR - http://www.mdpi.com/2225-1146/4/1/14
KW - Bayesian analysis; cointegration; linear normalization; orthogonal normalization; pairs trading; statistical arbitrage
LA - en
AU - Ardia, D.
AU - Gatarek, L. T.
AU - Hoogerheide, L.
AU - Van Dijk , H.
PY - 2016
DA - .
AB - We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior, which is shown to be equivalent to a Jeffreys’ prior, has under an orthogonal normalization for the selection of pairs of cointegrated stock prices and further, its effect for the estimation and prediction of the spread between cointegrated stock prices. We distinguish between models with a normal and Student t distribution since the latter typically provides a better description of daily changes of prices on financial markets. As an empirical application, stocks are used that are ingredients of the Dow Jones Composite Average index. The results show that normalization has little effect on the selection of pairs of cointegrated stocks on the basis of Bayes factors. However, the results stress the importance of the orthogonal normalization for the estimation and prediction of the spread—the deviation from the equilibrium relationship—which leads to better results in terms of profit per capital engagement and risk than using a standard linear normalization.
T2 - Econometrics
IS - 1
VL - 4
SP - 1
EP - 19
ER -
TY - JOUR
TI - The economic benefits of market timing the style allocation of characteristic-based portfolios
UR - http://www.sciencedirect.com/science/article/pii/S1062940816300171
KW - Exchange traded funds; Factor models; Portfolio choice; Stock characteristics; Style investing
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Wauters, M.
PY - 2016
DA - .
AB - Many exchange traded funds track simple characteristic-based equity portfolios such as the market capitalization, the fundamental value or the inverse volatility portfolio. This paper provides theoretical and empirical evidence for the economic benefits in exploiting the timing-gains that result from the time-varying relative performance of these characteristic-based portfolios. Under a factor model for expected returns, we show that this dynamic portfolio allocation can be efficient across the low-dimensional set of characteristic-based portfolios. We assess the out-of-sample performance on the S&P 100 universe over the period 1990–2013 and show gains in stability and significant positive risk-adjusted returns for the dynamic style portfolio. We conduct several robustness tests and extensions confirming the benefits of dynamic style allocation across characteristic-based portfolios.
T2 - The North American Journal of Economics and Finance
VL - 37
SP - 38
EP - 62
ER -
TY - JOUR
TI - Testing the equality of modified Sharpe ratios
UR - http://www.sciencedirect.com/science/article/pii/S1544612315000264
KW - Bootstrap test; Hedge fund; Modified Sharpe ratio; Non-normal returns; Performance measurement
LA - en
AU - Ardia, D.
AU - Boudt, K.
PY - 2015
DA - .
AB - The modified Sharpe ratio is commonly used to evaluate the risk-adjusted performance of an investment with non-normal returns, such as hedge funds. In this note, a test for equality of modified Sharpe ratios of two investments is developed. A simulation study demonstrates the good size and power properties of the test. An application illustrates the complementarity between the Sharpe ratio and modified Sharpe ratio test for performance testing on hedge fund return data.
T2 - Finance Research Letters
VL - 13
SP - 97
EP - 104
ER -
TY - JOUR
TI - Parametric stress-testing in non-normal markets via entropy pooling
UR - http://www.risk.net/risk-magazine/technical-paper/2410967/stress-testing-in-non-normal-markets-via-entropy-pooling
KW - Entropy Pooling, Kullback-Leibler, copula-marginal, stress-test, risk
LA - en
AU - Ardia, D.
AU - Meucci, A.
PY - 2015
DA - .
AB - A novel approach for stress-testing (portfolios of) financial assets is presented. The technique extends the parametric Entropy Pooling approach to skewed and thick-tailed markets. The technique rests on a copula-marginal decomposition for the entropy together with several approximation schemes which renders the numerical computations feasible for real-life problems. An illustration with a portfolio of European options is presented.
T2 - Risk Magazine
VL - June
SP - 1
EP - 5
ER -
TY - JOUR
TI - Implied expected returns and the choice of a mean-variance efficient portfolio proxy
UR - http://www.iijournals.com/doi/abs/10.3905/jpm.2015.41.4.068?journalCode=jpmImplied expected returns are the expected returns for which a supposedly mean–variance efficient portfolio is effectively efficient, given a covariance matrix. The authors analyze the properties of monthly implied expected stock returns and study their sensitivity to the choice of mean–variance efficient portfolio proxy. For the universe of S&P 100 stocks over the period from 1984 to 2014, they find that using as risk-based portfolio proxy with respect to a market capitalization or fundamental value portfolio brings its biggest gains in return forecasts’ stability and precision. For all the proxies considered, they report that the implied expected returns outperform forecasts based on a time-series model in stability and precision.
KW - Implied expected return, mean-variance, portfolio allocation, reverse engineering, risk-based allocation
LA - en
AU - Ardia, D.
AU - Boudt, K.
PY - 2015
DA - .
AB - Implied expected returns are the expected returns for which a supposedly mean–variance efficient portfolio is effectively efficient, given a covariance matrix. The authors analyze the properties of monthly implied expected stock returns and study their sensitivity to the choice of mean–variance efficient portfolio proxy. For the universe of S&P 100 stocks over the period from 1984 to 2014, they find that using as risk-based portfolio proxy with respect to a market capitalization or fundamental value portfolio brings its biggest gains in return forecasts’ stability and precision. For all the proxies considered, they report that the implied expected returns outperform forecasts based on a time-series model in stability and precision.
T2 - Journal of Portfolio Management
IS - 4
VL - 41
SP - 68
EP - 81
ER -
TY - CHAP
TI - Large scale portfolio optimization with DEoptim
T2 - Soft-Computing in Capital Market: Research and Methods of Computational Finance for Measuring Risk of Financial Instruments
CY - Boca Raton, Florida
AU - Ardia, D.
AU - Boudt, K.
AU - Mullen , K.
AU - Peterson, B.
LA - en
PY - 2014
PB - BrownWalker Press
ER -
TY - JOUR
TI - Worldwide equity risk prediction
UR - http://www.tandfonline.com/doi/pdf/10.1080/13504851.2013.806775
KW - GARCH, value-at-risk, equity, worldwide, false discovery rate
LA - en
AU - Ardia, D.
AU - Hoogerheide, L.
PY - 2014
DA - .
AB - Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indices worldwide. The value-at-risk forecast performance is investigated for different markets and industries, considering the test for correct conditional coverage using the false discovery rate (FDR) methodology. For most of the markets and industries we find the same two conclusions. First, an asymmetric GARCH specification is essential when forecasting the 95% value-at-risk. Second, for both the 95% and 99% value-at-risk it is crucial that the innovations’ distribution is fat-tailed (e.g., Student-t or – even better – a non-parametric kernel density estimate).
T2 - Applied Economics Letters
IS - 14
VL - 20
SP - 1333
EP - 1339
ER -
TY - JOUR
TI - Estimation frequency of GARCH-type models: Impact on Value-at-Risk and Expected Shortfall forecasts?
UR - http://www.sciencedirect.com/science/article/pii/S0165176514000640
KW - GARCH; Value-at-Risk; Expected Shortfall; Equity; Frequency; False discovery rate
LA - en
AU - Ardia, D.
AU - Hoogerheide, L.
PY - 2014
DA - .
AB - We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the implication for one-day ahead 95% and 99% Value-at-Risk (VaR) forecasts with the test for correct conditional coverage of Christoffersen (1998) and for Expected Shortfall (ES) forecasts with the block-bootstrap test of ES violations of Jalal and Rockinger (2008). Using the false discovery rate methodology of Storey (2002) to estimate the percentage of stocks for which the model yields correct VaR and ES forecasts, we conclude that there is no difference in performance between updating the parameter estimates of the GARCH equation at a daily or weekly frequency, whereas monthly or even quarterly updates are only marginally outperformed.
T2 - Economics Letters
VL - 123
SP - 187
EP - 190
ER -
TY - JOUR
TI - Quantitative portfolio construction and systematic trading strategies using factor entropy pooling
UR - http://www.risk.net/risk-magazine/technical-paper/2340264/portfolio-construction-and-systematic-trading-with-factor-entropy-pooling
KW - Trading signals, tactical allocation, Black-Litterman, equilibrium prior, shrinkage, risk management, Entropy Pooling, factor models, inequality views, portfolios from sorts, ranking, Kullback-Leibler
LA - en
AU - Meucci, A.
AU - Ardia, D.
AU - Colasante, M.
PY - 2014
DA - .
AB - The Entropy Pooling approach is a versatile theoretical framework to process market views and generalized stress-tests into an optimal "posterior" market distribution, which is then used for risk management and portfolio management. Entropy Pooling can be implemented non-parametrically or parametrically. The non-parametric implementation with historical scenarios is more suitable for risk management applications.
Here introduce the parametric implementation of Entropy Pooling under a factor structure, which we name Factor Entropy Pooling. The factor structure reduces the dimension of the problem and linearizes the parameter space, allowing for fast computation of the posterior market distribution.
We apply Factor Entropy Pooling to two portfolio construction problems.
First, we use the Factor Entropy Pooling to construct the "implied returns", i.e. a market distribution consistent with a target optimal portfolio, such as maximum diversification/risk parity, or the CAPM equilibrium. Our approach improves on the implied returns a-la-Black-Litterman, and the ensuing distribution can be used as the starting point for further portfolio construction.
Second, we use Factor Entropy Pooling to construct and backtest quantitative systematic trading strategies based on ranking views, or "portfolios from sorts". Unlike standard approaches, Factor Entropy Pooling closely ties to the actual empirical data.
T2 - Risk Magazine
IS - 5
VL - 27
SP - 56
EP - 61
ER -
TY - CHAP
TI - The short-run persistence of performance in funds of hedge funds
T2 - Reconsidering Funds of Hedge Funds: The Financial Crisis and Best Practices in UCITS, Tail Risk, Performance, and Due Diligence
CY - New-York
UR - http://www.sciencedirect.com/science/article/pii/B9780124016996000186
AU - Ardia, D.
AU - Boudt, K.
LA - en
PY - 2013
AB - There is extensive empirical evidence that funds of hedge funds (FoHFs) quickly change their investment bets as a function of the changing market conditions. In this chapter, we first analyze the stability of risk exposure and performance of FoHFs during the period January 2005–June 2011. We then study the short-run persistence of performance in the FoHFs industry. Past performance is measured using the 1-year trailing return as well as risk-adjusted measures such as the Sharpe ratio and the fund’s alpha based on the Carhart (1997) or Fung and Hsieh (2004) factor models. Over the examined timeframe, we consistently find that using risk-adjusted return measures improves the risk-adjusted performance of the momentum investment strategy. This finding holds for the financial crisis period as well as the pre- and post-crisis periods.
KW - Alpha, Funds of Hedge funds, Hot hands, Performance, Sharpe ratio
PB - G. N. Gregoriou
ER -
TY - JOUR
TI - Cross-sectional distribution of GARCH coefficients across S&P 500 constituents
UR - http://onlinelibrary.wiley.com/doi/10.1002/wilm.10232/abstract
KW - GARCH;GJR;equity;leverage effect;S&P 500 universe
LA - en
AU - Ardia, D.
AU - Hoogerheide, L.
PY - 2013
DA - .
AB - We investigate the time-variation of the cross-sectional distribution of asymmetric GARCH model parameters over the S&P 500 constituents for the period 2000-2012. We find the following results. First, the unconditional variances in the GARCH model obviously show major time-variation, with a high level after the dot-com bubble and the highest peak in the latest financial crisis. Second, in these more volatile periods it is especially the persistence of deviations of volatility from its unconditional mean that increases. Particularly in the latest financial crisis, the estimated models tend to Integrated GARCH models, which can cope with an abrupt regime-shift from low to high volatility levels. Third, the leverage effect tends to be somewhat higher in periods with higher volatility. Our findings are mostly robust across sectors, except for the technology sector, which exhibits a substantially higher volatility after the dot-com bubble. Further, the financial sector shows the highest volatility during the latest financial crisis. Finally, in an analysis of different market capitalizations, we find that small cap stocks have a higher volatility than large cap stocks where the discrepancy between small and large cap stocks increased during the latest financial crisis. Small cap stocks also have a larger conditional kurtosis and a higher leverage effect than mid cap and large cap stocks.
T2 - Wilmott Magazine
VL - 66
SP - 40
EP - 44
ER -
TY - JOUR
TI - Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?
UR - http://www.sciencedirect.com/science/article/pii/S016517651200122X
KW - GARCH; Bayesian; KLIC; Censored likelihood
LA - en
AU - Hoogerheide, L.
AU - Ardia, D.
AU - Corré, N.
PY - 2012
DA - .
AB - Using GARCH models for density prediction of stock index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between qualities of whole density forecasts, whereas the Bayesian approach exhibits significantly better left-tail forecast accuracy.
T2 - Economics Letters
IS - 3
VL - 116
SP - 322
EP - 325
ER -
TY - JOUR
TI - A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihoods
UR - http://www.sciencedirect.com/science/article/pii/S0167947310003440
KW - Marginal likelihood; Bayes factor; Importance sampling; Bridge sampling; Adaptive mixture of Student-tt distributions
LA - en
AU - Ardia, D.
AU - Basturk, N.
AU - Hoogerheide, L.
AU - Van Dijk , H.
PY - 2012
DA - .
AB - Strategic choices for efficient and accurate evaluation of marginal likelihoods by means of Monte Carlo simulation methods are studied for the case of highly non-elliptical posterior distributions. A comparative analysis is presented of possible advantages and limitations of different simulation techniques; of possible choices of candidate distributions and choices of target or warped target distributions; and finally of numerical standard errors. The importance of a robust and flexible estimation strategy is demonstrated where the complete posterior distribution is explored. Given an appropriately yet quickly tuned adaptive candidate, straightforward importance sampling provides a computationally efficient estimator of the marginal likelihood (and a reliable and easily computed corresponding numerical standard error) in the cases investigated, which include a non-linear regression model and a mixture GARCH model. Warping the posterior density can lead to a further gain in efficiency, but it is more important that the posterior kernel be appropriately wrapped by the candidate distribution than that it is warped.
T2 - Computational Statistics & Data Analysis
IS - 11
VL - 56
SP - 3398
EP - 3414
ER -
TY - JOUR
TI - Jump-diffusion calibration using Differential Evolution
UR - http://onlinelibrary.wiley.com/doi/10.1002/wilm.10034/abstract
KW - Jump-Diffusion, Maximum Likelihood, Optimization, Differential Evolution
LA - en
AU - Ardia, D.
AU - Ospina , J. D.
AU - Giraldo Gomez, J. D.
PY - 2011
DA - .
AB - The estimation of a jump-diffusion model via Differential Evolution is presented. Finding the maximum likelihood estimator for such processes is a tedious task due to the multimodality of the likelihood function. The performance of the Differential Evolution algorithm is compared with standard optimization techniques.
T2 - Wilmott Magazine
VL - 55
SP - 76
EP - 79
ER -
TY - JOUR
TI - DEoptim: An R package for global optimization by Differential Evolution
UR - https://www.jstatsoft.org/article/view/v040i06
KW - Global optimization, evolutionary algorithm, differential evolution, R software
LA - en
AU - Mullen , K.
AU - Ardia, D.
AU - Gil, D. L.
AU - Windover , D.
AU - Cline, J.
PY - 2011
DA - .
AB - This article describes the R package DEoptim, which implements the Differential Evolution algorithm for global optimization of a real-valued function of a real-valued parameter vector. The implementation of Differential Evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated by case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-Switching Generalized AutoRegressive Conditional Heteroskedasticity model for the returns of the Swiss Market Index.
T2 - Journal of Statistical Software
IS - 6
VL - 40
SP - 1
EP - 26
ER -
TY - JOUR
TI - Differential Evolution with DEoptim: An application to non-convex portfolio optimization
UR - https://journal.r-project.org/archive/2011-1/RJournal_2011-1_Ardia~et~al.pdf
KW - Differential optimization, non-convex portfolio optimization, DEoptim, R software
LA - en
AU - Ardia, D.
AU - Boudt, K.
AU - Carl, P.
AU - Mullen , K.
AU - Peterson, B.
PY - 2011
DA - .
AB - The R package DEoptim implements the differential evolution algorithm. This algorithm is an evolutionary technique similar to genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex optimization problem.
T2 - The R Journal
IS - 1
VL - 3
SP - 27
EP - 34
ER -
TY - JOUR
TI - Generalized marginal risk
UR - http://www.palgrave-journals.com/jam/journal/v12/n2/full/jam201030a.html
KW - Marginal Risk, Component Risk, Generalized Marginal Risk, Value-at-Risk, Expected Shortfall, Elliptical Distribution
LA - en
AU - Ardia, D.
AU - Keel, S.
PY - 2011
DA - .
AB - An important aspect of portfolio risk management is the analysis of the overall risk with respect to the assets' allocations. Marginal risk is the traditional tool, however, this metric is only meaningful when a position is levered or when the proceeds from the sale of a position are put in the cash account. This paper proposes an extension of the traditional marginal risk approach as a means of overcoming this defficiency. The new concept addresses situations where the change in a position results in changes to other positions as well. An illustration is provided for synthetic and real-world portfolios.
T2 - Journal of Asset Management
VL - 12
SP - 123
EP - 131
ER -
TY - JOUR
TI - Fully flexible extreme views
UR - http://www.risk.net/journal-of-risk/technical-paper/2161037/fully-flexible-extreme-views
KW - Entropy Pooling, Kullback-Leibler, Black-Litterman, VaR, CVaR, grid-probability pair, Monte Carlo, Gauss-Hermite polynomials, Newton-Raphson, kernel estimator
LA - en
AU - Meucci, A.
AU - Ardia, D.
AU - Keel, S.
PY - 2011
DA - .
AB - We extend the Fully Flexible Views generalization of the Black-Litterman approach to effectively handle extreme views on the tails of a distribution.
First, we provide a recursive algorithm to process views on the conditional value at risk, which cannot be handled directly by the original implementation of Fully Flexible Views.
Second, we represent both the prior and the posterior distribution on a grid, instead of by means of Monte Carlo scenarios: this way it becomes possible to cover parsimoniously even the far tails of the underlying distribution. Documented code is available for download.
T2 - Journal of Risk
IS - 2
VL - 14
SP - 39
EP - 49
ER -
TY - CHAP
TI - Efficient Bayesian estimation and combination of GARCH-type models
T2 - Rethinking Risk Measurement and Reporting
CY - London
UR - http://riskbooks.com/rethinking-risk-measurement-and-reporting-volumes-i-and-ii
AU - Ardia, D.
AU - Hoogerheide, L.
LA - en
PY - 2010
AB - This chapter proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient procedure named AdMitIS. The methodology automatically constructs a mixture of Student-t distributions as an approximation to the posterior density of the model parameters. This density is then used in importance sampling for model estimation, model selection and model combination. The procedure is fully automatic which avoids difficult and time consuming tuning of MCMC strategies. The AdMitIS methodology is illustrated with an empirical application to S&P index log-returns where non-nested GARCH-type models are estimated and combined to predict the distribution of next-day ahead log-returns.
KW - GARCH, Bayesian inference, MCMC, marginal likelihood, Bayesian model averaging, adaptive mixture of Student-t distributions, importance sampling
T3 - Risk Books
PB - Klaus Bocker
VL - II
ER -
TY - JOUR
TI - Bayesian estimation of the GARCH(1,1) model with Student-t innovations in R
UR - https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Ardia+Hoogerheide.pdf
KW - GARCH, Bayesian, MCMC, Student-t, R software
LA - en
AU - Ardia, D.
AU - Hoogerheide, L.
PY - 2010
DA - .
AB - This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns.
T2 - The R Journal
IS - 2
VL - 2
SP - 41
EP - 47
ER -
TY - JOUR
TI - Bayesian estimation of a Markov-switching threshold GARCH model with Student-t innovations
UR - http://onlinelibrary.wiley.com/doi/10.1111/j.1368-423X.2008.00253.x/abstract
KW - Asymmetry;Bayesian;GARCH;Markov-switching;SMI;Threshold
LA - en
AU - Ardia, D.
PY - 2009
DA - .
AB - A Bayesian estimation of a regime-switching threshold asymmetric GARCH model is proposed. The specification is based on a Markov-switching model with Student-t innovations and K separate GJR(1,1) processes whose asymmetries are located at free non-positive threshold parameters. The model aims at determining whether or not: (i) structural breaks are present within the volatility dynamics; (ii) asymmetries (leverage effects) are present, and are different between regimes and (iii) the threshold parameters (locations of bad news) are similar between regimes. A novel MCMC scheme is proposed which allows for a fully automatic Bayesian estimation of the model. The presence of two distinct volatility regimes is shown in an empirical application to the Swiss Market Index log-returns. The posterior results indicate no differences with regards to the asymmetries and their thresholds when comparing highly volatile periods with the milder ones. Comparisons with a single-regime specification indicates a better in-sample fit and a better forecasting performance for the Markov-switching model.
T2 - Econometrics Journal
IS - 1
VL - 12
SP - 105
EP - 126
ER -
TY - JOUR
TI - Adaptive mixture of Student-t distributions as a flexible distribution for efficient simulation: The R package AdMit
UR - https://www.jstatsoft.org/article/view/v029i03
KW - Adaptive mixture, Student-t distributions, importance sampling, independence chain Metropolis-Hasting algorithm, Bayesian, R software
LA - en
AU - Ardia, D.
AU - Hoogerheide, L.
AU - Van Dijk , H.
PY - 2009
DA - .
AB - This paper presents the R package AdMit which provides flexible functions to approximate a certain target distribution and to efficiently generate a sample of random draws from it, given only a kernel of the target density function. The core algorithm consists of the function AdMit which fits an adaptive mixture of Student-t distributions to the density of interest. Then, importance sampling or the independence chain Metropolis-Hastings algorithm is used to obtain quantities of interest for the target density, using the fitted mixture as the importance or candidate density. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. The relevance of the package is shown in two examples. The first aims at illustrating in detail the use of the functions provided by the package in a bivariate bimodal distribution. The second shows the relevance of the adaptive mixture procedure through the Bayesian estimation of a mixture of ARCH model fitted to foreign exchange log-returns data. The methodology is compared to standard cases of importance sampling and the Metropolis-Hastings algorithm using a naive candidate and with the Griddy-Gibbs approach.
T2 - Journal of Statistical Software
IS - 3
VL - 29
SP - 1
EP - 32
ER -
TY - JOUR
TI - AdMit: Adaptive mixtures of Student-t distributions
UR - https://journal.r-project.org/archive/2009-1/RJournal_2009-1_Ardia+et+al.pdf
KW - Adaptive mixture, Student-t distributions, importance sampling, independence chain Metropolis-Hasting algorithm, Bayesian, R software
LA - en
AU - Ardia, D.
AU - Hoogerheide, L.
AU - Van Dijk , H.
PY - 2009
DA - .
AB - This short note presents the R package AdMit which provides flexible functions to approximate a certain target distribution and it provides an efficient sample of random draws from it, given only a kernel of the target density function. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. To illustrate the use of the package, we apply the AdMit methodology to a bivariate bimodal distribution. We describe the use of the functions provided by the package and document the ability and relevance of the methodology to reproduce the shape of non-elliptical distributions.
T2 - The R Journal
IS - 1
VL - 1
SP - 25
EP - 30
ER -
TY - BOOK
TI - Financial Risk Management with Bayesian Estimation of GARCH Models: Theory and Applications
UR - http://www.springer.com/us/book/9783540786566
AU - Ardia, D.
PY - 2008
AB - This book presents in detail methodologies for the Bayesian estimation of single-regime and regime-switching GARCH models. These models are widespread and essential tools in financial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach offers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The first two chapters introduce the work and give a short overview of the Bayesian paradigm for inference. The next three chapters describe the estimation of the GARCH model with Normal innovations and the linear regression models with conditionally Normal and Student-t-GJR errors. For these models, we compare the Bayesian and Maximum Likelihood approaches based on real financial data. In particular, we document that even for fairly large data sets, the parameter estimates and confidence intervals are different between the methods. Caution is therefore in order when applying asymptotic justifications for this class of models. The sixth chapter presents some financial applications of the Bayesian estimation of GARCH models. We show how agents facing different risk perspectives can select their optimal VaR point estimate and document that the differences between individuals can be substantial in terms of regulatory capital. Finally, the last chapter proposes the estimation of the Markov-switching GJR model. An empirical application documents the in- and out-of-sample superiority of the regime-switching specification compared to single-regime GJR models. We propose a methodology to depict the density of the one-day ahead VaR and document how specific forecasters’ risk perspectives can lead to different conclusions on the forecasting performance of the MS-GJR model.
T2 - Lecture Notes in Economics and Mathematical Systems
PB - Springer
CY - Heidelberg
KW - Bayesian, MCMC, GARCH, GJR, Markov-switching, Value at Risk, Expected Shortfall, Bayes factor, DIC
LA - en
VL - 612
SP - 206
ER -
TY - JOUR
TI - Tests d'arbitrage sur options. Une analyse empirique des cotations de market-makers
LA - fr
AU - Ardia, D.
PY - 2007
DA - .
T2 - Banque et Marchés
VL - 89
SP - 45
EP - 54
ER -