• Corpus ID: 221879400

Portfolio Optimization on Multivariate Regime Switching GARCH Model with Normal Tempered Stable Innovation.

@article{Peng2020PortfolioOO,
  title={Portfolio Optimization on Multivariate Regime Switching GARCH Model with Normal Tempered Stable Innovation.},
  author={Cheng Peng and Young Shin Kim},
  journal={arXiv: Risk Management},
  year={2020}
}
We propose a Markov regime switching GARCH model with multivariate normal tempered stable innovation to accommodate fat tails and other stylized facts in returns of financial assets. The model is used to simulate sample paths as input for portfolio optimization with risk measures, namely, conditional value at risk and conditional drawdown. The motivation is to have a portfolio that avoids left tail events by combining models that incorporates fat tail with optimization that focuses on tail risk… 

Figures and Tables from this paper

Disasters, Large Drawdowns, and Long-term Asset Management
Long-term investors are often reluctant to invest in assets or strategies that can suffer from large drawdowns. A major challenge for such investors is to gain access to predictions of large

References

SHOWING 1-10 OF 29 REFERENCES
A multivariate regime-switching GARCH model with an application to global stock market and real estate equity returns
Abstract We consider a multivariate Markov-switching GARCH model which allows for regime-specific volatility dynamics, leverage effects, and correlation structures. Conditions for stationarity and
Measuring financial risk and portfolio optimization with a non-Gaussian multivariate model
TLDR
A multivariate market model with returns assumed to follow a multivariate normal tempered stable distribution that is consistent with two stylized facts that have been observed for asset distributions, which offers more realistic portfolio risk measures and a more tractable method for portfolio optimization.
Foster-Hart optimization for currency portfolios
Abstract We examine the effectiveness of Foster-Hart optimization for currency portfolios. Compared to stock trading, short selling is quite common in currency trading. Combining long and short
RIDING WITH THE FOUR HORSEMEN AND THE MULTIVARIATE NORMAL TEMPERED STABLE MODEL
In this paper, we study a model that captures four stylized facts about multivariate financial time series of equity returns: heavy tails, negative skew, asymmetric dependence, and volatility
A discussion on the innovation distribution of the Markov regime-switching GARCH model
The Markov Regime-Switching Generalized autoregressive conditional heteroskedastic (MRS-GARCH) model is a widely used approach to model the financial volatility with potential structural breaks. The
Comparative Analysis of Linear Portfolio Rebalancing Strategies: An Application to Hedge Funds
This paper applies formal risk management methodologies to optimization of a portfolio of hedge funds (fund of funds). We compare recently developed risk management methodologies: Conditional
A New Approach to Markov-Switching GARCH Models
TLDR
It is argued that the disaggregation of the variance process offered by the new model is more plausible than in the existing variants and the results suggest that a promising volatility model is an independent switching GARCH process with a possibly skewed conditional mixture density.
Optimization of conditional value-at risk
A new approach to optimizing or hedging a portfolio of nancial instruments to reduce risk is presented and tested on applications. It focuses on minimizing Conditional Value-at-Risk (CVaR) rather
MCMC-based estimation of Markov Switching ARMA–GARCH models
Regime switching models, especially Markov Switching (MS) models, are regarded as a promising way to capture nonlinearities in time series. Combining the elements of MS models with full
Conditional value-at-risk in portfolio optimization: Coherent but fragile
TLDR
It is concluded that CVaR, a coherent risk measure, is fragile in portfolio optimization due to estimation errors, which are magnified when the tail of the return distribution is made heavier.
...
1
2
3
...