The Asymptotics of Extreme Returns in the Australian Stock Market

Jeyasreedharan, Nagaratnam; Alles, Lakshman; Yatawara, Nihal

doi:10.2139/ssrn.1460371

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Despite the promise of useful implementation of EVT in financial market analysis, it has only recently gained the attention of researchers in Australia. Chan and Gray (2006) , Thomas et al (2009) andJeyasreedharan et al (2009) are amongst the few studies to have used the technique. The lack of implementation of EVT methods on Australian markets act as our motivation to test it further on Australian market.…”

Section: Introductionmentioning

confidence: 99%

Value at Risk Estimation using Extreme Value Theory

Singh

Allen

Powell

2011

Chan, F., Marinova, D. And Anderssen, R.S. (Eds) MODSIM2011, 19th International Congress on Modelling and Simulation.

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A common assumption in quantitative financial risk modelling is the distributional assumption of normality in the asset's return series, which makes modelling easy but proves to be inefficient if the data exhibit extreme tails. When dealing with extreme financial events like the Global Financial Crisis of 2007-2008 while quantifying extreme market risk, Extreme Value Theory (EVT) proves to be a natural statistical modelling technique of interest. Extreme Value Theory provides well established statistical models for the computation of extreme risk measures like the Return Level, Value at Risk and Expected Shortfall. In this paper we apply Univariate Extreme Value Theory to model extreme market risk for the ASX-All Ordinaries (Australian) index and the S&P-500 (USA) Index. We demonstrate that EVT can be successfully applied to Australian stock market return series for predicting next day VaR by using a GARCH(1,1) based dynamic EVT approach. We also show with backtesting results that EVT based method outperforms GARCH(1,1) and RiskMetrics T M based forecasts.

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Section: Introductionmentioning

confidence: 99%

Value at Risk Estimation using Extreme Value Theory

Singh

Allen

Powell

2011

Chan, F., Marinova, D. And Anderssen, R.S. (Eds) MODSIM2011, 19th International Congress on Modelling and Simulation.

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Risk and Dependence Analysis of Australian Stock Market - The Case of Extreme Value Theory

2012

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The ActiveSync protocol's implementation on some embedded devices leaves clients vulnerable to unauthorised remote policy enforcement. This paper discusses a proof of concept attack against the implementation of ActiveSync in common Smart phones including Android devices and iOS devices. A two-phase approach to exploiting the ActiveSync protocol is introduced. Phase 1 details the usage of a man-in-the-middle attack to gain a vantage point over the client device, whilst Phase 2 involves spoofing the server-side ActiveSync responses to initiate the unauthorised policy enforcement. These vulnerabilities are demonstrated by experiment, highlighting how the system can be exploited to perform a remote factory reset upon an Exchange-integrated Smart phone.

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The Asymptotics of Extreme Returns in the Australian Stock Market

Cited by 2 publications

References 17 publications

Value at Risk Estimation using Extreme Value Theory

Value at Risk Estimation using Extreme Value Theory

Risk and Dependence Analysis of Australian Stock Market - The Case of Extreme Value Theory

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