GARCH Diagnosis with Portmanteau Bicorrelation Test: An Application on the Malaysia's Stock Market

This study employed the Hinich portmanteau bicorrelation test (Hinich and Patterson, 1995; Hinich, 1996) as a diagnostic tool to determine the adequacy of the GARCH model in describing the returns generating process of Malaysia’s stock market, specifically the Kuala Lumpur Stock Exchange Composite Index (KLSE CI). The bicorrelation results demonstrated that, while GARCH model is commonly applied to financial time series, this model cannot provide an adequate characterization for the underlying process of KLSE CI. Further investigation using the windowed test procedure revealed that this was due to the presence of episodic non- stationarity in the data, which could not be captured by any kind of ARCH or GARCH model, even after modifications to the specifications of the GARCH model. Thus, this study points to the need to continue the search for a parsimonious and congruent model capable of capturing the episodic features presence in the returns series of KLSE CI.GARCH; Non-linearity; Non-stationarity; Data generating process; Bicorrelation; Malaysian stock market.

Time series irreversibility: a visibility graph approach

We propose a method to measure real-valued time series irreversibility which combines two differ- ent tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally effi- cient, does not require any ad hoc symbolization process, and naturally takes into account multiple scales. We find that the method correctly distinguishes between reversible and irreversible station- ary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic pro- cesses (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identifiy the irreversible nature of the series.Comment: submitted for publicatio

Garch diagnosis with portmanteau bicorrelation test an application on the Malaysia’s stock market

This study employed the Hinich portmanteau bicorrelation test (Hinich and Patterson, 1995; Hinich, 1996) as a diagnostic tool to determine the adequacy of the GARCH model in describing the returns generating process of Malaysia’s stock market, specifically the Kuala Lumpur Stock Exchange Composite Index (KLSE CI). The bicorrelation results demonstrated that, while GARCH model is commonly applied to financial time series, this model cannot provide an adequate characterization for the underlying process of KLSE CI. Further investigation using the windowed test procedure revealed that this was due to the presence of episodic non-stationarity in the data, which could not be captured by any kind of ARCH or GARCH model, even after modifications to the specifications of the GARCH model. Thus, this study points to the need to continue the search for a parsimonious and congruent model capable of capturing the episodic features presence in the returns series of KLSE CI

The new multidimensional time/multi-frequency transform for higher order spectral analysis

A new multidimensional time/multi-frequency higher order spectral(HOS) transform is proposed for transient signals with nonlinear polynomial variation of instantaneous frequency: the short time higher order chirp spectra (HOCS) based on the higher order chirp-Fourier transform and time-domain windowing technique. The proposed transform is compared with the classical multi-frequency HOS based on the Fourier transform. It is shown that the proposed transform is more effective for processing of transient processes in comparison with the classical transform

Episodic Non-Linearity And Non-Stationarity In Asean Exchange Rates Returns Series

A method proposed by Hinich and Patterson (1995) is employed in this study to examine the stability of the non-linear dependency structures underlying the exchange rates returns series of four ASEAN countries- Indonesia (IDR), the Philippines (PHP), Singapore (SGD) and Thailand (THB). The bicorrelation test results reveal the episodic and transient nature of these non-linear dependencies, which suggest that they are not persistent enough for investors to benefit from it. By transforming the returns into a set of binary data, the extended test procedure demonstrates that, while the GARCH-type models are commonly applied to financial time series such as exchange rates, they cannot provide an adequate characterization for the underlying process of IDR, PHP and THB bilateral exchange rates. Further investigation reveals that the violation of the covariance stationarity assumption as required by the GARCH process is due to the presence of episodic non-stationarity in the data. Given the prevalence of these episodic transient features across financial markets in the world, there is the need for researchers to take into account these salient features in their model construction

Statistical Inadequacy of GARCH Models for Asian Stock Markets: Evidence and Implications

This study employs the Hinich portmanteau bicorrelation test (Hinich 1996; Hinich and Patterson 1995) as a diagnostic tool to determine the adequacy of Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models for eight Asian stock markets. The bicorrelation test results demonstrate that this type of model cannot provide an adequate characterisation for the underlying process of all the selected Asian stock markets. Further investigation using the windowed test procedure reveals that the violation of the covariance stationarity assumption as required by the GARCH process is due to the presence of transient epochs of dependencies in the data. The inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolios selection, development of optimal hedging techniques and risk management. JEL Classification: G120, C520 Keywords: GARCH, non-stationarity, data generating process, bicorrelation, Asian stock market

Policy competition in the 2002 French legislative and presidential elections

The French two-round system of presidential elections forces candidates to choose strategies designed to maximize their votes in two different, potentially conflicting strategic contexts: a first round contest between many candidates, and a second round between (typically) a left- and a right-oriented candidate. Following a constitutional change in 2000, furthermore, presidential elections are synchronized with legislative elections, more tightly linking presidential candidates to the policy platforms of the parties they represent. This article examines the consequences of policy positioning by presidential candidates, measuring, comparing and assessing positioning in the legislative elections and in the first and second presidential election rounds. The measures come from an expert survey taken in 2002, from content analysis of party manifestos and presidential speeches, and from the 2002 French National Election Survey. The findings provide hard empirical confirmation of two commonly perceived propositions: first, that Jospin's first-round loss resulted from strategic error in moving too close to the policy centre, and second, that Chirac's won an overwhelming second-round victory because he collected all of the voters from candidates eliminated in the first round