Cointegration Portfolios of European Equities for Index Tracking and Market Neutral Strategies

Dunis, Christian L.; Ho, Richard Yan-Ki

doi:10.1007/978-3-319-30794-7_9

Cited by 8 publications

(11 citation statements)

References 17 publications

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“…If the number of cointegrating variables is more than one, the Vector Error Correction model will be employed. Dunis & Ho (2005) indicated that the theory of cointegration provides a sound methodology for modelling both long run and short run dynamics in a system. Hannan & Quinn (1979) described the VECM as a model which explains how the system is changing in each time period towards its long run equilibrium state.…”

Section: The Johansen Cointegrationmentioning

confidence: 99%

Household savings, financing and economic growth in South Africa

Mongale¹,

Mashamaite²,

Khoza³

2018

BEH

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The South African economy is characterised by low levels of household savings which play a very crucial role in stimulating sustained economic growth. At the same time consumers borrow in order to consume. The paper intends to investigate the impact of household savings and financing on economic growth in South Africa. The study is envisaged to assist monetary authorities and policy makers to mitigate this problem. An annual time series data covering the period from 1980 to 2014 is analysed by means of the Vector Error Correction Model approach. The Johansen Cointegration test results confirmed the existence of a long run relationship amongst variables under investigations. Moreover, the results suggest that financing, namely; credit extensions and leasing finance have positive relationships with the country's economic growth while household savings indicate a negative relationship with growth. That being the case, the recommendation is that since it has been established by other studies that a rapid increase in credit is not commonly perceived to be one of the leading indicators of financial instability, policymakers are advised to consider imposing stringent credit control measures so that the demand for financing can be kept under control.

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Section: The Johansen Cointegrationmentioning

confidence: 99%

Household savings, financing and economic growth in South Africa

Mongale¹,

Mashamaite²,

Khoza³

2018

BEH

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“…Bogomolov (2011) arrives at a similar conclusion for the Australian stock market. Dunis and Ho (2005) pursue two objectives. First, the authors use cointegration relationships to construct index tracking portfolios for the EuroStoxx 50 index.…”

Section: A Review Of Further Empirical Applicationsmentioning

confidence: 99%

“…First, the authors use cointegration relationships to construct index tracking portfolios for the EuroStoxx 50 index. More specifically, Dunis and Ho (2005) take different subsets (5, 10, 15, or 20 stocks) of the index constituents and estimate the joint cointegration vector for these constituents and their index. Then, they measure the tracking error return of this basket versus the index for different rebalancing frequencies.…”

Section: A Review Of Further Empirical Applicationsmentioning

confidence: 99%

“…Next, the Johansen procedure is used to find adequate securities among the 50 index constituents to track these benchmarks. According to Dunis and Ho (2005), going long the "plus" benchmark and short the "minus" benchmark allows for a market neutral investment strategy with potential "double alpha." The authors find significant outperformance compared to the EuroStoxx 50 index.…”

Section: A Review Of Further Empirical Applicationsmentioning

confidence: 99%

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Statistical Arbitrage Pairs Trading Strategies: Review and Outlook

Krauß

2016

Journal of Economic Surveys

163

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This survey reviews the growing literature on pairs trading frameworks, i.e., relative-value arbitrage strategies involving two or more securities. The available research is categorized into five groups: The distance approach uses nonparametric distance metrics to identify pairs trading opportunities. The cointegration approach relies on formal cointegration testing to unveil stationary spread time series. The time series approach focuses on finding optimal trading rules for mean-reverting spreads. The stochastic control approach aims at identifying optimal portfolio holdings in the legs of a pairs trade relative to other available securities. The category "other approaches" contains further relevant pairs trading frameworks with only a limited set of supporting literature. Drawing from this large set of research consisting of more than 90 papers, an in-depth assessment of each approach is performed, ultimately revealing strengths and weaknesses relevant for further research and for implementation. Terms of use: Documents in

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“…Dunis and Ho [9] examined long-short market neutral strategies on the Dow Jones EUROStoxx 50 index from Januray 2002 to June 2003. The results suggest that market neutral strategies can generate steady returns under adverse market circumstances.…”

Section: A Efficient Market Hypothesismentioning

confidence: 99%

Comparison of Statistical Arbitrage in Developed and Emerging Markets

Visagie¹,

Hoffman²

2017

IJTEF

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Abstract-Statistical arbitrage covers a variety of trading strategies that are based on statistical modelling and are usually characterized by a near market-neutral trading book. Statistical arbitrage strategies are generally used by hedge funds and retail traders with the objective of achieving excess returns regardless of the market regime. In this study we examine the performance of two statistical arbitrage systems in developed markets (Germany, Japan and the United States) and emerging markets (China and South Africa) over the period of 2006 to 2016. We investigate whether the performance of these systems are affected by different market regimes and whether excess returns have been altered since the financial crisis in 2008-2009. We also compare the performance of these systems in developed and emerging markets. Our results indicate that statistical arbitrage systems produce higher excess returns during non-trending markets and that these systems generally provide higher returns in emerging markets. The overall performance of the statistical arbitrage systems have weakened since the financial crisis, but a noticeable improvement in excess returns produced is apparent in the last three years of our study.

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Cointegration Portfolios of European Equities for Index Tracking and Market Neutral Strategies

Cited by 8 publications

References 17 publications

Household savings, financing and economic growth in South Africa

Household savings, financing and economic growth in South Africa

Statistical Arbitrage Pairs Trading Strategies: Review and Outlook

Comparison of Statistical Arbitrage in Developed and Emerging Markets

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