The causality between liquidity and volatility in the Polish stock market

Będowska-Sójka, Barbara; Kliber, Agata

doi:10.1016/j.frl.2019.04.008

Cited by 31 publications

(19 citation statements)

References 27 publications

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“…However, research shows that liquidity and volatility causality is bidirectional. Though, it should be acknowledged that liquidity is more often Granger causes volatility than volatility causes liquidity (Będowska-Sójka & Kliber, 2019).…”

Section: Introductionmentioning

confidence: 99%

Further evidence on the validity of CAPM: The Warsaw Stock Exchange application

Markowski

2020

JEM

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Aim/purpose-The purpose of the research is to verify the Capital Asset Pricing Model (CAPM) in the Polish capital market based on a conventional and downside risk approach. Design/methodology/approach-The author in this study, using individual securities and portfolios, compares the unconditional risk-return relationships with the conditional risk, estimated in up and down market using realised returns in cross-sectional regressions. Except for a beta coefficient, the CAPM is tested with co-skewness as a higher order co-moment and downside betas as a risk measure in a downside approach. Findings-The unconditional regressions give evidence of existing risk premium associated with co-skewness and downside beta, and confirmed the validity of the downside CAPM. The author, based on conditional relations, found that risk-return relations depend on the state of the stock market. The average premium for systematic risk in term of beta coefficient is significantly positive in up market periods and significantly negative in down market periods. The use of conditional models did not explicitly confirm the suitability of co-skewness in asset pricing. Research implications/limitations-The main implications include the fact that the conventional beta coefficient is an appropriate risk measure when we consider using it separately for up and down market. A valuable extension of this research would be a benchmarking analysis to compare results for the Polish capital market against other emerging and developed markets. Originality/value/contribution-The author in this paper proposes an alternative approach to testing risk-return relationships based on the CAPM in comparison to commonly used tests founded upon joint estimations of these relationships in periods of both positive and negative market excess return. The noteworthy contribution of this study is an application of the downside beta coefficient and the co-skewness coefficient in crosssectional regressions.

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Section: Introductionmentioning

confidence: 99%

Further evidence on the validity of CAPM: The Warsaw Stock Exchange application

Markowski

2020

JEM

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“…Her bir likidite ölçütü için VAR sistemi, en uygun gecikme uzunluğu ile tahmin edilecektir. (Hiemstra ve Jones, 1994;Brooks, 1998;Ong, 2015;Bedowska-Sojka ve Kliber, 2019) Response of VOV to Generalized One S.D. VOL Innovation…”

Section: Ekonometrik Yöntem Ve Ampirik Bulgularunclassified

“…Bu çalışmalarda çoğunlukla likidite yetersizliği primi, hisse senetleri likiditelerinin ortak hareketi (commonality) ve likidite ile getiri arasındaki ilişki ele alınmıştır. Söz konusu ilişkiyi, likidite düzeyi-getiri (Eleswarapu, 1997;Akbaş, 2011, Batten ve Vo, 2015, likidite oynaklığı-getiri (Chordia, 2001;Akar, 2015) ile likidite düzeyi-getiri oynaklığı (Hiemstra ve Jones, 1994;Ong, 2015;Bedowska-Sojka ve Kliber, 2019) olarak inceleyen çeşitli çalışmalar bulunmaktadır. Bu süreçte, araştırmacılar likiditenin doğrudan gözlenemeyen ve ölçülemeyen bir kavram olması kısıtıyla karşılaşmış ve dolayısıyla likidite göstergesi olarak çeşitli ölçütler ve vekiller kullanmışlardır.…”

Section: Introductionunclassified

Hisse Senedi Piyasasında Likidite ve Getiri Oynaklığı İlişkisi: Borsa İstanbul Örneği (The Relationship between Liquidity and Return Volatility in the Stock Market: The Case of Borsa İstanbul)

Gürgün

Canbaloğlu

2020

isarder

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Bu çalışmanın amacı Borsa İstanbul'da likidite düzeyi ile getiri oynaklığı arasındaki ilişkinin varlığı ve yönünün farklı likidite ölçütleri kullanılarak Ocak 2008-Ağustos 2019 dönemi için ampirik olarak analiz edilmesidir. Yöntem-Likidite düzeyi ile getiri oynaklığı arasındaki ilişki VAR modeli kullanılarak Granger (1969) nedensellik testi ve genelleştirilmiş etki tepki analizleri ile incelenmiştir. Bu kapsamda likiditeyi temsil etmek üzere en yüksek-en düşük farkı, Amihud likidite yetersizliği ve oynaklık hacim oranı olmak üzere üç farklı likidite ölçütü hesaplanmıştır. Getiri oynaklığı ise GARCH (1,1) modeliyle tahmin edilmiştir. Bulgular-Bulgular, Borsa İstanbul için tüm likidite ölçütleri ile getiri oynaklığı arasında çift yönlü Granger nedensellik ilişkisi ortaya koymaktadır. Etki tepki analizleri ise likidite düzeyindeki bir şokun getiri oynaklığını hızla artırdığını ve söz konusu artışın etkisinin uzun sürdüğünü göstermektedir. Diğer taraftan, bulgular getiri oynaklığında meydana gelen bir şokun likidite düzeyini aşağı çektiğini, ancak söz konusu tepkinin getiri oynaklığının likidite şokuna verdiğine kıyasla daha az olduğunu ileri sürmektedir. Tartışma-Çalışma, firmaların ve politika yapıcıların likiditeyi artırmaya yönelik önlemler almasını desteklemektedir. Bu bağlamda, gelecekteki çalışmalarda likiditenin belirleyicilerine odaklanmak yararlı olacaktır.

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“…Learning causality has been applied in myriad of highimpact applications that include computer vision [17,23], financial data analysis [24,25], environmental health [21,26] and education [22,27]. Also, causality has been viewed as a significant component to improve the accuracy of information prediction and retrieval [28,29].…”

Section: Introductionmentioning

confidence: 99%

Causality Inspired Retrieval of Human-object Interactions from Video

Zhou

Liu

Nishimura

et al. 2019

2019 International Conference on Content-Based Multimedia Indexing (CBMI)

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Notwithstanding recent advances in machine vision, video activity recognition from multiple cameras still remains a challenging task as many real-world interactions cannot be automatically recognised for many reasons, such as partial occlusion or coverage black-spots. In this paper we propose a new technique that infers the unseen relationship between two individuals captured by different cameras and use it to retrieve relevant video clips if there is a likely interaction between the two individuals. We introduce a human object interaction (HOI) model integrating the causal relationship between the humans and the objects. For this we first extract the key frames and generate the labels or annotations using the state-of-the-art image captioning models. Next, we extract SVO (subject, verb, object) triples and encode the descriptions into a vector form for HOI inference using the Stanford CoreNLP parser. In order to calculate the HOI co-existence and the possible causality score we use transfer entropy. From our experimentation, we found that integrating casual relations into the content indexing process and using transfer entropy to calculate the causality score leads to improvement in retrieval performance.

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The causality between liquidity and volatility in the Polish stock market

Cited by 31 publications

References 27 publications

Further evidence on the validity of CAPM: The Warsaw Stock Exchange application

Further evidence on the validity of CAPM: The Warsaw Stock Exchange application

Hisse Senedi Piyasasında Likidite ve Getiri Oynaklığı İlişkisi: Borsa İstanbul Örneği (The Relationship between Liquidity and Return Volatility in the Stock Market: The Case of Borsa İstanbul)

Causality Inspired Retrieval of Human-object Interactions from Video

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