Feedback trading strategies and long-term volatility

Kyriakou, Maria I.; Babalos, Vassilios; Kiohos, Apostolos; Koulakiotis, Athanasios

doi:10.1016/j.qref.2019.05.011

Cited by 7 publications

(7 citation statements)

References 33 publications

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“…His results revealed that FT was present in the specific real estate market. On the other hand, Kyriakou et al (2019) using securitized real estate prices confirmed the existence of FT and volatility asymmetry for several OECD countries for a long period covering different market phases.…”

Section: Introductionmentioning

confidence: 66%

Feedback trading strategies in international real estate markets

Balomenou

Babalos

Vortelinos

et al. 2020

IJHMA

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Purpose Motivated by recent evidence that securitized real estate returns exhibit higher levels of predictability than stock market returns and that feedback trading (FT) can induce returns autocorrelation and market volatility, the purpose of this study is to examine the impact of FT strategies on long-term market volatility of eight international real estate markets (UK, Germany, France, Italy, Sweden, Australia, Japan and Hong Kong). Design/methodology/approach Assuming that the return autocorrelation may vary over time and the impact of positive feedback trading (PFT) or negative feedback trading (NFT) could be a function of return volatility, the authors use a combination of a FT model and a fractionally integrated Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model. Findings The results are mixed, revealing that both PFT and NFT strategies persist. Specifically, the authors detect PFT in the real estate markets of France, Hong Kong and Italy as opposed to the real estate markets of Australia, Germany, Japan and Sweden where NFT was present. A noteworthy exception is the UK real estate market, with important and rational FT strategies to sustain. With respect to the long-term volatility persistence, this seems to capture the mean reversion of real estate returns in the UK and Hong Kong markets. In general, the results are not consistent with those reported in previous studies because NFT dominates PFT in the majority of real estate markets under consideration. Originality/value The main contribution of this study is the investigation of the link between short-term PFT or NFT and long-term volatility in eight international real estate markets, symmetrically. Particular attention has been given to the link between short-term FT and long-term volatility, by means of a fractionally integrated GARCH approach, a symmetric one. Moreover, investigating the relationship between returns’ volatility and investors’ strategies based on FT entails significant implications because real estate assets offer a good alternative investment for many investors and speculators.

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Section: Introductionmentioning

confidence: 66%

Feedback trading strategies in international real estate markets

Balomenou

Babalos

Vortelinos

et al. 2020

IJHMA

Self Cite

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“…have been found to be prone to feedback trading, aided by investors' extrapolative expectations regarding the property market; for example, Case et al (2012) reported a strong tendency of US homebuyers toward predicting future appreciations of housing prices, if the latter had recently appreciated. Evidence in favour of positive feedback trading in real estate stock market indices has been reported for a series of developed markets in Europe, the US and Asia-Pacific (Koulakiotis and Kiohos, 2016;Kyriakou et al, 2020;Balomenou et al, 2021), with Kyriakou et al (2020) documenting a switch to negative feedback trading in some European countries during the 2007-2009 global financial crisis [98]. Conditioning daily order imbalances on past market returns, Zhou and Lai (2008) further showed that Hong Kong property stocks exhibited significant positive feedback trading in 2004 and 2005, without its presence, however, bearing a destabilizing effect over their prices.…”

Section: Propertymentioning

confidence: 99%

“…(2012) reported a strong tendency of US homebuyers toward predicting future appreciations of housing prices, if the latter had recently appreciated. Evidence in favour of positive feedback trading in real estate stock market indices has been reported for a series of developed markets in Europe, the US and Asia–Pacific (Koulakiotis and Kiohos, 2016; Kyriakou et al. , 2020; Balomenou et al.…”

Section: Empirical Evidencementioning

confidence: 99%

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Feedback trading: a review of theory and empirical evidence

Economou

Gavriilidis

Gębka

et al. 2022

RBF

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PurposeThe purpose of this paper is to comprehensively review a large and heterogeneous body of academic literature on investors' feedback trading, one of the most popular trading patterns observed historically in financial markets. Specifically, the authors aim to synthesize the diverse theoretical approaches to feedback trading in order to provide a detailed discussion of its various determinants, and to systematically review the empirical literature across various asset classes to gauge whether their feedback trading entails discernible patterns and the determinants that motivate them.Design/methodology/approachGiven the high degree of heterogeneity of both theoretical and empirical approaches, the authors adopt a semi-systematic type of approach to review the feedback trading literature, inspired by the RAMESES protocol for meta-narrative reviews. The final sample consists of 243 papers covering diverse asset classes, investor types and geographies.FindingsThe authors find feedback trading to be very widely observed over time and across markets internationally. Institutional investors engage in feedback trading in a herd-like manner, and most noticeably in small domestic stocks and emerging markets. Regulatory changes and financial crises affect the intensity of their feedback trades. Retail investors are mostly contrarian and underperform their institutional counterparts, while the latter's trades can be often motivated by market sentiment.Originality/valueThe authors provide a detailed overview of various possible theoretical determinants, both behavioural and non-behavioural, of feedback trading, as well as a comprehensive overview and synthesis of the empirical literature. The authors also propose a series of possible directions for future research.

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“…Since then, the ability of feedback trading to induce return autocorrelation and its impact on destabilizing asset prices and market inefficiency have received much debate in most financial markets (Black, 1986). This includes several developed stock markets other than the US (Koutmos, 1997), foreign exchange markets (Laopodis, 2005; Tayeha and Kallinterakis, 2022), emerging equity markets (Aguirre and Saidi, 1999), stock index futures markets (Salm and Schuppli, 2010; Lai and Wang, 2015), Exchange-Traded Fund (ETF), contracts (Chau et al , 2011; Charteris et al , 2014), coal and electricity market (Chau et al , 2015), Bitcoin (Wang et al , 2022) and real estate (Kyriakou et al , 2020). Nonetheless, even with this increasing importance and interest, little is known about feedback trading in the cryptocurrency markets except for Bitcoin.…”

Section: Introductionmentioning

confidence: 99%

Feedback trading in the cryptocurrency market

Ahmed,

Alsamman,

Chebbi

2023

SEF

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Purpose This paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market. Design/methodology/approach It uses the GJR-GARCH model to investigate feedback trading in the cryptocurrency market. Findings The findings show a negative relationship between trading volume and autocorrelation in the cryptocurrency market. The GJR-GARCH model shows that only the USD Coin and Binance USD show an asymmetric effect or leverage effect. Interestingly, other cryptocurrencies such as Ethereum, Binance Coin, Ripple, Solana, Cardano and Bitcoin Cash show the opposite behavior of the leverage effect. The findings of the GJR-GARCH model also show positive feedback trading for USD Coin, Binance USD, Ripple, Solana and Bitcoin Cash and negative feedback trading for Ethereum and Cardano only. Originality/value This paper contributes to the literature by extending Sentana and Wadhwani (1992) to explore the presence of feedback trading in the cryptocurrency market using a sample of the most active cryptocurrencies other than Bitcoin, namely, Ethereum, USD coin, Binance Coin, Binance USD, Ripple, Cardano, Solana and Bitcoin Cash.

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Feedback trading strategies and long-term volatility

Cited by 7 publications

References 33 publications

Feedback trading strategies in international real estate markets

Feedback trading strategies in international real estate markets

Feedback trading: a review of theory and empirical evidence

Feedback trading in the cryptocurrency market

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