Evidence of feedback trading with Markov switching regimes

The existence of behavioural bias such as positive feedback trading (PFT) and herding is well researched for advanced economies. This paper explores whether foreign institutional investors (FIIs), a prominent investor group, pursue these strategies in India. The contribution lies in the application of multiple measures of herding. Results indicate that FIIs exhibit PFT behaviour in equity and to some extent, in debt. At the individual stock level, FIIs herd during non-extreme market conditions, but market-level measures indicate absence of herding in extreme market conditions. In the bullish market, they behave more rationally compared to bearish or normal market conditions.

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“…Few other studies also find the existence of PFT in both equity and bond market [e.g. Dean and Faff ( 2008 ); Sutthisit et al ( 2012 )]…”

Section: Resultsmentioning

confidence: 98%

Trading Behaviour of Foreign Institutional Investors: Evidence from Indian Stock Markets

Mukherjee

Tiwari

2022

Asia-Pac Financ Markets

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“…Interestingly they find that for six emerging stock markets, positive feedback trading is significant mostly during market declines, but not necessarily during market advances. Dean and Faff (2008) use a feedback model with Markov switching regimes to model Australian bond and equity markets. They find evidence of positive feedback trading in both the equity and the bond markets.…”

Section: The Basic Positive Feedback Trading Modelmentioning

confidence: 99%

Positive feedback trading: a review

Koutmos

2014

Review of Behavioral Finance

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Purpose – The literature on positive feedback trading has grown considerably in recent years. The purpose of this paper is to provide a review of the theoretical and empirical literature on positive feedback trading and especially the literature related to the Sentana and Wadhwani (1992) model. Design/methodology/approach – This literature review covers theoretical and empirical work in this area and it points out shortcomings and potential extensions of the basic feedback model. Findings – The evidence so far points in the direction of positive feedback trading being present in aggregate stock market indices, index futures, bond markets, foreign exchange markets and individual stocks. There are some important issues that require further investigation. For example, it is likely that feedback trading is a function of longer lags of past return. Likewise, asymmetric behavior during up and down markets appears to be the rule rather than the exception. More importantly, the models should allow for positive as well as negative feedback and be general enough to investigate feedback trading behavior in individual assets and not just the aggregate market. Research limitations/implications – The discussion points out theoretical and empirical limitations and shortcomings of the extant literature. Originality/value – This is the first paper to review positive feedback trading, implications, limitations and need for future research.

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“…For example, in bearish markets, expected returns, conditional volatilities and their dynamics, and correlations can differ from their respective counterparts in more normal or bullish market periods. Regime-specific dynamics may also be related to various types of trading patterns, as represented by "information" and "feedback" traders (Dean & Faff, 2008). See Guidolin (2011) and Ang and Timmermann (2012) for an overview over the many applications of MSMs.…”

Section: Introductionmentioning

confidence: 99%

A multivariate regime-switching GARCH model with an application to global stock market and real estate equity returns

Haas

Liu

2018

Studies in Nonlinear Dynamics &Amp; Econometrics

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Abstract:We consider a multivariate Markov-switching GARCH model which allows for regime-specific volatility dynamics, leverage effects, and correlation structures. Conditions for stationarity and expressions for the moments of the process are derived. A Lagrange Multiplier test against misspecification of the within-regime correlation dynamics is proposed, and a simple recursion for multi-step-ahead conditional covariance matrices is deduced. We use this methodology to model the dynamics of the joint distribution of global stock market and real estate equity returns. The empirical analysis highlights the importance of the conditional distribution in Markovswitching time series models. Specifications with Student's t innovations dominate their Gaussian counterparts both in-and out-of-sample. The dominating specification appears to be a two-regime Student's t process with correlations which are higher in the turbulent (high-volatility) regime.

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Evidence of feedback trading with Markov switching regimes

Abstract: Feedback trading, Markov switching, Australia, G10,

Cited by 22 publications

References 42 publications

Trading Behaviour of Foreign Institutional Investors: Evidence from Indian Stock Markets

Trading Behaviour of Foreign Institutional Investors: Evidence from Indian Stock Markets

Positive feedback trading: a review

A multivariate regime-switching GARCH model with an application to global stock market and real estate equity returns

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