Negative Feedback Trading Research Articles

Feedback Trading and Its Implications for Return Autocorrelations in India During COVID

In emerging capital markets, feedback trading is a widely pursued strategy by investors. Such behavior may potentially lead to volatility and cause negative autocorrelation in market returns, especially during high volatility. In India, such a linkage has not been explored so far, though institutional investors have pursued feedback trading for the last two decades. Also, COVID-19 has led to higher volatility in the markets and might have altered investors’ behavior. This article focuses on finding whether feedback trading is still pursued by institutional investors in Indian equity markets post-COVID and also whether the presence of feedback traders exerts any influence on autocorrelations in market returns. Asymmetric GARCH models are employed to explore the linkage. Findings suggest that while foreign institutional investors continue to pursue positive feedback trading, as in the pre-pandemic period, domestic investors pursue negative feedback trading. However, in the post-pandemic period, as other types of trading became weak or perished, positive feedback traders have started dominating, leading to negative autocorrelation in market returns during heightened volatility. Evidence of negative autocorrelation was not present in the pre-pandemic period. Further, negative news leads to more volatility in returns. JEL Codes: F21, F32, G11

Arbitrage opportunities and feedback trading in regulated bitcoin futures market: An intraday analysis

The study uses 5-min intraday Bitcoin futures and spot prices to investigate the additive and multiplicative impact of arbitrage opportunities on feedback trading in the Bitcoin futures market. The basis, equal to the difference between Bitcoin spot and futures prices, is used to proxy arbitrage opportunities. The study uses quantile regressions to capture different market conditions. The study documents episodic cases of positive and negative feedback trading. The resulting evidence reveals that the intensity and type of feedback trading largely depend on market conditions and the degree of arbitrage opportunities. From the multiplicative model, the impact of arbitrage opportunities on positive feedback trading is strongest in the extreme bear market, lowest in the regular market conditions, and absent in the bull market conditions. Channel “breakouts” analysis indicates positive feedback traders dominate during bear and normal market conditions. When the basis declines by varying magnitudes across quantiles, positive feedback trading shifts to negative feedback trading. The findings suggest widening basis intensifies negative feedback trading during bull market conditions. However, when the basis decreases by varying scales across upper quantiles, negative feedback trading switches to positive feedback trading. By observing the trading signals, investors can adjust their portfolio positions to maximize returns and minimize risk.

Determinants and dynamic interactions of trader positions in the gold futures market

We investigate the determinants of different traders’ trading positions in the gold futures market. With a threshold value determined endogenously by our model, we find that when the gold futures price falls below the threshold, money managers adopt positive feedback trading strategies while swap dealers adopt negative feedback trading strategies. When the futures price rises above the threshold, money managers turn to negative feedback trading and swap dealers reduce the intensity of their negative feedback. In addition, money managers and swap dealers play the transmitter role in trading spillovers to other traders, and their trading transmitter role weakens during periods with high gold prices.

Feedback trading in the cryptocurrency market

PurposeThis paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market.Design/methodology/approachIt uses the GJR-GARCH model to investigate feedback trading in the cryptocurrency market.FindingsThe 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/valueThis 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.

Bitcoin futures risk premia

AbstractThis paper presents an empirical analysis of bitcoin futures risk premia. Based on the relevant theories and empirical findings of commodity futures risk premia, we study a battery of predictors, including position‐based measures, market microstructure factors, and macroeconomic variables. We find that trading activity and extreme sentiment of speculators and retailers present significant predicting power on the subsequent bitcoin futures price changes over different time horizons. We also find evidence that the lower transaction cost, the higher bitcoin futures risk premiums. Regarding macroeconomic variables, financial conditions index, TED spread, US M2 money stock, and funding cost of financial institutions could predict bitcoin futures returns. The return impact of net position changes of hedgers is likely to be affected by extremes in macroeconomic variables. Speculators behave like negative feedback traders, while retailers are positive feedback traders. This detailed analysis of the risk premia of this emerging derivatives market provides critical implications.

Trading Behavior in Agricultural Commodity Futures around the 52-Week High

Utilizing the Commodity Futures Trading Commission’s Commitment of Traders report, we examine the behavior of traders in three large agricultural futures markets (corn, soybean, and wheat) when prices are at a key technical trading level—the 52-week high (the highest price during the past year). Our empirical results confirm that, consistent with hedging behavior, commercial traders tend to be negative feedback traders, while non-commercial traders tend to be momentum traders. In both cases, there is a moderating effect when the market is at the 52-week high. For non-commercial traders, this effect is concentrated in short positions. Although we find no evidence of a broad market timing ability from any trader type, trader positions appear to be more informative when the market is at the 52-week high. Our results have implications for traders attempting to time market entry.

Investor sentiment spillover effect and market quality in crude oil futures

This study examines the influence of investor sentiment on trading behavior in crude oil futures. We find that money manager traders (i.e., hedge funds) adopt positive feedback trading strategies in normal periods and turn to negative feedback trading in pessimistic periods. Meanwhile, swap dealers adopt negative feedback trading in normal periods and reduce the intensity of their negative feedback trading during pessimistic periods. We also find that the sentiment-driven trading of money manager traders and swap dealers does not hurt the quality of the crude oil futures market in either pessimistic or optimistic periods. In contrast, producers' (hedgers’) positions increase volatility and pricing errors in the crude oil futures market.

Minimum Shareholding Proportion of Equity Funds and Stock Volatility Evidence from a Quasi-Natural Experiment

China’s fund market is getting bigger and bigger. By September 2021, the number of funds in the market had exceeded 8000, with a net value of nearly 24 trillion yuan. Among them, the number of equity funds has doubled compared with 2015, and the net value has increased four times compared with 2015, and it still maintains a rapid growth momentum. Do mutual funds play a role in market stabilization? To demonstrate this issue, we combined the passive trading technique with the positive and negative feedback trading strategies and explained how the minimum position ratio of equity funds affects stock price volatility. Then, using empirical data, we apply the difference-in-differences model to analyze how shifting proportions of the equity funds’ lowest shareholding affects stock volatility. The result shows that the volatility of high-institutional stocks was significantly reduced in comparison with other stocks after 2014. This result is further confirmed in the stocks held by large-scale funds. We used PSM-DID to solve potential endogenous problems and found that the results still support the hypothesis. This evidence supports the point of statement that the equity funds in the Chinese capital market can stabilize the market especially after 2014.

Disagreement between hedge funds and other institutional investors and the cross‐section of expected stock returns

AbstractWe find strong disagreements between hedge funds and other institutions in their common stock trades are twice as likely as agreements. Overall success of hedge funds’ trades and poor performance of non‐hedge funds’ trades are both confined to disagreement stocks. Although hedge funds are commonly positive feedback traders, they are neither positive nor negative feedback traders for stocks heavily sold by other institutions. Hedge funds also depend less on earnings news. Our findings highlight the importance of disagreement in studying the performance of institutional investors’ trades and are consistent with the notion that skilled investors rely less on public information.

Feedback trading in global stock markets under uncertainty of COVID-19

PurposeAlthough some research has been carried out on feedback trading in different asset classes, there have been few empirical investigations that consider both major and emerging stock markets (Koutmos, 1997; Antoniou et al., 2005; Kim, 2009) stock index futures (Salm and Schuppli, 2010). In this study, the author examines positive/negative feedback trading in both developed-emerging-frontier-standalone (51) stock markets for 2010–2020 and sub-periods including COVID-19 period.Design/methodology/approachThe hypothesis “feedback trading behaviour led the price boom/bust in the stock markets during the first quarter of COVID-19 pandemic” is tested by employing the Sentana and Wadhwani (1992) framework and using asymmetrical GARCH models (GJRGARCH, EGARCH) in accordance with the empirical literature.FindingsThe following conclusions can be drawn from the present study; (1) There is no evidence to support a significant distinction between developed, emerging, frontier or standalone markets or high/upper middle, lower middle income economies in the case of feedback trading. It is more likely to be a general phenomenon reflecting the outcomes of general human psychology (2) in the long term (2010–2020) based on the feedback trading results Asian stock markets appear to be far from efficiency.Research limitations/implicationsStock markets are selected based on data availability.Practical implicationsSeveral inferences can be drawn about overall results. First, investors and portfolio managers should beware of their investment decisions during bearish market conditions where volatility is on the rise and also when there is a strong reaction to bad news/negative shocks in the market. Moreover, investing in Asia stock markets may require more attention since those markets are reputed to be more “idiosyncratic”, less reliant on economic and corporate fundamentals in their pricing. Moreover, the impact of foreign investors on stock market volatility and returns and weaker implementation of regulations also affect the efficiency of the markets (Lipinsky and Ong, 2014).Originality/valueTo the best of the author’s knowledge, most studies in the field of feedback trading in stock markets have only focused on a small sample of countries and second, the effect of COVID-19 uncertainty on the stock markets have not been addressed in the literature with respect to feedback trading. This paper fills these literature gaps. This study is expected to provide useful insights for understanding the instabilities in stock markets particularly under conditions of high uncertainty and to fill the gap in the literature by comparing the results for a large sample of countries both in the long term and in the pandemic.Highlights for reviewThis study has shown that feedback trading is more prevalent in Asian stock markets in the long run in Europe, America or Middle East for the period 2010–2020.Positive feedback traders generally dominated most of the stock markets during the early period of COVID-19 pandemic.Another major finding was that the stock markets in Malaysia, Japan, the Philippines, Estonia, Portugal and Ukraine are dominated by negative feedback traders which may be interpreted as “disposition effect” meaning that they sell the “past winners”.In Indonesia, New Zealand, China, Austria, Greece, UK, Finland, Spain, Iceland, Norway, Switzerland, Poland, Turkey, Chile and Argentina neither positive nor negative feedback trading exists even under uncertain conditions.

Bayesian analysis of time-varying interactions between stock returns and foreign equity flows

This study discusses the trading behavior of foreign investors with respect to economic uncertainty in the South Korean stock market from a time-varying perspective. We employ a news-based measure of economic uncertainty along with the model of time-varying parameter vector autoregression with stochastic volatility. The empirical analysis reveals several new findings about foreign investors’ trading behaviors. First, we find evidence that positive feedback trading often appears during periods of high economic uncertainty, whereas negative feedback trading is exclusively observable during periods of low economic uncertainty. Second, the foreign investors’ feedback trading appears mostly to be well-timed and often leads the time-varying economic uncertainty except in periods of global crises. Third, lagged negative (positive) response of net flows to economic uncertainty is found to be coupled with lagged positive (negative) feedback trading. Fourth, the study documents an asymmetric response of foreign investors with regard to negative and positive shocks of economic uncertainty. Specifically, we find that they instantly turn to positive feedback trading after a negative contemporaneous response of net flows to shocks of economic uncertainty. In contrast, they move slowly toward negative feedback trading after a positive response of net flows to uncertainty shocks.

Transactions of the National Pension Service of Korea in the KOSPI200 futures market

It is known that the National Pension Service (NPS) of Korea contributes to the market stability because it tends to pursue the negative feedback trading strategy in the Korean stock market. While many studies deal with institutional investors’ trading in the financial derivatives market, the NPS’s trading in the derivatives market is rarely studied. Using the NPS’s trading data for the period from January 2010 to March, 2020, the authors examine the transactions of the NPS in the KOSPI200 futures market. We find that the NPS’s net investment flow (NIF) in KOSPI200 futures is negatively associated with the past returns of KOSPI200 futures and the KOPI200 index. However, we also find that the NPS’s NIF of KOSPI200 futures is positively associated with its NIF in KOSPI200 stocks. Along with the legal restriction on the NPS’s trading in the derivatives market, the result suggests that the NPS uses KOSPI200 futures to deviate the problems related to non-synchronous trading in the spot market. To the best of our knowledge, this paper is the first study of the NPS’s transactions of KOSPI200 futures. The paper suggests that the NPS does not trade KOSPI200 futures for hedging or arbitrage profit but for complementing its transactions in the spot market of KOSPI200 stocks.

COVID-19 pandemic effect on trading and returns: Evidence from the Chinese stock market

Using a daily foreign and institution flows data, this paper studies how institutional and foreign investors respond to the COVID-19 pandemic events in China. The results indicate that during the COVID-19 crisis foreign investors play a market stabilization role showing significant negative feedback trading, whereas institution investors do not stabilize the market. And compared to the pre-COVID-19 period, foreign investors even exhibit stronger negative feedback trading. Further analyses confirm that foreign investors’ negative feedback is mainly driven by their response to negative returns. Moreover, both institutional and foreign investors’ trading show stronger forecastability of future returns during the pandemic period. And the negative returns after foreigners’ selling and positive returns after institutional buying are much stronger during the crisis period.

Feedback trading strategies in international real estate markets

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.

Leveraged Trading, Irrational Sentiment and Sustainability in the Stock Market: Evidence from China

Leveraged trading exhibits the characteristics of “strong margin trading and weak short selling” in the Chinese stock market. On the basis of monthly data on leveraged trading in the Chinese stock market from January 2014 to December 2016, we aim to empirically examine the relationship between leveraged trading and investor sentiment, and analyze the characteristics of investor sentiment contained in the leverage ratio. The results show that (1) as the leverage ratio increases, the pattern of investor trading changes from the positive feedback trading of “chasing up and down” to the negative feedback trading of “selling high and buying low”; (2) leveraged trading has the typical characteristics of irrational sentiment; (3) inverse arbitrage strategies based on leverage ratios is effective in one month in the Chinese market. The findings in this paper provide empirical support for clarifying the influence mechanism between leveraged trading and investor sentiment, and can serve as a useful reference for reducing the impact of leveraged trading on volatility and maintaining the sustainability of the stock market.

Disagreement between Hedge Funds and Other Institutional Investors and the Cross-Section of Expected Stock Returns

We find that strong disagreements between hedge funds and other institutions in their common stock trades are twice as likely as agreements. The overall success of hedge funds’ trades is confined to disagreement stocks. While hedge funds are on average positive feedback traders, albeit weaker than other institutions, they are neither positive nor negative feedback traders for stocks heavily sold by other institutions. Hedge funds also depend less on earnings news. Our findings highlight the importance of disagreement in studying the performance of institutional investors’ trades and are consistent with the notion that skilled investors rely less on public information.

With Regard to Local Contents Rule (Non-tariff Barriers to Trade): After Announcing the Shanghai-Hong Kong Stock Connect, is the Chinese Capital Market Suitable for Korean Investors?

Purpose – As the U.S.-China trade war has become considerably worse, the Chinese government is considering applying non-tariff barriers to trade, especially local contents rule. The main purpose of this research is to check whether it is suitable for Korean investors to invest in the current Chinese capital market. Design/methodology – In order to check the stability of the recent Chinese capital market, we investigated the behavior of foreign equity investment (including Korean equity investment) in the Chinese capital market after China announced the Shanghai-Hong Kong Stock Connect (SH-HK Connect). In this paper, we researched whether international portfolio investment would or would not contribute to an increase the volatility of an emerging market’s stock market (Chinese capital market) when foreign investors make investment decisions based on the objective of short-term gains by rushing into countries whose markets are booming and fleeing from countries whose markets are falling. Findings – The empirical results indicate that foreign investors show strong, negative feedback trading behavior with regard to the stock index of the Shanghai Stock Exchange (SSE), and when the performance of foreign investors in the Chinese stock market was fairly good. Also, we found evidence that the behavior of foreign investors significantly decreased volatility in SSE stock returns. Consequently, the SH-HK Connect brought on a win-win effect for both the Chinese capital market and foreign investors. Originality/value – It appeared that the Chinese capital market was very suitable for Korean investors after the China’s declaration of the SH-HK Connect. However, the win-win effect was brought on by the Chinese government’s aggressive capital control but the capital controls could possibly cause financial turmoil in the Chinese capital market. Therefore, Chinese reform in industrial structure and the financial sector should keep pace with suitable capital control policies.

Foreign investor trading behavior has evolved

Foreign (equity portfolio) investors have been characterized as return chasers in both the empirical and theoretical literature. Using 1996–1998 investor trading data from Korea, Choe et al. (2005) document that foreign investors trade at disadvantaged prices, because they trade after prices have moved against them. Using a 2004–2015 sample of Korean data, we show that these established facts have changed: foreigners do not any longer trade after prices have moved against them and are no longer disadvantaged; they trade at more favorable prices compared with domestic institutions. We document an essentially monotonic evolution of foreign investor trading behavior over time, from return chasing toward well-timed negative feedback trading, which parallels the improvement in their trading prices. Using marketwide-foreign investor trading data available from around the world, we show that foreigners’ shift away from positive feedback trading is a pervasive phenomenon. These findings imply a major empirical update on foreign investor trading behavior.

INVESTOR ASING DAN RETURN PASAR: APAKAH INVESTOR ASING MENDESTABILIZE BURSA EFEK INDONESIA

The purpose of this study is to analyze the impact of the presence of foreign investors on market returns on the Indonesia Stock Exchange. To see the impact of foreign investor trading activities, this study proposes three hypotheses that will be proven. The first hypothesis is that foreign investors will increase portfolio diversification or the so-called base-broadening hypothesis. The second hypothesis is that foreign investors will cause price pressures on stocks or the price pressure hypothesis. The third hypothesis is that foreign investors use certain strategies in their trading, namely the feedback trading strategy. Of the 401 companies selected 32 companies as samples. Furthermore, from the three hypotheses proposed, the only proven hypothesis is the price pressure. Thus, foreign investors can cause destabilize prices on the Indonesia Stock Exchange. The destabilize implication is that investors are possible to use negative feedback trading strategies to make a profit. Keywords: base-broadening, price pressure, feedback trading

Feedback Trading Strategies: The Case of Greece and Cyprus

Abstract This paper examines whether or not feedback trading strategies are present in the Athens (ASE) and Cyprus Stock Exchanges (CSE). The analysis employs two econometric models: the feedback trading strategy model, introduced by Sentana and Wadhwani (1992), and the exponential autoregressive model, proposed by LeBaron (1992). These two theoretical frameworks, separately, were joined with the FIGARCH (1, d, 1) approach. Both models assume two different groups of traders - the “rational” investors that build their portfolio by following the firms’ fundamentals and the “noise” speculators that ignore stock fundamentals and focus on a positive (negative) feedback trading strategy. The empirical results revealed that negative feedback trading strategies exist in the two underlying stock markets