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04/11/ · 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., – The discussion points out theoretical and empirical limitations and shortcomings of the extant literature., – This is the first paper to review positive feedback trading, implications, limitations and Cited by: 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. Positive feedback trading is consistent with the market adage that one should not try to ﬁcatch a falling knifeﬂ – that is, one should not trade against a strong trend in price. Some recent empirical studies are also consistent with such behaviour. Hasbrouck () finds that a flow of new market orders for a. 11/05/ · The positive feedback trading (or trend-chasing) behavior in the literature generally states that market participants buy (sell) securities in response to their previous price going up (down), which leads to positive autocorrelations in returns in the short-run (De Long et al., ).Author: Jying-Nan Wang, Yen-Hsien Lee, Hung-Chun Liu, Ming-Chih Lee.
Skip to Main Content. A not-for-profit organization, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Positive Expected Feedback Trading Gain for all Essentially Linearly Representable Prices Abstract: We study a specific feedback stock trading rule, the simultaneously long short SLS strategy.
This strategy is known to yield positive expected gains when the underlying stock returns are governed by a geometric Brownian motion or by Merton’s jump diffusion model. In this paper, we generalize these results to a set of price models called essentially linearly representable prices that are given by means of a set of stochastic differential equations based on semi martingales.
Particularly, we show that the SLS trader’s expected gain is almost always positive and that it does not depend on the chosen price model but only on the trend. The basic novelties of this work are, first, the extension of the results in the literature to a set of SDEs and, second, that we do not need a solution of the SDEs, but we work on the level of SDEs directly, i.
Published in: 12th Asian Control Conference ASCC. Article :. INSPEC Accession Number:
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Nonlinear Dynamic Positive Feedback Trading and the Complexity of Stock Price. Bang Xiao. Abstract This thesis has applied the theory from behavioural finance theory and by merging with the concept of chaos theory from natural science, this thesis focuses on the impact of positive feedback trading on the price formation process. By using the Hurst exponent estimation and calculating the correlation dimension value, the market index and individual firms from China have presented the nonlinearity and chaotic characteristics, thus demonstrating the source of complexity.
This thesis proposes a new model that uses the Hurst exponent as the signal for thresholds to indicate changes in market conditions. The result suggested, by combining the threshold and assumptions from the positive feedback model, that the new model offers a better explanation for the complexity of the stock market which presents chaos. The model is found to be statistically significant and superiorin all comparative testing.
Date of Award Original language English Awarding Institution Coventry University Supervisor Karl Shutes Supervisor. Keywords Positive Feedback Trading Hurst Exponent Nonlinearity Complexity Chaos. Nonlinear Dynamic Positive Feedback Trading and the Complexity of Stock Price Xiao, B.
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Scott H. Irwin , Satoko Yoshimaru. A major issue in recent years is the role that large, managed futures funds and pools play in futures markets. Many market participants argue that managed futures trading increases price volatility due to the size of managed futures trading and reliance on positive feedback trading systems. The purpose of this study is to provide new evidence on the impact of managed futures trading on futures price volatility.
A unique data set on managed futures trading is analyzed for the period 1 December through 31 March The data set includes the daily trading volume of large commodity pools for 36 different futures markets. Regression results are unequivocal with respect to the impact of commodity pool trading on futures price volatility. For the 72 estimated regressions two for each market , the coefficient on commodity pool trading volume is significantly different from zero in only four cases.
These results constitute strong evidence that, at least for this sample period, commodity pool trading is not associated with increases in futures price volatility. Managed futures, positive feedback trading, and futures price volatility. N2 – A major issue in recent years is the role that large, managed futures funds and pools play in futures markets.
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The positive feedback received lately from the Russian market and, in particular, from the plastics, rubber and packaging industry as well as the process industries associated with it has now been confirmed very emphatically at the two trade fairs interplastica the 21 st International Plastics and Rubber Trade Fair , and upakovka — Processing and Packaging.
The upswing in major market segments is leading to strong demand for plastic and rubber products as well as packaging. The manufacturers of these products are investing as much as they can in modern production technologies and materials, in order to be able to satisfy the increasingly exacting requirements made by their customers. About companies from 30 countries presented their innovations at the two trade fairs in the SAO Expocenter in Krasnaja Presnja from January and were unanimous in reporting a tremendous response and impressive business success.
Werner M. This is where they can get to know the new developments on the world market and enter into intensive negotiations with the suppliers directly. The exhibitors that maintained a consistent presence in Russia under poorer market conditions as well are now benefitting to a particularly large extent from their good contacts in the industry. In addition to the conclusion of many sales contracts, the high quality of the demand was a very important sign that an economically attractive future is beginning.
The trade visitors were in turn very impressed by the wide range of innovative products and services on show that gave them a valuable insight into trends and future market opportunities.
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The mechanism of feedback has a very simple definition: „the return to the input of a part of the output“ [ 1 ]. This simplicity should however not undermine the importance of feedback mechanisms and their ubiquitousness in our life, both on macro- and micro-scales. In order to further present the concept of feedback mechanisms I introduce a simplifying division between the systemic view of feedback and the decision making view of feedback.
Systemic view. From the point of view of a system understood as „a regularly interacting or interdependent group of items forming a unified whole“ [ 2 ] , feedback mechanisms have a very important role to play. Through „feeding back“ a part of output again into the system, we obtain a perfect regulatory mechanism. This regulation is based on two basic kinds of feedback, namely: positive and negative feedback. Positive feedback mechanisms.
We call a feedback mechanism positive if the resulting action goes in the same direction as the condition that triggers it. A good example of positive feedback is a turbo-charger fitted to the engines of vehicles. As we accelerate, increasing revolutions of the engine after crossing some threshold , set the turbo-charger on, that in fact increases the speed even further. Summarizing, a part of output acceleration was „fed back“ to the process again, causing action going in the same direction further acceleration.
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Positive feedback trading: evidence from futures markets. N2 – Shiller hypothesises that the positive feedback mechanism in financial markets may exhibit longer memory in the sense that feedback may operate over long time intervals. This paper tests the Shiller hypothesis using data from major index futures markets. The analysis is based on a modified dynamic capital asset pricing model that assumes two types of investors: 1 expected utility maximisers 2 positive feedback traders who sell during market declines and buy during market advances.
According to the model, the interaction of the two groups induces negative time varying autocorrelation. There is some evidence of time-varying negative autocorrelation, consistent with the notion that some participants engage in positive feedback trading. AB – Shiller hypothesises that the positive feedback mechanism in financial markets may exhibit longer memory in the sense that feedback may operate over long time intervals.
Portsmouth Research Portal. Standard Positive feedback trading: evidence from futures markets. In: Global Business and Economics Review GBER , Vol. Antoniou, A.
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We present evidence that equity momentum strategies are partially driven by positive-feedback trading intermediated via the mutual fund sector. We identify a U. As a result, trading strategies that load on flow-driven positive-feedback trading including momentum in stocks, styles, and factors experienced a profitability decline. Consistent with the proposed channel, the profitability decline was limited to the U. Previously circulated as „Discontinued Positive Feedback Trading and the Decline in Asset Pricing Factor Profitability.
We thank seminar participants at The Ohio State University, the University of Utah, the University of Washington, Hong Kong University of Science and Technology, and Arrowstreet Capital, as well as WFA and the National Bureau of Economic Research Behavior Finance Workshop participants for comments and George Aragon for sharing data. Ben-David is with The Ohio State University and the National Bureau of Economic Research, Li is with the University of Utah, Rossi is with the University of Arizona, and Song is with the University of Washington.
The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. Download Citation Data. Home Research Working Papers Discontinued Positive Feedback Trading…. Share Twitter LinkedIn Email. Working Paper DOI Issue Date March
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Positive feedback trading is present for the full sample period, before and during the crisis, interacting significantly with a variety of factors related to Krugerrand’s pricing, yet dissipates. Positive feedback trading in low frequency data (weekly or monthly) is often associated with “momentum trading” and other explanations that appeal to boundedly rational traders (De Long et al. (), Jagadeesh and Titman (), Grinblatt, Titman and Wermers ()). Our focus is very different. At the level of tick-by-tick.
Asymmetries of Positive Feedback Trading in Individual Stocks : Evidence from China. Researcher login. CityU Scholars. View graph of relations. Author s Die Wan W. Liu Junbo WANG Xiaoguang Yang. Related Research Unit s Department of Economics and Finance. Heterogeneous regression models and a non-parametric Sentana-Wadhwani model are developed and applied to prove the existence of rise-favor asymmetric feedback trading.
However, the result is in contrast with the stylized findings using market indices. Further empirical research shows that this distinction could be explained by the average effect of indices.