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Economists have analyzed noise trading from various viewpoints in the past, and they drew the most diverse conclusions. Noise trading has been interpreted as a facilitator of market liquidity, as a source of inefficiency, as a driver of easy money for more informed traders or for herds of uninformed ones. However, in an environment populated by High-Frequency traders, most financial theories need to be revisited, the theory about noise trading being one of them. By making use of a computer-based Agent-Based Model, this paper creates a scenario where a shock breaks the equilibrium and only some market participants receive, and act upon, such information. The results are that old-fashioned parameters, as informedness, arbitrage, market efficiency and herding behavior no longer carry the same meaning as they used to. The focus shifts from searching the mythical ‘true value’ of a security to executing orders with the shortest possible latency, to exploit trading opportunities and maximize profits. [ABSTRACT FROM AUTHOR]

As a significant source of financing resources, the stock market plays a vital role in directing savings to the productive sectors of the economy in all countries. Therefore, the study of factors affecting this market is of particular importance. The primary purpose of this paper is to investigate the effect of Noise Trading and the withdrawal of the United States from the Joint Comprehensive Plan of Action (JCPOA) on the return of the Tehran Stock Exchange Market. The sample includes 248 companies listed on the Tehran Stock Exchange selected by systematic removal method, and the data has been collected from the Rahavard365.com website and the Tehran Stock Exchange Organization website. Empirical results based on pooling data and estimate by generalized least squares (GLS) method during 2011-2018 applying for the STATA (15) software showed that United States withdrawal from JCPOA, herding behavior, and company size have a significant positive effect on the return of the Tehran Stock Exchange Market, While the noise trading has a significant negative effect on this return

I present an asymmetric information model of financial markets in which there is uncertainty and learning not only about fundamentals but also about the proportion of informed‐to‐noise traders in the market. Extreme news leads to an increase in both types of uncertainty, while it decreases price informativeness. Uncertainty about the market composition constitutes a type of liquidity risk and is associated with high expected returns. The resulting price–volume relationship is U‐shaped and positively sloped. In a dynamic extension of the model I show that this mechanism generates momentum as well as history‐dependent volatility and price informativeness. [ABSTRACT FROM AUTHOR]

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This study aimed to evaluate the significance and severity of the relationship between market sentiment and the volatility of the Tehran Stock Exchange Price Index (TEPIX). We drew on the principal component analysis (PCA) to provide a composite sentiment index using a set of proxies. In addition, ARIMA-E-GARCH hybrid models were applied to model the volatility of the TEPIX and other control variables. Subsequently, GLS regression was used to measure the impact of market sentiment and the control variables variation on the volatility of the TEPIX. The findings showed that the influences of optimistic and pessimistic sentiment on the volatility of TEPIX were both statistically significant and respectively, negative and positive. However, the severity of these negative and positive effects was slight. Furthermore, we found that the stock exchange volatility was highly affected by the volatility of the inflation and the liquidity much more than the other variables such as optimistic and pessimistic sentiment. [ABSTRACT FROM AUTHOR]

At present, the proportion of individual financial investors in China is relatively high, the phenomenon of noisy trading is frequent, and the market system risk caused by the polarization of investor sentiment cannot be ignored. Therefore, exploring the polarization of investor sentiment under the influence of sudden financial events is of great practical significance for alleviating abnormal fluctuations in financial markets and building a long-term and stable market mechanism. Based on the B–A scale-free network and J–A model, this paper combines the multi-agent system and the DSSW model to construct a polarization model of investor sentiment. Through simulation tests and empirical tests, it is concluded that the polarization of investor sentiment stems from the herd effect and exclusion effect of investor behavior, and that increasing the coefficient of destabilization ε and reducing the effect interval threshold D 1 and D 2 will aggravate the polarization of investor sentiment in the equilibrium state, while increasing the effect parameter α and β will not affect the polarization of investor sentiment in the equilibrium state, but will accelerate the number of interactions required to reach the equilibrium state. Finally, this paper puts forward targeted policy recommendations to provide references for responding to unexpected financial events. [ABSTRACT FROM AUTHOR]

Following the increasing importance of sustainable development and the popularity of ESG investing activities, ESG ratings have grown to be crucial references for investors' decision-making. However, there are substantial disagreements among different rating agencies. This study examines the impact of ESG rating disagreement on idiosyncratic return volatility using data from five prominent rating agencies: SynTao Green Finance, Huazheng, Hexun, Bloomberg, and Rankins ESG Ratings. The findings suggest that ESG rating disagreement will increase idiosyncratic return volatility. This relation is driven by investor attention and noise trading. Heterogeneity tests reveal that the higher analyst coverage and greater analyst forecast bias, the more pronounced the impact of ESG rating disagreement on idiosyncratic return volatility. While firms with foreign investors and more institutional investors can alleviate the interference. • The increase in investor attention and noise trading is the channel through which ESG rating divergence affects idiosyncratic return volatility. • The higher analyst coverage and forecast error exacerbate the impact of ESG rating divergence. Meanwhile, QFII and institutional investors mitigate the negative effects of ESG rating divergence. • ESG rating disagreements have the negative impact on information efficiency. [ABSTRACT FROM AUTHOR]

At present, the proportion of individual financial investors in China is relatively high, the phenomenon of noisy trading is frequent, and the market system risk caused by the polarization of investor sentiment cannot be ignored. Therefore, exploring the polarization of investor sentiment under the influence of sudden financial events is of great practical significance for alleviating abnormal fluctuations in financial markets and building a long-term and stable market mechanism. Based on the B–A scale-free network and J–A model, this paper combines the multi-agent system and the DSSW model to construct a polarization model of investor sentiment. Through simulation tests and empirical tests, it is concluded that the polarization of investor sentiment stems from the herd effect and exclusion effect of investor behavior, and that increasing the coefficient of destabilization ε and reducing the effect interval threshold D1 and D2 will aggravate the polarization of investor sentiment in the equilibrium state, while increasing the effect parameter α and β will not affect the polarization of investor sentiment in the equilibrium state, but will accelerate the number of interactions required to reach the equilibrium state. Finally, this paper puts forward targeted policy recommendations to provide references for responding to unexpected financial events.

We draw a parallel between noise trading and the "readiness potential" in neuroscience. The latter can be explained in terms of neuronal noise accumulation which can tip the scale ahead of voluntary actions, in particular their timing in situations of weak evidence. This principle may apply to trading by technical noise traders. Based on our initial findings we propose that excess volatility, as a measure of price noise, indirectly reflects the signature of collective neuronal noise. In other words, we've potentially identified an internal contributor to Black's "cumulative noise", with neurons and prices reflexively participating in a joint random walk. [ABSTRACT FROM AUTHOR]

Classic finance believes that stock price changes are related to systematic changes in the company's intrinsic values. However, recent research shows that behavioral factors play a very important role in determining stock prices and returns of investors, one of these behavioral patterns is noise trading. The purpose of this study is to investigate the effect of unsystematic risk fluctuations on noise transactions. For this study, we use the random variance of the capital asset pricing model-disrupted unit as a measure of unsystematic risk fluctuations and for measuring noise trading We used a comparison of company market value with industry companies the average market value. The research sample included 92 companies listed in the Tehran Stock Exchange during the period of 2011-2016. The result of the test the hypothesis of the research showed that the relationship between unsystematic risk fluctuations and noise trading using is positive and significant and thus unsystematic risk fluctuations can be used as a criterion for detecting noise trading.

This article investigates the effect of cross‐shareholdings on stock price synchronicity, as a measure of price informativeness, of the listed firms in the Chinese stock market. We gauge firms' levels of cross‐shareholdings in terms of centrality in the cross‐shareholding network. It is confirmed that it is through a noise‐reducing process that cross‐shareholdings promotes price synchronicity and reduces price delay. More importantly, this effect on price informativeness is pronounced for large firms and in the periods of market downturns. Overall, our analyses provide insights into the relation between the ownership structure and price informativeness. [ABSTRACT FROM AUTHOR]

Using volatile and correlated liquidity shocks to investors as a source of noise trading, I show that noise in stock prices impedes real efficiency. A one-standard-deviation increase in mutual fund flow-driven volatility pressure leads to a 2.6%–4.0% decline in return on assets and a $22.6 million loss in cash flow in the subsequent two years. Noise in stock prices does not affect product market demand, but it reduces firms' total factor productivity, profit margin, and performance in research and development and acquisitions. Further evidence suggests that noise in stock prices impedes real efficiency through three plausible channels: distorting firms' investment decisions through misleading price signals, increasing the cost of capital, and reducing the efficacy of equity-based incentive contracts. This paper was accepted by Gustavo Manso, finance. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the risk-return tradeoff allowing for the presence of noise traders, i.e., a subset of investors who either base their trading strategies on sentiment or hold unjustified optimistic/pessimistic views regarding market prospects. We measure noise traders' sentiment relying on two sets of indices, namely the Baker and Wurgler sentiment index and the Michigan Consumer Confidence Index, in the US stock market. Under the assumption of the presence of noise traders' sentiment, the risk-return tradeoff is tested through two sets of models: Merton's Intertemporal CAPM and the GARCH-in-mean model. First, we find that the relationship between risk and return allowing for the presence of noise trader risk as measured by the Baker and Wurgler sentiment index is positive and statistically significant when tested through Merton's Intertemporal CAPM. Second, the risk-return tradeoff tested through GARCH-in-mean models augmented by noise traders' risk as measured through survey-based measures of sentiment establishes no clear evidence for a significant mean–variance relationship. Overall, we confirm Merton's (1973) hypothesis that the more risk an investor bears, the greater his expected returns. This paper contributes to the asset pricing literature by trying to shed some light on the risk-return tradeoff from the standpoint of behavioral finance. [ABSTRACT FROM AUTHOR]

Today, non-informed investors sudden arrival in the capital stock market cause disruption, and noise trading play a central role in the behavioral finance literature. These transactions cause the asset price to deviate from their intrinsic values. Equity prices are also jointly determined through intrinsic value and distorted trader risk. As a result, noise trading can lead to mispricing. The purpose of the present study is to investigate the effect of idiosyncratic volatility as an indicator of impaired trading on stock pricing. In this regard, 120 compnanies using systematic elimination method is selected as the sample of the research from companies listed in Tehran Stock Exchange for the period of 2011 to 2016. The results show that idiosyncratic volatility have a positive and significant effect on the level of stock pricing based on Rhodes (2005), Burger (1995) and Walking (1985) models. Therefore, idiosyncratic volatility as an indicator of noise trading has a positive and significant effect on inaccurate pricing based on all three methods. As a result, one of the strategies is to prevent mispricing, noise control or noise trading. As a result, the entry of uninformed traders into the stock market disrupts and causes the price to deviate from its intrinsic value. New financial behaviors express it. The results of the present study also emphasize this point. In this regard, one of the ways to prevent incorrect stock pricing is to control disruptive transactions. [ABSTRACT FROM AUTHOR]

Derivatives, and their influence on the dynamics of underlying stock markets, is an interesting topic of debate, which predates their introduction. The unresolved influence of derivatives on their underlying stock markets still intrigues many. In this regard, researchers/stakeholders are still curious about the (de)stabilizing influence of derivatives on the overall market. In disposition of these observations, two contradicting hypothesis have been studied widely and have remained the focus of attention in several theoretical and empirical studies. These hypotheses are explained in several ways. Among many, one explanation refers to the destabilizing influence of derivatives, due to the enhanced involvement of noise traders, after the introduction of derivatives. This aspect remains the topic of discussion for this study. After the formal introduction of the SSFs (Single Stock Futures) in Pakistan, this topic became a cause of concern for the stakeholders of this market as well. Hence, this study attempts to tap into this aspect of the de(stabilization) debate, by proposing a modified version of the famous Sentana & Wadhwani (1982) model. In order to tap the potential shortcomings of the S&W model, this study contributes to the extant literature in several ways: 1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market, due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speaking, the modified version of the model not only extends the original model in terms of its explanation, but also empirically tests this aspect in the Single Stock Futures (SSFs) market of Pakistan. This model tested whether SSFs promote, or inhibit the noise trading post-SSFs. After putting it to test, the newer model did not report any negative or positive impact of the introduction of SSFs on the underlying stocks. This may conclude that the proclaimed (de)stabilizing role of the SSFs, in the context of Pakistan, is not justified. This may also imply that the stringent regulatory frameworks, post the Global Financial Crisis, (GFC) for the resumed SSFs, are not justified and require revision. [ABSTRACT FROM AUTHOR]

This study examines disagreements between actual and options-implied futures prices and the corresponding adjustments in a sophisticated setting. We identify the market that triggers each type of price disagreement and find that the market in which the disagreement is initiated adjusts more to eliminate the mispricing. Futures prices adjust less for options-initiated price disagreements with out-of-the-money (OTM) options-implied prices than they do for disagreements with at-the-money (ATM) prices. Options markets adjust more when disagreements are initiated by OTM options than they do when disagreements are initiated by ATM options. Adjustments in both the futures and options markets consistently suggest that OTM options trading provides inferior information. Price disagreements are positively correlated with the participation of domestic investors, especially when they trade OTM options, implying that domestic investors are noisier and less informed than foreign investors are. Highlights We examine disagreements between actual and options-implied futures prices and the corresponding adjustments. The market in which the disagreement is initiated adjusts more to eliminate the mispricing. Out-of-the-money options-initiated price disagreements are positively correlated with domestic investors' trades. [ABSTRACT FROM AUTHOR]

• This paper investigate intraday returns predictability in emerging market. • We find not only intraday momentum but also reversal effect in Chinese stock market. • We confirm that noise trading is the driving factor that causes intraday returns predictability. • The existence of transaction costs hinders the intervention of arbitrageurs. Taking intraday first-half-hour returns as predictor, we find significant intraday momentum and a reversal effect in the Chinese stock market. This momentum and reversal effect is robust even when including previous day returns, overnight returns, and day-of-week effect. We confirm that noise trading is the driving factor that causes the predictability of intraday returns. Although the investment strategy based on the first-half-hour returns can generate abnormal returns, the presence of costs prevents arbitrageur's intervention and makes the intraday returns predictability exist persistently. [ABSTRACT FROM AUTHOR]

Based on the theory of irrational behavior hypothesis, this paper investigates the relation between risk-taking and stock price synchronicity from the perspective of information transparency. Several findings were extracted as follows:Firstly, because of the noise-trading, the high level of risk-taking reduces the stock price synchronicity in China which are supported by a series of robustness tests. Furthermore, opportunistic behaviors such as earnings management and bad news hiding is the possible mechanism of the relation between risk-taking and stock price synchronicity; managerial overconfidence aggregates such negative relationship. This study provides the theoretical explanation and empirical evidence for the relationship between risk taking and stock price synchronicity for the first time, the very important implication of this study is that although risk-taking would decrease stock price synchronicity, which is not the reflection of effective information disclosure or capital pricing. On the contrary, risk-taking decreases information transparency and induces more opportunistic behaviors. [ABSTRACT FROM AUTHOR]

The investor recognition hypothesis and the bonding hypothesis, which help us understand the market quality of stocks that are cross-listed on different stock markets, imply improved market efficiency after cross-listing because of increased investor participation. However, the noise trading of inexperienced investors in the Chinese stock market negatively affects market efficiency. By employing propensity score matching and multivariate regression analysis, we show that the increased individual investor participation actually lowers market efficiency in their home market after cross-listing. This effect is more evident for stocks that were either listed first on the Chinese stock market or listed on the Chinese stock market and the Hong Kong stock exchange (SEHK) on the same date than for stocks that were listed first on the SEHK. [ABSTRACT FROM AUTHOR]

This study aims to analyze the behavior of traders in Amman Stock Exchange (ASE):-firstly at the market level by analyzing the market return volatility, defining the time frame of this volatility, and classifying it as transitory volatility or a permanent volatility, Daily closing of Amman free float market index will be used to indicate the market return during the period from 1/1/1992 to 31/12/2015 where 5899 observations were obtained. Secondly at the firms level by selecting a sample of trading companies and interpreting the results through analyzing some important features of the companies, such as share price and ownership structure, Daily closing of share price of the selected companies will be used to indicate the return during the period from 1/1/2015 to 31/12/2015 where 240 observations were obtained for each company during this period. To achieve the goals of this study, the Variance ratio test, GARCH test, and CGARCH test will be used. The study highlighted an important result that the common culture of traders on ASE was Noise Trading; the significance of this finding was statistically proven at the confidence level of 1%. This study recommends the competent authorities to enact a slew of strict measures: the implementation of Capital Gains Tax in a bid to slash frequent selloffs and purchasing of noise traders and increasing the commission of brokers in return for completing selloffs and purchasing deals. The study also affirmed the necessity of intervening periodically to raise awareness of the negative impact of speculation including the instability, increasing the firm’s cost of capital and the damage to traders’ confidence in the stock markets. [ABSTRACT FROM AUTHOR]

This study attempts to analyze the effects of investor sentiment on volatility of nine stock markets, and capture the asymmetry in terms of negative and positive news during the period from January, 2004 to June, 2015. Empirical evidence from a sentiment-augmented TGARCH model demonstrates that there is an asymmetric property for all markets. The estimated coefficient of country-specific consumer confidence index used as a proxy for investor sentiment is statistically significant and negative for France and Germany, but statistically significant and positive for Ireland alone. The results provide evidence that in France and Germany, stock market volatility is sensitive to negative shock in investor sentiment, supporting the existence of the leverage effect; in Ireland, however, no such sensitivity exists. The results of this study should be of a particular interest for both domestic and international investors, academic researchers and policymakers in terms of international portfolio diversification. Investors can potentially improve their portfolio performance by considering investor sentiment, while policymakers can take steps to stabilize investor sentiment, thereby reducing stock market volatility and uncertainty. [ABSTRACT FROM AUTHOR]

Based on the inefficiency market structure of DSSW model, this paper derives and analyzes the equilibrium between followers and noise traders by endogenising the strategies of noise traders under the situation of manipulation and social network. Our study draws conclusions that informed manipulation enhances the price informativeness, while uninformed manipulation brings noise to price, which results in price informativeness increasing first and then decreasing. Moderate pessimism functions as the sufficient condition for the noise traders to follow. Furthermore, market may converge to three kinds of equilibrium with no noise traders, no followers, or coexistence of followers and noise traders. [ABSTRACT FROM AUTHOR]

By incorporating behavioural sentiment in a model of a limit order market, we show that behavioural sentiment not only helps to replicate most of the stylized facts in limit order markets simultaneously, but it also plays a unique role in explaining those stylized facts that cannot be explained by noise trading, such as fat tails in the return distribution, long memory in the trading volume, an increasing and non-linear relationship between trade imbalance and mid-price returns, as well as the diagonal effect, or event clustering, in order submission types. The results show that behavioural sentiment is an important driving force behind many of the well-documented stylized facts in limit order markets. [ABSTRACT FROM PUBLISHER]

Based on the arbitrage risk and the arbitrage asymmetry, this paper investigates the different rates of return between the portfolios with different idiosyncratic volatilities by estimating the idiosyncratic risk premium. Further, this paper examines the effect of cash dividend payment, stock liquidity and investor sentiment on the idiosyncratic risk premium. The results show that the relationship between the idiosyncratic volatility and the stock return is positive, namely the idiosyncratic risk premium is positive. The results also show that the higher the cash dividend that a company pays, the higher the information transparency and the lower the noise trading risk, the lower the idiosyncratic risk premium. The more optimistic the investors and the higher the unexpected liquidity, the higher the idiosyncratic risk premium. [ABSTRACT FROM AUTHOR]

We hypothesize and test an inverse relation between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: volume and noisiness. As represented by the expected turnover rate (volume) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with the ex post and ex ante return volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between noisiness and volatility is amplified in times of market crisis. The negative noisiness-volatility relation is also supported by our analysis on the effects of trade size on price volatility. The overall results demonstrate that volatility increases as noise trading declines. [ABSTRACT FROM AUTHOR]

We examine the cross-sectional determinants of individual trading activity based on given Big Five personality traits. Our unique data set is obtained by a self-reported questionnaire with 2147 individual investors. We find that Agreeableness, Extraversion and Openness are central in explaining cross-sectional differences in trading activity. Openness is found to be a main driver of excess trading. Overconfidence as predicted by low levels of Agreeableness relates to excessive trading, while high levels of Extraversion do not. Our performance prediction conditional on investor personality is that Agreeableness saves individual investors from losing money via trading, while Openness will endanger terminal wealth. [ABSTRACT FROM AUTHOR]

Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioural finance perspectives. In particular, it develops a new theory of herding behaviour and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or timestamp, trade-volume, and trade-price of ten sample scripts listed for their trading in both markets - the Bombay Stock Exchange (BSE) and the National stock Exchange (NSE). The study contributes to the literature with original findings. It shows that investors in the two Indian stock markets show crowd of positive and negative herding as well significantly and there is huge noise along with information in the markets' equilibrium pricing mechanism. [ABSTRACT FROM AUTHOR]

This article critically investigates the possibility that private information offering systematic profit opportunities exists in the spot foreign exchange market. Using a unique dataset with trader-specific limit and market order histories for more than 10,000 traders, we detect transaction behavior consistent with the informed trading hypothesis, where traders consistently make money. We then work within the theoretical framework of a high-frequency version of a structural microstructure trade model, which directly measures the market maker's beliefs. Both the estimates of the trade model parameters and our model-free analysis of the data suggest that the time-varying pattern of the probability of informed trading is rooted in the strategic arrival of informed traders on a particular day-of-week, hour-of-day, or geographic location (market). [ABSTRACT FROM AUTHOR]

In Financial Economics, the "noise" and "noise traders" play critical roles in stocks' equilibrium pricing mechanism. It includes economic and non-economic aspects. The paper empirically explores the nature and magnitude of noise traders' risk in India during the present recovery phase. Besides the daily trading data, it utilizes intra-day 1D and 5D trade-prices, trade-volumes, and trade-times of the Nifty-Fifty firms listed both in the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE). The study utilizes the NSE-Nifty and the BSE-Sensex indices for market return data. It examines whether stocks' return variations incorporate noise traders' risk or not and whether informed traders' short-run arbitrage forces them to long-short positioning for hedging or not. The study argues that noise has systematic and firm-specific components those vary over time. These components include idiosyncratic and noise aspects. At lag-periods, traders' longshort positions over these markets can hedge fundamental systematic and fundamental firm-specific shocks and may detach noise shocks. Once stocks are traded at long - short horizons, traders' long-short returns expose the noise aspects across stocks The study also compares the results for the current price-volume-trade time data with those of two years earlier. The findings suggest that intra-day returns from 1D and 5D data impound significant noise while daily (weekly) returns show its high (moderate) exposures. The conditional volatilities of long-short returns in the GARCH models show that the time-varying idiosyncratic noise is highly persistent at presence of noise traders. The study confirms that stocks' prices impound information and noise during the trading days. [ABSTRACT FROM AUTHOR]

This paper introduces constant-collateral pyramiding trading strategies, which can be implemented in the futures markets. For these strategies, expressions are derived for effective constraints on the number of futures contracts in the trader's portfolio and on the trader's wealth. Implications of the results are drawn regarding the degree of pyramiding adopted by a subgroup of noise traders who underestimate the probability of receiving a margin call when they engage in positive feedback strategies. Suggestions are made regarding how market regulators can use margin requirements to encourage these traders to adopt less aggressive pyramiding strategies. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to examine whether the mandatory adoption of International Financial Reporting Standards (IFRS) has produced an impact on the level of noise trading and volatility dynamics in three major central and eastern European (CEE) markets. Design/methodology/approach – The paper employs the theoretical framework proposed by Sentana and Wadhwani to allow the existence of both rational investors and trend-chasing traders in examining the extent to which mandatory IFRS adoption affects the level of noise trading and volatility in the market place. Findings – The results show that noise trading was mostly significant prior to the IFRS introduction, with its significance dissipating following the implementation. Moreover, the paper finds that the level and persistence of stock return volatility has greatly decreased after the implementation of IFRS. Research limitations/implications – These findings are important in understanding the effect of IFRS adoption on the information environment and market dynamics and bear some important implications for the corporate managers, accounting professions and policy makers. For instance, the documented dissipation in noise trading post-IFRS implies that the activity in the sample markets is dominated by rational fundamental investors for whom financial reports constitute part of their decision-making input. Thus, it is crucial that the enforcement of IFRS constitutes a key priority of local authorities as a contributing factor to the efficiency and transparency of the market environment. Practical implications – The finding that moving towards the international accounting standards helps to improve the quality and stability of financial markets should provide a useful reference for many other countries which have recently introduced and/or been considering switching to IFRS as their mandatory accounting standards. Originality/value – This paper provides the first investigation of the effect of accounting standards' harmonization upon the level of noise trading and volatility of three major transition markets (the Czech Republic, Hungary, and Poland) in the CEE area. [ABSTRACT FROM AUTHOR]

This article investigates the role of institutional investors in the Taiwanese equity markets in the resolution of noise trading, which we define as the deviation of a stock's price from its fundamental value within a trading day. We use a sample of stocks traded on the Taiwan Stock Exchange (TWSE) that experience extreme price movements characterized by price limit hits between March 2003 and March 2007, and assess the noise trading component of the price movements. Specifically, we examine whether overreaction occurs in the Taiwanese equity markets, and whether noise trading disrupts the price discovery process. We shed light on whether the unique features of the retail trading segment of the market slows the speed of correction following an overreaction, and relate these findings to those from studies of the US market. Our results show that noise trading in the Taiwanese equity markets is prevalent, and that a protracted correction process takes place. Further, we document a disruptive role of institutional investors, namely, that in contrast to the US equity markets, they appear to move the market away from equilibrium, and slow the speed of correction following an overreaction. [ABSTRACT FROM AUTHOR]

We propose two new risk measures (i-beta and i-gamma) for a stock, which aim to distinguish between noise and information. Noise allows the stock price evolution to happen along a continuous path. Market wide economic information is transmitted via price jumps. Noise is idiosyncratic and does not propagate across securities. The main contribution is the development of an exact closed-form non-parametric jump risk estimator that boosts the ‘signal-to-noise’ ratio by utilizing co-skew moments. Empirically, the procedure is used to extract the i-beta and i-gamma for Google and Yahoo on NASDAQ, and provide a possible explanation of their seemingly low Sharpe ratio during the 2006–2008 period based on their asymmetrically high i-beta value. [ABSTRACT FROM AUTHOR]

Although prior research documents that prices respond to earnings announcements, only a little of the price variation is explained by these announcements. To further investigate the properties of the information environment around these announcements we use NYSE TAQ data and compute the maximum likelihood estimates (MLEs) of the primitive parameters of a Kyle (Econometrica 53(6):1315–1336, ) type model within and around earnings announcement windows. These include the precision of fundamentals given only public information, the precision of private signals, and the variance of uninformed liquidity trading (noise). We find that liquidity noise is higher while the precision of beliefs given only public information is lower within an earnings announcement window. The precision of private information is higher in an event window, consistent with greater information acquisition to try and interpret a public announcement. We also document that Kyle’s λ is higher in an event window, showing an overall increase in information asymmetry. Our overall findings suggest that the earnings announcement window is distinguished from the preceding and subsequent windows not by being a period with more public information but as a period with different public information. [ABSTRACT FROM AUTHOR]

This paper develops and simulates a model of a Bayesian market maker who transacts with noise and position traders in derivative markets. The impact of noise trading is examined relative to price determination in FX futures, noise transmission from futures to options, and risk-management behaviour linking the two markets. The model simulations show noise trading in futures results in wider bid–ask spreads, increased price volatility, and greater variation in hedging costs. Above all, the Bayesian market maker manages price-risk by trend chasing not for speculative purposes, but to avoid being caught on the wrong side of the market. The pecuniary effects from this risk-management strategy suggest that noise trading tends to constrain the market maker's capacity to arbitrage; particularly when the underlying price is mean averting as opposed to a Martingale and trading sessions exhibit significant price volatility. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]