What brings the equilibrium consensus in the stock markets? We hypothesize that the markets’ equilibrium consensus depends on the noise of investors’ attention mania (NIAM). We refer to the NIAM as investors’ attention heterogeneity and explore its impacts on the National Stock Exchange (NSE) Nifty and Bombay Stock Exchange (BSE) Sensex stocks market returns. We use the methodology of the autoregressive distributed lag (ARDL) and augmented generalized autoregressiuve conditional heteroskedacity (GARCH)-X model, and we examine if there is the presence of NIAM at online attention searches within and across the attention layers, and within and across the stated two stock markets from 2004 to 2019 for investors’ economic–political attention searches. We have revealed that the impacts of the NIAM on the market returns are diverse in nature at the different attention layers and stock markets as well. Besides the ARCH and GARCH effects, we also document the presence of familiarity bias, attention confidence or confusion, and attention integration in the short run and long run.
What drives intraday traders' sentiments in the stock markets: information or noise? This paper argues that the market microstructure noise (MMN) manifests intraday traders' aggregate sentiments depicted by chaotic and noisy market returns. It examines if intraday stock market returns, returns' variances and higher order moments are erratic, noisy and nonnormal. It shows that the intraday Bombay Stock Exchange (BSE) Sensex and National Stock Exchange (NSE) Nifty index returns approximate to zero-mean, zero-variance but skewed and leptokurtic in distributions. In exploring the intraday market index returns, standardisation process reveals noises in the BSE market, but it is evened up in the NSE market. Since intraday traders' market sentiments and decision choices are behavioural, noisy but adaptive, their decision choices need strategies given that those strategies have numerical "attractions" that determine choice probabilities. We explore the adaptive Experience Weighted Attraction (EWA) learning parameters to show persistent MMN in intraday traders' adaptive learning behaviours.
In a brief review of the literature on stocks' pricing, the study shows that information vis-à-vis noise serves critical roles in the equilibrium process. It is dynamic in nature and there are different infiltrating aspects from the standard finance to behavioral finance points of views. The aspects of market efficiency, fundamental risk, noise traders' risk, and implementation costs make the stock markets noisy and thereby, limit the arbitrage opportunity of informed traders. Investors' psychological bases viz., belief and preferences contribute more in the equilibrium process. Beliefs include representativeness, conservativeness, and anchoring, availability biases, optimism and wishful thinking, overconfidence, and herd behavior tendency on the part of the investors. On the preferences, investors are influenced by disposition effect, prospects based on reference points, mental accounting, ambiguity aversion, and self control.The study explores the empirical literature also and reviews the six puzzles in the standard finance. Finally, the work identifies a few research gaps to be addressed in the literature.Growing Science Ltd. All rights reserved. 5
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 long-short 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.
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