in recent years noise has been well known as an environmental pollution. particularly its effects will be more serious in some environments including hospitals which patients need a calm and peaceful condition. this study aims to evaluate hospitals noise pollution level. this study is a cross-sectional study. noise measurements were made in all hospital wards in a workday and weekend from 8 to ...

I investigate the different roles played by two components of trading volume, informed-trading and liquidity-trading, in the volatility-volume relation at the aggregate level. Using transaction data and an extended trading model of Easley, Kiefer, O’Hara and Paperman (1996), I estimate a marketwide private information arrival rate (PIAR) variable and use it to control for the informed trading c...

This paper is about how to estimate the integrated covariance 〈X,Y 〉T of two assets over a fixed time horizon [0, T ], when the observations of X and Y are “contaminated” and when such noisy observations are at discrete, but not synchronized, times. We show that the usual previous-tick covariance estimator is biased, and the size of the bias is more pronounced for less liquid assets. This is an...

High-frequency realized variance approaches offer great promise for estimating asset prices’ covariation, but encounter difficulties connected to the Epps effect. This paper models the Epps effect in a stochastic volatility setting. It adds dependent noise to a factor representation of prices. The noise both offsets covariation and describes plausible lags in information transmission. Non-synch...

As the evolvement of financial trading technology with wireless network infrastructure, mobile trading technology has emerged to meet investors’ requirements to access the financial markets regardless of time and place. However, being like a “two-edged sword”, mobile trading technology may affect investors’ irrational trading behaviors negatively. This research investigates both the positive an...

Using a new data set on investor sentiment, we show that institutional and individual sentiment seem to proxy for smart money and noise trader risk, respectively. First, using bias-adjusted long-horizon regressions, we show that institutional sentiment forecasts stock market returns at intermediate horizons correctly, whereas individuals consistently get the direction wrong. Second, even the si...

In this paper we explore the specific role of randomness in financial markets, inspired by the beneficial role of noise in many physical systems and in previous applications to complex socio-economic systems. After a short introduction, we study the performance of some of the most used trading strategies in predicting the dynamics of financial markets for different international stock exchange ...

To solve the problem of multisensor data fusion under non-Gaussian channel noise. The advanced M-estimates are known to be robust solution while trading off some accuracy. In order to improve the estimation accuracy while still maintaining the equivalent robustness, a two-stage robust fusion algorithm is proposed using preliminary rejection of outliers then an optimal linear fusion. The numeric...

We study the dynamics of a version of the batch minority game, with random external information and with different types of inhomogeneous decision noise (additive and multiplicative), using generating functional techniques à la De Dominicis. The control parameters in this model are the ratio alpha=p/N of the number p of possible values for the external information over the number N of trading a...