Recent literature on realized volatility suggests that the observed price process of an asset may be decomposed into two parts: the unobservable, efficient price process and microstructure noise. In this article we present a methodology to sequentially estimate spot volatility from noisy data by separating these components. We use different liquidity-based measures, traded volume and quoted spr...

Disclosure can negatively affect stock market efficiency and real investment performance in markets populated with uninformed noise traders whose trading is affected by disclosure. We formalize this idea by analyzing a model where disclosure attracts noise traders and where firms infer information from stock prices to guide real investment decisions. The model predicts that disclosure can reduc...

Noise models for both single-pulse and coded Brillouin optical time-domain analyzers (BOTDA) are established to quantify the actual signal-to-noise ratio (SNR) enhancement provided by pulse coding at any fiber position in operating condition. Simulation experimental results show that polarization noise spontaneous scattering (SpBS) signal beating could highly penalize performance of coded-BOTDA...

in this research the asymmetric and non-linear correlation between the market returns and trading volume variables has modeled with the dcc-garch approach; and the impacts of market shocks, weekend and calendar effects on the market returns and trading volume are surveyed. the estimation results of parameters of the model by the maximum likelihood method show that previous day’s market return h...

We propose a model in which investors cannot costlessly process information from asset prices. At the trading stage, are boundedly rational, and their interpretation of prices injects noise into price, generating source endogenous trading. Our setup predicts price momentum yields excessive return volatility volume. In an overall equilibrium, optimally choose sophistication levels by balancing b...

Although brokers’ trading is endemic in securities markets, the form of this trading differs between markets. Whereas in some securities markets, brokers may trade with their customers in the same transaction (simultaneous dual trading or SDT), in other markets, brokers are only allowed to trade after their customers in a separate transaction (consecutive dual trading or CDT). We show theoretic...

AI has long been applied to the problem of predicting financial markets. While AI researchers see financial forecasting as a fascinating challenge, predicting markets has powerful implications for financial economics – in particular the study of market efficiency. Recently economists have turned to AI for tools, using genetic algorithms to build trading strategies, and exploring the returns tho...

The purpose of this report is to review the evidence on the profitability of technical analysis. To achieve this purpose, the report comprehensively reviews survey, theoretical and empirical studies regarding technical trading strategies. We begin by overviewing survey studies that have directly investigated market participants’ experience and views on technical analysis. The survey literature ...

On line Knowledge e-marketplaces (Ke-markets) posses some special challenges for buyers and sellers. Unlike most markets, the product of exchange has some unique characteristics. It is mostly intangible, making it difficult for the buyer to assess and value beforehand. Its value is contextdependent, making it difficult for the supplier to price it in a transparent marketplace of multiple buyers...

represent its worthiness if it is completed before the deadline. For example, consider a stock trading system of an investment consulting company that allows customers to make their orders of the stocks, each customer may set a deadline for the completion of the order transaction. The commission of the company is a percent (say 3%) of the dealed stock price for each transaction. From the standp...