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Earnings capacity is a key element in the stock market valuation of firms. Higher sustainable profits should lead to higher dividend payments and boost firms’ equity values. We use past earnings as a proxy for future cash flows and hence for payments to shareholders. To the extent that bank managers smooth earnings, they also increase the correlation between reported earnings in consecutive years and augment the salience of this driver. We postulate that these three drivers affect bank equity performance indirectly. Rather than treating them as independent sources of systematic risk, we assume that they affect bank share. | Daily Stock Market Forecast from Textual Web Data B. Wuthrich V. Cho S. Leung D. Permunetilleke K. Sankaran J. Zhang W. Lam The Hong Kong University of Science and Technology Clear Water Bay Hong Kong The Chinese University Shatin Hong Kong ABSTRACT Data mining can be described as making better use of data . Every human being is increasingly faced with unmanageable amounts of data hence data mining or knowledge discovery apparently affects all of us. It is therefore recognized as one of the key research areas. Ideally we would like to develop techniques for making better use of any kind of data for any purpose . However we argue that this goal is too demanding yet. It may sometimes be more promising to develop techniques applicable to specific data and with a specific goal in mind. In this paper we describe such an application driven data mining system. Our aim is to predict stock markets using information contained in articles published on the Web. Mostly textual articles appearing in the leading and influential financial newspapers are taken as input. From those articles the daily closing values of major stock market indices in Asia Europe and America are predicted. Textual statements contain not only the effect e.g. the stocks plummet but also why it happened e.g. because of weakness in the dollar and consequently a weakening of the treasury bonds . Exploiting textual information in addition to numeric time series data increases the quality of the input. Hence improved predictions are expected. The forecasts are available real-time via www.cs.ust.hk beat Predict daily at 7 45 am Hong Kong time. Hence all predictions are ready before Tokyo Hong Kong and Singapore the major Asian markets start trading. The system s accuracy for this tremendously difficult but also extremely challenging application is highly promising. 1. INTRODUCTION These days more and more crucial and commercially valuable information becomes available on the World Wide Web. Also financial .
