Xem 1-20 trên 44 kết quả Forecasting trends
  • Technological innovations are key causal agents of surprise and disruption. These innovations, and the disruption they produce, have the potential to affect people and societies and therefore government policy, especially policy related to national security. Because the innovations can come from many sectors, they are difficult to predict and prepare for. The purpose of predicting technology is to minimize or eliminate this surprise.

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  • This chapter presents the following content: Quantitative approaches to forecasting, components of a time series, measures of forecast accuracy, smoothing methods, trend projection, trend and seasonal components, regression analysis, qualitative approaches.

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  • When you complete this chapter you should be able to: Understand the three time horizons and which models apply for each; explain when to use each of the four qualitative models; apply the naive, moving-average, exponential smoothing, and trend methods; compute three measures of forecast accuracy; develop seasonal indices; conduct a regression and correlation analysis; use a tracking signal.

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  • Time Series Forecasting – Part I presents about What is a Time Series? Components of Time Series, Evaluation Methods of Forecast, Smoothing Methods of Time Series, Time series models, Components of a time series, Trend component.

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  • Research problems and questions and how they relate to debates in Research Methods Recommended additional reading: Research Methods for Business Students, (Saunders, M, Lewis, P et al. 2007) Chapters 1 and 2 1.1 Chapter Overview 1.1.1 Learning Outcomes By the end of this chapter successful students will be able to: 1. Understand the learning and teaching strategy for this chapter 2. Distinguish business and management research from other kinds of research 3. Understand the issues relating to identifying and reformulating problems for research 4. Identify the key debates in research methods...

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  • Chapter 2 SINGLE-MARKET ANALYSIS. Trading With Tunnel Vision Can Put You on the Losing Side of a Trade. Analysis of the behavior of financial markets for the purpose of identifying and forecasting market direction has historically and traditionally been divided into two distinct schools: fundamental analysis and technical analysis.

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  • Chapter 4 TODAY’S MARKETS HAVE CHANGED. Why Trend Forecasting Beats Trend Following and How Traders Can Profit. Moving averages are one of the most popular technical indicators used to identify the trend direction of financial markets. Moving averages form the basis of a myriad of singlemarket trend following trading strategies

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  • Chapter 5 VANTAGEPOINT FORECASTS MARKET DIRECTION. How to Get a Sneak Preview of Where the Markets Are Going and How to Use This Information to Your Advantage. VantagePoint uses the pattern recognition capabilities of neural networks to analyze market data from each target market plus selected related markets in order to make forecasts for that target market.

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  • However, some scientists are working on earthquake precursors and forecasting research and this is a big challenge. Chapter in this book will be devoted to different aspects of the Earthquake Research and analysis, from theoretical advances for practical applications. The first two chapters for statistical analysis. About ten chapters in Part II focus on research precursors of earthquakes and forecasting. Some proposed new methods for early detection, as well as observations of earthquakes through the use of social sensors....

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  • In the present paper we use a model to forecast default probabilities and estimate default correlations based on the threshold model described above. The default probability measures the probability of an obligor’s assets falling short of a threshold. In addition, asset correlations are modeled as a measure of co-movement of the asset values of two obligors. Default correlations can then be derived analytically.

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  • Over $4 trillion is currently managed by equity mutual funds in the U.S., with roughly 90 percent invested in actively managed accounts. These mutual funds hold over 25 percent of the outstanding equity value of the average U.S. common stock. This high level of ownership makes it very unlikely that the equity fund industry as a whole is able to outperform the market by a large margin. However, several recent papers show some evidence of manager skills among subgroups of funds (see, for example, Gruber (1996)).

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  • Since the mid-1990s, the Indian financial system has been steadily if incrementally deregulated and more exposed to international financial markets. Its rapid transformation has been accompanied by strong economic growth, increased market robustness, and a considerable increase in efficiency. Reforms are continuing with the development of appropriate market regulation and an associated payment and settlement system, as well as greater integration into global financial markets.

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  • This study contains two objectives. The Örst is the identiÖcation of the public perception of monetary policy to establish a relationship between this perception, the behaviour of monetary authorities and some key economic variables. The second objective is the identiÖcation of the relationship between monetary policy and the term structure of interest rates. In particular, we are interested by the link with long-term interest rates. From this perspective, the works of Kozicki and Tinsley (1998, 2001a, 2001b) are interesting for two reasons.

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  • Liquid fuel consumption by medium- and heavy-duty vehicles (MHDVs) represents 26 percent of all U.S. liquid transportation fuels consumed and has increased more rapidly—in both absolute and percentage terms—than consumption by other sectors. In early recognition of these trends, which are forecast to continue until 2035 (DOE, EIA, 2009), the Energy Independence and Security Act of 2007 (EISA; Public Law 110-140, Dec. 19, 2007), Section 108, was passed, requiring the U.S. Department of Transportation (DOT), for the first time in history, to establish fuel economy standards for MHDVs.

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  • The Cisco® Visual Networking Index (VNI) Global Mobile Data Traffic Forecast Update is part of the comprehensive Cisco VNI Forecast, an ongoing initiative to track and forecast the impact of visual networking applications on global networks. This paper presents some of Cisco’s major global mobile data traffic projections and growth trends. Executive Summary The Mobile Network in 2011 and 2012 Global mobile data traffic grew 2.3-fold in 2011, more than doubling for the fourth year in a row. The 2011 mobile data traffic growth rate was higher than anticipated.

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  • We examine the effect of mandatory International Financial Reporting Standards (‘IFRS’) adoption on firms’ information environment. We find that after mandatory IFRS adoption consensus forecast errors decrease for firms that mandatorily adopt IFRS relative to forecast errors of other firms. We also find decreasing forecast errors for voluntary adopters, but this effect is smaller and not robust. Moreover, we show that the magnitude of the forecast errors decrease is associated with the firm-specific differences between local GAAP and IFRS.

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  • The next section discusses contractual use of accounting earnings and implications for the inclusion of cash flow forecasts in earnings and the relative abilities of earnings and cash flows to forecast future earnings. Section 3 models operating cash flows and the accounting process by which operating cash flow forecasts are incorporated in earnings.

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  • NATO is a political and military alliance that has been a suc- cessful example of an international structure, able to demon- strate both national and institutional strength. Formed for the collective defence against a common enemy, NATO did not dissolve when the Warsaw Pact disappeared, although its po- litical unity has begun to fade. The vulnerability – particularly of European citizens – that arises from a weak EU, weak national resolve and a weakened NATO is enormous when a combination of hostile actors and larger impersonal trends converge against Europe.

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  • Tetlock, Saar-Tsechansky and Macskassy (2008) describe a news-based automated trading strategy based on relative occurrence of negative words in firm specific financial news in an effort to predict firms’ accounting earnings and stock returns. A simplified bag of words representation was used to interpret textual data according to the relative frequency of negative words defined by the Harvard psychosocial dictionary. Key findings of Tetlock et al.

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  • Two other studies also examine the relation between earnings and the price response to splits; unfortunately, due to methodological differences their results provide no evidence regarding the issue raised by AHP. For example, McNichols and Dravid [19] find that split announcement-period abnormal returns are positively related to analysts' earnings forecast errors observed for the fiscal year-end that follows the announcement. At first glance, this result appears inconsistent with AHP. However, unless one knows the source of analysts' underestimation of post-split earnings, i.e.

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