In this thesis, I examine the factors associated with analysts’ voluntary practice of issuing cash flow forecasts and earnings forecasts on the same day. I draw on Hughes and Pae’s (2004) management partial disclosure equilibrium and predict how an analyst decides to issue a cash flow forecast revision along with and according to her bad news and good news earnings forecast revision. In particular, I predict that analysts strategically choose to supplement earnings forecasts with positive cash flow news when they deliver bad news earnings forecasts. Consistent with my prediction, I find that analysts are more likely to issue cash flow forecast revisions in the opposite direction to their earnings forecast revisions when they issue downward earnings forecast revisions than when they issue upward earnings forecast revisions. The results suggest that analysts may not make their decisions to issue cash flow forecasts as objectively as they ought to do in their role as independent information intermediaries. Rather, analyst decisions to issue cash flow forecasts are akin to managers’ strategic decisions to voluntarily disclose supplemental information to affect investors’ confidence in their primary news (earnings forecasts). / Thesis (Ph.D, Management) -- Queen's University, 2009-05-27 16:20:09.248

Thesis (M.S. - Hydrology and Water Resources)--University of Arizona. / Includes bibliographical references (leaves 131-136).

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p. 134-143).

Statistical post-processing techniques are used to remove systematic biases in modeled data. Models have shortcomings in the physical parameterization of weather events and have the inability to handle sub-grid phenomena successfully. The accuracy of forecasts interpolated to station points is limited by the horizontal resolution of the model. The magnitude of the bias at a station point depends upon geographical location and season. A neural network (NN) is a statistical downscaling method that seeks to model the linear or non-linear relationship between a set of different predictors and the predictand. NN’s have a training rule whereby the weights of connections between predictors and the predictand, are adjusted on the basis of the data. NN systems have been developed by using as input, different model variables from the NCEP Ensemble Prediction System (EPS) and Eta model to forecast minimum/maximum temperature and rainfall (Quantitative Precipitation Forecast (QPF) and Probability of Precipitation (PoP)), respectively. Results show some potential for improved NN forecasts over the forecast generated by the Numerical Weather Prediction (NWP) models. The implementation of a NN system can serve as a guidance tool in operational forecasting but with one difficulty that the NWP model has to be frozen, meaning no upgrades or changes on the model. / Dissertation (MSc)--University of Pretoria, 2009. / Geography, Geoinformatics and Meteorology / Unrestricted

Budget and budgeting have become more than just control mechanisms over the past few years. They are seen as functions for strategic planning and a method to implement or assist the strategy implementation. The research report investigated whether the budget is a strategic enabler though different contributors of the budgeting process.In previous research the dissatisfactions of the budgetary process were identified, but this excluded the impact that the budget process had on the strategic plans of an organisation. Other research was done on how strategy was done in organisations, but not which methods or instruments were used to implement strategy in organisations. This study investigated the experiences and the views of financial and non-financial senior managers and executives on the budgetary process factors that would influence the implementation of the strategic plan of the organisation. In order to understand the views of the participants, a qualitative research approach was taken in the form of semi-structured expert interviews.The findings reflect that some of these factors that were identified do contribute to the budgeting process and to the budget for being a strategic enabler in an organisation. The surprising findings were that the non-financial respondents did not believe that the use of balanced scorecards would attribute to the implementation of a strategy and that the respondents did not agree to the cycle time of the budgets proposed. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

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<p>Forecasting, cost management and pricing policies are topics which have beenwidely investigated over time. Due to a lack of scientific research about therelationships between each of those subjects, these methods have beeninvestigated in combination with their outcomes. The purpose of this work was todevelop a framework which can be used by managers who want to make adecision in either of the subjects mentioned before. By the use of a qualitative, interpretive research design, a literature review was performed which led to some interesting findings. Generally, it can be said that the methods are not related directly, although the outcomes are linked and can often be used as a criterion for the decision making process for the other methods.</p>

<p>Stock recommendations,frequently produced under time pressure, are susceptible to being the result of automatic and intuitive thinking. This is associated with using heuristics in decision-making which is studied by an entire school of research – the heuristics and bias approach. Heuristics of representativeness, availability and anchoring including associated biases as defined by Tversky and Kahneman provide the theoretical framework for the study. This study is aimed at extending the understanding of biases in general and cognitive biases with regard to stock recommendations. A total of thirty equity recommendations were analyzed. A t-test showed that more biases were present in the incorrect recommendations. Overconfidence, illusion of validity and anchoring were among the most frequently observed. The vast majority of recommendations were characterized by insensitivity to predictability indicating that forecasters are seemingly unaware of the difficulty of accurately predicting where the stock price is going to be within the next three to six months.</p>

Financial analysts are considered inefficient when they do not fully incorporate relevant information into their forecasts. In this dissertation, I investigate differences in the observable efficiency of analysts' earnings forecasts between firms that consistently meet or exceed analysts' earnings expectations and those that do not. I then analyze the extent to which the market incorporates this (in)efficiency into its earnings expectations. Consistent with my hypotheses, I find that analysts are relatively less efficient with respect to prior returns for firms that do not consistently meet expectations than for firms that do follow such a strategy, especially when prior returns convey bad news. However, forecast errors for firms that consistently meet expectations do not appear to be serially correlated to a greater extent than those for firms that do not consistently meet expectations. It is not clear whether the market considers such inefficiency when setting its own expectations. While the evidence suggests they may do so in the context of a shorter historical pattern of realized forecast errors, other evidence suggests they may not distinguish between predictable and surprise components of forecast error when the historical forecast error pattern is more established.