Investment class (behavioral bias) - Assignment Example

In most of these studies, researchers have been critical in finding out whether the biases are intentional or unintentional and whether or not forecast bias take place to serve any good to forecasters and estimator. In the current paper, an existing model proposed by Knill, Minnick and Nejadmalayeri (2011, p 13) is examined with a new touch of behavioral bias to find out how behavioral bias such as overconfidence can be incorporated into the framework outlined by the researchers. Furthermore, the effects of experience and information asymmetry shall be analysed to find their impact on such forecast bias that take place.

The existing model The existing model or framework proposed by Knill, Minnick and Nejadmalayeri (2011, p. 87) is one that can best be described as integrated as it makes use of a number of components and aspects of general forecasting such as public information and private assessment. The model also considers common and idiosyncratic components of earnings forecast where there is the use of previously disclosed information. This means that the model is built on the ideologies of Bayesians since there is the dependence on existing forecasts as a means of guaranteeing positive deviations to purchase private signals from firms (Knill, Minnick and Nejadmalayeri, 2011, p. 4). For analysts who make use of this framework or model therefore, there are avenues of selecting several factors and characteristic phenomena in the assessment process, all in a bid to coming out with a rational forecast bias.

While some of these avenues may be directed at public information, others are directed at private information. Again, while some of the avenues tilt towards common components of earnings, others tilt towards idiosyncratic components of earnings; all in a bid to ensuring biases, even if they arise would give raise to a predetermined objective of the forecaster. How Behavioral bias can be incorporated into the model Already, it has been said that the existing model or framework is an integrated model.

This means that there are several aspects of theoretical and methodological forecasting that have been put together to make its use effective (Nutt, Easterwood and Easterwood, 1999, p. 45). Indeed, this general basis of the model gives it practical reasons why there could be major additions and incorporations into it. For example, it is proposed that behavioral bias can easily be fit into the framework to make it even more effective. In its, behavioral bias may be defined as that kind or type of bias that is founded on the basis of experience and personal connections and rhetoric (Mest and Plummer, 2003, p. 108). As against the original model where analysts forecast is based on uncertainty, building behavioral bias such as overconfidence would demand some appreciable levels of certainty.

Such levels of certainty would not come about to suggest that analysts would certainly get the results they anticipate or desire but that analysts would express certainty based on a previous experience that worked for a similar trend of earnings forecast. Indeed, as irrationality cannot be totally avoided, so would it be irrational to assume that exactly the same factors would prevail for a previous experi