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The purpose of the study is to investigate, synthesize and critically evaluate empirical research findings on the behavioral traits of fund managers from 1994 to 2024. The ultimate goal is to provide a unified body of literature on three broad topics: first, fund managers' demographic and professional characteristics, such as age, gender, level of education and years of industry experience; second, fund managers' social and political connections; and third, fund managers' behavioral biases that lead to irrational investment decisions.

The relevant papers from selected journals were discovered and manually validated using the Scopus database. From 317 retrieved documents, 57 relevant articles were chosen and analyzed after the forward and backward search of the existing articles.

This paper presents a categorized summary of behavioral factors that have gained a foothold in influencing the behavior of fund managers in fund management research, with several studies demonstrating their significance leading to improved prediction and model precision, as this review indicates. In addition, the study summarized the contributions of prior empirical studies within the aforementioned three major categories and illustrated their consequences.

The present study contributes to the understanding of the effects of behavioral finance theories on fund managers by providing meaningful explanations of their behavioral traits based on empirical evidence and existing trends and knowledge gaps, both of which can influence the future direction of research.

This paper aims to present the estimation of the output voltage of metal oxide semiconductor field effect transistor (MOSFET) using the extended Kalman filter (EKF) method.

The method uses EKF for MOSFET output voltage estimation. To implement the EKF method, the state space model has been obtained using Kirchhoff’s current law and Enz-Krummenacher-Vittoz model of the MOSFET circuit.

The proposed method can be used for any mode of MOSFET operation besides near the quiescent point region. The nonlinearity that occurs in the saturation region of MOSFET can also be considered in the proposed method. The proposed method can also be used for a large input signal. Though Kalman filter can be used for the small amplitude input signal, it results in inaccurate estimation due to the linearization of the nonlinear system.

The method is able to track the parameters when they are slowly changing with time.

The proposed method presents maximal precision of simulation as the maximal precision of simulation requires modeling of the circuit in terms of device parameters and circuit elements.