Robust Regression and Sensitivity Analysis in Estimating Mutual Funds

Language: English

Published by Forgotten Books, 2024

1334538948 / 9781334538940

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Print on Demand. This book delves into the performance of mutual funds during a pivotal period in American financial history: 1945 to 1964. Challenging conventional wisdom of the time, the author investigates whether portfolio managers possessed superior forecasting capabilities, a question that continues to be debated today. By applying statistical techniques such as sensitivity analysis and robust regression, the author scrutinizes the performance of a sample of ten mutual funds. The book examines the impact of specific years, like 1962, on fund performance and identifies how various statistical approaches can influence the interpretation of data. Ultimately, the author presents a detailed analysis of mutual fund performance that highlights the need for robust statistical analysis and the complexities of interpreting data in the financial world. This book is a valuable resource for anyone interested in the history of investment management, the application of statistical methods to financial data, and the ongoing quest to understand the complexities of market behavior. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.

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Title
Robust Regression and Sensitivity Analysis in Estimating Mutual Funds
Author
Oded Berman, Eduardo Modiano
Publisher
Forgotten Books
Publication year
2024
Condition
New
Book Type
print-on-demand item
Binding
Paperback
Language
English
ISBN 10
1334538948
ISBN 13
9781334538940
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Forgotten Books

London, United Kingdom

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Forgotten Books’ Classic Reprint Series utilizes the latest technology to regenerate facsimiles of historically important writings. Careful attention has been made to accurately preserve the original format of each page whilst digitally enhancing the quality of the aged text.

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