Erscheinungsdatum: 08.05.2018, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Exploiting Investor Sentiment for Portfolio Optimization, Autor: Banholzer, Nicolas, Verlag: GRIN Verlag, Sprache: Englisch, Rubrik: Mathematik // Wahrscheinlichkeitstheorie, Seiten: 120, Informationen: Paperback, Gewicht: 184 gr, Verkäufer: averdo
Exploiting Investor Sentiment for Portfolio Optimization ab 44.99 € als Taschenbuch: Magisterarbeit. Aus dem Bereich: Bücher, Wissenschaft, Mathematik,
Exploiting Investor Sentiment for Portfolio Optimization ab 34.99 € als pdf eBook: . Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik,
Exploiting Investor Sentiment for Portfolio Optimization ab 44.99 EURO Magisterarbeit
Exploiting Investor Sentiment for Portfolio Optimization ab 34.99 EURO
The book introduces financial, economic and behavioral contributions to risk management. Chapters highlight the use of Pair Copula Constructions to portfolio optimization, the connection between risk models and transaction cost economics, and the herding behavior in future markets that provide new insights to diversification of portfolios, financial risk estimation, behavior of financial institutions and investor strategies.
Revision with unchanged content. This book deals with portfolio optimization under partial information. We consider an investor who can invest in a money market and a stock market. For our intended application a good model for the drift is of uttermost importance. We assume that the investor can only observe the stock prices but not the drift process, hence he has only partial information. The investor's objective is to maximize the expected utility of consumption and/or terminal wealth under partial information. We derive an explicit representation of the optimal consumption and trading strategies using Malliavin calculus. We show that the results apply to both classical models for the drift process, linear Gaussian dynamics and a continuous time Markov chain with finitely many states. We discuss several problems which might arise and how to overcome them, e.g. by dynamic risk constraints or non-constant volatility models. The results are applied to historical prices and yield promising results. The book is aimed at graduate students and researches interested in portfolio optimization under partial information.
Ports along the 7,517 odd Kilometer long peninsular coastline of India have suddenly become the cynosure of investor and public policy attention in India. Cumulative pressure for widespread policy-related reforms in the port sector coupled with growing investor interest in taking up port projects has been building up ever since the country embarked on the path of economic liberalization and opened its doors to forces of globalization. The pace of growth has particularly gathered momentum since the government invited private sector participation in development of port infrastructure, especially in designated major ports of the country in 1996. The story of India s efforts to modernize its port infrastructure and bring them on par with the international benchmarks arguably got a kick-start with the establishment of Nhava Sheva International Container Terminal (NSICT). Overall macro-economic development objectives of public policy rather than considerations of business and enterprise-level efficiency and optimization of port organizations have guided much of the understanding about the working of the ports in the country. The report covers the details of around 12 Ports situated in th
The Book is an attempt by the researcher to explore the various investment avenues available to the investors. A researcher has used various statistical and accounting techniques to achieve the objectives in order to identify the various avenues of investments and behavior of investors towards those avenues. In today's environment, it is prudent for any investor to look into the real interest earned as inflation is moving out of gear. It is imperative that the returns be higher without the risk of losing the principle in an investment. This necessitates for optimization of risk and reward.