Forecasting Stock Price Volatility - An Indian Perspective


Book Description

The book threw light on the growth and development of the stock market and observed that the development of the stock market highly depends on volatility and forecasting is an important area of research in financial market. The book measured the extent of stock price volatility in select companies of Automobile, Infrastructure, Manufacturing, Pharmaceutical and Services and identified suitable model for forecasting the volatility of the share prices in India. It evaluated the comparative ability of different statistical and econometric forecasting models in the context of Indian Stocks. Three different competing models were considered for the book and for forecasting performance of different models two forecasting error statistics viz., Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) were used and the best model was suggested for each sector. The EGARCH model provides the most accurate forecast compared to other competing models in the book. The book also made a few observations which may help the investors to understand better about the stock market.







Modeling and Forecasting of Time-Varying Conditional Volatility of the Indian Stock Market


Book Description

Volatility forecasting is an important area of research in financial markets and immense effort has been expended in improving volatility models since better forecasts translate themselves into better pricing of options and better risk management. In this direction, the present paper attempts to model and forecast the volatility (conditional variance) of the S&P CNX Nifty index returns of Indian stock market, using daily data for the period from January 1, 1996 to January 29, 2010. The forecasting models that are considered in this study range from the simple GARCH(1, 1) model to relatively complex GARCH models, including the Exponential GARCH(1, 1) and Threshold GARCH(1, 1) models. Based on out-of-sample forecasts and a majority of evaluation measures, the results show that the asymmetric GARCH models do perform better in forecasting conditional variance of the Nifty returns rather than the symmetric GARCH model, confirming the presence of leverage effect. The findings are consistent with those of Banerjee and Sarkar (2006) that relatively asymmetric GARCH models are superior in forecasting the conditional variance of Indian stock market returns rather than the parsimonious symmetric GARCH models.




Stock Market Volatility


Book Description

Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel







Forecasting Financial Markets in India


Book Description

Papers presented at the Forecasting Financial Markets in India, held at Kharagpur during 29-31 December 2008.




How can I get started Investing in the Stock Market


Book Description

This book is well-researched by the author, in which he has shared the experience and knowledge of some very much experienced and renowned entities from stock market. We want that everybody should have the knowledge regarding the different aspects of stock market, which would encourage people to invest and earn without any fear. This book is just a step forward toward the knowledge of market.




Pricing Derivative Securities (2nd Edition)


Book Description

This book presents techniques for valuing derivative securities at a level suitable for practitioners, students in doctoral programs in economics and finance, and those in masters-level programs in financial mathematics and computational finance. It provides the necessary mathematical tools from analysis, probability theory, the theory of stochastic processes, and stochastic calculus, making extensive use of examples. It also covers pricing theory, with emphasis on martingale methods. The chapters are organized around the assumptions made about the dynamics of underlying price processes. Readers begin with simple, discrete-time models that require little mathematical sophistication, proceed to the basic Black-Scholes theory, and then advance to continuous-time models with multiple risk sources. The second edition takes account of the major developments in the field since 2000. New topics include the use of simulation to price American-style derivatives, a new one-step approach to pricing options by inverting characteristic functions, and models that allow jumps in volatility and Markov-driven changes in regime. The new chapter on interest-rate derivatives includes extensive coverage of the LIBOR market model and an introduction to the modeling of credit risk. As a supplement to the text, the book contains an accompanying CD-ROM with user-friendly FORTRAN, C++, and VBA program components.




Food Price Volatility and Its Implications for Food Security and Policy


Book Description

This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.




Threshold Models in Non-linear Time Series Analysis


Book Description

In the last two years or so, I was most fortunate in being given opportunities of lecturing on a new methodology to a variety of audiences in Britain, China, Finland, France and Spain. Despite my almost Confucian attitude of preferring talking (i.e. a transient record) to writing (i.e. a permanent record), the warm encouragement of friends has led to the ensuing notes. I am also only too conscious of the infancy of the methodology introduced in these notes. However, it is my sincere hope that exposure to a wider audience will accelerate its maturity. Readers are assumed to be familiar with the basic theory of time series analysis. The book by Professor M.B. Priestley (1981) may be used as a general reference. Chapter One is addressed to the general question: "why do we need non-linear time series models?" After describing some significant advantages of linear models, it singles out several major limitations of linearity. Of course, the selection reflects my personal view on the subject, which is only at its very beginning, although there does seem to be a general agreement in the literature that time irr'eversibility and limit cycles are among the most obvious.