This book focuses on the impact of high-frequency data in forecasting market volatility and options price. New technologies have created opportunities to obtain better, faster, and more efficient datasets to explore financial market phenomena at the most acceptable data levels. It provides reliable intraday data supporting financial investment decisions across different assets classes and instruments consisting of commodities, derivatives, equities, fixed income and foreign exchange.
This book emphasises four key areas, (1) estimating intraday implied volatility using ultra-high frequency (5-minutes frequency) currency options to capture traders' trading behaviour, (2) computing realised volatility based on 5-minute frequency currency price to obtain speculators' speculation attitude, (3) examining the ability of implied volatility to subsume market information through forecasting realised volatility and (4) evaluating the predictive power of implied volatilityfor pricing currency options. This is a must-read for academics and professionals who want to improve their skills and outcomes in trading options.

Explains how to handle big data in trading Discusses the role of data analytics in capital markets? Includes sample high-frequency datasets

Autorentext

Dr. Thi Le is a Research Associate at Murdoch University, Australia. She served both industries and academia with ten years of teaching experiences in Finance and Accounting and working experiences in several industry projects. Her research interests include derivatives, financial forecasting, fintech, supply chain, and accounting framework. She has published many research papers in prominent international journals, conferences and received a number of industry grants.

Inhalt
Chapter 1. Introduction of Thesis.- Chapter 2. Literature Review.- Chapter 3. Methodology and Data.- Chapter 4. Implied Volatility Forecasting Realized Volatility.- Chapter 5. Implied Volatility Estimating Currency Options Price.- Chapter 6. Conclusion of Thesis.