The Forecasting Performance on Option Trading Strategies under Different Models

The Forecasting Performance on Option Trading Strategies under Different Models PDF Author: 李正元
Publisher:
ISBN:
Category :
Languages : zh-CN
Pages :

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The Forecasting Performance on Option Trading Strategies under Different Models

The Forecasting Performance on Option Trading Strategies under Different Models PDF Author: 李正元
Publisher:
ISBN:
Category :
Languages : zh-CN
Pages :

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Book Description


Volatility Surface and Term Structure

Volatility Surface and Term Structure PDF Author: Kin Keung Lai
Publisher: Routledge
ISBN: 1135006989
Category : Business & Economics
Languages : en
Pages : 113

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Book Description
This book provides different financial models based on options to predict underlying asset price and design the risk hedging strategies. Authors of the book have made theoretical innovation to these models to enable the models to be applicable to real market. The book also introduces risk management and hedging strategies based on different criterions. These strategies provide practical guide for real option trading. This book studies the classical stochastic volatility and deterministic volatility models. For the former, the classical Heston model is integrated with volatility term structure. The correlation of Heston model is considered to be variable. For the latter, the local volatility model is improved from experience of financial practice. The improved local volatility surface is then used for price forecasting. VaR and CVaR are employed as standard criterions for risk management. The options trading strategies are also designed combining different types of options and they have been proven to be profitable in real market. This book is a combination of theory and practice. Users will find the applications of these financial models in real market to be effective and efficient.

Performance Evaluation of Neural Networks and GARCH Models for Forecasting Volatility and Option Strike Prices in a Bull Call Spread Strategy

Performance Evaluation of Neural Networks and GARCH Models for Forecasting Volatility and Option Strike Prices in a Bull Call Spread Strategy PDF Author: Ajitha Vejendla
Publisher:
ISBN:
Category : Neural networks (Computer science)
Languages : en
Pages : 76

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Book Description
"Investing in options has many advantages: they provide increased cost efficiency; they have the potential to deliver higher percentage returns due to increased leverage; and they offer a number of hedging and strategic alternatives. It is therefore worthwhile to investigate the option trading strategies that offer high payoffs. This thesis provides a performance evaluation of models used in the pricing of options for a bull spread options strategy. This strategy involves the purchase of a lower strike price option, along with the sale of a second higher strike price option. The strategy is highly profitable when the price of the underlying primitive reaches the second out-of-the-money strike price before the expiration date of the options, but no further. The challenge lies in choosing the optimal out-of-the-money option strike price. The option exercise price, past primitive price jumps, and primitive volatility shifts are the important factors that are to be analyzed. Since the understanding of the primitive volatility is important, this thesis applies performance measures to compare implied volatility and historical volatility using various neural network models. GARCH implied volatility values are provided as input to both the FNN and RNN models, generating a next day forecast for implied volatility. The performance of implied volatility as a volatility measurement is compared against the historical volatility. Based on these results, the neural network models, along with the GARCH models, are further evaluated for their forecasting ability of option strike prices in a bull call spread strategy. The purpose of the research is to see the performance of different neural network models for different stock options and volatility periods. The trading profitability of these models gives us an indication of the performance ability of the FNN, RNN and GARCH models"--Abstract, leaf iv.

Advanced Options Trading

Advanced Options Trading PDF Author: Robert T. Daigler
Publisher: McGraw Hill Professional
ISBN: 9781557385529
Category : Business & Economics
Languages : en
Pages : 356

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Book Description
This book thoroughly explains the options markets. Moreover, the work contains several unique features, including computer codes to calculate changes in options properties and a historic evaluation of options strategies and pricing theories. As a result, traders learn what works and what doesn't wor

Option Income Strategy Trade Filters

Option Income Strategy Trade Filters PDF Author: Brian Johnson
Publisher:
ISBN: 9780996182317
Category : Investment analysis
Languages : en
Pages : 110

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Book Description
Brian Johnson, a professional investment manager with many years of trading and teaching experience, is the author of two pioneering books on options: 1) Option Strategy Risk / Return Ratios: A Revolutionary New Approach to Optimizing, Adjusting, and Trading Any Option Income Strategy, and 2) Exploiting Earnings Volatility: An Innovative New Approach to Evaluating, Optimizing, and Trading Option Strategies to Profit from Earnings Announcements. His new in-depth (100+ page) article, Option Income Strategy Trade Filters, represents the culmination of years of research into developing a systematic framework for optimizing the timing of Option Income Strategy (OIS) trades. His research was based on the analysis of 15,434 OIS trades, each with a comprehensive set of objective, tradable entry and exit rules. The results for each of the 15,000 plus trades were scaled to a constant dollar amount at risk, to ensure all trades were equally-weighted when calculating the performance metrics. The back-test results were all based on actual option prices and are summarized in this article for a selection of back-testing filters, making this one of the most comprehensive studies of option income strategy results ever published. The results of over 100 different back-tests are provided. The OIS strategy back-test results for ten different types of filters are evaluated in this article, including unique filter combinations that delivered exceptional results. A custom market-edge hypothesis was created in advance for each filter type, which was then used to evaluate the filter-specific results. This critical step helped identify robust, exploitable relationships, rather than spurious correlations. Several of the resulting filters generated over 95% winning trades, with average returns of over six percent per trade (including losing trades). The ratios of cumulative gains to cumulative losses were over 20 to 1 for a few of the best performing filters. Option Income Strategy Trade Filters is written in a clear, understandable fashion and provides detailed examples of how to create and test market-edge hypotheses using the recent advances in back-testing software. Very few formulas were included. As a result, the material in the article should be accessible to all option traders. Useful for traders with a wide range of option trading experience, this practical guide begins with a detailed review of option income strategies, including basic examples that provide the requisite foundation for subsequent chapters. Portions of this crucial background material also appeared in Brian Johnson's first book: Option Strategy Risk / Return Ratios. Chapter 2 includes a comprehensive description of the option income strategy, position model, and trade plan used to generate the back-test data. Every entry and exit rule is explained in detail, including actual graphical examples. The performance metrics for the 15,434 unfiltered OIS trades are summarized at the end of this chapter, which provide a performance benchmark for evaluating the effectiveness of the trade filters introduced in the next three chapters. The trade filters are grouped by classification, with a chapter devoted to each class or type. The market-edge hypotheses and corresponding results for trend filters are analyzed in Chapter 3. Unlike trend filters, discriminating filters exclude an increasing percentage of trades as the filter condition or threshold becomes more extreme or restrictive. The discriminating filter market-edge hypotheses and results are analyzed in Chapter 4. Chapter 5 is devoted entirely to a very unique and powerful example of a discriminating filter: the OIS Universal Filter (OISUF). The final chapter examines practical considerations and prospective applications of trade filters and other resources in managing option income strategies in actual market conditions.

Forecasting Expected Returns in the Financial Markets

Forecasting Expected Returns in the Financial Markets PDF Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080550673
Category : Business & Economics
Languages : en
Pages : 299

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Book Description
Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques. *Forecasting expected returns is an essential aspect of finance and highly technical *The first collection of papers to present new and developing techniques *International authors present both academic and practitioner perspectives

Trading on Corporate Earnings News

Trading on Corporate Earnings News PDF Author: John Shon
Publisher: FT Press
ISBN: 0132615851
Category : Business & Economics
Languages : en
Pages : 225

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Book Description
Profit from earnings announcements, by taking targeted, short-term option positions explicitly timed to exploit them! Based on rigorous research and huge data sets, this book identifies the specific earnings-announcement trades most likely to yield profits, and teaches how to make these trades—in plain English, with real examples! Trading on Corporate Earnings News is the first practical, hands-on guide to profiting from earnings announcements. Writing for investors and traders at all experience levels, the authors show how to take targeted, short-term option positions that are explicitly timed to exploit the information in companies’ quarterly earnings announcements. They first present powerful findings of cutting-edge studies that have examined market reactions to quarterly earnings announcements, regularities of earnings surprises, and option trading around corporate events. Drawing on enormous data sets, they identify the types of earnings-announcement trades most likely to yield profits, based on the predictable impacts of variables such as firm size, visibility, past performance, analyst coverage, forecast dispersion, volatility, and the impact of restructurings and acquisitions. Next, they provide real examples of individual stocks–and, in some cases, conduct large sample tests–to guide investors in taking advantage of these documented regularities. Finally, they discuss crucial nuances and pitfalls that can powerfully impact performance.

Forecasting Volatility in the Financial Markets

Forecasting Volatility in the Financial Markets PDF Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080471420
Category : Business & Economics
Languages : en
Pages : 428

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Book Description
Forecasting Volatility in the Financial Markets, Third Edition assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey Leading thinkers present newest research on volatility forecasting International authors cover a broad array of subjects related to volatility forecasting Assumes basic knowledge of volatility, financial mathematics, and modelling

Forecasting Volatility in the Financial Markets

Forecasting Volatility in the Financial Markets PDF Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080494978
Category : Business & Economics
Languages : en
Pages : 417

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Book Description
'Forecasting Volatility in the Financial Markets' assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modelling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.The editors have brought together a set of contributors that give the reader a firm grounding in relevant theory and research and an insight into the cutting edge techniques applied in this field of the financial markets.This book is of particular relevance to anyone who wants to understand dynamic areas of the financial markets.* Traders will profit by learning to arbitrage opportunities and modify their strategies to account for volatility.* Investment managers will be able to enhance their asset allocation strategies with an improved understanding of likely risks and returns.* Risk managers will understand how to improve their measurement systems and forecasts, enhancing their risk management models and controls.* Derivative specialists will gain an in-depth understanding of volatility that they can use to improve their pricing models.* Students and academics will find the collection of papers an invaluable overview of this field. This book is of particular relevance to those wanting to understand the dynamic areas of volatility modeling and forecasting of the financial marketsProvides the latest research and techniques for Traders, Investment Managers, Risk Managers and Derivative Specialists wishing to manage their downside risk exposure Current research on the key forecasting methods to use in risk management, including two new chapters

The Forecasting Performance of Stock Options Prices in a Thin Market

The Forecasting Performance of Stock Options Prices in a Thin Market PDF Author: Gordon T. Gemmill
Publisher:
ISBN:
Category : Options (Finance)
Languages : en
Pages : 12

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Book Description