Author: 陳柏霖Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Option Pricing Using Machine Learning with Intraday Data of TAIEX Option
Author: 陳柏霖HCI in Business, Government and Organizations
Author: Fiona NahPublisher: Springer Nature
ISBN: 3031360494
Category : Computers
Languages : en
Pages : 442
Book Description
This two-volume set of HCIBGO 2023, constitutes the refereed proceedings of the 10h International Conference on HCI in Business, Government and Organizations, held as Part of the 24th International Conference, HCI International 2023, which took place in July 2023 in Copenhagen, Denmark.The total of 1578 papers and 396 posters included in the HCII 2023 proceedings volumes was carefully reviewed and selected from 7472 submissions. The HCIBGO 2023 proceedings focuses in topics such as artificial intelligence and machine learning, blockchain, service design, live streaming in electronic commerce, visualization, and workplace design.
Pricing Options with Futures-Style Margining
Author: Alan WhitePublisher: Routledge
ISBN: 113568782X
Category : Business & Economics
Languages : en
Pages : 225
Book Description
This book examines the applicability of a relatively new and powerful tool, genetic adaptive neural networks, to the field of option valuation. A genetic adaptive neural network model is developed to price option contracts with futures-style margining. This model is capable of estimating complex, non-linear relationships without having prior knowledge of the specific nature of the relationships. Traditional option pricing models require that the researcher or practitioner specify the distribution of the underlying asset. In addition, the methodology is able to easily accommodate additional inputs(something that cannot be preformed with existing models. Since 1973, options on stock have been traded on organized exchanges in the United States. An option on a stock gives the option owner the right to buy or sell the stock for a pre-set price.. Since the introduction of stock options, the options market has experienced tremendous growth and has spawned even more exotic types of derivative securities. Obviously, valuing these securities is an issue of great importance to investors and hedgers in the financial marketplace. Existing pricing models produce systematic pricing errors and new models have to be developed for options with differing characteristics. The genetic adaptive neural network is found to provide more accurate valuation than a traditional option pricing model when applied to the 3-month Eurodollar futures-option contract traded on the London International Financial Futures and Options Exchange.
Option Pricing Using Machine Learning Techniques
Author: Pavel PodkovyrovOption Pricing With Machine Learning
Author: Daniel Alexandre BlochPublisher:
ISBN:
Category :
Languages : en
Pages : 49
Book Description
An option pricing model is tied to its ability of capturing the dynamics of the underlying spot price process. Its misspecification will lead to pricing and hedging errors. Parametric pricing formula depends on the particular form of the dynamics of the underlying asset. For tractability reasons, some assumptions are made which are not consistent with the multifractal properties of market returns. On the other hand, non-parametric models such as neural networks use market data to estimate the implicit stochastic process driving the spot price and its relationship with contingent claims. When pricing multidimensional contingent claims, or even vanilla options with complex models, one must rely on numerical methods such as partial differential equations, numerical integration methods such as Fourier methods, or Monte Carlo simulations. Further, when calibrating financial models on market prices, a large number of model prices must be generated to fit the model parameters. Thus, one requires highly efficient computation methods which are fast and accurate. Neural networks with multiple hidden layers are universal interpolators with the ability of representing any smooth multidimentional function. As such, supervised learning is concerned with solving function estimation problems. The networks are decomposed into two separate phases, a training phase where the model is optimised off-line, and a testing phase where the model approximates the solution on-line. As a result, these methods can be used in finance in a fast and robust way for pricing exotic options as well as calibrating option prices in view of interpolating/extrapolating the volatility surface. They can also be used in risk management to fit options prices at the portfolio level in view of performing some credit risk analysis. We review some of the existing methods using neural networks for pricing market and model prices, present calibration, and introduce exotic option pricing. We discuss the feasibility of these methods, highlight problems, and propose alternative solutions.
PRICING OPTIONS WITH FUTURES-STYLE MARGINING
Author: ALAN. WHITEPublisher:
ISBN: 9781003249740
Category : BUSINESS & ECONOMICS
Languages : en
Pages :
Book Description
First Published in 2000. In 1973, options on stock became available on an organized exchange when the Chicago Board of Trade created the Chicago Board Options Exchange (CBOE). Options existed prior to this time, but the contracts lacked standardization and a central exchange. Since that introduction, the options market has experienced tremendous growth and has spawned even more exotic types of derivative securities. Although a great deal of work has been done in the area of option pricing, there still exists a number of problems related to estimating or predicting option prices. The purpose of this study is to utilize Genetic Adaptive Neural Networks (GANNs) to develop a method of pricing futures options with futures-style margining.
Advanced Options Trading
Author: Robert T. DaiglerPublisher: McGraw Hill Professional
ISBN: 9781557385529
Category : Business & Economics
Languages : en
Pages : 356
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
Tests of Option Pricing Models Using Transactions Data
Author: Mihir BhattacharyaAdvanced Option Pricing Models
Author: Jeffrey Owen KatzPublisher: McGraw-Hill
ISBN: 9780071626446
Category : Business & Economics
Languages : en
Pages : 452
Book Description
"Advanced Option Pricing Models" details specific conditions under which current option pricing models fail to provide accurate price estimates and then shows option traders how to construct improved models for better pricing in a wider range of market conditions. Model-building steps cover options pricing under conditional or marginal distributions, using polynomial approximations and "curve fitting," and compensating for mean reversion. The authors also develop effective prototype models that can be put to immediate use, with real-time examples of the models in action.
Basic Black-Scholes
Author: Timothy Falcon CrackPublisher:
ISBN: 9780995117396
Category :
Languages : en
Pages : 284
Book Description
[Note: eBook now available; see Amazon author page for details.] THE AUTHOR: Dr. Crack studied PhD-level option pricing at MIT and Harvard Business School, taught undergrad and MBA option pricing at Indiana University (winning many teaching awards), was an independent consultant to the New York Stock Exchange, worked as an asset management practitioner in London, and has traded options for over 20 years. This unique mix of learning, teaching, consulting, practice, and trading is reflected in every page. This revised 5th edition gives clear explanations of Black-Scholes option pricing theory, and discusses direct applications of the theory to trading. The presentation does not go far beyond basic Black-Scholes for three reasons: First, a novice need not go far beyond Black-Scholes to make money in the options markets; Second, all high-level option pricing theory is simply an extension of Black-Scholes; and Third, there already exist many books that look far beyond Black-Scholes without first laying the firm foundation given here. The trading advice does not go far beyond elementary call and put positions because more complex trades are simply combinations of these. UNIQUE SELLING POINTS -The basic intuition you need to trade options for the first time, or interview for an options job. -Honest advice about trading: there is no simple way to beat the markets, but if you have skill this advice can help make you money, and if you have no skill but still choose to trade, this advice can reduce your losses. -Full immersion treatment of transactions costs (T-costs). -Lessons from trading stated in simple terms. -Stylized facts about the markets (e.g., how to profit from reversals, when are T-costs highest/lowest during the trading day, implications of the market for corporate control, etc.). -How to apply European-style Black-Scholes pricing to the trading of American-style options. -Leverage through margin trading compared to leverage through options, including worked spreadsheet example. -Black-Scholes pricing code for the HP17B, HP19B, and HP12C. -Three downloadable spreadsheets. One allows the user to forecast T-costs for option positions using simple models. Another allows the user to explore option sensitivities including the Greeks. -Practitioner Bloomberg Terminal screenshots to aid learning. -Simple discussion of continuously-compounded returns. -Introduction to "paratrading" (trading stocks side-by-side with options to generate additional profit). -Unique "regrets" treatment of early exercise decisions and trade-offs for American-style calls and puts. -Unique discussion of put-call parity and option pricing. -How to calculate Black-Scholes in your head in 10 seconds (also in Heard on The Street: Quantitative Questions from Wall Street Job Interviews). -Special attention to arithmetic Brownian motion with general pricing formulae and comparisons to Bachelier (1900) and Black-Scholes. -Careful attention to the impact of dividends in analytical American option pricing. -Dimensional analysis and the adequation formula (relating FX call and FX put prices through transformed Black-Scholes formulae). -Intuitive review of risk-neutral pricing/probabilities and how and why these are related to physical pricing/probabilities. -Careful distinction between the early Merton (non-risk-neutral) hedging-type argument and later Cox-Ross/Harrison-Kreps risk-neutral pricing -Simple discussion of Monte-Carlo methods in science and option pricing. -Simple interpretations of the Black-Scholes formula and PDE and implications for trading. -Careful discussion of conditional probabilities as they relate to Black-Scholes. -Intuitive treatment of high-level topics e.g., bond-numeraire interpretation of Black-Scholes (where N(d2) is P(ITM)) versus the stock-numeraire interpretation (where N(d1) is P(ITM)). -Introduction and discussion of the risk-neutral probability that a European-style call or put option is ever in the money during its life.