In this paper, we compare three methods of estimating the volatility of daily SBP 100 Index for options. The implied volatility, calculated via the Black-Scholes model, is currently the most popular method of estimating volatility and is used by traders in the pricing of options. Historical volatility has been used to predict the implied volatility, but the estimates are poor predictors. A neural network for predicting volatility is shown to be far superior to the historical method
The theory of option pricing made a dramatic step forward when Black and Scholes published a centen...
Options are an important financial derivative for the investors to control their investment risks in...
In this paper, the performance of artificial neural networks in option pricing was analyzed and comp...
Currently the most popular method of estimating volatility is the implied volatility. It is calculat...
Volatility forecast is an important task in financial markets. It has held the most attention among ...
A great deal of research in the financial domain involves the development of models for pricing fina...
Part 3: Computational Intelligence and AlgorithmsInternational audienceIn this paper, a Computationa...
This thesis examines the application of neural networks in the context of option pricing. Throughout...
Author's OriginalAbility to forecast market variables is critical to analysts, economists and invest...
Volatility is a measurement of the risk of financial products. A stock will hit new highs and lows o...
The Black-Scholes model is the standard approach used for pricing financial options. However, althou...
Volatility is one of the most commonly used terms in the trading platform. In financial markets, vol...
A neural network model that processes financial input data is developed to estimate the market price...
Volatility is one of the major factor that causes uncertainty in short term stock market movement. E...
In this research, different models are used to construct volatility surfaces and these models are co...
The theory of option pricing made a dramatic step forward when Black and Scholes published a centen...
Options are an important financial derivative for the investors to control their investment risks in...
In this paper, the performance of artificial neural networks in option pricing was analyzed and comp...
Currently the most popular method of estimating volatility is the implied volatility. It is calculat...
Volatility forecast is an important task in financial markets. It has held the most attention among ...
A great deal of research in the financial domain involves the development of models for pricing fina...
Part 3: Computational Intelligence and AlgorithmsInternational audienceIn this paper, a Computationa...
This thesis examines the application of neural networks in the context of option pricing. Throughout...
Author's OriginalAbility to forecast market variables is critical to analysts, economists and invest...
Volatility is a measurement of the risk of financial products. A stock will hit new highs and lows o...
The Black-Scholes model is the standard approach used for pricing financial options. However, althou...
Volatility is one of the most commonly used terms in the trading platform. In financial markets, vol...
A neural network model that processes financial input data is developed to estimate the market price...
Volatility is one of the major factor that causes uncertainty in short term stock market movement. E...
In this research, different models are used to construct volatility surfaces and these models are co...
The theory of option pricing made a dramatic step forward when Black and Scholes published a centen...
Options are an important financial derivative for the investors to control their investment risks in...
In this paper, the performance of artificial neural networks in option pricing was analyzed and comp...