What if an AI didn’t just mimic your mind, but could predict your every next move? Researchers at Helmholtz Munich have ...

A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA)— that ...

Behavioral scientists have been trying to uncover the patterns that humans follow when making decisions for decades. The ...

Learn how enterprises evaluate open versus closed AI models to optimize costs, security, and performance across different business use cases.

The Full Model column of Table 3 presents the empirical results of the negative binomial regression model. From the results of the Negative Binomial Regression model, it is evident that after ...

How implied volatility works in equity options trading Implied volatility is a critical component in options pricing models and trading strategies. It's calculated using complex mathematical formulas ...

The binomial options pricing model, developed by John Cox, Stephen Ross, and Mark Rubinstein in 1979, offers a different approach that addresses some of Black-Scholes' limitations.

The pricer is able to price Vanilla (European and American) and Exotic (Asian, Barrier, Lookback) options using Black Scholes formula, Binomial/Trinomial trees, and Monte Carlo simulations. Pricing ...

The binomial option pricing model presents two advantages for option sellers over the Black-Scholes model. The first is its simplicity, which allows for fewer errors in the commercial application.

Taking the Knightian uncertainty of financial market into consideration, the randomness and fuzziness of stock price should been evaluated by both probabilistic expectation and fuzzy expectation. We ...