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Future of option pricing: use of log logistic distribution instead of log normal distribution in Black Scholes model

机译:期权定价的未来:在Black scholes模型中使用对数逻辑分布而不是对数正态分布

摘要

Options are historically being priced using Black Scholes option pricing model and one of the prominent features of it is normal distribution. In this research paper I will calculate European call options using log logistic distribution instead of normal distribution. My argument is that a model with logistic distribution reflects better fit of option prices as compared to normal distribution. In this research paper I have used historic data on stocks, value European call options using both logistic and normal distribution and then finally compare the results in order to check the validity of my argument. What I have found is that European call options prices based on log logistic distribution better reflect stock prices on expiry date and Black Scholes Model based on normal distribution tend to overprice European call options. Another interesting fact is that before 1987 stock market crash, Black Scholes model valued options more correctly on average. But with time as the volatility of stocks increased and with more and more crashes normal distribution tend to underestimate the probability of default and thus generally overpriced options. At this point of time log logistic distribution is better serving the purpose but all depends on volatility of the stocks. If volatility levels further increase then fat tails of log logistic distribution have to become even fatter, that’s why keeping an eye on facts and incorporating all relevant variables in your model is very important. In finance there is never a universal truth every thing depends on what’s happening in the market.
机译:期权在历史上是使用Black Scholes期权定价模型定价的,其显着特征之一就是正态分布。在这篇研究论文中,我将使用对数逻辑分布而不是正态分布来计算欧式看涨期权。我的观点是,与正态分布相比,具有逻辑分布的模型反映出更好的期权价格拟合度。在这篇研究论文中,我使用了股票的历史数据,同时使用逻辑分布和正态分布对欧洲看涨期权进行了估值,然后最终对结果进行比较,以检验我的论点的有效性。我发现基于对数逻辑分布的欧洲看涨期权价格能更好地反映到期日的股票价格,而基于正态分布的布莱克斯科尔斯模型往往会使欧洲看涨期权定价过高。另一个有趣的事实是,在1987年股市崩盘之前,Black Scholes模型平均更正确地估计了期权的价值。但是随着时间的流逝,随着股票波动性的增加以及越来越多的崩盘,正态分布往往会低估违约的可能性,从而普遍低估期权的价格。在这个时间点上,对数物流分布更好地达到了目的,但是所有都取决于库存的波动性。如果波动率水平进一步提高,那么逻辑对数分布的尾巴就变得更加肥大,这就是为什么密切关注事实并将所有相关变量纳入模型非常重要的原因。在金融领域,从来没有一个普遍的真理,每一件事都取决于市场上正在发生的事情。

著录项

  • 作者

    Raja Ammar;

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  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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