A Comparative Study of Support Vector Machine and Artificial Neural Network for Option Price Prediction

Option pricing has become one of the quite important parts of the financial market. As the market is always dynamic, it is really difficult to predict the option price accurately. For this reason, various machine learning techniques have been designed and developed to deal with the problem of predicting the future trend of option price. In this paper, we compare the effectiveness of Support Vector Machine (SVM) and Artificial Neural Network (ANN) models for the prediction of option price. Both models are tested with a benchmark publicly available dataset namely SPY option price-2015 in both testing and training phases. The converted data through Principal Component Analysis (PCA) is used in both models to achieve better prediction accuracy. On the other hand, the entire dataset is partitioned into two groups of training (70%) and test sets (30%) to avoid overfitting problem. The outcomes of the SVM model are compared with those of the ANN model based on the root mean square errors (RMSE). It is demonstrated by the experimental results that the ANN model performs better than the SVM model, and the predicted option prices are in good agreement with the corresponding actual option prices.

A Full Asymptotic Series of European Call Option Prices in the SABR Model with Beta = 1

We develop two new pricing formulae for European options. The purpose of these formulae is to better understand the impact of each term of the model, as well as improve the speed of the calculations. We consider the SABR model (with β=1) of stochastic volatility, which we analyze by tools from Malliavin Calculus. We follow the approach of Alòs et al. (2006) who showed that under stochastic volatility framework, the option prices can be written as the sum of the classic Hull-White (1987) term and a correction due to correlation. We derive the Hull-White term, by using the conditional density of the average volatility, and write it as a two-dimensional integral. For the correction part, we use two different approaches. Both approaches rely on the pairing of the exponential formula developed by Jin, Peng, and Schellhorn (2016) with analytical calculations. The first approach, which we call “Dyson series on the return’s idiosyncratic noise” yields a complete series expansion but necessitates the calculation of a 7-dimensional integral. Two of these dimensions come from the use of Yor’s (1992) formula for the joint density of a Brownian motion and the time-integral of geometric Brownian motion. The second approach, which we call “Dyson series on the common noise” necessitates the calculation of only a one-dimensional integral, but the formula is more complex. This research consisted of both analytical derivations and numerical calculations. The latter show that our formulae are in general more exact, yet more time-consuming to calculate, than the first order expansion of Hagan et al. (2002).

The SABR Model: Explicit Formulae of the Moments of the Forward Prices/Rates Variable and Series Expansions of the Transition Probability Density and of the Option Prices

The SABR stochastic volatility model with β-volatility β ? (0,1) and an absorbing barrier in zero imposed to the forward prices/rates stochastic process is studied. The presence of (possibly) nonzero correlation between the stochastic differentials that appear on the right hand side of the model equations is considered. A series expansion of the transition probability density function of the model in powers of the correlation coefficient of these stochastic differentials is presented. Explicit formulae for the first three terms of this expansion are derived. These formulae are integrals of known integrands. The zero-th order term of the expansion is a new integral formula containing only elementary functions of the transition probability density function of the SABR model when the correlation coefficient is zero. The expansion is deduced from the final value problem for the backward Kolmogorov equation satisfied by the transition probability density function. Each term of the expansion is defined as the solution of a final value problem for a partial differential equation. The integral formulae that give the solutions of these final value problems are based on the Hankel and on the Kontorovich-Lebedev transforms. From the series expansion of the probability density function we deduce the corresponding expansions of the European call and put option prices. Moreover we deduce closed form formulae for the moments of the forward prices/rates variable. The moment formulae obtained do not involve integrals or series expansions and are expressed using only elementary functions. The option pricing formulae are used to study synthetic and real data. In particular we study a time series (of real data) of futures prices of the EUR/USD currency's exchange rate and of the corresponding option prices. The website: http://www.econ.univpm.it/recchioni/finance/w18 contains material including animations, an interactive application and an app that helps the understanding of the paper. A more general reference to the work of the authors and of their coauthors in mathematical finance is the website:http://www.econ.univpm.it/recchioni/finance.

Critical Exercise Price for American Floating Strike Lookback Option in a Mixed Jump-Diffusion Model

This paper studies the critical exercise price of American floating strike lookback options under the mixed jump-diffusion model. By using It formula and Wick-It-Skorohod integral, a new market pricing model established under the environment of mixed jumpdiffusion fractional Brownian motion. The fundamental solutions of stochastic parabolic partial differential equations are estimated under the condition of Merton assumptions. The explicit integral representation of early exercise premium and the critical exercise price are also given, then the American floating strike lookback options factorization formula is obtained, the results is generalized the classical Black-Scholes market pricing model.

The Barone-Adesi Whaley Formula to Price American Options Revisited

This paper presents a method to solve the American option pricing problem in the Black Scholes framework that generalizes the Barone-Adesi, Whaley method [1]. An auxiliary parameter is introduced in the American option pricing problem. Power series expansions in this parameter of the option price and of the corresponding free boundary are derived. These series expansions have the Baroni-Adesi, Whaley solution of the American option pricing problem as zero-th order term. The coefficients of the option price series are explicit formulae. The partial sums of the free boundary series are determined solving numerically nonlinear equations that depend from the time variable as a parameter. Numerical experiments suggest that the series expansions derived are convergent. The evaluation of the truncated series expansions on a grid of values of the independent variables is easily parallelizable. The cost of computing the n-th order truncated series expansions is approximately proportional to n as n goes to infinity. The results obtained on a set of test problems with the first and second order approximations deduced from the previous series expansions outperform in accuracy and/or in computational cost the results obtained with several alternative methods to solve the American option pricing problem [1]-[3]. For example when we consider options with maturity time between three and ten years and positive cost of carrying parameter (i.e. when the continuous dividend yield is smaller than the risk free interest rate) the second order approximation of the free boundary obtained truncating the series expansions improves substantially the Barone-Adesi, Whaley free boundary [1]. The website: http://www.econ.univpm.it/recchioni/finance/w20 contains material including animations, an interactive application and an app that helps the understanding of the paper. A general reference to the work of the authors and of their coauthors in mathematical finance is the website: http://www.econ.univpm.it/recchioni/finance.

Pricing European Options Based on a Logarithmic Truncated t-Distribution

The t-distribution has a “fat tail” feature, which is more suitable than the normal probability density function to describe the distribution characteristics of return on assets. The difficulty of using t-distribution to price European options is that a fat tail can lead to a deviation in one integral required for option pricing. We use a distribution called logarithmic truncated t-distribution to price European options. A risk neutral valuation method was used to obtain a European option pricing model with logarithmic truncated t-distribution.

考虑国际金融风险影响的上证50ETF期权定价研究

近年来如何刻画国际金融风险对中国市场的影响,成为学术界的热门热点之一。已有文献大多集中于研究国际股票市场之间的风险溢出效应,较少关注国际股票市场对中国期权市场的风险外溢效应。本文将标普500ETF走势嵌入上证50ETF的收益率过程,构建IFR_BS模型(BS Model with the Impact of International Financial Risk);然后应用特征函数微扰法和Fourier-Cosine定价方法,推导出该模型下欧式期权的近似解析定价公式。数值实验和实证结果表明:(1)IFR_BS模型可以较好地刻画上证50ETF收益率分布的“尖峰”、“肥尾”和“有偏”等统计特征。(2)考虑国际金融风险溢价的IFR_BS模型下的期权定价公式,可以解决BS模型对短到期期权尤其是短到期深度OTM期权估值不足的问题。

可变风险溢价结构下跳扩散模型的期权定价

风险溢价结构是真实测度与风险中性测度间的纽带,能够帮助提取投资者的风险偏好特征。本文针对跳扩散模型构建了灵活的风险溢价形式,允许期权市场隐含信息参与校准跳跃风险的市场价格,进而研究存在跳跃情形下的期权定价,并探索市场风险溢价结构。数值分析和实证研究表明,可变风险溢价结构有助于准确刻画市场定价核曲线,且市场风险溢价结构具有明显的时变特征,跳跃风险溢价能够较好解释隐含波动率曲面。此外,跳扩散模型的可变风险溢价结构在样本内外都具有明显的期权定价优势。考虑了不同样本长度、定价方法、定价区间以及期权产品后,以上结论均是稳健的。本研究有助于系统了解不同市场风险溢价结构与定价规律,有利于深入探索跳跃风险溢价补偿机制。

基于“分解-重组-预测-集成”模式的Heston期权定价模型

精准合理地期权定价对于改善市场流动性、优化投资者结构、稳定金融市场拥有重要意义。本文提出了一种结合“分解-重组-预测-集成”思想的Heston期权定价模型,该模型利用Heston模型进行初始定价,通过自适应噪声完全集合经验模态分解(CEEMDAN)对定价误差进行分解与重构,获得高频项、低频项及趋势项,然后使用门控循环单元(GRU)估计高频项及低频项,使用差分整合移动平均自回归(ARIMA)估计趋势项,所有估计值集成汇总得到定价误差估计值,最后使用定价误差估计值对Heston模型的初始定价结果进行修正后获得最终定价结果。使用华夏上证50ETF、华泰柏瑞沪深300ETF和嘉实沪深300ETF期权数据验证模型,实证结果显示,在模型结构更加简单的基础上,本文提出模型的精度普遍优于基准模型。

基于前景理论框架和Heston模型的行为期权定价

行为期权定价是当前国际金融领域的热门研究主题之一。虽然随机波动率模型已成为国际衍生品定价领域的标准模型,但该模型对短到期期权(尤其是虚值期权)的定价仍不准确,其原因之一是传统的期权定价方法忽略了现实市场中的非理性心理和行为因素。针对上述问题,本文运用前景理论期权定价框架,引入价值函数来刻画投资者面对收益与损失的前景价值判断,引入决策权重函数来修正Heston随机波动率模型刻画的资产价格路径的概率密度函数,将期权合约签订与交割的现金流视为分散的心理账户情形,在市场均衡条件下推导出Heston模型下欧氏行为期权的定价公式。上证50ETF期权的实证结果表明:考虑了前景理论的Heston随机波动率模型,能显著地提升短到期虚值期权的定价准确度;参数校正结果发现,定价性能的提升要归因于Heston模型中纳入的表征非理性心理与情绪的行为参数;相对而言,投资者对实值期权的风险态度偏中性,因此行为参数对其定价精度的提升有限。

收益率服从q-高斯分布的二叉树期权定价模型及实证分析

以股票价格收益率服从q-高斯分布为基础,使用二叉树定价方法,得到收益率符合q-高斯分布的新型二叉树期权定价模型及数值解法;以部分2023年中证1000和上证50的股指期权价格数据为样本,利用MATLAB进行参数估计、模拟计算股指期权看涨期权价格,并进行图像拟合;最后,对一般二叉树模型、新型二叉树模型所求价格与实际期权价格进行比较,得出收益率服从q-高斯分布的新型二叉树期权定价模型更优的结论,为收益率具有尖峰厚尾特征的相关股指期权定价问题提供了一定的方法和依据.

随机利率模型下信用价差期权的保险精算定价及其应用

将应用信用价差期权来规避企业债券的信用价差风险.首先运用保险精算方法,在金融市场上的无风险利率具有随机波动的前提下,建立信用价差期权模型,利用保险精算定价方法得到信用价差期权的定价公式.然后结合企业债券的信用价差风险,设计信用价差期权,利用已给出相应期权公式进行风险管理.

引入隔夜信息的期权定价模型研究

已有的实证研究表明,隔夜信息在提高波动率预测准确性、解释金融市场异象方面有重要的作用。然而,关于隔夜信息对期权市场影响的研究,特别是对期权定价效果作用的研究仍数量有限。为了同时刻画由日对数收益率进行分解后得到的日内和隔夜收益率过程,本文提出了二元Heston-Nandi GARCH模型,并推导出了具有显式解的期权定价公式。基于对上证50ETF期权的实证研究,本文对比了二元Heston-Nandi GARCH模型和传统一元模型的定价效果。样本内和样本外的实证结果均表明,在日收益率中区分日内和隔夜收益率,能够有效降低模型的定价误差。

基于FFT与Transformer算法的混合期权定价模型研究

为解决经典期权定价模型与实际价格数据偏差较大的问题,选取BS期权定价模型,采用快速傅里叶变换(Fast Fourier Transform,FFT)结合Transformer多头注意力机制深度学习算法,对上证300ETF期权与上海期货交易所黄金期权数据进行实证研究,通过改进的Transformer算法对基于FFT算法的期权定价模型与实际金融市场期权价格数据之间的残差值进行二次训练。结果表明,与其他算法(BS、FFT-BS)及其他混合算法(FFT-BS+ARIMA、FFT-BS+LSTM)模型相比,基于FFT-BS+Transformer的算法在R^(2)、MSE、NRMSE以及MAE等统计指标上均有很好的表现,且针对不同波动、不同品种的期权,该混合算法模型均取得了较好的结果。将改进后的Transformer算法应用到期权定价中,可弥补经典期权定价模型的不足,提供了更加精确的期权定价模型。

基于DCF-BS模型的可衍生电影版权投资价值评估——以英皇影业投资《古董局中局》为例

针对可衍生电影版权投资收益的不确定性,本文运用期权定价方法给出衍生品追加投资选择权价值评估的BS模型,进而给出可衍生电影版权投资价值评估的DCF-BS模型。将模型应用于英皇影业对《古董局中局》的投资价值评估案例,以检验模型有效性。结果表明:DCF-BS模型相对单纯的DCF模型不仅适用于可衍生电影版权价值评估,而且估值结果并不是传统的DCF模型估值与BS模型估值的简单相加,而是两种模型相互融合的结果,即估值结果对票房收益的高度不确定性表现出较低的敏感性,对促进可衍生电影的市场化投资具有重要意义。

European option pricing model in a stochastic and fuzzy environment

The primary goal of this paper is to price European options in the Merton＇s frame- work with underlying assets following jump-diffusion using fuzzy set theory. Owing to the vague fluctuation of the real financial market, the average jump rate and jump sizes cannot be recorded or collected accurately. So the main idea of this paper is to model the rate as a triangular fuzzy number and jump sizes as fuzzy random variables and use the property of fuzzy set to deduce two different jump-diffusion models underlying principle of rational expectations equilibrium price. Unlike many conventional models, the European option price will now turn into a fuzzy number. One of the major advantages of this model is that it allows investors to choose a reasonable European option price under an acceptable belief degree. The empirical results will serve as useful feedback information for improvements on the proposed model.

基于4/2-CIR模型的欧式期权定价及实证研究

在假设波动率服从均值回复过程的条件下,探讨了具有随机利率的4/2随机波动率模型下的期权定价问题。首先,基于4/2随机波动率模型提出4/2-CIR随机混合模型,并利用快速傅里叶变换方法推出4/2-CIR随机混合模型下的欧式期权定价公式。其次,通过数值分析的方法,对比4/2随机波动率模型与4/2-CIR随机混合模型的定价结果,分析新模型的定价性能,并运用交叉验证法,对模型中参数进行敏感性分析。最后,选取上证50ETF期权数据进行实证分析。研究发现:随机利率对模型定价结果具有显著影响;期权价格对利率的波动率参数不敏感,而对其它参数都较敏感;与经典B-S模型及4/2随机波动率模型相比,4/2-CIR随机混合模型的定价误差更小,定价结果更接近真实值。

碳排放期权定价及实证研究——以湖北碳排放交易中心为例

碳期权作为碳金融市场上重要的交易产品,合理定价有利于投资者做出理性的碳期权套期保值决策,降低碳交易市场风险。因此,本文基于湖北碳排放交易中心碳配额数据构建定价模型,以此对我国八大碳交易市场价格提供一定的借鉴。本文将GARCH模型和期权定价模型B-S引入碳排放交易期权的定价研究中。通过碳排放交易中心配额期货收盘价的数据检验,发现价格波动情况具有非正态性和尖峰厚尾的特征,并采用GARCH模型拟合预测碳价收益率波动率,将预测的数据求取标准差后得到最终日波动率,从而带入B-S定价模型中进行价值估值。结果表明,GARCH模型具有良好的拟合性,有利于提高定价的精准度。

Black-Scholes模型下亚式期权定价的一种快速傅里叶算法

针对几何平均亚式期权,利用快速傅里叶变换方法得到含特征函数的表达式,从而更快速求解亚式期权.对期权价格进行傅里叶变换,得到表达式可以用标的资产价格对数的特征函数来表示,该表达式可以输出期权价格的结果.对其进行离散化处理,再利用快速傅里叶变换来求解,以输出结果.对Black-Scholes模型下的几何亚式期权定价的表达式进行计算,得出其期权定价模型的特征函数,便可以带入快速求解出相应的期权价值.利用Black-Scholes模型在该方法求解的几何平均亚式期权价值与Black-Scholes模型下原始期权价值的数据进行对比,验证了该方法的有效性和高效性.

基于偏微分方程算法的期权定价方法研究

在现代金融理论研究领域,金融衍生产品定价问题的核心内容是期权定价问题。随着期权种类的增加和模型的扩展,研究期权定价方法尤为重要。对于不存在解析解的期权定价问题,采用偏微分模型方程的精准求解就成为解决该问题的关键一环。因此,本研究结合其他领域如流体力学中的数值求解方法,发展了一种基于间断有限元(DGM)的偏微分方程求解算法,并结合不同算例对算法进行了验证和分析,该算法的精准求解为期权的成功定价奠定了良好的基础。