Accounting for the impact of higher order moments in foreign equity option pricing model

This paper investigates the pricing of foreign equity option whose value depends on foreign equity prices and exchange rate. We assume that the underlying asset returns of foreign equity option is not a Brownian motion, and use the Gram-Charlier series expansion to augment a normal density with two additional terms to capture the effects of skewness and kurtosis. The empirical study shows that the higher order moments (skewness and kurtosis) clearly affect the estimated prices of foreign equity options. This approach enables us to capture more accurately the foreign equity option prices.     

Pricing currency options in a fractional Brownian motion with jumps

A new framework for pricing the European currency option is developed in the case where the spot exchange rate fellows a fractional Brownian motion with jumps. An analytic formula for pricing European foreign currency options is proposed using the equivalent martingale measure and the estimation method of parameters in the pricing model is given, enabling option prices to be computed efficiently and accurately. For the purpose of understanding the pricing model, some properties of this pricing model are discussed in the latter part of this paper. Finally, the numerical simulations illustrate that our model is flexible and easy to implement.     

A nonparametric kernel regression approach for pricing options on stock market index

Previous options studies typically assume that the dynamics of the underlying asset price follow a geometric Brownian motion (GBM) when pricing options on stocks, stock indices, currencies or futures. However, there is mounting empirical evidence that the volatility of asset price or return is far from constant. This article, in contrast to studies that use parametric approach for option pricing, employs nonparametric kernel regression to deal with changing volatility and, accordingly, prices options on stock index. Specifically, we first estimate nonparametrically the volatility of asset return in the GBM based on the Nadaraya–Watson (N–W) kernel estimator. Then, based on the N–W estimates for the volatility, we use Monte Carlo simulation to compute option prices under different settings. Finally, we compare the index option prices under our nonparametric model with those under the Black–Scholes model and the Stein–Stein model.     

Single Beta Models and Currency Futures Prices

The conditional capital asset pricing model is applied to foreign currency futures prices, covariance risk being measured relative to excess returns from a broadly diversified international portfolio of equities. Positive time-varying risk premia are found in all five currencies tested when the difference between the US and the average foreign interest rates is used as an instrumental variable for the expected excess return from the common stock portfolio.     

International asset prices and portfolio choices under Bayesian learning

We calculate equilibrium asset prices and portfolio choices from a two-country OLG international asset pricing model under the assumption that investors are on a Bayesian learning path. Investors from both countries receive identical information flows, but domestic investors start off with less precise priors concerning foreign fundamentals. Learning is shown to produce first-order effects on the properties of asset prices, in the form of increased equity returns, volatility clustering, and time-varying correlations across national stock markets. Moreover, on a learning path, estimation risk generates portfolio biases similar to those observed empirically, i.e. a strong preference towards domestic securities and excessive turnover in foreign securities. These findings are robust to changes in prior beliefs, the calibration of initial information asymmetries, and the parameterization of the model. We use real GDP data for the US and Europe to calibrate the model and show that in the event of a financial liberalization during the 1970s, high excess returns, time-varying volatility, substantial home bias, and excess turnover should have been observed.     

Asset prices and economic fluctuations: The implications of stochastic volatility

This paper investigates whether the multi-factor stochastic volatility of stock returns is related to economic fluctuations and affects asset prices. We address these issues in a dynamic Fama-French three-factor volatility model framework. Consistent with the ICAPM with stochastic volatility (Campbell et al., 2017), we find that the conditional volatility of the size and value factors is significantly related to economic uncertainty. These volatilities are also significant pricing factors. The out-of-sample forecasting analysis further reveals that the conditional volatility can predict stock returns and deliver economic gain in asset allocation. Our analysis sharpens the understanding on the link between the stock market and economic fundamentals.     

Pricing foreign equity options with regime-switching

In this paper, we investigate the valuation of two types of foreign equity options under a Markovian regime-switching mean-reversion lognormal model, where some key model parameters in the dynamics of the foreign equity price and the foreign exchange rate are modulated by a continuous-time, finite-state Markov chain. A fast Fourier transform (FFT) approach is applied to provide an efficient way to evaluate the option prices. Numerical analysis and empirical studies are provided to illustrate the practical implementation of the proposed pricing model.     

金融资产收益率波动预测——基于我国股票市场跳跃行为研究

金融资产收益率波动是资产定价和金融风险管理的核心部分,而跳跃是收益率波动中的重要组成部分。基于修正Z-检验,本文检测识别我国股市波动中跳跃行为,并且研究了跳跃的时序特征,统计结果表明,在市场大波动时期,和连续成份相比,跳跃对于波动率具有极其重要的贡献。建立包含跳跃的已实现波动率非齐次自回归模型,在波动模型中纳入滞后绝对日收益率和杠杆效应预测股指收益率波动。实证分析结果显示,对于短期的波动预测,包含跳跃和两种影响因素的波动模型表现最好,然而对于提前1月的长期预测,跳跃和连续波动成份分离模型预测明显优于其它模型,这些事实说明跳跃对股指波动率预测具有重要的影响,好坏消息对波动率非对称性具有短期显著影响,而对长期水平的波动率预测影响不显著。     

Equilibrium asset pricing under the Lévy process with stochastic volatility and moment risk premiums

In this paper, we extend Zhang, Zhao and Chang's (2012) production-based equilibrium asset pricing model from a jump diffusion setting to a Lévy process with stochastic volatility. This paper is a further extension of Fu and Yang (2012), which is under a Lévy process with a constant volatility. Using newly developed closed-form formulas of equity premium and pricing kernel, we are able to price Schouten's (2005) moment swaps analytically. Numerical results show that our pricing formula performs very well. Our model explains Zhao, Zhang and Chang's (2013) empirical observations on moment risk premiums.     

A comparison of pricing and hedging performances of equity derivatives models

This article investigates the pricing/hedging conundrum, i.e. the observation of a mismatch between derivatives models’ pricing and hedging performances, that has so far been under-emphasized as the literature tends to focus on increasingly complicated option pricing models, without adequately addressing hedging performance. Hence, we analyse the ability of the Black–Scholes, Practitioner Black–Scholes, Heston–Nandi and Heston models to Delta-hedge a set of call options on the S&P500 index and Apple stock. We extend earlier studies in that we consider the impact of asset dynamics, apply a stringent payoff replication strategy, look at the impact of moneyness at maturity and test for the robustness to the parameters’ calibration frequency and Delta-Vega hedging. The study shows that adding risk factors to a model, as stochastic volatility, should only be considered in light of the data dynamics. Even then, however, more complicated models generally fare poorly for hedging purposes. Hence, a better fit of a model to option prices is not a good indicator of its hedging performance, and so of its ability to describe the underlying dynamics. This can be understood for reasons of over-fitting. Those findings hint to a potentially appealing hedging-based calibration of models’ parameters, rather than the standard pricing-based one.     

Calibration of implied volatility for the exchange rate for the Chinese Yuan from its derivatives

Revised implied volatility curves and surfaces for the Chinese Yuan (CNY) exchange rate are obtained from market quotations for CNY non-deliverable options by solving an inverse problem of foreign exchange option pricing, which is calculated using a regularization approach in an optimal control framework. To take account of the market expectation for the CNY exchange rate, a stochastic adjusted factor is applied that follows a Vasicek model with parameters fitted from market quotations for CNY non-deliverable forwards. A well-posed numerical scheme is implemented.     

CAN FINANCING CONSTRAINTS EXPLAIN THE ASSET PRICING PUZZLES IN PRODUCTION ECONOMIES?*

General Equilibrium asset pricing models have a difficult time simultaneously delivering a sizable equity premium, a low and counter cyclical real risk free rate, and cyclical variation in return volatility. To explain these stylized facts, this article introduces occasionally binding financing constraints that impede producers’ ability to invest. The financial frictions drive a wedge between the marginal rate of substitution and firms’ internal stochastic discount factors so that the shadow value of capital is not tied to the average price of capital. The model delivers higher and more volatile asset returns during recessions as well as a counter cyclical equity premium.     

Analysis of High Frequency Data in Finance: A Survey

This study examines the use of high frequency data in finance, including volatility estimation and jump tests. High frequency data allows the construction of model-free volatility measures for asset returns. Realized variance is a consistent estimator of quadratic variation under mild regularity conditions. Other variation concepts, such as power variation and bipower variation, are useful and important for analyzing high frequency data when jumps are present. High frequency data can also be used to test jumps in asset prices. We discuss three jump tests: bipower variation test, power variation test, and variance swap test in this study. The presence of market microstructure noise complicates the analysis of high frequency data. The survey introduces several robust methods of volatility estimation and jump tests in the presence of market microstructure noise. Finally, some applications of jump tests in asset pricing are discussed in this article.     

The Effects of US Macroeconomic Surprises on the Intraday Movements of Foreign Exchange Rates: Cases of USD-EUR and USD-JPY Exchange Rates

This paper characterizes the intraday dynamics of the high frequency US Dollar (USD)–Euro (EUR) and US Dollar (USD)–Japanese Yen (JPY) foreign exchange rates that have been subject to macroeconomic fundamentals. Even though the FIGARCH model with a normality assumption is found to be a good starting point, it appears to be inappropriate to represent the underlying movements of the high frequency returns due to the occurrences of jumps. Hence, this paper relies on the FIGARCH model with the mixture distribution that allows for the time-varying jumps that are determined by the US macroeconomic surprises. This paper generally finds that the US macroeconomic surprises are closely related to the intraday movements in the volatility process of the high frequency returns process through the jumps. In particular, the US macroeconomic surprises appear to affect the movements in the volatility process of the foreign exchange rates asymmetrically depending on the signs of the surprises and spuriously increasing the long memory persistence in the volatility process due to the jumps.     

Option implied beta and option return

We study the information content of option-implied betas for future equity option returns, using data on the S&P 500 index options and all of the component stock options. We find a significantly strong relation between option-implied betas and option returns cross-sectional. The paper presents evidence that call (put) option returns increase (decrease) with the option-implied betas of the underlying stock. A trading strategy of buying high (low) implied beta call (put) option portfolio and selling low (high) implied beta call (put) option portfolio generates a statistically and economically significant return. Our results are robustly persistent even after controlling for various cross-sectional effects and are not explained by the risk factors in asset pricing.     

Exchange rates change,asset-denominated currency difference and stock price fluctuation

This paper examines differences in the connectedness between exchange rates and stock prices for companies with different asset currencies on the Hong Kong stock market, and it seeks to explain those differences by proposing a hypothesis on asset-denominated currency difference. Under a framework of investor heterogeneity, we establish a dynamic, discrete theoretical model to analyse the connectedness between exchange rates, the stocks of local Hong Kong companies, the stocks of companies from the mainland and foreign exchange interventions. Using monthly data from January 2000 to August 2018, we adopt the time-varying parameter vector auto-regression (TVP-VAR) model to empirically study the dynamic relationships between exchange rates and the prices of both Hong Kong-based and mainland-based stocks. The results show significant differences in the ways that exchange rates and prices for the two types of stocks are linked. The exchange rates are positively correlated with mainland stocks and negatively correlated with Hong Kong stocks. Moreover, foreign exchange intervention is found to be an effective means for stabilising exchange rates, although such intervention tends to increase stock volatility.

Abbreviations: TVP-VAR - time-varying parameter vector auto-regression model; MCMC - Monte Carlo-Markov Chain method.     

An improved framework for approximating option prices with application to option portfolio hedging

As the price of the underlying asset changes over time, delta of the option changes and a gamma hedge is required along with delta hedge to reduce risk. This paper develops an improved framework to compute delta and gamma values with the average of a range of underlying prices rather than at the conventional fixed ‘one point’. We find that models with time-varying volatility price options satisfactorily, and perform remarkably well in combination with the delta and delta-gamma approximations. Significant improvements are achieved for the GARCH model followed by stochastic volatility models. The new approach can ensure significant improvement in modelling option prices leading to better risk-management decision-making.     

Empirical of the Taiwan stock index option price forecasting model – applied artificial neural network

This work presents a novel neural network model for forecasting option prices using past volatilities and other options market factors. Out of different approaches to estimating volatility in the option pricing model, this study uses backpropagation neural network to forecast prices for Taiwanese stock index options. The ability to develop accurate forecasts of grey prediction volatility enables practitioners to establish an appropriate hedging strategy at in-the-money option.     

Currency internationalization and valuation effects: based on the threshold model

ABSTRACT

Based on the three functions of currency internationalization, including exchange medium, pricing currency and foreign reserve, this paper explores how the degree of currency internationalization affects the impact of the exchange rate and the asset price on valuation effects. Using samples of 161 countries or regions from 2001 to 2016 and the threshold regression method, we find that, firstly, there is a threshold effect of the exchange rate on valuation effects due to currency internationalization. The higher the comprehensive level of currency internationalization is, the greater the positive impact of the exchange rate on valuation effects will be. Secondly, the threshold effect of the asset price on valuation effects due to currency internationalization is not significant because of the high stickiness of asset price. Besides, compared with developed countries, currency internationalization is more important to increase valuation effects through exchange rate channel and asset price channel in developing countries or regions. Finally, there are some differences in the three types of currency internationalization functions. The promotion of exchange medium function will lead to a greater positive impact of the exchange rate on valuation effects, as well as pricing currency function. However, the foreign reserve function has no such effect.     

Pricing Nikkei 225 Options Using Realized Volatility

This article examines option pricing performance using realized volatilities with or without handling microstructure noise, non‐trading hours and large jumps. The dynamics of realized volatility is specified by ARFIMA(X) and HAR(X) models. The main results using put options on the Nikkei 225 index are that: (i) the ARFIMAX model performs best; (ii) the Hansen and Lunde (2005a) adjustment for non‐trading hours improves the performance; (iii) methods for reducing microstructure noise‐induced bias yield better performance, while if the Hansen–Lunde adjustment is used, the other methods are not necessarily needed; and (iv) the performance is unaffected by removing large jumps from realized volatility.