隐含波动率对公司债信用利差的预测能力研究——来自上证50ETF期权的证据

本文以2015年2月至2018年3月在证券交易所发行与交易的一般公司债券为样本,建立面板固定效应模型分信用等级来研究上证50ETF期权隐含波动率对公司债信用利差的影响。研究结果显示隐含波动率对不同评级公司债信用利差影响显著且为正,隐含波动率可以用来预测公司债信用利差。借助本文的研究,不仅可以检验隐含波动率是否能够包含经济运行态势的信息,评估上证50ETF期权的定价效率,也可以为投资者对冲信用风险提供一种新策略。     

买卖权平价关系偏离能预测现货市场收益吗? ——基于上证50ETF期权的实证研究

选取隐含波动率差指标,以上证50ETF期权为研究样本,研究了期权市场买卖权平价关系偏离能否预测标的资产未来的收益信息.将分组分析和回归分析两种方法相融合,并将样本数据划分为三个不同阶段进行分析,结果显示,在发展初期期权市场包含标的资产未来较短时间内的收益信息,但信息含量很少;随着期权市场的发展,即在发展中期和发展期,期权市场包含标的资产未来更长时间范围内的收益信息且信息方向发生改变;期权市场能否准确预测现货市场信息与投资者情绪显著相关.     

期权定价模型中的波动率分析

期权定价模型是布莱克的一种典型的相对经济理论,它在金融实践过程中产生巨大的经济影响,这种期权的模型需要输入参数中在市场中无法直接观察取得的重要变量,即波动率数值,也就是说,基于历史数据来计量历史波动。人们通常在期权经济定价中,结合期权的价格,采用定量模型倒推出隐含的波动率,这种隐含的波动率对于投资者未来市场的预期有很重要的作用,对于期权市场和经济市场的避险和套期保值业务来说,为了能够进行更好的风险规避和管理,就必须要了解隐含波动率的波动规律。     

期权定价模型中的波动率分析

布莱克-斯科尔斯的期权定价模型是一个对经济理论、金融实践产生巨大影响的模型。该模型需要输入的参数中唯一无法在市场中直接观察到的重要变量是基础资产的波动率。基于历史数据来计量的历史波动率有严重缺陷,于是人们根据期权的市场价格,利用Black-Scholes定价模型倒推出隐含波动率。隐含波动率反映投资者对未来市场的共同预期;对于避险者的套期保值业务来说,这是进行风险管理的一项重要指标。然而,隐含波动率在使用过程中也存在着＂波动率微笑＂、＂波动率偏斜＂及＂波动率期限结构＂等现象。究其根源,皆源自于Black-Scholes模型所依据的某些假设条件与实际情况不相符合。     

外汇期权信息含量与在岸离岸市场效率

央行在“8·11”汇改后放松了汇率中间价的管理,采用更为市场化的方式形成中间价,这种变化对于人民币汇率衍生品市场的影响尚属未知。为此,本文从人民币期权组合的Black-Scholes隐含波动率历史报价数据中提取出在岸、离岸市场人民币期权的无模型隐含波动率和风险中性偏度,在将样本划分为汇改前后三个不同的阶段的基础上,检验了期权隐含指标对未来汇率分布的预测能力。实证结果表明,在“8·11”汇改之后,随着人民币中间价形成机制变得更加市场化,期权价格中包含了越来越多关于未来汇率分布的信息,在岸和离岸期权市场的信息效率都有显著提高,意味着人民币中间价形成机制的市场化能显著提升我国金融市场效率。因此,在兼顾金融安全的角度上,稳步促进人民币中间价形成机制市场化进程将有利于我国金融市场效率的提高。     

沪深300波动率指数的编制方法

推出股票价格波动率指数旨在衡量市场的波动性水平,当今最有名的波动率指数是美国芝加哥期权交易所推出的波动率指数,该指数对投资者以及市场都具有深刻意义。本文欲构造反映我国A股市场全貌的波动率指数,但由于我国市场上并无期权交易,因此本文无法效仿国外编制波动率指数的隐含波动率法,而选用历史波动率法来进行波动率预测,通过对沪深300指数的分析,本文发现通过garch模型来预测波动率,进而编制波动率指数是可行的,从而提出我国应研究推出波动率指数的政策建议。     

RVIX指数的构建及其有效性检验

以无模型隐含波动率理论为基础,改进期权选取机制、还原隐含波动率计算方法、利用近期合约和远期合约以及下季合约分类插值构建更为符合中国市场行情的RVIX指数,并利用t-Copula模型和混合Copula模型探究在一般和异常情况下RVIX指数是否能预测未来市场的真实波动率以及对哪个期限的市场真实波动率预测更为合适.实证研究结果表明:RVIX指数相对于中国波指IVX有所改进,且在极端情况下改进效果更为突出.一般情况下,RVIX指数能预测未来市场的真实波动率且对未来一周市场真实波动率的预测最为准确;当异常事件发生时,RVIX指数仍然有效,其暴跌时用于预测未来一周市场真实波动率的暴跌,暴涨时用于预测未来一个月市场真实波动率的暴涨更为合适.     

交易量的信息含量:台湾期权市场的证据

本文应用台湾股指期权市场详细的交易数据,对台指期权交易量的信息含量进行了全面系统的实证检验。我们从全市场、不同投资者以及不同在值程度期权分类角度分别构建了多个五分钟交易量指标,并检验它们对未来台指走势的预测能力。我们发现,全市场的期权交易量指标基本不具备未来指数走势预测能力,但境内机构投资者和境外机构投资者交易量中包含显著的预测信息,价外期权的信息明显地优于价内期权和平价期权。     

投资者情绪与股票收益--基于个人和机构投资者情绪的对比研究北大核心

通过对噪音交易模型(DSSW模型)的修正,本文以2005—2015年上交所A股市场为研究对象,选用新增开户数构建投资者情绪指标,研究个人和机构投资者情绪之间的关联性并且对比这两类投资者的情绪对股票收益的影响。结果表明:个人和机构投资者情绪的相互影响是不对称的,主要为机构投资者情绪影响个人投资者情绪。当期个人投资者情绪、滞后一期机构投资者情绪对市场超额收益有显著性影响,机构投资者情绪能够预测股票市场,而个人投资者情绪不具有预测作用。     

投资者情绪与股票收益——基于个人和机构投资者情绪的对比研究

通过对噪音交易模型(DSSW模型)的修正,本文以2005—2015年上交所A股市场为研究对象,选用新增开户数构建投资者情绪指标,研究个人和机构投资者情绪之间的关联性并且对比这两类投资者的情绪对股票收益的影响。结果表明:个人和机构投资者情绪的相互影响是不对称的,主要为机构投资者情绪影响个人投资者情绪。当期个人投资者情绪、滞后一期机构投资者情绪对市场超额收益有显著性影响,机构投资者情绪能够预测股票市场,而个人投资者情绪不具有预测作用。     

The information content of option-implied information for volatility forecasting with investor sentiment

This study explores the effect of investor sentiment on the volatility forecasting power of option-implied information. We find that the risk-neutral skewness has the explanatory power regarding future volatility only during high sentiment periods. Furthermore, the implied volatility has varying volatility forecasting ability depending on the level of investor sentiment. Our findings suggest that the effectiveness of volatility forecasting models based on option-implied information varies over time with the level of investor sentiment. We confirm the important role of investor sentiment in volatility forecasting models exploiting option-implied information with strong evidence from in-sample and out-of-sample analyses. We also present improvements in the accuracy of volatility forecasts from volatility forecasting models derived by incorporating investor sentiment in these models.     

Can happiness predict future volatility in stock markets?

In this paper, we use the Twitter based happiness index as a proxy for investor sentiment in order to examine whether happiness influences future market volatility of country VIX indexes. Our sample includes the major stock markets of the USA, Canada, UK, Germany, France, Netherlands, Switzerland, Japan, China, Hong Kong, India, Brazil, South Korea, and South Africa. Using linear and nonlinear causality tests, we find that Twitter happiness significantly causes the future volatility of the sample countries. The robustness checks show no divergence from our primary findings and provide strong evidence of a nonlinear relationship between investor sentiment and future stock market volatility.     

INVESTOR EXPECTATIONS OF VOLATILITY INCREASES AROUND LARGE STOCK SPLITS AS IMPLIED IN CALL OPTION PREMIA

Recent studies find abnormal common stock price behavior associated with ex-dates of stock splits. Volatility increases are substantia) and abrupt. This study extends previous analyses to the options market by examining investor perceptions of volatility increases through implied standard deviations of returns. Investors fail to anticipate volatility increases until the ex-date. Furthermore, abnormal option returns are present. The increased volatility and these results suggest option market inefficiency.     

Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets

This paper first investigates the relationship between investor sentiment, captured by internet search behaviour, and the unexpected component of stock market volatility during the COVID-19 pandemic. According to data on 12 major stock markets, our research indicates a positive correlation between the Google search volume index on COVID-19 and the unexpected volatility of stock markets. The result suggests that greater COVID-19-related investor sentiment during this pandemic is associated with higher stock market uncertainty.Our study further examines whether country-level governance plays a role in protecting stock markets during this pandemic and reveals that the unexpected conditional volatility is lower when a country's governance is more effective. The impact of investor sentiment and country governance on unexpected volatility after the initial shock of COVID-19 is also investigated. The findings demonstrate the importance of establishing good country-level governance that can effectively reduce stock market uncertainty in the context of this pandemic, and support continual policy development related to investor protection.     

Volume,volatility and information linkages in the stock and option markets

This paper examines the relationship between option trading activity and stock market volatility. Although the option market is uniquely suited for trading on volatility information, there is little analysis on how trading activity in this market is linked to stock price volatility. The bulk of the discussion tends to focus on whether trading activity in the stock market is informative about stock volatility. To analyze the information in option trading activity for stock market volatility, a sample of 15 stocks with the highest option trading volume is selected. For each stock, it is noted that the trading activities in the put and call option markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call option trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.     

Sentiment and stock market connectedness: Evidence from the U.S. – China trade war

We assess the impact of monthly and daily investor sentiment on stock market return and volatility connectedness during the U.S.-China trade war period. Our analyses focus on the connectedness between the two economies and their major trading partners. We also investigate the asymmetric impact of sentiment on volatility connectedness by exploring the upside and downside markets separately. We consistently document a negative relationship between investor sentiment and stock market connectedness for both return and volatility. We further confirm that investor sentiment exerts a larger impact on volatility connectedness in the downside market compared to the upside market.     

Investor sentiment and return predictability of disagreement

This study examines the influence of investor sentiment on the relationship between disagreement among investors and future stock market returns. We find that the relationship between disagreement and future stock market returns time-varies with the degree of investor sentiment. Higher disagreement among investors’ opinions predicts significantly lower future stock market returns during high-sentiment periods, but it has no significant effect on future stock market returns during low-sentiment periods. Our findings imply that investor sentiment is related to several causes of short-sale impediments suggested in the previous literature on investor sentiment, and that the stock return predictability of disagreement is driven by investor sentiment. We demonstrate that investor sentiment has a significant impact on the stock market return predictability of disagreement through in-sample and out-of-sample analyses. In addition, the profitability of our suggested trading strategy exploiting disagreement and investor sentiment level confirms the economic significance of incorporating investor sentiment into the relationship between disagreement among investors and future stock market returns.     

Is VIX an investor fear gauge in BRIC equity markets?

This study examines the intertemporal relationships between CBOE market volatility index (VIX) and stock market returns in Brazil, Russia, India, and China (BRIC), and between VIX and U.S. stock market returns, to uncover if VIX serves as an investor fear gauge in BRIC and U.S. markets. We conduct the VIX-returns analysis for the 1993–2007 period.Our results suggest a strong negative contemporaneous relation between daily changes (innovations) in VIX and U.S. stock market returns. This relation is stronger when VIX is higher and more volatile. A significant negative contemporaneous relation between VIX and equity returns also exists for China and Brazil during 1993–2007 and for India during 1993–1997. Similar to the U.S. market, the immediate negative relation between the Brazilian stock returns and VIX changes is much stronger when VIX is both high and more volatile. Our results also indicate a strong asymmetric relation between innovations in VIX and daily stock market returns in U.S., Brazil, and China, suggesting that VIX is more of a gauge of investor fear than investor positive sentiment. However, the asymmetric relationship between stock market returns and VIX is much weaker when VIX is large and more volatile. These results have potential implications for portfolio diversification and for stock market and option trading timing in the equity markets of Brazil, India, and China. Overall, our results indicate that VIX is not only an investor fear gauge for the U.S. stock market but also for the equity markets of China, Brazil, and India.     

Overconfidence among option traders

The investor overconfidence theory predicts a direct relationship between market‐wide turnover and lagged market return. However, previous research has examined this prediction in the equity market, we focus on trading in the options market. Controlling for stock market cross‐sectional volatility, stock idiosyncratic risk, and option market volatility, we find that option trading turnover is positively related to past stock market return. In addition, call option turnover and call to put ratio are also positively associated with the past stock market return. These findings are consistent with the overconfidence theory. We also find that overconfident investors trade more in the options market than in the equity market. We rule out explanations other than investor overconfidence, such as momentum trading and varying risk preferences, for our findings.     

Asymmetric information about volatility: How does it affect implied volatility,option prices and market liquidity?

This paper develops a model of asymmetric information in which an investor has information regarding the future volatility of the price process of an asset and trades an option on the asset. The model relates the level and curvature of the smile in implied volatilities as well as mispricing by the Black-Scholes model to net options order flows (to the market maker). It is found that an increase in net options order flows (to the market maker) increases the level of implied volatilities and results in greater mispricing by the Black-Scholes model, besides impacting the curvature of the smile. The liquidity of the option market is found to be decreasing in the amount of uncertainty about future volatility that is consistent with existing evidence. This revised version was published online in June 2006 with corrections to the Cover Date.