权证发行对标的股票价格风险影响的实证研究

研究权证发行对标的证券价格风险的影响,对研究资本市场的有效性及权证定价等方面具有重要的意义。目前我国已经发行的备兑权证,运用资本资产定价模型(CAPM)和GARCH-M模型,探讨权证的发行时正股的无风险报酬、系统性风险(Beta)和总风险(报酬率波动性)是否有显著影响。实证结果表明,无论是认购权证、认沽权证,还是蝶式权证的发行对正股的无风险报酬、系统性风险的影响基本上均不显著,但对半数以上发行权证的股票的总风险有显著影响。抑制权证市场的投机性,发挥其本身应发挥的价格发现功能、促进股票的流动性、降低股价波动性等的功能,就必须从风险相互对冲的角度,循序渐进地大力发展权证等衍生产品的规模,促进衍生品市场健康、有序地发展。     

金融衍生品的定价能力研究:以中国市场权证为例

文章应用线性多因子模型研究了我国权证的定价能力,发现权证是非冗余的,故对风险资产的收益率有解释能力,且对小公司和价值股的解释能力强于大公司和成长股.文章还利用随机贴现因子的思想,用GMM方法做了稳健性检验.两种方法从不同角度得到同样的结论,权证价格中包含定价因素,金融衍生品的发展能提高市场定价效率,使市场趋于完全.     

我国权证市场定价效率现状及对策探析

自从2005年8月22日我国第一只权证上市以来,我国权证市场迅速发展,交易极其活跃,市场成交额已经名列世界前茅。但飞速发展的同时也存在一系列问题,表现突出的就是定价效率低下。本文通过对我国权证市场的研究,找出定价效率低下的原因,并针对性的提出相应的对策,以此希望我国权证市场能够更规范更有效的发展。     

国内权证市场的投资策略

权证实质是一种看涨、看跌期权。权证的定价比较复杂，有多个因素可决定权证的价格，其中正股价格、执行价格、到期日、股价波动率等几项是最主要的。在国内投资权证，可以选择利用波动率构建无风险套利组合；根据国内权证收益率特点确定在折价时买入权证而在溢价比率非常高时卖出权证；针对不同的市场预期，选择投资不同的权证类型等投资策略。     

国内权证市场的投资策略

权证实质是一种看涨、看跌期权。权证的定价比较复杂,有多个因素可决定权证的价格,其中正股价格、执行价格、到期日、股价波动率等几项是最主要的。在国内投资权证,可以选择利用波动率构建无风险套利组合;根据国内权证收益率特点确定在折价时买入权证而在溢价比率非常高时卖出权证;针对不同的市场预期,选择投资不同的权证类型等投资策略。     

基于人工神经网络的权证定价模型研究

近年来，人工神经网络方法已开始广泛运用于金融衍生产品的定价研究中。权证作为我国推出的第一个金融衍生产品，它的定价效率对维护权证市场的供求平衡具有非常重要的作用，本文在Black—Scholes权证定价模型的基础上，利用MATLAB神经网络工具箱，构建了一个RBF神经网络权证定价模型，并以江西铜业的认股权证江铜CWBI作为样本进行实证研究，对权证定价的新方法提出了一种新的解决方案。     

权证的杠杆效应浅析

权证作为一种金融衍生工具,具有较强的杠杆特性,可以使投资者通过较小的成本获得相对于投资正股获得更高的收益。本文通过权证收益率函数,分析投资权证的杠杆特性,并研究权证的价格对杠杆效应所造成的影响。     

GARCH-M框架下权证定价研究

利用标的股票的日收盘价格数据进行GARCH-M参数估计,然后利用物理测度和风险中性测度之间的局部风险中性定价关系,为目前国内的备兑权证进行定价。定价结果表明GARCH框架下的权证定价模型比历史波动率模型能够更好地吻合市场数据,但和市场价格之间仍有差距。分析了这种差异的原因,并给出相应的对策建议。     

单项资产β系数的简单线性回归分析

单项资产的β系数表示某个资产的收益率与市场组合之间的相关性，即反映了相对于市场组合的平均风险而言单项资产系统风险的大小。本文对伊泰B股收益率与整个上证股市收益率进行简单的线性回归，分析伊泰B股收益率与上证股市收益率的相关性，进而可以看出伊泰B股对上证股市市场风险的贡献程度。     

CAPM在深圳A股市场的实证检验

本文利用深圳A股市场的权重股日收益率数据对资本资产定价模型进行了实证检验,结果表明CAPM理论不适用于深圳A股市场,并说明了相关原因。     

股指期货如何影响股市稳定性?——对全球主要市场的三角度实证检验

以全球多个市场作为实证检验对象,从股市波动率变化、系统风险变化以及股市正反馈交易行为影响三个角度,分析股指期货市场稳定作用的含义,即对股市波动的影响及其作用表现,较为全面地解读股指期货的市场稳定作用。研究发现:三个角度都支持股指期货的市场稳定作用;而抑制正反馈交易的作用最为基础、直接和显著,是股指期货市场稳定作用的更为恰当的判断标准。     

Why Doesn't the Black‐‐Scholes Model Fit Japanese Warrants and Convertible Bonds?

In this paper, we investigate the systematic departures of traded prices of Japanese equity warrants and convertible bonds from their theoretical Black–Scholes values. We briefly consider transactions costs and the dilution adjustment as potential explanations of the discrepancy. However, our major focus is on shifts in volatility of the prices of the underlying stocks as a function of the stock price changes; such shifts are not taken into account in the Black–Scholes values. We assume that the pseudo‐probability distributions of prices of stocks of cross‐sections of companies which are roughly similar in size are identical. This simple assumption, which can be generalized, enables us to infer the implied probability distribution and binomial tree for stock price changes using the Derman and Kani (1994), Rubinstein (1994) and Shimko (1993) approach. The cross‐section of warrant prices implies an inverse volatility smile and a positively skewed probability density for stock prices. Rubinstein's identifying assumptions generate an implied binomial tree in which the relative size of up‐steps and down‐steps, and thus volatility, changes systematically as stock prices change. We briefly consider potential explanations for the implied behaviour, and for the difference in the smile pattern between index options and the warrants and convertibles.     

Do Chinese Retail Option Traders Know Anything about Market Volatility?

This paper examines the information content of implied volatility in the Chinese covered warrant market and finds that the implied volatility is consistently higher than the realized volatility for all warrants and across all maturities. The implied volatility has very little information content for future volatility in the Chinese warrant market which is dominated by retail investors. Possible explanations for the results are regulatory issues such as restrictions on the short-selling of warrants, differential trading rules for stocks and warrants, high leverage and low trading costs and a market dominated by retail investors.     

Systematic ESG exposure and stock returns: Evidence from the United States during the 1991–2019 period

Using a sample of US stocks over the period 1991–2019, we test whether stocks with high exposure to a social index exhibit high returns. Using a univariate analysis, our in-sample results show that stocks with high sensitivities to the MSCI KLD 400 Social Index underperform stocks with low sensitivities by an annual risk-adjusted performance of 7.02%. The negative premium is also larger in the post-crisis period of 2007–2019 and is equal to 10.25%. The out-of-sample results offer, however, only weak evidence of such a finding, with a risk-adjusted performance difference of merely −0.84% over the full sample period and no significant differences between the pre-crisis and post-crisis periods. In the multivariate regression, we find evidence of a negative relationship between exposure to the social index and stock performance. Moreover, we find that stocks with high exposure to the social index display a low corporate social responsibility score, a high Tobin’s Q, high long-term debt, a large size, high total risk, a high market beta, a high SMB coefficient, a low HML coefficient, and a small MOM coefficient.     

The Impact of Liquidity Risk: A Fresh Look*

This paper takes a fresh look at the importance of liquidity risk using a comprehensive liquidity measure, weighted spread, in a Value‐at‐Risk (VaR) framework. The weighted spread measure extracts liquidity costs by order size from the limit order book. Using a unique, representative data set of 160 German stocks over 5.5 years, we show that liquidity risk is an important risk component. Actually, liquidity risk is increasing the total price risk by over 25%, even at 10‐day horizons and for liquid blue chip stocks and especially in larger, yet realistic order sizes beyond €1 million. When correcting for liquidity risk, it is commonly assumed that liquidity risk can be simply added to price risk. Our empirical results show that this is not correct, as the correlation between liquidity and price is non‐perfect and total risk is thus overestimated.     

Does Prepayment Risk of Mortgages Affect Excess Returns of Bank Stocks?

This paper explores the relationship between the prepayment risk embedded in conventional, fixed-rate residential mortgages and excess returns for bank stocks. There are two interesting findings in this study. First, commercial banks traded in the Nasdaq market are more meanvariance efficient than the other seven groups of industrial stocks. Second, the prepayment risk factor is significant for these banks. The prepayment risk mainly reflects a call option embedded in a mortgage plus foreclosure costs associated with a mortgage put option. This risk is measured by a remaining part of mortgage rates after excluding the influence of real estate market, maturity, and default risks on mortgage rates. The results of this study suggest that the prepayment risk factor does significantly affect excess returns for bank stocks in the period with high levels of mortgage refinancing activities. JEL Classification G210     

对包钢股票β值的检验

β值是指企业的系统风险,也就是企业不能通过投资分散掉的风险。例如全球经济形势,利率水平等所产生的风险。企业的β系数表示了资产的回报率对市场变动的敏感程度,可以衡量该资产的不可分散风险。本文基于投资组合理论,首先简单分析了单个资产系统风险对于确定单个资产收益率的重要意义,随后运用上证指数（000001）与包头钢铁有限责任公司的股票（600010）的相关数据,运用E-views6.0进行一元线性回归分析,确定了包钢集团的β值。最后,本文对得到的模型进行了统计意义与计量经济学检验,为今后计算单项资产β值实现规避风险的研究提供了有益的借鉴。本文选取了包钢股票2009年9月至2014年9月近五个年度的月度数据,运用EXCEL、新浪股票、E-views6.0等相关网络及系统软件对其进行分析研究,最终得出包钢股票的β值。     

Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective

We construct a multilayer network to study the interconnectedness between convertible bonds and underlying stocks in China by using the high-frequency data of 43 publicly listed firms. Most of convertible bonds have conspicuous cross-market influence on underlying stocks, especially on their corresponding underlying stocks. Traditional service firms are susceptible to the price fluctuations of other firms, whereas the high-tech firms are likely to cause the fluctuations of others. Global connection density increases after positive events but decreases after negative events. Our study provides useful information for regulators to formulate supervisory policies and help investors to optimize investment portfolios.     

Information revelation in the futures market: Evidence from single stock futures

This paper analyzes 31 months of data on 137 single‐stock futures (SSFs) traded on OneChicago. The results indicate that on the days they trade, SSFs contribute approximately 24% of the price discovery for underlying stocks. Information revelation in the SSFs market decreases with the ratio of spreads in the futures and the stock markets and the volatility in the stock market. Moreover, the quality of the market for the underlying stocks improves substantially after the introduction of the SSFs market, with the largest improvement occurring on days with SSFs trading. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:335– 353, 2008