50ETF

  • 详情 因子模型能定价期权收益吗?
    金融资产因子结构映照着风险与收益的权衡,因子模型能否同样描绘期权收益?期权合约存续时间极短、风险敞口变化频繁,难以应用传统因子模型进行定价。工具主成分分析方法(IPCA)提供了新的解决方案,动态风险载荷形式与期权风险特征高度吻合。本文尝试采用IPCA模型揭示上证50ETF期权的因子结构。研究结果表明,三因子IPCA模型能够解释超过87%的单个期权收益变化和超过99%的投资组合收益变化,表现优于现有的期权因子模型以及静态PCA模型。IPCA因子与期权在值状态偏度、剩余期限斜率以及Gamma价值紧密联系,能够解释40%至60%的因子变化。本文的研究对于优化投资组合风险管理具有重要意义,有助于监管者提高期权市场定价效率,促进衍生品市场稳健发展。
  • 详情 Short-Selling Cost and Implied Volatility Spreads: Evidence from the Chinese Sse 50etf Options Market
    This paper will partially solve the puzzle of implied volatility spreads from the perspective of short-selling (option-implied borrowing rate). Specifically, we use Chinese SSE 50 ETF options data to examine the relationship between the option-implied volatility spreads and option-implied borrow rate. Using nonparametric regression models, we find that there is a clear negative correlation between the implied volatility spreads and the implied borrowing rate. Furthermore, our results show that there is a significant nonlinearity between these two variables. Finally, it is interesting to note that the option volatility spreads are zero when the option prices include the short selling cost.
  • 详情 Is Chinese option market efficient? Evidence from the first exchange-traded option
    By testing properties implied by one-dimensional diffusion option pricing models, we find that call (put) prices in the Chinese 50ETF option market move in opposite (same) direction with the underlying between 13.39% and 27.89% (between 12.45% and 33.98%) of the time for 5-minute and 1-day sampling intervals respectively. Given fundamental different investor structures in U.S. and China option markets, we also observe some important unique features in the 50ETF option price dynamics. More importantly, we demonstrate that these striking violations reduce substantially in 2016 compared with those in 2015, indicating that Chinese stock option market becomes more efficient.
  • 详情 期权隐含高阶矩的期限结构及收益率可预测性:来自A股期权市场的证据
    本文从含有时变高阶矩的条件资本资产定价模型(CAPM)出发,基于我国上证 50ETF期权数据,检验了期权隐含的风险中性各阶矩的期限结构中是否包含有助于预测市场收益率和波动率的有效信息。采用偏最小二乘回归(PLS)的数据降维方法,我们发现:在 2015 到 2020年样本期内,从 50ETF 期权的隐含方差和高阶矩的期限结构中所提取的因子能显著地样本外预测未来 2 至 8 周的市场收益,且该预测能力在控制了常见的经济预测变量后仍十分显著。并且,从期权隐含方差的期限结构中所提取的因子能样本外预测市场波动。基于上述市场收益率和波动率预测的择时策略可以给投资者带来显著的经济价值。我们的实证分析表明:有别于已有文献中的经济预测变量,50ETF 期权市场可为投资者提供关于市场收益与风险之间短期权衡关系的特有信息。