Implied Volatility and Forward Price Term Structures

2009 ◽  
Author(s):  
Raquel M. Gaspar
2017 ◽  
Vol 52 (6) ◽  
pp. 2727-2754 ◽  
Author(s):  
Aurelio Vasquez

The slope of the implied volatility term structure is positively related to future option returns. I rank firms based on the slope of the volatility term structure and analyze the returns for straddle portfolios. Straddle portfolios with high slopes of the volatility term structure outperform straddle portfolios with low slopes by an economically and statistically significant amount. The results are robust to different empirical setups and are not explained by traditional factors, higher-order option factors, or jump risk.


2021 ◽  
Vol 235 ◽  
pp. 02043
Author(s):  
Wenqi Yang ◽  
Jingkun Ma

This article focuses on the implied volatility forecast of the SSE 50 ETF options market from June 1, 2017, to August 30, 2019, and constructs AR (1) model and ARMA-GARCH model based on liquidity characteristics to compare and analyze the prediction effect of implied volatility on different option types and term structures. The results show that, during the sample period of the SSE 50 ETF options market, the effect of model fitting of the ARMA-GARCH model is significantly better than the AR (1) model; the fitting sequences predicted by the two models have typical time-varying and synchronization characteristics, and the prediction effect of the ARMA-GARCH model in the whole period is significantly better than the AR (1) model.


2014 ◽  
Vol 7 (2) ◽  
pp. 158-180 ◽  
Author(s):  
Pierre-Arnaud Henri Drouhin ◽  
Arnaud Simon

Purpose – This paper aims to analyze the statistical characteristics of changes in property forward prices. As highlighted in a survey conducted at the MIT Center for Real Estate in 2006, the relatively weak understanding in their prices is one of the most important barriers in their use. In this context, the analysis of the forward price term structure is essential. Do the short- and long-term forward prices behave similarly? Do property derivatives behave like other derivative assets or other related assets? This study also investigates the lead–lag relationship between spot and forward returns for different maturities. Design/methodology/approach – Using four years and nine months of data on the UK Investment Property Databank (IPD), all property total return swaps are examined. We strip the swaps into their forwards and study their statistical characteristics (the first four moments and their autocorrelation levels). The relationships among the forward contracts, the underlying asset (IPD index and IPD unsmoothed) and other assets (risk-free rate, listed real estate) are explored. Using the Yiu et al. (2005) methodology, the lead–lag relationship between the spot and the forwards is assessed. Findings – The index appears to be significantly less volatile and less efficient, in terms of correlation than its own derivative contracts. Moreover, changes in forward prices are leading indicators of the IPD index. Their risks tend to converge with the implied volatility of the REIT’s operating asset but without being affected by the general stock market risks. Regarding the forward price–discovery function, investors should collect information not only from the spot market but also, maybe primarily, from the derivative market. Originality/value – In this paper, we use a never-exploited database that is relative to the quotes of the UK IPD swaps. It is the first attempt to analyze the statistical characteristics of their changes. Our results show that these prices are clearly superior to the spot series, in terms of risks but without behaving affected by the tyranny of the past values. These findings may conduct to consider new methods to unsmooth current real estate indices. Characterized by a strong sensitivity to the changes in the information set, property derivative-based indicators should lead to increased efficiency in the spot market.


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