Purpose -The purpose of this paper is to investigate the relationship between customer's electronic word-of-mouth (eWOM) regarding their direct service experiences with firms and these firms' company value. The authors drew on the marketing-finance interface research approach to demonstrate how interactive social media adopted by individual customer relate to important firms' financial performances. Design/methodology/approach -The authors used seven American airline companies' customers' tweets collected during a 52-week observation period and paired with their corresponding financial data using stock returns and volatilities. Sentiment analysis algorithm and a vector autoregressive (VAR) model quantified the strong association between customer's eWOM and these firms' stock returns and volatilities. Findings -The results show that customer's eWOM regarding a firm positively associate with the firm's stock return but negatively associate with its stock volatility; as negative valence of customer's eWOM increases, the positive effect of eWOM on firm's stock return decreases; the negative eWOM impacts on the stock market more profoundly compared with when both positive and negative sensitivities are considered; and eWOM's wear-out effect is much shorter than that of traditional WOM. Originality/value -The authors address a literature gap where little is known for how customer's eWOM, that is evaluating firm services, can ultimately impact on firms' long-term financial performances. The authors discuss how findings from this study offer implications for marketing management as well as strategic insights for practitioners and investment analysts alike.

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Both CDS and out-of-money put option can protect investors against downside risk, so they are related while not being mutually replaceable. This study provides a straightforward linkage between corporate CDS and equity option by inferring stock volatility from CDS spread and, thus, enables a direct analogy with the implied volatility from option price. I find CDS inferred volatility (CIV) and option implied volatility (OIV) are complementary, both containing some information that is not captured by the other. CIV dominates OIV in forecasting stock future realized volatility. Moreover, a trading strategy based on the CIV-OIV mean reverting spreads generates significant risk-adjusted return. These findings complement existing empirical evidence on cross-market analysis.

We develop the Nelson–Siegel model in the context of option‐implied volatility term structure and study the time series of volatility components. Three components, corresponding to the level, slope, and curvature of the volatility term structure, can be interpreted as the long‐, medium‐, and short‐term volatilities. The long‐term component is persistent and driven by macroeconomic variables, the medium‐term by market default risk, and the short‐term by financial market conditions. The three‐factor Nelson–Siegel model has superior performance in forecasting the volatility term structure, with better out‐of‐sample forecasts than the popular deterministic implied volatility function and a restricted two‐factor model, providing support to the literature of component volatility models. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 34:788–806, 2014

This is the first study to examine the intraday price discovery and volatility transmission processes between the Singapore Exchange and the China Financial Futures Exchange. Using one-and five-minute high-frequency data from May to November 2011, the authors find that the Chinese Securities Index 300 index futures dominate Singapore's A50 index futures in both intraday price discovery and intraday volatility transmission. However, A50 futures contracts also make a substantial contribution (26-37 percent) to the price discovery process. These results have important implications for both traders and policymakers.