Advances in variance analysis permit the splitting of the total quadratic variation of a jump-diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions and highlight the upside/downside variance spread as a driver of the asymmetry in stock price distributions. To appraise the economic gain of this decomposition, we design a new and flexible option pricing model in which the underlying asset price exhibits distinct upside and downside semivariance dynamics driven by the model-free proxies of the variances. The new model outperforms common benchmarks, especially the alternative that splits the quadratic variation into diffusive and jump components.

This paper proposes a method to compute ex-ante trading costs at the intraday level from limit order books. Using nearly 500 of the largest traded companies in the NYSE ArcaBook, we show that these costs have nontrivial intraday dynamics, are negatively related to volume and positively related to volatility. When ex-ante trading costs are incorporated into price impact specifications, the results show that this measure provides relevant information about price changes of the market at a high frequency level. Our evidence suggest that ex-ante trading costs constitute a new source of information for the study of intraday liquidity.