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Full-Text Articles in Social and Behavioral Sciences
Conditional Superior Predictive Ability, Jia Li, Zhipeng Liao, Rogier Quaedvlieg
Conditional Superior Predictive Ability, Jia Li, Zhipeng Liao, Rogier Quaedvlieg
Research Collection School Of Economics
This article proposes a test for the conditional superior predictive ability (CSPA) of a family of forecasting methods with respect to a benchmark. The test is functional in nature: under the null hypothesis, the benchmark’s conditional expected loss is no more than those of the competitors, uniformly across all conditioning states. By inverting the CSPA tests for a set of benchmarks, we obtain confidence sets for the uniformly most superior method. The econometric inference pertains to testing conditional moment inequalities for time series data with general serial dependence, and we justify its asymptotic validity using a uniform non-parametric inference method …
Reading The Candlesticks: An Ok Estimator For Volatility, Jia Li, Dishen Wang, Qiushi. Zhang
Reading The Candlesticks: An Ok Estimator For Volatility, Jia Li, Dishen Wang, Qiushi. Zhang
Research Collection School Of Economics
Academic research on nonparametric “spot” volatility inference often relies on high-quality transaction data that are not available to an average investor. Most investors, however, have free access to intraday candlestick charts through their online trading applications. Based on such data, we propose an Optimal candlesticK (OK) estimator for the spot volatility at a given time point. Under a standard infill asymptotic setting for Itˆo semimartingale price process, we show that the OK estimator is asymptotically unbiased and has minimal asymptotic variance within a class of linear estimators. In addition, its estimation error can be coupled by a Brownian functional, whose …