id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-324254-qikr9ryf	Lyócsa, Štefan	FX Market Volatility Modelling: Can we use low-frequency data?	2020-09-30		.txt	text/plain	5763	342	56	With an increased forecast horizon, low-frequency volatility models become competitive, suggesting that if high-frequency data are not available, low-frequency data can be used to estimate and predict long-term volatility in FX markets. Despite the wide interest of academia, the existing literature provides evidence only that i) volatility estimators based on high-frequency data are theoretically preferred (Andersen et al., 1 The basic specification of the HAR model has also been enhanced, e.g., by the inclusion of semivariances (Patton and Sheppard, 2015) , the disentanglement of the realized volatility into continuous and jump components (e.g., Andersen et al., 2012) , the introduction of the measurement error of the realized volatility into the HAR model as in (Bollerslev et al., 2016) , the inclusion of nontrading volatility components (Lyócsa and Molnár, 2017, Lyócsa and Todorova, 2020) , and the use of hidden Markov chains (Luo et al., 2019) .	./cache/cord-324254-qikr9ryf.txt	./txt/cord-324254-qikr9ryf.txt