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profit opportunities in various financial markets. A t-test confirms the presence of overreactions and also suggests that … trading robot approach is then used to test two trading strategies aimed at exploiting the detected anomalies to make abnormal … profits. The results suggest that a strategy based on counter-movements after overreactions does not generate profits in the …
Persistent link: https://www.econbiz.de/10013043917
Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the implemented techniques and the type of source on which...
Persistent link: https://www.econbiz.de/10012629835
This paper aims to examine the relation between idiosyncratic volatility (IVOL) and stock returns with full-sample and … prospect theory. This paper also suggests IVOL opposite strategy for investors to generate significant returns by collecting …
Persistent link: https://www.econbiz.de/10012219258
Examinations of the dynamics of daily returns and volatility in stock markets of the US, Hong Kong and mainland China …
Persistent link: https://www.econbiz.de/10011296721
trading simulation approach. The results suggest that hourly returns during the day of positive/negative overreactions are … significantly higher/lower than those during the average positive/negative day. Overreactions can usually be detected before the day … overreactions and ETHUSD negative overreactions) a contrarian effect is detected instead …
Persistent link: https://www.econbiz.de/10012859990
This paper explores price (momentum and contrarian) effects on the days characterised by abnormal returns and the following ones in two commodity markets. Specifically, using daily Gold and Oil price data over the period 01.01.2009-31.03.2020 the following hypotheses are tested: H1) there are...
Persistent link: https://www.econbiz.de/10012827113
Forecasts of stock market volatility is an important input for market participants in measuring and managing investment … Machine Learning methods, and specifically Artificial Neural Network (ANN) models to forecast volatility. The ANN models are …
Persistent link: https://www.econbiz.de/10013310404
This paper explores the frequency of price overreactions in the Ukrainian stock market by focusing on the PFTS Index …) for the period of 2013–2015. Using static approach to detect overreactions, a number of hypotheses are tested: the … frequency of price overreactions is informative about crisis events in the economy (H1), can be used for price prediction …
Persistent link: https://www.econbiz.de/10012912811
This paper explores the frequency of price overreactions in the US stock market by focusing on the Dow Jones Industrial … Index over the period 1990-2017. It uses two different methods (static and dynamic) to detect overreactions and then carries …: whether or not the frequency of overreactions varies over time (H1), is informative about crises (H2) and/or price movements …
Persistent link: https://www.econbiz.de/10012916527
This paper explores price overreactions in the FOREX by using both daily and intraday data on the EURUSD, USDJPY … detect overreactions and then various statistical methods, including cumulative abnormal returns analysis, to test the … the detected anomalies, which can be seen as evidence of market inefficiency …
Persistent link: https://www.econbiz.de/10012889664