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Alex Plastun - One of the best experts on this subject based on the ideXlab platform.
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Price Overreactions in the cryptocurrency market
Journal of Economic Studies, 2019Co-Authors: Guglielmo Maria Caporale, Alex PlastunAbstract:The purpose of this paper is to examine price Overreactions in the case of the following cryptocurrencies: bitcoin, litecoin, ripple and dash.,A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U-test) tests confirm the presence of price patterns after Overreactions: the next day price changes in both directions are bigger than after “normal” days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited to generate profits.,The results suggest that a strategy based on counter-movements after Overreactions is not profitable, whilst one based on inertia appears to be profitable but produces outcomes not statistically different from the random ones. Therefore, the Overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the efficient market hypothesis (EMH).,The Overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the EMH.
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Long-term price Overreactions: are markets inefficient?
Journal of Economics and Finance, 2018Co-Authors: Guglielmo Maria Caporale, Luis A. Gil-alana, Alex PlastunAbstract:This paper examines long-term price Overreactions in various financial markets (commodities, US stock market and FOREX). First, a number of statistical tests are carried out for Overreactions as a statistical phenomenon. Second, a trading robot approach is applied to test the profitability of two alternative strategies, one based on the classical Overreaction anomaly, the other on a so-called “inertia anomaly”. Both weekly and monthly data are used. Evidence of anomalies is found predominantly in the case of weekly data. In the majority of cases strategies based on Overreaction anomalies are not profitable, and therefore the latter cannot be seen as inconsistent with the EMH.
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Price Overreactions in the Cryptocurrency Market
CESifo Working Papers, 2018Co-Authors: Guglielmo Maria Caporale, Alex PlastunAbstract:This paper examines price Overreactions in the case of the following cryptocurrencies: BitCoin, LiteCoin, Ripple and Dash. A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U test) tests confirm the presence of price patterns after Overreactions: the next-day price changes in both directions are bigger than after “normal” days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited to generate profits. The results suggest that a strategy based on counter-movements after Overreactions is not profitable, whilst one based on inertia appears to be profitable but produces outcomes not statistically different from the random ones. Therefore the Overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the Efficient Market Hypothesis (EMH).
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On the Frequency of Price Overreactions
2018Co-Authors: Guglielmo Maria Caporale, Alex PlastunAbstract: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 out various statistical tests (both parametric and non-parametric) including correlation analysis, augmented Dickey–Fuller tests (ADF), Granger causality tests, and regression analysis with dummy variables. The following hypotheses are tested: whether or not the frequency of Overreactions varies over time (H1), is informative about crises (H2) and/or price movements (H3), and exhibits seasonality (H4). The null cannot be rejected except for H4, i.e. no seasonality is found. On the whole it appears that the frequency of Overreactions can provide useful information about market developments and for designing trading strategies.
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Short-Term Price Overreactions: Identification, Testing, Exploitation
2014Co-Authors: Guglielmo Maria Caporale, Luis A. Gil-alana, Alex PlastunAbstract:This paper examines short-term price reactions after one-day abnormal price changes and whether they create exploitable profit opportunities in various financial markets. A t-test confirms the presence of Overreactions and also suggests that there is an “inertia anomaly”, i.e. after an Overreaction day prices tend to move in the same direction for some time. A 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 FOREX and the commodity markets, but it is profitable in the case of the US stock market. By contrast, a strategy exploiting the “inertia anomaly” produces profits in the case of the FOREX and the commodity markets, but not in the case of the US stock market.
Guglielmo Maria Caporale - One of the best experts on this subject based on the ideXlab platform.
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Price Overreactions in the cryptocurrency market
Journal of Economic Studies, 2019Co-Authors: Guglielmo Maria Caporale, Alex PlastunAbstract:The purpose of this paper is to examine price Overreactions in the case of the following cryptocurrencies: bitcoin, litecoin, ripple and dash.,A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U-test) tests confirm the presence of price patterns after Overreactions: the next day price changes in both directions are bigger than after “normal” days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited to generate profits.,The results suggest that a strategy based on counter-movements after Overreactions is not profitable, whilst one based on inertia appears to be profitable but produces outcomes not statistically different from the random ones. Therefore, the Overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the efficient market hypothesis (EMH).,The Overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the EMH.
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Long-term price Overreactions: are markets inefficient?
Journal of Economics and Finance, 2018Co-Authors: Guglielmo Maria Caporale, Luis A. Gil-alana, Alex PlastunAbstract:This paper examines long-term price Overreactions in various financial markets (commodities, US stock market and FOREX). First, a number of statistical tests are carried out for Overreactions as a statistical phenomenon. Second, a trading robot approach is applied to test the profitability of two alternative strategies, one based on the classical Overreaction anomaly, the other on a so-called “inertia anomaly”. Both weekly and monthly data are used. Evidence of anomalies is found predominantly in the case of weekly data. In the majority of cases strategies based on Overreaction anomalies are not profitable, and therefore the latter cannot be seen as inconsistent with the EMH.
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Price Overreactions in the Cryptocurrency Market
CESifo Working Papers, 2018Co-Authors: Guglielmo Maria Caporale, Alex PlastunAbstract:This paper examines price Overreactions in the case of the following cryptocurrencies: BitCoin, LiteCoin, Ripple and Dash. A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U test) tests confirm the presence of price patterns after Overreactions: the next-day price changes in both directions are bigger than after “normal” days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited to generate profits. The results suggest that a strategy based on counter-movements after Overreactions is not profitable, whilst one based on inertia appears to be profitable but produces outcomes not statistically different from the random ones. Therefore the Overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the Efficient Market Hypothesis (EMH).
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On the Frequency of Price Overreactions
2018Co-Authors: Guglielmo Maria Caporale, Alex PlastunAbstract: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 out various statistical tests (both parametric and non-parametric) including correlation analysis, augmented Dickey–Fuller tests (ADF), Granger causality tests, and regression analysis with dummy variables. The following hypotheses are tested: whether or not the frequency of Overreactions varies over time (H1), is informative about crises (H2) and/or price movements (H3), and exhibits seasonality (H4). The null cannot be rejected except for H4, i.e. no seasonality is found. On the whole it appears that the frequency of Overreactions can provide useful information about market developments and for designing trading strategies.
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Long-Term Price Overreactions: Are Markets Inefficient?
SSRN Electronic Journal, 2015Co-Authors: Guglielmo Maria Caporale, Luis A. Gil-alana, Oleksiy PlastunAbstract:This paper examines long-term price Overreactions in various financial markets (commodities, US stock market and FOREX). First, t-tests are carried out for Overreactions as a statistical phenomenon. Second, a trading robot approach is applied to test the profitability of two alternative strategies, one based on the classical Overreaction anomaly, the other on a so-called “inertia anomaly”. Both weekly and monthly data are used. Evidence of anomalies is found predominantly in the case of weekly data. In the majority of cases strategies based on Overreaction anomalies are not profitable, and therefore the latter cannot be seen as inconsistent with the EMH.
Nikolaos Pavlidis - One of the best experts on this subject based on the ideXlab platform.
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Individual Analysts Earnings Forecasts: Evidence For Overreaction In The UK Stock Market
International Business & Economics Research Journal (IBER), 2011Co-Authors: Dimitris Kenourgios, Nikolaos PavlidisAbstract:This paper presents an analysis of two forms of Overreaction (generalized Overreaction and Overreaction to prior earnings changes) in analysts earnings forecasts for the UK stock market, using a sample of individual forecasts of earning per share from a British investment bank over the period 1989-2002. Given that previous UK empirical research over 1980s and mid 90s has provided limited and contradictory findings, we investigate whether and how Overreaction of analysts forecasts varies across forecast horizons, firm size (small and large) and growth opportunities (high and low P/E ratio) in order to provide further and comparable evidence. Overall, our findings support the generalized Overreaction hypothesis but reject the firm size effect, the Overreaction for high P/E ratio companies and the higher Overreaction regarding the forecasting horizon. Keywords: Overreaction, Underreaction, Analysts forecasts, forecast horizons, size effect, price/earnings ratio.
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Individual Analysts’ Earnings Forecasts: Evidence for Overreaction in the UK Stock Market
2005Co-Authors: Dimitris Kenourgios, Nikolaos PavlidisAbstract:This paper presents an analysis of two forms of Overreaction (generalized Overreaction and Overreaction to prior earnings changes) in analysts’ earnings forecasts for the UK stock market, using a sample of individual forecasts of earning per share from a British investment bank over the period 1989-2002. Given that previous UK empirical research over 1980s and mid ‘90s has provided limited and contradictory findings, we investigate whether and how Overreaction of analysts forecasts varies across forecast horizons, firm size (small and large) and growth opportunities (high and low P/E ratio) in order to provide further and comparable evidence. Overall, our findings support the generalized Overreaction hypothesis but reject the firm size effect, the Overreaction for high P/E ratio companies and the higher Overreaction regarding the forecasting horizon.
Dimitris Kenourgios - One of the best experts on this subject based on the ideXlab platform.
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Individual Analysts Earnings Forecasts: Evidence For Overreaction In The UK Stock Market
International Business & Economics Research Journal (IBER), 2011Co-Authors: Dimitris Kenourgios, Nikolaos PavlidisAbstract:This paper presents an analysis of two forms of Overreaction (generalized Overreaction and Overreaction to prior earnings changes) in analysts earnings forecasts for the UK stock market, using a sample of individual forecasts of earning per share from a British investment bank over the period 1989-2002. Given that previous UK empirical research over 1980s and mid 90s has provided limited and contradictory findings, we investigate whether and how Overreaction of analysts forecasts varies across forecast horizons, firm size (small and large) and growth opportunities (high and low P/E ratio) in order to provide further and comparable evidence. Overall, our findings support the generalized Overreaction hypothesis but reject the firm size effect, the Overreaction for high P/E ratio companies and the higher Overreaction regarding the forecasting horizon. Keywords: Overreaction, Underreaction, Analysts forecasts, forecast horizons, size effect, price/earnings ratio.
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Overreaction Hypothesis in Emerging Balkan Stock Markets
2009Co-Authors: Dimitris Kenourgios, Aristeidis SamitasAbstract:This paper examines Overreaction hypothesis in four emerging Balkan stock markets (Bulgaria, Romania, Croatia,Turkey), using average returns of four developed markets (US, UK, Germany and Greece), during the period 2000-2007. The hypothesis tested is that developed market movements create Overreaction to Balkan ones. We apply the Dimson’s (1979) aggregated coefficients method upon the conventional market model and an asymmetric non-linear smooth-transition generalized autoregressive conditional heteroskedasticity (ANST –GARCH) model. The findings provide evidence on accepting the Overreaction hypothesis in Balkan markets and on excess volatility with asymmetric mean reversion patterns. The findings also support that a “momentum” portfolio strategy is the most appropriate for exceptional returns in emerging Balkan markets.
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Individual Analysts’ Earnings Forecasts: Evidence for Overreaction in the UK Stock Market
2005Co-Authors: Dimitris Kenourgios, Nikolaos PavlidisAbstract:This paper presents an analysis of two forms of Overreaction (generalized Overreaction and Overreaction to prior earnings changes) in analysts’ earnings forecasts for the UK stock market, using a sample of individual forecasts of earning per share from a British investment bank over the period 1989-2002. Given that previous UK empirical research over 1980s and mid ‘90s has provided limited and contradictory findings, we investigate whether and how Overreaction of analysts forecasts varies across forecast horizons, firm size (small and large) and growth opportunities (high and low P/E ratio) in order to provide further and comparable evidence. Overall, our findings support the generalized Overreaction hypothesis but reject the firm size effect, the Overreaction for high P/E ratio companies and the higher Overreaction regarding the forecasting horizon.
Oleksiy Plastun - One of the best experts on this subject based on the ideXlab platform.
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Momentum and Contrarian Effects in the Ukrainian Stock Market: Case of Daily Overreactions
2020Co-Authors: Oleksiy Plastun, Nataliya Strochenko, Olga Zhmaylova, Liudmyla Sliusareva, Sergiy BashlayAbstract:This paper examines momentum and contrarian effects in the Ukrainian stock market after one-day abnormal returns. To do this, UX futures data over the period 2010–2018 are used. The following hypotheses are tested: H1) hourly returns on Overreaction days differ from hourly returns on normal days, H2) there are price patterns on Overreaction days, and H3) to test these hypotheses, visual inspection and average analysis are used, as well as t-tests, cumulative abnormal returns, and trading simulation approaches. The results suggest that there are statistically significant differences between intraday dynamics during the usual days and the Overreactions day. There is a strong momentum effect present on the day of Overreaction: prices tend to change only in the direction of the Overreaction during the whole day. The fact of the Overreaction becomes clear after 13:00-14:00. This gives a lot of time to explore the momentum effect in the day of Overreaction. On the day after the Overreaction, prices tend to go in the opposite direction: contrarian pattern is detected, which is in line with the Overreaction hypothesis. Based on detected price patterns, rules of trading and trading strategies for the Ukrainian stock market are developed. Momentum Strategy (based on price patterns on the day of Overreaction) generates several successful trades; close to with 90%, and their number being is profitable (trading results differ from the random ones – confirmed by t-tests). Contrarian Strategy (based on price patterns on the day after the Overreaction) demonstrates low efficiency, and results do not differ from random trading.
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Exploring Frequency of Price Overreactions in the Ukrainian Stock Market
2018Co-Authors: Oleksiy Plastun, Inna Makarenko, Lyudmila Khomutenko, Yanina Belinska, Maryna Dmytrivna DomashenkoAbstract:This paper explores the frequency of price Overreactions in the Ukrainian stock market by focusing on the PFTS Index over the period 2006–2017 and UX index over the period 2008–2017, as well as some “blue chips” (BAVL, UNAF, MSICH, CEEN) 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 purposes (H2), and exhibits seasonality (H3). To do this, various statistical tests (both parametric and non-parametric), including correlation analysis, augmented Dickey-Fuller tests (ADF), Granger causality tests, and regression analysis with dummy variables, are carried out. Hypotheses H1 and H2 are confirmed: frequency of price Overreactions can be used as a crisis predictor (a sharp increase in the number of Overreactions is associated with a crisis period) and could be used to predict stock returns. No seasonality in the Overreactions frequency is found. Implications of this research include crisis prediction and stock market prices forecasting and can be used for designing trading strategies.
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Long-Term Price Overreactions: Are Markets Inefficient?
SSRN Electronic Journal, 2015Co-Authors: Guglielmo Maria Caporale, Luis A. Gil-alana, Oleksiy PlastunAbstract:This paper examines long-term price Overreactions in various financial markets (commodities, US stock market and FOREX). First, t-tests are carried out for Overreactions as a statistical phenomenon. Second, a trading robot approach is applied to test the profitability of two alternative strategies, one based on the classical Overreaction anomaly, the other on a so-called “inertia anomaly”. Both weekly and monthly data are used. Evidence of anomalies is found predominantly in the case of weekly data. In the majority of cases strategies based on Overreaction anomalies are not profitable, and therefore the latter cannot be seen as inconsistent with the EMH.
