Force-majeure events and financial market’s behavior

Efficient market hypothesis fails from time to time. There are many reasons why it happens. We will try to concentrate on one of them – force-majeure events – situations when something important happens unexpectedly. In this case market simply can’t absorb information in one moment. So for some period of time it becomes inefficient and stays inefficient until new information will not be included by the market. Such situations give us possibility to predict the market’s behavior. This is our intuitive assumption. To confirm or refuse it we will analyze the reaction of financial markets to the biggest force-majeure events during last 20 years. Also we will try to develop a trading strategy based on financial market’s reaction to force- majeure events

Ефект місяця року на ринку криптовалют і портфельний менеджмент

Purpose – to investigate the Month of the year effect in the cryptocurrency market. Design/Method/Research Approach. A number of parametric and non-parametric technics are used, including average analysis, Student's t-test, ANOVA, Kruskal-Wallis statistic test, and regression analysis with the use of dummy variables. Findings. In general (case of overall testing – when all data is analyzed at once) calendar the Month of the Year Effect is not present in the cryptocurrency market. But results of separate testing (data from the period “suspicious for being anomaly” with all the rest of the data, except the values which belong to the “anomaly data set”) shows that July and August returns are much lower than returns on other months. These are the worst months to buy Bitcoins. Theoretical implications. Results of this paper claim to find some holes in the efficiency of the cryptocurrency market, which can be exploited. This contradicts the Efficient Market Hypothesis. Practical implications. Results of this paper claim to find some holes in the efficiency of the cryptocurrency market, which can be exploited. This provides opportunities for effective portfolio management in the cryptocurrency market. Originality/Value. This paper is the first to explore Month of the Year Effect in the cryptocurrency market.   Paper type – empirical.   Authors gratefully acknowledge financial support from the Ministry of Education and Science of Ukraine (0117U003936).Мета роботи – дослідити ефект місяця року на ринку криптовалют. Дизайн/Метод/Підхід дослідження. Застосовано ряд параметричних і непараметричних методів, у тому числі аналіз середніх, t-критерій Стьюдента, ANOVA, статистичний тест Крускала-Уолліса, регресійний аналіз із використанням фіктивних змінних. Результати дослідження. В цілому (в разі загального тестування: всі дані проаналізовано одночасно) ефект місяця року не присутній на ринку криптовалют. Але результати окремого тестування (дані за період порівняно з усіма іншими даними, за винятком значень, які відносять до цього періоду), показали зміну цін на біткоіни в липні і в серпні набагато нижчу, ніж за інші місяці. Це найгірші місяці для покупки біткоінів. Теоретичне значення дослідження. Згідно з результатами даного дослідження з’ясовано, що на ринку криптовалют присутні «провали» в ефективності, які можна застосувати з метою отримання надприбутків. Це суперечить гіпотезі ефективного ринку. Практичне значення дослідження. Згідно з результатами даного дослідження, такі «провали» в ефективності можна застосувати під час побудови і оптимізації торгових стратегій. Це надає можливості для більш ефективного управління інвестиційним портфелем на ринку криптовалют. Оригінальність/Цінність/Наукова новизна дослідження. Ефект місяця року на ринку криптовалют до цього не розглядався в науковій літературі.   Тип статті – емпіричний.   Автори вдячно визнають фінансову підтримку Міністерства освіти і науки України (0117U003936). &nbsp

The Overreaction Hypothesis: The Case of Ukrainian Stock Market

This paper examines the short-term price reactions after one-day abnormal price changes on the Ukrainian stock market. The original method of abnormal returns calculation is examined. We find significant evidence of overreactions using the daily data over the period 2008-2012. Our analysis confirms the hypothesis that after an abnormal price movement the size of contrarian price movement is usually higher then after normal (typical) daily fluctuation. Comparing Ukrainian data with the figures from US stock market it is concluded that the Ukrainian stock market is less efficient which gives rise to opportunities for extra profits obtained from trading based on contrarian strategies. Based on results of the research we also recommend some rules of trading on short-term market overreactions

Calendar anomalies in the Ukrainian stock market

This paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student’s t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: day-of-the-week effect; turn-of-the-month effect; turn-of-the-year effect; month-of-the-year effect; January effect; holiday effect; Halloween effect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the turn-of-the-year and Halloween effect for the PFTS index, and the month-of-the-year effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the turn-of-the-year effect for the PFTS index and the month-of-the-year effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency

Calendar anomalies in the Ukrainian stock market

This paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student’s t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: day-of-the-week effect; turn-of-the-month effect; turn-of-the-year effect; month-of-the-year effect; January effect; holiday effect; Halloween effect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the turn-of-the-year and Halloween effect for the PFTS index, and the month-of-the-year effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the turn-of-the-year effect for the PFTS index and the month-of-the-year effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency

Market efficiency of traditional stock market indices and social responsible indices: the role of sustainability reporting

Corporate social responsibility, disclosed in sustainability reporting, influences the financial performance of companies. As a result, traditional stock market indices (TI) are expanded with the social responsible stock market indices (SRI). The aim of this study was to establish whether there are any differences in the behavior of the TI and SRI. To do this, the authors analyzed their efficiency. They used R/S analysis to calculate the Hurst exponent as a measure of persistence (long-term memory property). The presence of persistence was evidence in favor of less efficiency. According to empirical results, SRI has lower efficiency, in particular the Dow Jones Sustainability Index. Lower efficiency was also observed in the emerging markets with a responsible investment segment, compared to the traditional stock market indices. Further standardization and a common methodological approach to corporate sustainability reporting disclosure are proposed

Competitiveness in the Ukrainian stock market and local crisis of 2013–2015

This paper investigates competitiveness in the Ukrainian stock market during local crisis of 2013–2015. The following hypothesis is tested: crisis decreases competitiveness in the stock market. The analysis is carried out for the most liquid stocks in the Ukrainian Exchange (UX) over the period from 2010 to 2017 using both traditional measurements of market concentration (Hirschman Index, Lerner Index, Comprehensive Concentration Index, Entropy Index, Gini coefficient, etc.) and some alternative methods like regression analysis with dummy variables and Kruskal-Wallis test. The results suggest that the current degradation of the Ukrainian stock market is closely related with significant changes in the market concentration which are caused by the local crisis

Persistence in the cryptocurrency market

This paper examines persistence in the cryptocurrency market. Two different long-memory methods (R/S analysis and fractional integration) are used to analyse it in the case of the four main cryptocurrencies (BitCoin, LiteCoin, Ripple, Dash) over the sample period 2013–2017. The findings indicate that this market exhibits persistence (there is a positive correlation between its past and future values), and that its degree changes over time. Such predictability represents evidence of market inefficiency: trend trading strategies can be used to generate abnormal profits in the cryptocurrency market

Short-term price overreactions: Identification, testing, exploitation

This paper examines short-term price reactions after one-day abnormal price changes and whether they create exploitable profit opportunities in various financial markets. Statistical tests confirm the presence of overreactions and also suggest 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 in some cases it can be profitable in 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

Long memory and data frequency in financial markets

This paper investigates persistence in financial time series at three different frequencies (daily, weekly and monthly). The analysis is carried out for various financial markets (stock markets, FOREX, commodity markets) over the period from 2000 to 2016 using two different long memory approaches (R/S analysis and fractional integration) for robustness purposes. The results indicate that persistence is higher at lower frequencies, for both returns and their volatility. This is true of the stock markets (both developed and emerging) and partially of the FOREX and commodity markets examined. Such evidence against the random walk behaviour implies predictability and is inconsistent with the Efficient Market Hypothesis (EMH), since abnormal profits can be made using trading strategies based on trend analysis