Profitability of technical trading strategies under market manipulation

Most technical trading strategies use the official closing price for analysis. But what is the effect when the official closing price is subject to market manipulation? This paper answers this question by testing the difference of profitabilities between using the official closing price and the last tick price. The results show a significant improvement of profitability by using the last tick price over the official closing price based on a data set in Hong Kong from 2011 to 2018.

On extreme value theory in the presence of technical trend: pre and post Covid-19 analysis of cryptocurrency markets

Purpose Research on price extremes and overreactions as potential violations of market efficiency has a long tradition in investment literature. Arguably, very few studies to date have addressed this issue in cryptocurrencies trading. The purpose of this paper is to consider the extreme value modelling for forecasting COVID-19 effects on cryptocoin markets. Additionally, this paper examines the importance of technical trading indicators in predicting the extreme price behaviour of cryptocurrencies. Design/methodology/approach This paper decomposes the daily-time series returns of four cryptocurrency returns into potential maximum gains (PMGs) and potential maximum losses (PMLs) at first and then tests their lead–lag relations under an econometric framework. This paper also investigates the non-random properties of cryptocoins by computing the incremental explanatory power of PML–PMG modelling with technical trading indicators controlled. Besides, this paper executes an event study to identify significant changes caused by COVID-19-related events, which is capable of analysing the cryptocoin market overreactions. Findings The findings of this paper produce the evidence of both market overreactions and trend persistence in the potential gains and losses from coins trading. Extreme price behaviour explains volatility and price trends in crypto markets before and after the outbreak of a pandemic that substantiate the non-random walk behaviour of crypto returns. The presence of technical trading indicators as control variables in the extreme value regressions significantly improves the predictive power of models. COVID-19 crisis affects the market efficiency of cryptocurrencies that improves the usefulness of extreme value predictions with technical analysis. Research limitations/implications This paper strongly supports for the robustness of technical trading strategies in cryptocurrency markets. However, the “beast is moving quick” and uncertainty as to the new normalcy about the post-COVID-19 world puts constraint on making best predictions. Practical implications The paper contributes substantially to our understanding of the pricing efficiency of cryptocurrency markets after the COVID-19 outbreak. The findings of continuing return predictability and price volatility during COVID-19 show that profitable investment opportunities for cryptocoin traders are prevailing in pandemic times. Originality/value The paper is unique to understand extreme return reversals behaviour of cryptocurrency markets regarding events related to COVID-19 breakout.

The Predictability and profitability of Trading Range Break-out Trading Rules: Evidence from Pakistan Stock Exchange

The efficient market hypothesis has been one of themost extensively researched topics in the academic literature for decades. An implication ofweak form of efficiency is that the technical trading rules will not produce abnormal returns. The purpose of this research is to analyze findings of application of trading range breakout test on daily closing share prices of 100 companies listed on a Pakistan Stock Exchange over ten years from 2006 to 2015,thus examining its efficiency at the weak form. The results show strong support for trading range break-out rules having both predictability and profitability for PSX. It refers that the returns from these rules are not same as investors earn from a naïve buy and hold strategy. The uses of the trading range break-out rules produce abnormal returns to investors and hence nullify the weak form of efficiency on PSX.

The Financialization of Crude Oil Markets and Its Impact on Market Efficiency: Evidence from the Predictive Ability and Performance of Technical Trading Strategies

Oil price forecasts are of crucial importance for many policy institutions, including the European Central Bank and the Federal Reserve Board, but projecting oil market evolutions remains a complicated task, further exacerbated by the financialization process that characterizes the crude oil markets. The efficiency (in Fama’s sense) of crude oil markets is revisited in this research through the investigation of the predictive ability of technical trading rules (TTRs). The predictive ability and trading performance of a plethora of TTRs are explored on the crude oil markets, as well as on the energy sector ETF XLE, while taking a special focus on the turbulent COVID-19 pandemic period. We are interested in whether technical trading strategies, by signaling the right timing of market entry and exits, can predict oil market movements. Research findings help to confidently conclude on the weak-form efficiency of the WTI crude oil and the XLE fund markets throughout the 1999–2021 period relative to the universe of TTRs. Moreover, results attest that TTRs do not add value to the Brent market beyond what may be expected by chance over the pre-pandemic 1999–2019 period, confirming the efficiency of the market before 2020. Nonetheless, research findings also suggest some temporal inefficiency of the Brent market during the 1 and ¼ years of pandemic period, with important consequences for energy markets’ practitioners and issuers of policy. Research findings further imply that there is evidence of a more intense financialization of the WTI crude oil market, which requires tighter measures from regulators during distressed markets. The Brent oil market is affected mainly by variations in oil demand and supply at the world level and to a lesser degree by financialization and the activity of market practitioners. As such, we conclude that different policies are needed for the two oil markets and also that policy issuers should employ distinct techniques for oil price forecasting.