scholarly journals HAS THE GLOBAL PANDEMIC OF 2020 LED TO PERSISTENCE IN THE SHARE PRICES OF LARGE GLOBAL COMPANIES?

2021 ◽  
Author(s):  
Hortense Santos ◽  
◽  
Rui Dias ◽  
Cristina Vasco ◽  
Paulo Alexandre ◽  
...  
Keyword(s):  
Stock Prices ◽  
Research Question ◽  
Correlation Coefficients ◽  
Trading Strategies ◽  
Fluctuation Analysis ◽  
Additional Risk ◽  
Share Prices ◽  
Global Pandemic ◽  
Global Companies ◽  
Detrended Fluctuation

This paper aims to analyze the predictability of the stocks of Apple, Microsoft Amazon.com, Tesla, Facebook, Samsung, Electronics, Johnson & Johnson, Walmart, in the period from October 1, 2019 to January 11, 2021. To carry out such an analysis, it is intended to answer two research questions, namely: (i) is there predictability in the stock prices of the companies under analysis? (ii) Can investors diversify risk by incorporating these companies’ shares into their portfolios? The results of the Exponents Detrended Fluctuation Analysis (DFA) show that Apple (0.51) Microsoft (0.49), Amazon.com (0.53), Samsung Electronics (0.53), Johnson & Johnson (0.53) do not have long memories in their time series, that is, investors cannot obtain abnormal profitability without incurring additional risk. Walmart (0.41) has anti-persistence, while Tesla (0.60), Facebook (0.55) indicate some predictability, meaning investors adjusting their trading strategies to the necessary missteps may have some above-average profitability, which partly rejects the first question of the research. To answer the second research question, we estimated the Detrended cross-correlation coefficient (pDCCA) model, which indicates 17 mean correlation coefficients (≈ 0.333 → ≈ 0.666), 7 strong cross-trend correlation coefficients (0.666 → ≈ 1,000), 4 weak correlation coefficients (≈ 0.000 → ≈ 0.333). These results show that investors should be careful to incorporate the shares of these companies into a single portfolio; the suggestion would be to group only the shares of companies that do not present predictability and have low rhoDCCA. The authors consider that this evidence will be important for institutional investors when carrying out trading strategies based on maximizing profitability, but also mitigating risk when diversifying.

The Impact of the COVID-19 Pandemic on Stock Markets

2020 ◽  
Vol 1 (2) ◽  
pp. 57-70
Author(s):  
Rui Dias ◽  
João Manuel Pereira
Keyword(s):  
Financial Markets ◽  
Global Economy ◽  
Structural Breaks ◽  
Research Question ◽  
Causal Link ◽  
Data Series ◽  
Fluctuation Analysis ◽  
Wald Tests ◽  
The Impact ◽  
Detrended Fluctuation

COVID-19 has had a marked impact on the global economy, resulting in uncertainty, pessimism, and adverse effects on financial markets. In light of this event, this paper aims to test whether the evolution of COVID-19 (confirmed cases and deaths) is responsible for the stock market indices in eight European countries, from December 31, 2019 to July 23, 2020. Two key research questions have been raised to determine this causal link: Does the increase in COVID-19 cases and deaths cause shockwaves in Europe's financial markets? If so, does the presence of long memories cause high levels of arbitration? The results show mostly structural breaks in March 2020. In contrast, the VAR Granger Causality/Block Exogeneity Wald Tests model shows that the COVID-19 data series (confirmed cases and deaths) do not cause shocks in Europe's financial markets, which in return does not validate the first research question. The results of the exponents detrended fluctuation analysis (DFA) shows significant long memories ranging between 0.61-0.73.

scholarly journals A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets

2019 ◽  
Vol 12 (2) ◽  
pp. 67 ◽  
Author(s):  
Kyriazis
Keyword(s):  
Long Memory ◽  
Detrended Fluctuation Analysis ◽  
Efficient Market Hypothesis ◽  
Trading Strategies ◽  
Fluctuation Analysis ◽  
Efficient Market ◽  
Systematic Survey ◽  
Rescaled Range ◽  
Pricing Behavior ◽  
Detrended Fluctuation

This study conducts a systematic survey on whether the pricing behavior of cryptocurrencies is predictable. Thus, the Efficient Market Hypothesis is rejected and speculation is feasible via trading. We center interest on the Rescaled Range (R/S) and Detrended Fluctuation Analysis (DFA) as well as other relevant methodologies of testing long memory in returns and volatility. It is found that the majority of academic papers provides evidence for inefficiency of Bitcoin and other digital currencies of primary importance. Nevertheless, large steps towards efficiency in cryptocurrencies have been traced during the last years. This can lead to less profitable trading strategies for speculators.

scholarly journals THE IMPACT OF COVID-19 ON EXCHANGE RATE VOLATILITY: AN ECONOPHYSICS APPROACH

2020 ◽  
Author(s):  
Rui Dias ◽  
◽  
Hortense Santos ◽  
Keyword(s):  
Exchange Rates ◽  
Correlation Coefficient ◽  
Cross Correlation ◽  
Exchange Rate Volatility ◽  
Correlation Coefficients ◽  
Weak Form ◽  
Fluctuation Analysis ◽  
Global Pandemic ◽  
Exchange Markets ◽  
The Impact

This paper aims to analyze the efficiency, in its weak form, between exchange rates, US-RMB, US-EUR, US-JPY, US-MYR, US-PHP, US-SGD, US-THB, US-CHF, US-GBP, in the period from July 1, 2019 to October 27, 2020. To perform this analysis, different approaches were undertaken to assess whether: (i) the impact of the global pandemic created long memories in international foreign exchange markets? The results of the exponents Detrended Fluctuation Analysis (DFA) show that the exchange rates US-THB (0.60), US-MYR (0.59), US-SGD (0. 59), present long memories, to a lesser extent the exchange pairs US-GBP (0.56), US-EUR (0.53). On the other side, exchange rates US-RMB (0. 47), US-JPY (0. 43), US-CHF (0. 46), US-PHP (0. 38) show anti persistence, while the Detrended cross-correlation coefficient (𝑝𝐷𝐶𝐶𝐴) results show 19 average correlation coefficients (≌ 0.333 → ≌ 0.666), 10 weak correlation coefficient (≌ 0,000 → ≌ 0.333), 7 strong non-trend cross correlation coefficients (0.666→ ≌ 1,000). In conclusion, we show that the exchange pairs analyzed show some predictability, that is, there are levels of arbitrage that can be explored by investors; we also found that the exchange rates analyzed have characteristics of diversification, due to the low autocorrelation between markets. The objective of this study was not to analyze abnormal profitability by investors without incurring additional risk.

STATISTICAL REVISIT TO THE MIKE-FARMER MODEL: CAN THIS MODEL CAPTURE THE STYLIZED FACTS IN REAL WORLD MARKETS?

Fractals ◽  
2013 ◽  
Vol 21 (02) ◽  
pp. 1350008 ◽  
Author(s):  
LING-YUN HE ◽  
XING-CHUN WEN
Keyword(s):  
Real World ◽  
Stock Prices ◽  
Double Auction ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Stylized Facts ◽  
Volatility Clustering ◽  
World Markets ◽  
Continuous Double Auction ◽  
Detrended Fluctuation

According to current literature, the Mike-Farmer (MF) model1 is constructed empirically based on the continuous double auction mechanism in an order-driven market, which can successfully capture the diffusive behavior of stock prices at the transaction level. In our paper, we revisit the statistical properties of the generated series of prices based on the MF model to clarify whether it can reproduce the stylized facts in real world markets. However, the Detrended Fluctuation Analysis (DFA) scaling exponent of volatility Hv ≈ 0.6, which may be slightly lower than that in real markets; while a modified version of the MF model proposed by Gu and Zhou2 can improve the DFA scaling exponent of volatility Hv ≈ 0.75, which is closer to the empirical findings. Finally, we test the existence of another commonly found two stylized facts in the real world: the volatility clustering, and leverage effect.

scholarly journals On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market

2020 ◽  
Vol 13 (1) ◽  
pp. 8 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Stephen Chan ◽  
Jeffrey Chu ◽  
Hana Sulieman
Keyword(s):  
Market Efficiency ◽  
High Frequency ◽  
Trading Strategies ◽  
High Frequency Data ◽  
Fluctuation Analysis ◽  
Bear Market ◽  
The Past ◽  
Arbitrage Opportunities ◽  
Rolling Window ◽  
Detrended Fluctuation

The market for cryptocurrencies has experienced extremely turbulent conditions in recent times, and we can clearly identify strong bull and bear market phenomena over the past year. In this paper, we utilise algorithms for detecting turnings points to identify both bull and bear phases in high-frequency markets for the three largest cryptocurrencies of Bitcoin, Ethereum, and Litecoin. We also examine the market efficiency and liquidity of the selected cryptocurrencies during these periods using high-frequency data. Our findings show that the hourly returns of the three cryptocurrencies during a bull market indicate market efficiency when using the detrended-fluctuation-analysis (DFA) method to analyse the Hurst exponent with a rolling window. However, when conditions turn and there is a bear-market period, we see signs of a more inefficient market. Furthermore, our results indicated differences between the cryptocurrencies in terms of their liquidity during the two market states. Moving from a bull to a bear market, Ethereum and Litecoin appear to become more illiquid, as opposed to Bitcoin, which appears to become more liquid. The motivation to study the high-frequency cryptocurrency market came from the increasing availability of higher-frequency cryptocurrency-pricing data. However, it also comes from a movement towards higher-frequency trading of cryptocurrency. In addition, the efficiency of cryptocurrency markets relates not only to whether prices are predictable and arbitrage opportunities exist, but, more widely, to topics such as testing the profitability of trading strategies and determining the maturity of cryptocurrency markets.

scholarly journals THE IMPACT OF THE COVID-19 ON THE FINANCIAL MARKETS: EVIDENCE FROM G7

2020 ◽  
Author(s):  
Paula Heliodoro ◽  
◽  
Rui Dias ◽  
Paulo Alexandre ◽  
Maria Manuel ◽  
...  
Keyword(s):  
United Kingdom ◽  
Financial Markets ◽  
Open Space ◽  
Research Question ◽  
Correlation Coefficients ◽  
Stock Index ◽  
Global Pandemic ◽  
Canadian Market ◽  
Stock Indexes ◽  
The Impact

This essay aims to analyse the impact of the 2020 global pandemic on the stock indexes of France (CAC 40), Germany (DAX 30), USA (DOW JONES), United Kingdom (FTSE 100), Italy (FTSE MID), Japan (Nikkei 225) and Canada (TSX 300), from January 2018 to June 2020, with the sample being divided into two sub periods: first sub period from January 2018 to August 2019 (Pre-Covid); second period from September 2019 to June 2020 (Covid-19). In order to carry out this analysis, different approaches were taken in order to analyse whether: (i) the global pandemic (Covid-19) increased the persistence of the G7 financial markets? In the Pre-Covid period, we can verify the presence of long memories in the Canadian market (TSX), while the markets in France (CAC 40) and Italy (FTSE MID) show signs of balance, since the random walk hypothesis was not rejected. The German (DAX 30), USA (DJI), United Kingdom (FTSE 100) and Japan (NIKKEI 225) markets have anti-persistence (0 <α <0.5). In period II, the Covid-19-time scale is contained, and we verified the presence of significant long memories, except for the US stock index (0.49). These findings make it possible to show that the assumption of the market efficiency hypothesis may be called into question, because these markets are predictable, which validate the research question. The results of the pDCCA correlation coefficients, in the Pre-Covid period, show 14 pairs of median markets (0.333 → ≌ 0.666). We can also see 7 pairs of markets with strong correlation coefficients (0.666 → ≌ 1,000), showing that these markets have a tendency towards integration, this evidence may call into question the hypothesis of portfolio diversification. In period II (Covid-19) the λ_DCCA correlation coefficients have 7 strong market pairs (0.666 → ≌ 1,000), 5 pairs have weak pDCCA coefficient (0.000 → ≌ 0.333), 5 market pairs show anti-correlation (-1.000 → ≌ 0.000), and 4 market pairs show median coefficients (pDCCA) (0.333 → ≌ 0.666) (out of 21 possible). When compared to the previous subperiod, we found that the majority of the pDCCAs decreased, which shows that the markets have decreased their integration, making it possible to diversify portfolios in certain markets, especially in the Japanese market (NIKKEI 225). These conclusions open space for market regulators to take measures to ensure better informational information, in the stock markets, in the 7 most advanced economies in the world.

COVID-19 Pandemic and Its Influence on Safe Havens

2021 ◽  
pp. 289-303
Author(s):  
Rui Teixeira Dias ◽  
Pedro Pardal ◽  
Hortense Santos ◽  
Cristina Vasco
Keyword(s):  
Hong Kong ◽  
South Korea ◽  
Detrended Fluctuation Analysis ◽  
Research Question ◽  
Fluctuation Analysis ◽  
Safe Harbor ◽  
Portfolio Rebalancing ◽  
Gold Market ◽  
Regional Markets ◽  
Detrended Fluctuation

This chapter aims to analyze the rebalancing of portfolios in the financial markets of China Hong Kong, Malaysia, Singapore, Indonesia, Japan, Philippines, Thailand, South Korea, gold (Bullion(Zurich) kg(995) CHF), silver (Paris Spot E/KG), platinum (Paris Spot E/KG), in the period from 2 September 2019 to 2 September 2020. The rhoDCCA results show that platinum is not a safe port for portfolio rebalancing in these regional markets, while silver is also not a safe port for the markets of Malaysia (KLSE), South Korea (KOSPI). As far as gold is concerned, the authors do not see any strong rhoDCCA which could be a safe harbor for these regional markets in this period of the 2020 pandemic crisis, which partly validates the first research question. The exponents detrended fluctuation analysis (DFA) show pronounced long memories, with the exception made to the gold market that shows signs of balance, that is, the second question of investigation is validated.

Profit Opportunities from Vedanta and Cairn India Merger

2019 ◽  
Vol 23 (01) ◽  
pp. 65-89
Author(s):  
Pitabas Mohanty ◽  
Supriti Mishra
Keyword(s):  
Stock Prices ◽  
Trading Strategies ◽  
Share Prices ◽  
The Uk ◽  
Formal Communication ◽  
To Receive

On June 14, 2015, Vedanta Resources PLC of the UK announced the merger of two of its Indian subsidiaries, namely, Vedanta Limited and Cairn India Limited. Per the terms of the merger, Vedanta Limited would issue one share of itself for every share of Cairn India. In addition, it would also issue a preference share of INR 10 in face value. The stock prices of the two companies, however, soon started trading outside the range suggested by the above exchange ratio. This gave rise to different possible trading strategies for the investors with different possible outcomes. The case is written around mid-September 2015, when the share prices of both companies declined and the shareholders were yet to receive any formal communication from the management.

How fast do stock prices adjust to market efficiency? Evidence from a detrended fluctuation analysis

2013 ◽  
Vol 392 (7) ◽  
pp. 1631-1637 ◽  
Author(s):  
Juan C. Reboredo ◽  
Miguel A. Rivera-Castro ◽  
José G.V. Miranda ◽  
Raquel García-Rubio
Keyword(s):  
Market Efficiency ◽  
Stock Prices ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Detrended Fluctuation

scholarly journals Efficiency of Asean-5 Markets: An Detrended Fluctuation Analysis

2020 ◽  
Vol 12 (2) ◽  
pp. 13-19
Author(s):  
Rui Dias ◽  
Paula Heliodoro ◽  
Paulo Alexandre
Keyword(s):  
Random Walk ◽  
Financial Markets ◽  
Stock Prices ◽  
Detrended Fluctuation Analysis ◽  
Abnormal Returns ◽  
Weak Form ◽  
The Philippines ◽  
Fluctuation Analysis ◽  
Chinese Market ◽  
Detrended Fluctuation

This study intends to analyse efficiency, in its weak form, in the financial markets of Indonesia, Malaysia, Philippines, Singapore, Thailand (ASEAN-5), and China, during the global pandemic (Covid-19). Different approaches have been undertaken to carry out this analysis in order to determine whether: (i) ASEAN-5 financial markets and China are efficient, in their weak form, during the analysis period? The results indicate that the random walk hypothesis is rejected in all markets. The values of the variance ratios are, in all cases, lower than the unit, which implies that the returns are autocorrelated over time and, there is a reversion to the average, in all indices. In corroboration, the exponents Detrended Fluctuation Analysis (DFA), indicate significant long memories with a larger incidence in the Philippines and Singapore markets, however the Chinese market evidences anti persistence. These results demonstrate that stock prices do not completely reflect the available information and that stock prices movements are not i.i.d. This has implications for investors, as some returns can be expected, creating opportunities for arbitrage and abnormal returns, contrary to the assumptions of random walk and information efficiency. These conclusions also allow market regulators to implement measures to ensure better information in these regional markets.

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