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In this paper, we use a statistical arbitrage method in different developed and emerging countries to show that the profitability of the strategy is based on the degree of market efficiency. We will show that our strategy is more profitable in emerging ones and in periods with greater uncertainty. Our method consists of a Pairs Trading strategy bas...
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... presented by Ramos-Requena et al. [35], to comply with this property, investors must consider pairs with a value of the Hurst exponent (H) below 0.5. Figures 1-3 show the relationship between the H value and the average return obtained for each of the periods studied (2000-07, 2007-14, 2014-20), in which all the countries considered in this paper are included. It can be seen that, as the value of H decreases, the average profitability increases for the three periods studied, it being significant that pairs with a value of 0.5 give negative average profitability. ...
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Citations
... Secondly, and considering the possibility of arbitrage, the presence of inefficiencies ends up generating windows of opportunities for abnormal gains, which, as they are detected and taken advantage of by various agents in the stock market, are no longer relevant, which implies a reduction of movements in the market focused on that strategy, which, in turn, ends up increasing market efficiency. Such conclusion is corroborated by the analyses of Dima et al. (2021), Balladares et al. (2021), andSánchez-Granero et al. (2020), signaling that the existence of a higher degree of inefficiency enables the use of graphical analyses to obtain abnormal returns. ...
... Physicists have provided a completely different perspective through the introduction of the Hurst exponent to study market efficiency (Beben and Orłowski 2001;Di Matteo et al. 2005;Zunino et al. 2007;Cajueiro and Tabak 2005;Kristoufek and Vosvrda 2014;Sánchez-Granero et al. 2020;Balladares et al. 2021). Hurst (1951) attempted to optimize the storage capacity of a reservoir intended to regulate the natural contributions of the Nile River. ...
This research aims to improve the efficiency in estimating the Hurst exponent in financial time series. A new procedure is developed based on equality in distribution and is applicable to the estimation methods of the Hurst exponent. We show how to use this new procedure with three of the most popular algorithms (generalized Hurst exponet, total triangles area, and fractal dimension) in the literature. Findings show that this new approach improves the accuracy of the original methods, mainly for longer series. The second contribution of this study is that we show how to use this methodology to test whether the series is self-similar, constructing a confidence interval for the Hurst exponent for which the series satisfies this property. Finally, we present an empirical application of this new procedure to stocks of the S &P500 index. Similar to previous contributions, we consider this to be relevant to financial literature, as it helps to avoid inappropriate interpretations of market efficiency that can lead to erroneous decisions not only by market participants but also by policymakers.
... Pairs Trading is a market-neutral statistical arbitrage strategy. Recent studies (Ramos-Requena et al. [30]) have proved that it is a profitable strategy in periods of high instability in developed markets and also in nonefficient markets (Sanchez-Granero et al. [47] and Balladares et al. [48]) such as emerging ones. ...
Based on recent works on stocks comovement, Pairs Trading’s strategy is enhanced by reducing the stock universe to the stocks with the lower volatility on a given date. From this universe of low volatility stocks, pairs are selected by looking for pairs whose series present a high degree of antipersistence. Finally, a “reversion to the mean” strategy is applied to these pairs. It is shown that, with this approach to Pairs Trading, positive results can be obtained for stock from the Nasdaq stock exchange, mainly during bull markets and low volatility periods.
... What are the impacts of contagion risks from the economic crisis? We want to note that the contagion effect refers to the extreme correlation coefficients among different economies, and it mainly occurs when the value of correlation coefficients increases during extreme events such as economic crises [3][4][5]. ...
Contagion has been one of the most widely studied and challenging problems in recent economic research. This paper aims at capturing the main impact of contagion risk of the U.S. on foreign direct investment inflows in 18 emerging countries. To quantify the degree of contagion, the time-varying tail dependence copula is employed. Then, the Granger causality test and time series regression analysis are used to investigate the temporal and contemporaneous effects of contagion risk on investment inflows, respectively. Overall, the results confirm the time-varying contagion effects of the U.S. economy on 18 emerging economies. The size of contagion effects gradually increases for all countries, except Thailand, the Philippines, Argentina, and Chile. Furthermore, the results of the Granger causality test and regression reveal that temporal and contemporaneous effects of contagion risk on investment inflows exist in 8 out of 18 countries.
Nowadays, statistical arbitrage is one of the most attractive fields of study for researchers, and its applications are widely used also in the financial industry. In this work, we propose a new approach for statistical arbitrage based on clustering stocks according to their exposition on common risk factors. A linear multifactor model is exploited as theoretical background. The risk factors of such a model are extracted via Principal Component Analysis by looking at different time granularity. Furthermore, they are standardized to be handled by a feature selection technique, namely the Adaptive Lasso, whose aim is to find the factors that strongly drive each stock’s return. The assets are then clustered by using the information provided by the feature selection, and their exposition on each factor is deleted to obtain the statistical arbitrage. Finally, the Sequential Least SQuares Programming is used to determine the optimal weights to construct the portfolio. The proposed methodology is tested on the Italian, German, American, Japanese, Brazilian, and Indian Stock Markets. Its performances, evaluated through a Cross-Validation approach, are compared with three benchmarks to assess the robustness of our strategy.
