Herd behaviors in the stock and foreign exchange markets

Abstract

The herd behaviors of returns for the won-dollar exchange rate and the KOSPI are analyzed in Korean financial markets. It is shown that the probability distribution P (R) of price returns R for three values of the herding parameter tends to a power-law behavior P (R) ≃ R −β with the exponents β = 2.2(the won-dollar exchange rate) and 2.4(the KOSPI). The financial crashes are found to occur at h > 2.33 when the relative increase in the probability distribution of exteremely high price returns is observed. Especially, the distribution of normalized returns shows a crossover to a Gaussian distribution for the time step ∆t = 252. Our results will be also compared to the other well-known analyses.

Financial Return Distributions: Past, Present, and COVID-19

“…This surprising behavior of the stock markets led the authors to formulate the so-called “inverse cubic law”—a conjecture that the power-law tails of the return distributions with the scaling exponent are a universal property of all stock markets at short and medium time scales [ 18 ]. Indeed, similar statistical characteristics were found by other researchers in data collected from other stock markets [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ], Forex [ 36 ], commodity markets [ 36 , 37 ], and the cryptocurrency market [ 36 , 38 , 39 , 40 ].…”

“…The former are characterized by higher liquidity and a higher transaction number than the latter; therefore, generally, the situation is parallel to the previous cases. Studies of the data from the emerging markets report thick tails with small scaling exponents more frequently than the mature markets [ 25 , 26 , 28 , 52 , 66 , 94 , 104 , 105 , 106 , 107 , 108 , 109 , 110 ].…”

Cluster behavior of a simple model in financial markets

“…This could be demonstrated in Refs. [31,32]. Note also that the distribution of returns is robust in a short range of the time scale, which shows that α ≈ 3.05 ± 0.04 through the fitting for the time scale δt = 5 is approximately equal to the value of α for the time scale δt = 1.…”

Event-Driven Business Intelligence Approach for Real-Time Integration of Technical and Fundamental Analysis in Forex Market

“…Moreover, many other researches focused on traders' overconfidence and proved its influence in forex market (Barber and Odean, 2000;Glaser and Weber, 2007;Oberlechner and Osler, 2008). In the same context, some works proved the impact of loss aversion and herding behaviour (Kim et al, 2004;O'Connelle and Teo, 2009) and some others showed the effects of feedback trading on forex market which is also considered important in forex trading (Aguirre and Said, 1999;Bjnnes and Rime, 2005;Laopodis, 2005).…”