Immediate price impact of a stock and its warrant: Power-law or logarithmic model?

Xu, Hai-Chuan; Jiang, Zhi‐Qiang; Zhou, Wei‐Xing

doi:10.1142/s0217979217500485

Cited by 6 publications

(6 citation statements)

References 33 publications

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“…A uniform price-impact curve suitable for different markets has been investigated, the power-law dependence of the return on the size has been found [39,40]. The empirically estimated exponent ranges from 1 3 to 2 3 [41,42,43,44]. Following the work done in refs.…”

Section: The Modelmentioning

confidence: 98%

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Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders

Liu

Chen

et al. 2018

Physica A: Statistical Mechanics and its Applications

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By incorporating market impact and momentum traders into an agent-based model, we investigate the conditions for the occurrence of self-reinforcing feedback loops and the coevolutionary mechanism of prices and strategies. For low market impact, the price fluctuations are originally large. The existence of momentum traders has little impact on the change of price fluctuations but destroys the equilibrium between the trend-following and trendrejecting strategies. The trend-following herd behaviors become dominant. A self-reinforcing feedback loop exists. For high market impact, the existence of momentum traders leads to an increase in price fluctuations. The trend-following strategies of rational individuals are suppressed while the trend-following strategies of momentum traders are promoted. The crowdanticrowd behaviors become dominant. A negative feedback loop exists. A theoretical analysis indicates that, for low market impact, the majority effect is beneficial for the trend-followers to earn more, which in turn promotes the trend-following strategies. For high market impact, the minority effect causes the trend-followers to suffer great losses, which in turn suppresses the Email address: zlxxwj@163.com (Li-Xin Zhong a )

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Section: The Modelmentioning

confidence: 98%

“…The price impact against the transaction size has been investigated in refs. [39,40,41,42,43,44]. A uniform price-impact curve suitable for different markets has been investigated, the power-law dependence of the return on the size has been found [39,40].…”

Section: The Modelmentioning

confidence: 99%

Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders

Liu

Chen

et al. 2018

Physica A: Statistical Mechanics and its Applications

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“…Market impact is related to the discrepancy between an individual’s expected price and the actual transaction price [ 47 , 48 ], which depends on how long the individual queues up for his transaction turn. During such a sequential process of clearing the deals, the transaction price ranges from its present value to a new value, which is satisfied with the equation [ 47 ] For β = 0, the buyers and the sellers finish their transactions with the latest historical price P ( t − 1).…”

Section: The Modelmentioning

confidence: 99%

Market impact shapes competitive advantage of investment strategies in financial markets

Liu

2022

PLoS ONE

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The formation of an efficient market depends on the competition between different investment strategies, which accelerates all available information into asset prices. By incorporating market impact and two kinds of investment strategies into an agent-based model, we have investigated the coevolutionary mechanism of different investment strategies and the role of market impact in shaping a competitive advantage in financial markets. The coevolution of history-dependent strategies and reference point strategies depends on the levels of market impact and risk tolerance. For low market impact and low risk tolerance, the majority-win effect makes the trend-following strategies become dominant strategies. For high market impact and low risk tolerance, the minority-win effect makes the trend-rejecting strategies coupled with trend-following strategies become dominant strategies. The coupled effects of price fluctuations and strategy distributions have been investigated in depth. A U-shape distribution of history-dependent strategies is beneficial for a stable price, which is destroyed by the existence of reference point strategies with low risk tolerance. A δ-like distribution of history-dependent strategies leads to a large price fluctuation, which is suppressed by the existence of reference point strategies with high risk tolerance. The strategies that earn more in an inefficient market lose more in an efficient market. Such a result gives us another explanation for the principle of risk-profit equilibrium in financial markets: high return in an inefficient market should be coupled with high risk in an efficient market, low return in an inefficient market should be coupled with low risk in an efficient market.

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“…If t is a partially filled sell order, a i (t) = −5, whose price is lower than the best bid price and whose quantity is greater than the amount of matched orders on the buy limit order book. These two types of orders are the most aggressive and have the highest immediate price impact [61][62][63].…”

Section: Data Descriptionmentioning

confidence: 99%

Linear and Nonlinear Correlations in the Order Aggressiveness of Chinese Stocks

Yue

Chen

et al. 2017

Fractals

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The diagonal effect of orders is well documented in different markets, which states that the orders are more likely to be followed by the orders of the same aggressiveness and implies † † Corresponding author. The detrending moving average analysis shows that there are crossovers in the scaling behaviors of overall fluctuations and order aggressiveness exhibits linear long-term correlations. We design an objective procedure to determine the two Hurst indexes delimited by the crossover scale. We find no correlations in the short term and strong correlations in the long term for all stocks except for an outlier stock. The long-term correlation is found to depend on several firm specific characteristics. We also find that there are nonlinear long-term correlations in the order aggressiveness when we perform the multifractal detrending moving average analysis. 1750041-1

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Immediate price impact of a stock and its warrant: Power-law or logarithmic model?

Cited by 6 publications

References 33 publications

Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders

Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders

Market impact shapes competitive advantage of investment strategies in financial markets

Linear and Nonlinear Correlations in the Order Aggressiveness of Chinese Stocks

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