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[量化金融] 订单驱动下单个交易的普遍价格影响函数 市场 [推广有奖]

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可人4 在职认证  发表于 2022-3-7 22:11:00 来自手机 |AI写论文

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摘要翻译:
交易规模$\omega$直接影响所交易股票的价格形成。对美国和澳大利亚股票市场交易数据的经济物理分析揭示了市场特有的标度规律,其中,当股票资本额$C$作为标度关系的论据时,可以获得每个市场的价格影响主曲线。然而,在规模调整中引入股票资本化的基本原理尚不清楚,对于小额交易,价格变化$R$与交易规模$\omega$之间的反常负相关也无法解释。在这里,我们表明,这些问题可以通过考虑导致交易的订单的侵略性和适当的规范化技术来解决。利用来自中国市场的订单簿数据,我们发现来自填充和部分填充限价订单的交易具有非常不同的价格影响。当交易量不太大时,部分填充订单的交易对价格的影响是不变的,而填充订单的交易表现出幂律行为$r\sim\omega^\alpha$与$\alpha\约2/3$。当收益和成交量用股票相关的平均数归一化时,两种类型的交易都出现了与资本化无关的标度律。但是,在股票资本化方面不能建立规模关系。此外,还验证了$\alpha=\alpha_\omega/\alpha_r$之间的关系,其中$\alpha_\omega$和$\alpha_r$是交易规模和收益的尾指数。这些观察结果也使我们能够解释在小规模交易中$R$和$\omega$之间的反常负相关。我们预计,这些规律性可能会在其他订单驱动的市场中存在。
---
英文标题:
《Universal price impact functions of individual trades in an order-driven
  market》
---
作者:
Wei-Xing Zhou (ECUST)
---
最新提交年份:
2008
---
分类信息:

一级分类:Quantitative Finance        数量金融学
二级分类:Trading and Market Microstructure        交易与市场微观结构
分类描述:Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构,流动性,交易和拍卖设计,自动化交易,基于代理的建模和做市
--
一级分类:Physics        物理学
二级分类:Physics and Society        物理学与社会
分类描述:Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体(人类或其他)的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统(如能源网、运输网络)的物理和工程。
--

---
英文摘要:
  The trade size $\omega$ has direct impact on the price formation of the stock traded. Econophysical analyses of transaction data for the US and Australian stock markets have uncovered market-specific scaling laws, where a master curve of price impact can be obtained in each market when stock capitalization $C$ is included as an argument in the scaling relation. However, the rationale of introducing stock capitalization in the scaling is unclear and the anomalous negative correlation between price change $r$ and trade size $\omega$ for small trades is unexplained. Here we show that these issues can be addressed by taking into account the aggressiveness of orders that result in trades together with a proper normalization technique. Using order book data from the Chinese market, we show that trades from filled and partially filled limit orders have very different price impact. The price impact of trades from partially filled orders is constant when the volume is not too large, while that of filled orders shows power-law behavior $r\sim \omega^\alpha$ with $\alpha\approx2/3$. When returns and volumes are normalized by stock-dependent averages, capitalization-independent scaling laws emerge for both types of trades. However, no scaling relation in terms of stock capitalization can be constructed. In addition, the relation $\alpha=\alpha_\omega/\alpha_r$ is verified, where $\alpha_\omega$ and $\alpha_r$ are the tail exponents of trade sizes and returns. These observations also enable us to explain the anomalous negative correlation between $r$ and $\omega$ for small-size trades. We anticipate that these regularities may hold in other order-driven markets.
---
PDF链接:
https://arxiv.org/pdf/0708.3198
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关键词:Quantitative observations correlation QUANTITATIV observation 规模 建立 经济 股票 价格

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