具有异质阶次分割策略的广义 Lillo-Mike-Farmer 模型的精确解法

IF 1.3 3区 物理与天体物理 Q3 PHYSICS, MATHEMATICAL
Yuki Sato, Kiyoshi Kanazawa
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引用次数: 0

摘要

Lillo-Mike-Farmer(LMF)模型是一个描述金融市场中机构投资者拆单行为的成熟经济物理学模型。在最初的文章(Lillo 等人,Phys Rev E 71:066122, 2005)中,LMF 假设交易者的拆单策略是同质的,并基于若干启发式推理得出了订单符号自相关函数(ACF)的幂律渐近解。本报告提出了一个广义的 LMF 模型,该模型纳入了交易者拆单行为的异质性,无需启发式方法即可精确求解。我们发现,订单符号 ACF 中的幂律指数对任意异质订单提交概率分布都是稳健的。另一方面,ACF 中的前因子对交易策略的异质性非常敏感,并且在原始同质 LMF 模型中被系统性低估。我们的工作突出表明,预测 ACF 预因子比预测 ACF 指数更具挑战性,因为许多微观细节(实际数据分析中的复杂成分)开始变得重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Exact Solution to a Generalised Lillo–Mike–Farmer Model with Heterogeneous Order-Splitting Strategies

Exact Solution to a Generalised Lillo–Mike–Farmer Model with Heterogeneous Order-Splitting Strategies

The Lillo–Mike–Farmer (LMF) model is an established econophysics model describing the order-splitting behaviour of institutional investors in financial markets. In the original article (Lillo et al. in Phys Rev E 71:066122, 2005), LMF assumed the homogeneity of the traders’ order-splitting strategy and derived a power-law asymptotic solution to the order-sign autocorrelation function (ACF) based on several heuristic reasonings. This report proposes a generalised LMF model by incorporating the heterogeneity of traders’ order-splitting behaviour that is exactly solved without heuristics. We find that the power-law exponent in the order-sign ACF is robust for arbitrary heterogeneous order-submission probability distributions. On the other hand, the prefactor in the ACF is very sensitive to heterogeneity in trading strategies and is shown to be systematically underestimated in the original homogeneous LMF model. Our work highlights that predicting the ACF prefactor is more challenging than the ACF exponent because many microscopic details (complex ingredients in actual data analyses) start to matter.

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来源期刊
Journal of Statistical Physics
Journal of Statistical Physics 物理-物理:数学物理
CiteScore
3.10
自引率
12.50%
发文量
152
审稿时长
3-6 weeks
期刊介绍: The Journal of Statistical Physics publishes original and invited review papers in all areas of statistical physics as well as in related fields concerned with collective phenomena in physical systems.
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