Epistemic Limits of Empirical Finance: Causal Reductionism and Self-Reference

Daniel Polakow, Tim Gebbie, Emlyn Flint
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Abstract

The clarion call for causal reduction in the study of capital markets is intensifying. However, in self-referencing and open systems such as capital markets, the idea of unidirectional causation (if applicable) may be limiting at best, and unstable or fallacious at worst. In this research, we critically assess the use of scientific deduction and causal inference within the study of empirical finance and econometrics. We then demonstrate the idea of competing causal chains using a toy model adapted from ecological predator/prey relationships. From this, we develop the alternative view that the study of empirical finance, and the risks contained therein, may be better appreciated once we admit that our current arsenal of quantitative finance tools may be limited to ex post causal inference under popular assumptions. Where these assumptions are challenged, for example in a recognizable reflexive context, the prescription of unidirectional causation proves deeply problematic.
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实证金融的认知极限:因果还原论与自我参照
减少对资本市场研究的因果关系的呼声日益高涨。然而,在自我参照和开放的系统中,如资本市场,单向因果关系的想法(如果适用)往好了说可能是有限的,往坏了说可能是不稳定或谬误的。在本研究中,我们批判性地评估了实证金融学和计量经济学研究中科学演绎和因果推理的使用。然后,我们使用一个从生态捕食者/猎物关系改编的玩具模型来展示竞争因果链的概念。由此,我们提出了另一种观点,即一旦我们承认我们目前的量化金融工具库可能仅限于在流行假设下的事后因果推理,那么对实证金融及其所包含的风险的研究可能会得到更好的理解。当这些假设受到挑战时,例如在可识别的反射环境中,单向因果关系的处方被证明是有问题的。
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