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🔬 7 parts

Causality & Lead-Lag in Markets

Who moves whom — Granger causality, transfer entropy, PCMCI discovery, and the causal ML toolbox (double ML, causal forests, synthetic control) applied to crypto markets.

  1. 01
    Toda-Yamamoto vs Differenced Granger: Does the BTC Lead-Lag Survive?
    Aug 7, 2026 #causal-inference

    Toda-Yamamoto vs Differenced Granger: Does the BTC Lead-Lag Survive?

    Granger causality on crypto prices done two ways — differenced returns and Toda-Yamamoto on levels — with a correct Wald implementation, an effective-N corrected causality matrix, and a rolling-stability test of whether the lag is tradeable at all.

  2. 02
    Transfer Entropy: Which Way Does Information Flow Between Crypto Assets?
    Aug 24, 2026 #causal-inference

    Transfer Entropy: Which Way Does Information Flow Between Crypto Assets?

    DCC-GARCH tells you when crypto dependence tightens. Transfer entropy tells you which way it points. A directed information-flow measure, its null calibration, and an honest account of what it does and does not add over average pairwise correlation.

  3. 03
    PCMCI: Causal Discovery in Multivariate Crypto Time Series
    Aug 18, 2026 #causal-inference

    PCMCI: Causal Discovery in Multivariate Crypto Time Series

    How PCMCI's two-stage MCI test recovers directed causal links between crypto assets where correlation and bivariate Granger cannot — the construction, the tigramite pipeline, and the real-data study it still needs.

  4. 04
    交易中异质处理效应的因果森林
    Aug 1, 2026 #causal-inference

    交易中异质处理效应的因果森林

    本博客每个回测估计条件平均值。因果森林估计条件处理效果 — tau(x) 而非 mu(x) — 具有诚实分裂、自适应核权重表示以及告诉您发现的异质性是否真实的校准测试。

  5. 05
    Double Machine Learning:估计因果参数而非预测收益
    Aug 2, 2026 #causal-inference

    Double Machine Learning:估计因果参数而非预测收益

    本博客至今所有模型回答'什么预测什么'。Double ML 回答'什么导致什么'——带有可辩护的标准误。部分线性模型、Neyman 正交性、order book 数据上的清理交叉拟合,以及为何有效 DML 置信区间仅对一个预先指定的问题成立的诚实说明。

  6. 06
    The Other Way a Regression Lies: Endogeneity, 2SLS, and the Gamma Calibration Problem
    Aug 10, 2026 #causal-inference

    The Other Way a Regression Lies: Endogeneity, 2SLS, and the Gamma Calibration Problem

    Selection bias in the search is not the only way a regression fools you. When the regressor is correlated with the error, more data makes the estimate more confidently wrong. Instrumental variables applied to the one endogeneity problem this blog has already left open: permanent impact from net taker flow.

  7. 07
    Synthetic Control Methods for Evaluating Trading Strategies
    Aug 21, 2026 #causal-inference

    Synthetic Control Methods for Evaluating Trading Strategies

    This series has priced the selection route to a false edge — DSR prices the winner, PBO prices the search. Neither touches confounding: the strategy that made money because volatility doubled the week you deployed it. The Synthetic Control Method builds a weighted counterfactual from a donor pool of untouched instruments and gives you a falsification criterion and a placebo p-value.