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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
    交易中異質治療效果的因果森林
    Aug 1, 2026 #causal-inference

    交易中異質治療效果的因果森林

    本博客每個回測估計條件平均值。因果森林估計條件治療效果 — tau(x) 而非 mu(x) — 具有誠實分裂、自適應核權重表示以及告訴您發現的異質性是否真實的校準測試。
  5. 05
    Double Machine Learning：估計因果參數而非預測報酬
    Aug 2, 2026 #causal-inference

    Double Machine Learning：估計因果參數而非預測報酬

    本博客至今所有模型回答「什麼預測什麼」。Double ML 回答「什麼導致什麼」——帶有可辯護的標準誤。部分線性模型、Neyman 正交性、order book 數據上的清理交叉擬合，以及為何有效 DML 信賴區間僅對一個預先指定的問題成立的誠實說明。
  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.