Markets: A Rigorous Course
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Readings and resources

Core about 10 min

Read first

  1. Chan, E. P., Algorithmic Trading: Winning Strategies and Their Rationale (Wiley, 2013), ch. 2 (ADF, Hurst, half-life, Johansen) and ch. 3 (Bollinger bands, Kalman filter for pairs). The practitioner's view; read it alongside 13A.2–13A.9.
  2. Hamilton, J. D., Time Series Analysis (Princeton UP, 1994): ch. 17 (unit roots; the proofs behind 13A.2), ch. 18–19 (spurious regression and cointegration), ch. 20 (Johansen), ch. 13 (the Kalman filter).
  3. M04 · 4.1 and 4.6, for turning a pair rule into a testable hypothesis and counting the variants you try.

For depth

  • Johansen, S., Likelihood-Based Inference in Cointegrated Vector Autoregressive Models (Oxford UP, 1995), ch. 4–6, 11.
  • Durbin, J. and Koopman, S. J., Time Series Analysis by State Space Methods (2nd ed., Oxford UP, 2012), ch. 4 (filtering, smoothing, likelihood).
  • Vidyamurthy, G., Pairs Trading: Quantitative Methods and Analysis (Wiley, 2004).

Papers

  • Dickey, D. A. and Fuller, W. A. (1979), "Distribution of the estimators for autoregressive time series with a unit root", JASA 74(366):427–431.
  • Said, S. E. and Dickey, D. A. (1984), "Testing for unit roots in autoregressive-moving average models of unknown order", Biometrika 71(3):599–607.
  • MacKinnon, J. G. (2010), "Critical values for cointegration tests", Queen's Economics Department Working Paper 1227, https://ideas.repec.org/p/qed/wpaper/1227.html .
  • Shiller, R. J. and Perron, P. (1985), "Testing the random walk hypothesis: power versus frequency of observation", Economics Letters 18(4):381–386.
  • Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. and Shin, Y. (1992), "Testing the null hypothesis of stationarity against the alternative of a unit root", Journal of Econometrics 54:159–178.
  • Granger, C. W. J. and Newbold, P. (1974), "Spurious regressions in econometrics", Journal of Econometrics 2(2):111–120.
  • Phillips, P. C. B. (1986), "Understanding spurious regressions in econometrics", Journal of Econometrics 33(3):311–340.
  • Engle, R. F. and Granger, C. W. J. (1987), "Co-integration and error correction: representation, estimation, and testing", Econometrica 55(2):251–276.
  • Phillips, P. C. B. and Ouliaris, S. (1990), "Asymptotic properties of residual based tests for cointegration", Econometrica 58(1):165–193.
  • Johansen, S. (1988), "Statistical analysis of cointegration vectors", Journal of Economic Dynamics and Control 12(2–3):231–254; Johansen, S. (1991), "Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models", Econometrica 59(6):1551–1580.
  • Stock, J. H. and Watson, M. W. (1993), "A simple estimator of cointegrating vectors in higher order integrated systems", Econometrica 61(4):783–820. Phillips, P. C. B. and Hansen, B. E. (1990), "Statistical inference in instrumental variables regression with I(1) processes", Review of Economic Studies 57(1):99–125.
  • Gonzalo, J. and Granger, C. W. J. (1995), "Estimation of common long-memory components in cointegrated systems", JBES 13(1):27–35. Hasbrouck, J. (1995), "One security, many markets: determining the contributions to price discovery", Journal of Finance 50(4):1175–1199.
  • Bertram, W. K. (2010), "Analytic solutions for optimal statistical arbitrage trading", Physica A 389(11):2234–2243, doi:10.1016/j.physa.2010.01.045.
  • Leung, T. and Li, X. (2015), "Optimal mean reversion trading with transaction costs and stop-loss exit", International Journal of Theoretical and Applied Finance 18(3).
  • Gatev, E., Goetzmann, W. N. and Rouwenhorst, K. G. (2006), "Pairs trading: performance of a relative-value arbitrage rule", Review of Financial Studies 19(3):797–827.
  • Avellaneda, M. and Lee, J.-H. (2010), "Statistical arbitrage in the US equities market", Quantitative Finance 10(7):761–782.
  • Muth, J. F. (1960), "Optimal properties of exponentially weighted forecasts", JASA 55(290):299–306.
  • Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions", Econometrica 28(3):591–605. Quandt, R. E. (1960), "Tests of the hypothesis that a linear regression system obeys two separate regimes", JASA 55(290):324–330. Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point", Econometrica 61(4):821–856.
  • Brown, R. L., Durbin, J. and Evans, J. M. (1975), "Techniques for testing the constancy of regression relationships over time", JRSS B 37(2):149–192.
  • Bai, J. and Perron, P. (1998), "Estimating and testing linear models with multiple structural changes", Econometrica 66(1):47–78; Bai, J. and Perron, P. (2003), "Computation and analysis of multiple structural change models", Journal of Applied Econometrics 18(1):1–22.
  • Gregory, A. W. and Hansen, B. E. (1996), "Residual-based tests for cointegration in models with regime shifts", Journal of Econometrics 70(1):99–126.
  • Khandani, A. E. and Lo, A. W. (2007), "What happened to the quants in August 2007?", Journal of Investment Management 5:29–78, https://web.mit.edu/~alo/www/Papers/august07.html ; Khandani, A. E. and Lo, A. W. (2011), "What happened to the quants in August 2007? Evidence from factors and transactions data", Journal of Financial Markets 14(1):1–46, https://web.mit.edu/~alo/www/Papers/august07b.html .
  • Lehmann, B. N. (1990), "Fads, martingales, and market efficiency", Quarterly Journal of Economics 105(1):1–28. Lo, A. W. and MacKinlay, A. C. (1990), "When are contrarian profits due to stock market overreaction?", Review of Financial Studies 3(2):175–205.
  • Shleifer, A. and Vishny, R. W. (1997), "The limits of arbitrage", Journal of Finance 52(1):35–55.

Indian sources

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