Reference
Resources
Books, courses, papers and data the modules lean on, with a note on what to take from each.
Papers 256
- The Dynamics of Commodity Spot and Futures Markets: A Primer verified
Robert S. Pindyck (2001), The Energy Journal 22(3), 1–29
The clearest short treatment of storage, convenience yield and volatility. Read first for M10.
- Updated SEBI study: 93% of individual traders incurred losses in equity F&O between FY22 and FY24 verified
SEBI press release, 23 Sep 2024
Base rates for retail F&O outcomes.
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SEBI, Department of Economic and Policy Analysis; released with PR 50/2026, 20 Aug 2026
The latest retail F&O loss data, after the October 2024 framework; canonical treatment in M01 · 1.11 Case 1. Press release: https://www.sebi.gov.in/media-and-notifications/press-releases/aug-2026/sebi-studies-indicate-key-trends-in-retail-participation-trading-behaviour-and-profitability-in-the-equity-derivatives_103838.html . The PDF's text could not be machine-extracted on 6 Nov 2026; the course's figures come from summaries (e.g. https://www.corplawupdates.in/updates/sebi-equity-derivatives-retail-trader-study-fy26) and should be checked against the PDF tables.
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SEBI, press release 24 Jul 2024
Base rates for retail intraday outcomes in the cash segment.
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Rama Cont (2001), Quantitative Finance 1(2):223–236
The list of stylized facts that M02 · 2.5 tests on the Nifty.
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Andrew W. Lo and A. Craig MacKinlay (1988), Review of Financial Studies 1(1):41–66
The variance-ratio test of M02 · 2.3, with the heteroskedasticity-robust statistic.
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Edward O. Thorp (2006), in Zenios & Ziemba (eds.), Handbook of Asset and Liability Management, Vol. 1, ch. 9
The binary case, continuous approximation and fractional Kelly match M03 · 3.2–3.4. DOI: https://doi.org/10.1016/S1872-0978(06)01009-X
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L. C. MacLean, E. O. Thorp and W. T. Ziemba (2010), Quantitative Finance 10(7):681–687
Why full Kelly is too aggressive in practice; links M14 · 14.8 back to M03.
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J. L. Kelly Jr. (1956), Bell System Technical Journal 35(4):917–926
The original growth-optimal betting paper.
- The Statistics of Sharpe Ratios verified
Andrew W. Lo (2002), Financial Analysts Journal 58(4):36–52
Short and complete; M04 · 4.5 follows it (standard errors, serial correlation, annualisation).
- … and the Cross-Section of Expected Returns verified
Campbell R. Harvey, Yan Liu and Heqing Zhu (2016), Review of Financial Studies 29(1):5–68
Multiple testing in factor research: why a t-statistic of 2 is no longer enough.
- The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-Normality verified
David H. Bailey and Marcos López de Prado (2014), Journal of Portfolio Management 40(5)
The deflated Sharpe ratio of M04 · 4.6.
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D. H. Bailey, J. Borwein, M. López de Prado and Q. J. Zhu (2017), Journal of Computational Finance
Combinatorially symmetric cross-validation and PBO.
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Narasimhan Jegadeesh and Sheridan Titman (1993), Journal of Finance 48(1):65–91
Cross-sectional momentum.
- Time Series Momentum verified
Tobias J. Moskowitz, Yao Hua Ooi and Lasse H. Pedersen (2012), Journal of Financial Economics 104(2):228–250
Trend following across asset classes; link is the AQR data page.
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Andrew W. Lo, Harry Mamaysky and Jiang Wang (2000), Journal of Finance 55(4):1705–1765
Chart patterns detected by kernel regression and tested statistically. Link is NBER WP 7613.
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Carol L. Osler (2000), FRBNY Economic Policy Review 6(2):53–68
Evidence that published support and resistance levels predict intraday trend interruptions.
- A simple implicit measure of the effective bid-ask spread in an efficient market verified
Richard Roll (1984), Journal of Finance 39(4):1127–1139
The Roll model of M05 · 5.2.
- Continuous auctions and insider trading verified
Albert S. Kyle (1985), Econometrica 53(6):1315–1335
Strategic informed trading and Kyle's lambda (M05 · 5.4).
- Optimal execution of portfolio transactions verified
Robert Almgren and Neil Chriss (2000), Journal of Risk 3(2):5–39
The mean–variance execution trajectory of M05 · 5.7; author preprint widely available.
- Trading is hazardous to your wealth: the common stock investment performance of individual investors verified
Brad M. Barber and Terrance Odean (2000), Journal of Finance 55(2):773–806
Turnover destroys retail returns.
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A. Craig MacKinlay (1997), Journal of Economic Literature 35(1):13–39
Read all of it: the source for M12 · 12.1–12.3 and the earnings event studies of M06A.
- Post-earnings-announcement drift: delayed price response or risk premium? verified
Victor L. Bernard and Jacob K. Thomas (1989), Journal of Accounting Research 27 (Supplement):1–36
The classic PEAD paper behind M06A · 6A.2.
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Fischer Black and Myron Scholes (1973), Journal of Political Economy 81(3):637–654
The original derivation.
- Theory of Rational Option Pricing verified
Robert C. Merton (1973), Bell Journal of Economics and Management Science 4(1):141–183
No-arbitrage bounds, continuous dividends and the rigorous continuous-time argument.
- Variance Risk Premiums verified
Peter Carr and Liuren Wu (2009), Review of Financial Studies 22(3):1311–1341
Synthetic variance swaps and the size of the variance risk premium (M09 · 9.4).
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Cboe Global Markets
The VIX computation of M09 · 9.6. Cboe now publishes the method as an index-methodology document (v5 dated 11 Sep 2025 at the time of checking, 6 Nov 2026); the old vixwhite.pdf link is retired. India VIX uses the same construction (NSE India VIX white paper).
- Facts and Fantasies about Commodity Futures verified
Gary Gorton and K. Geert Rouwenhorst (2006), Financial Analysts Journal 62(2):47–68
Commodity futures risk premium and roll returns (M10 · 10.3).
- The Golden Dilemma verified
Claude B. Erb and Campbell R. Harvey (2013), Financial Analysts Journal 69(4):10–42
Gold's real price, its relation to inflation, and why it is hard to value (M10 · 10.6).
- Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market verified
Lutz Kilian (2009), American Economic Review 99(3):1053–1069
Supply versus demand oil shocks: the structural VAR that separates oil supply, aggregate demand and oil-specific precautionary demand. Used in M10 · 10.8.1 and M12 · 12.7.
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John B. Taylor (1993), Carnegie-Rochester Conference Series on Public Policy 39:195–214
The Taylor rule of M11 · 11.6.
- Measuring Geopolitical Risk verified
Dario Caldara and Matteo Iacoviello (2022), American Economic Review 112(4):1194–1225
Construction and properties of the GPR index (M12 · 12.4).
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Ivo Welch and Amit Goyal (2008), Review of Financial Studies 21(4):1455–1508
Out-of-sample failure of the classic predictors (M13 · 13.3). Working paper: https://nber.org/papers/w10483
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John Y. Campbell and Samuel B. Thompson (2008), Review of Financial Studies 21(4):1509–1531
Out-of-sample R² with economically motivated restrictions (M13 · 13.3).
- A new approach to the economic analysis of nonstationary time series and the business cycle verified
James D. Hamilton (1989), Econometrica 57(2):357–384
The regime-switching model and filter of M13 · 13.5.
- Strictly proper scoring rules, prediction, and estimation verified
Tilmann Gneiting and Adrian E. Raftery (2007), JASA 102(477):359–378
The theory behind M13 · 13.7.
- Co-integration and error correction: representation, estimation, and testing verified
Robert F. Engle and Clive W. J. Granger (1987), Econometrica 55(2):251–276
The two-step method of M13A · 13A.5.
- Pairs trading: performance of a relative-value arbitrage rule verified
E. Gatev, W. N. Goetzmann and K. G. Rouwenhorst (2006), Review of Financial Studies 19(3):797–827
The distance method and its historical returns.
- Portfolio Selection verified
Harry Markowitz (1952), Journal of Finance 7(1):77–91
Mean–variance optimisation (M14 · 14.1).
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Victor DeMiguel, Lorenzo Garlappi and Raman Uppal (2009), Review of Financial Studies 22(5):1915–1953
Estimation error makes sample mean–variance lose to 1/N (M14 · 14.2).
- Prospect Theory: An Analysis of Decision under Risk verified
Daniel Kahneman and Amos Tversky (1979), Econometrica 47(2):263–291
Read with Tversky and Kahneman (1992), 'Advances in prospect theory', Journal of Risk and Uncertainty 5(4):297–323, https://econpapers.repec.org/RePEc:kap:jrisku:v:5:y:1992:i:4:p:297-323
- Are investors reluctant to realize their losses? verified
Terrance Odean (1998), Journal of Finance 53(5):1775–1798
The disposition effect in brokerage data (M14 · 14.9).
- Securities Scam: Genesis, Mechanics and Impact verified
S. K. Barua and J. R. Varma (1993), Vikalpa 18(1)
The academic account of how the scam worked, read with Dalal and Basu for M01 Case 3.
- An econometric analysis of nonsynchronous trading verified
Andrew W. Lo and A. Craig MacKinlay (1990), Journal of Econometrics 45(1–2):181–211
How stale prices induce spurious autocorrelation in index returns; context for the variance-ratio results of M02 · 2.3.
- On estimating the expected return on the market: an exploratory investigation verified
Robert C. Merton (1980), Journal of Financial Economics 8(4):323–361
Sampling more often does not sharpen the estimate of the mean (M02 · 2.4).
- The variation of certain speculative prices verified
Benoit Mandelbrot (1963), Journal of Business 36(4):394–419
The original case for heavy tails in price changes (M02 · 2.6).
- A simple general approach to inference about the tail of a distribution verified
Bruce M. Hill (1975), Annals of Statistics 3(5):1163–1174
The Hill tail-index estimator derived and applied in M02 · 2.6.
- Inverse cubic law for the distribution of stock price variations verified
P. Gopikrishnan, M. Meyer, L. A. N. Amaral and H. E. Stanley (1998), European Physical Journal B 3(2):139–140
Tail exponent of about 3 for individual stock returns.
- Scaling of the distribution of fluctuations of financial market indices verified
P. Gopikrishnan, V. Plerou, L. A. N. Amaral, M. Meyer and H. E. Stanley (1999), Physical Review E 60(5):5305–5316
The inverse cubic law for index returns and how it changes with horizon.
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R. K. Pan and S. Sinha (2008), Physica A 387:2055–2065
Finds a tail exponent of about 3 for NSE and BSE index returns at 1-minute and daily scales: the Indian evidence for M02 · 2.6.
- Efficient tests for normality, homoscedasticity and serial independence of regression residuals verified
Carlos M. Jarque and Anil K. Bera (1980), Economics Letters 6(3):255–259
The Jarque–Bera normality test.
- No contagion, only interdependence: measuring stock market comovements verified
Kristin J. Forbes and Roberto Rigobon (2002), Journal of Finance 57(5):2223–2261
Correlations conditioned on high volatility are biased upward; the conditioning bias of M02 · 2.9 (Proposition 2.15); reused in M14.
- Extreme correlation of international equity markets verified
François Longin and Bruno Solnik (2001), Journal of Finance 56(2):649–676
Correlation rises in bear-market tails but not in bull-market tails; why diversification weakens when it is needed (M14).
- Asymmetric correlations of equity portfolios verified
Andrew Ang and Joseph Chen (2002), Journal of Financial Economics 63(3):443–494
Downside correlations exceed upside correlations in US equity portfolios.
- Optimal gambling systems for favorable games verified
Leo Breiman (1961), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, 65–78
The asymptotic optimality of the growth-optimal (Kelly) strategy cited in M03 · 3.2.
- On the maximum drawdown of a Brownian motion verified
M. Magdon-Ismail, A. F. Atiya, A. Pratap and Y. S. Abu-Mostafa (2004), Journal of Applied Probability 41(1):147–161
The distribution of maximum drawdown for Brownian motion with drift (M03 · 3.8).
- The numeraire portfolio verified
John B. Long Jr. (1990), Journal of Financial Economics 26(1):29–69
The growth-optimal portfolio as a numeraire under which asset prices are fair; a further property of Kelly.
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President's Working Group on Financial Markets (1999)
The official report on LTCM, quoted in M03 · 3.10.1 on correlations going to one.
- Momentum Crashes verified
Kent Daniel and Tobias J. Moskowitz (2016), Journal of Financial Economics 122(2):221–247
Momentum's crash risk after market rebounds (M04 · 4.3). Link is the NBER working paper; the numbers quoted in M04 are from it (sample 1927:01–2013:03).
- Momentum Has Its Moments verified
Pedro Barroso and Pedro Santa-Clara (2015), Journal of Financial Economics 116(1)
Volatility-scaling momentum to tame its crashes (M04 · 4.3).
- When Are Contrarian Profits Due to Stock Market Overreaction? verified
Andrew W. Lo and A. Craig MacKinlay (1990), Review of Financial Studies 3(2):175–205
Decomposes contrarian profits into own-autocorrelation and cross-autocovariance terms: the source of M04 Proposition 4.6; cited again for stat-arb in M13A.
- Evidence of Predictable Behavior of Security Returns verified
Narasimhan Jegadeesh (1990), Journal of Finance 45(3)
Short-term (one-month) reversal (M04 · 4.3).
- Fads, Martingales, and Market Efficiency verified
Bruce N. Lehmann (1990), Quarterly Journal of Economics 105(1):1–28
Weekly reversal profits (M04 · 4.3); the contrarian ancestor of the stat-arb strategies of M13A.
- The 52-Week High and Momentum Investing verified
Thomas J. George and Chuan-Yang Hwang (2004), Journal of Finance 59(5)
Nearness to the 52-week high predicts returns: the evidence behind the Minervini/Weinstein-style rules of M04 · 4.2.
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R. David McLean and Jeffrey Pontiff (2016), Journal of Finance 71(1):5–32
Anomaly returns fall after publication: expect live performance below the backtest (M04; factor discussion of M06A).
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William Brock, Josef Lakonishok and Blake LeBaron (1992), Journal of Finance 47(5):1731–1764
Moving-average and trading-range-break rules tested with bootstrap nulls (M04 · 4.1).
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Ryan Sullivan, Allan Timmermann and Halbert White (1999), Journal of Finance 54(5):1647–1691
Re-tests Brock et al. with White's Reality Check: the technical-rule results do not survive out of sample (M04 · 4.1).
- A Reality Check for Data Snooping verified
Halbert White (2000), Econometrica 68(5):1097–1126
Bootstrap test of the best of many strategies against a benchmark (M04 · 4.6).
- A Test for Superior Predictive Ability verified
Peter R. Hansen (2005), Journal of Business & Economic Statistics 23(4)
The SPA test, a less conservative refinement of White's Reality Check (M04 · 4.6).
- Stepwise Multiple Testing as Formalized Data Snooping verified
Joseph P. Romano and Michael Wolf (2005), Econometrica 73(4)
Stepwise procedure that identifies which strategies beat the benchmark (M04 · 4.6).
- A Simple Sequentially Rejective Multiple Test Procedure verified
Sture Holm (1979), Scandinavian Journal of Statistics 6(2):65–70
Holm's step-down control of the family-wise error rate (M04 · 4.6).
- Controlling the False Discovery Rate verified
Yoav Benjamini and Yosef Hochberg (1995), JRSS B 57(1):289–300
The Benjamini–Hochberg FDR procedure of M04 · 4.6. Read with Benjamini and Yekutieli (2001), Annals of Statistics 29(4), for arbitrary dependence (title not given in the notes).
- The Sharpe Ratio Efficient Frontier verified
David H. Bailey and Marcos López de Prado (2012), Journal of Risk 15(2)
Source of the probabilistic Sharpe ratio (PSR) and minimum track record length (MinTRL) of M04 · 4.5.
- The Stationary Bootstrap verified
Dimitris N. Politis and Joseph P. Romano (1994), JASA 89(428)
Block bootstrap with random block lengths, for resampling serially dependent returns.
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Carol L. Osler (2003), Journal of Finance 58(5):1791–1819
Clustered stop-loss and take-profit orders at round numbers as the mechanism behind support and resistance (M04A · 4A.2). Link is FRBNY Staff Report 125 (working paper).
- Technical analysis and liquidity provision verified
Kenneth A. Kavajecz and Elizabeth R. Odders-White (2004), Review of Financial Studies 17(4):1043–1071
Support and resistance levels coincide with depth in the limit-order book (M04A · 4A.2).
- Candlestick technical trading strategies: Can they create value for investors? verified
Ben R. Marshall, Martin R. Young and Lawrence C. Rose (2006), Journal of Banking & Finance 30(8):2303–2323
Candlestick patterns tested with bootstrap nulls find no value (M04A · 4A.1).
- The high-volume return premium verified
Simon Gervais, Ron Kaniel and Dan H. Mingelgrin (2001), Journal of Finance 56(3):877–919
Unusually high volume predicts higher subsequent returns (M04A · 4A.3, 4A.5).
- The relation between price changes and trading volume: a survey verified
Jonathan M. Karpoff (1987), Journal of Financial and Quantitative Analysis 22(1):109–126
Survey of the volume–price-change relation behind M04A · 4A.3.
- A continuity correction for discrete barrier options verified
Mark Broadie, Paul Glasserman and Steven Kou (1997), Mathematical Finance 7(4):325–349
Shift the barrier to correct continuous-monitoring formulas for stops checked only at discrete times (M04A · 4A.6, 4A.8).
- A stopped Brownian motion formula verified
Howard M. Taylor (1975), Annals of Probability 3(2):234–246
Drawdown-type stopping of Brownian motion, behind the barrier results of M04A · 4A.6. Volume, issue and pages checked against Crossref (DOI 10.1214/aop/1176996395), 6 Nov 2026.
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John P. Lehoczky (1977), Annals of Probability 5(4):601–607
Trailing-stop exit as a stopping time based on the running maximum (M04A · 4A.8); shows the maximum at the stop is exponential for Brownian motion. Open access on Project Euclid; citation checked 6 Nov 2026 (DOI 10.1214/aop/1176995770).
- Bid, ask and transaction prices in a specialist market with heterogeneously informed traders verified
Lawrence Glosten and Paul Milgrom (1985), Journal of Financial Economics 14(1):71–100
The sequential-trade model of M05 · 5.3: the spread as compensation for adverse selection.
- A theory of intraday patterns: volume and price variability verified
Anat Admati and Paul Pfleiderer (1988), Review of Financial Studies 1(1):3–40
Why volume and volatility concentrate at the open and close: the intraday U-shape of M05.
- Direct estimation of equity market impact verified
Robert Almgren, Chee Thum, Emmanuel Hauptmann and Hong Li (2005), Risk, July 2005
Empirical temporary and permanent impact functions from institutional orders (M05 · 5.5).
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B. Tóth et al. (2011), Physical Review X 1, 021006
The square-root impact law and a latent-liquidity explanation for it (M05 · 5.5).
- No-dynamic-arbitrage and market impact verified
Jim Gatheral (2010), Quantitative Finance 10(7):749–759
Constraints that rule out price manipulation linking impact shape and decay (M05 · 5.5).
- The implementation shortfall: paper versus reality verified
André Perold (1988), Journal of Portfolio Management 14(3):4–9
The implementation-shortfall benchmark of M05 · 5.6.
- The total cost of transactions on the NYSE verified
Stephen Berkowitz, Dennis Logue and Eugene Noser (1988), Journal of Finance 43(1):97–112
The VWAP benchmark for measuring execution cost (M05 · 5.6).
- Market intraday momentum verified
Lei Gao, Yufeng Han, Sophia Zhengzi Li and Guofu Zhou (2018), Journal of Financial Economics 129(2):394–414
The first half-hour return predicts the last half-hour return (M05 · 5.8).
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Carlo Zarattini, Andrea Barbon and Andrew Aziz (2024), Swiss Finance Institute Research Paper 24-98
Opening-range breakout evidence discussed in M05 · 5.8; a working paper, read critically.
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Carlo Zarattini, Andrea Barbon and Andrew Aziz (2024), Swiss Finance Institute Research Paper 24-97
Intraday momentum on SPY with volatility-based bands (M05 · 5.8); a working paper, read critically.
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Brad Barber, Yi-Tsung Lee, Yu-Jane Liu and Terrance Odean (2014), Journal of Financial Markets 18:1–24
Taiwan day traders: fewer than 1% earn predictably positive returns net of fees (M05 · 5.10; M14).
- Learning, fast or slow verified
Brad Barber, Yi-Tsung Lee, Yu-Jane Liu, Terrance Odean and K. Zhang (2020), Review of Asset Pricing Studies 10(1):61–93
Day traders keep trading despite losses: learning about one's own skill is slow (M05 · 5.10).
- Day trading for a living? verified
Fernando Chague, Rodrigo De-Losso and Bruno Giovannetti (2019), working paper, SSRN 3423101
Brazilian futures day traders who persisted for 300+ days: almost all lost money (M05 · 5.10; M14).
- Capital asset prices: a theory of market equilibrium under conditions of risk verified
W. F. Sharpe (1964), Journal of Finance 19(3):425–442
The CAPM behind the cost of equity of M06 · 6.5.
- The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets verified
J. Lintner (1965), Review of Economics and Statistics 47(1):13–37
The independent derivation of the CAPM (M06 · 6.5).
- The capital asset pricing model: theory and evidence verified
E. Fama and K. French (2004), Journal of Economic Perspectives 18(3):25–46
Why the CAPM fails empirically yet survives in practice (M06 · 6.5).
- The detection of earnings manipulation verified
M. D. Beneish (1999), Financial Analysts Journal 55(5):24–36
The Beneish M-score of M06 · 6.8.
- Value investing: the use of historical financial statement information to separate winners from losers verified
J. D. Piotroski (2000), Journal of Accounting Research 38 (Supplement):1–41
The Piotroski F-score of M06 · 6.8.
- An empirical evaluation of accounting income numbers verified
R. Ball and P. Brown (1968), Journal of Accounting Research 6(2):159–178
The first earnings event study, and the first sighting of post-announcement drift (M06A · 6A.2).
- Evidence that stock prices do not fully reflect the implications of current earnings for future earnings verified
V. L. Bernard and J. K. Thomas (1990), Journal of Accounting and Economics 13(4):305–340
PEAD as underreaction to the autocorrelation of earnings surprises (M06A · 6A.2).
- Arbitrage risk and post-earnings-announcement drift verified
R. R. Mendenhall (2004), Journal of Business 77(4):875–894
Drift is larger where arbitrage is riskier (M06A · 6A.2).
- Investor inattention and Friday earnings announcements verified
S. DellaVigna and J. M. Pollet (2009), Journal of Finance 64(2):709–749
Friday announcements get a weaker immediate response and more drift (M06A · 6A.2).
- Driven to distraction: extraneous events and underreaction to earnings news verified
D. Hirshleifer, S. S. Lim and S. H. Teoh (2009), Journal of Finance 64(5):2289–2325
More drift on days crowded with other announcements (M06A · 6A.2).
- Rest in peace post-earnings announcement drift verified
C. Martineau (2022), Critical Finance Review 11(3–4):613–646
PEAD has largely disappeared in recent US large caps (M06A · 6A.2).
- Common stock repurchases and market signalling verified
T. Vermaelen (1981), Journal of Financial Economics 9(2):139–183
Tender-offer buybacks as signals (M06A · 6A.4).
- Market underreaction to open market share repurchases verified
D. Ikenberry, J. Lakonishok and T. Vermaelen (1995), Journal of Financial Economics 39(2–3):181–208
Long-run drift after open-market buyback announcements (M06A · 6A.4).
- Characteristics of risk and return in risk arbitrage verified
M. Mitchell and T. Pulvino (2001), Journal of Finance 56(6):2135–2175
Merger arbitrage pays like a short put on the market (M06A · 6A.7).
- Limited arbitrage in mergers and acquisitions verified
M. Baker and S. Savaşoğlu (2002), Journal of Financial Economics 64(1):91–115
Why merger-arbitrage spreads stay wide (M06A · 6A.7).
- Why new issues are underpriced verified
K. Rock (1986), Journal of Financial Economics 15(1–2):187–212
The winner's-curse explanation of IPO underpricing (M06A · 6A.8).
- The long-run performance of initial public offerings verified
J. R. Ritter (1991), Journal of Finance 46(1):3–27
IPOs underperform over the following years (M06A · 6A.8).
- The new issues puzzle verified
T. Loughran and J. R. Ritter (1995), Journal of Finance 50(1):23–51
Long-run underperformance of IPOs and seasoned offerings (M06A · 6A.8).
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T. Loughran, J. R. Ritter and K. Rydqvist (1994), Pacific-Basin Finance Journal 2(2–3):165–199
Underpricing across countries, including India (M06A · 6A.8). Link is Ritter's updated international table.
- Are insider trades informative? verified
J. Lakonishok and I. Lee (2001), Review of Financial Studies 14(1):79–111
Insider purchases carry information; sales mostly do not (M06A · 6A.9).
- Decoding inside information verified
L. Cohen, C. Malloy and L. Pomorski (2012), Journal of Finance 67(3):1009–1043
Separating opportunistic from routine insider trades (M06A · 6A.9).
- Earnings, book values, and dividends in equity valuation verified
J. A. Ohlson (1995), Contemporary Accounting Research 11(2):661–687
The residual-income model behind P/B valuation of banks (M06A · 6A.10).
- Common risk factors in the returns on stocks and bonds verified
E. F. Fama and K. R. French (1993), Journal of Financial Economics 33(1):3–56
The three-factor model (M06A · 6A.12).
- A five-factor asset pricing model verified
E. F. Fama and K. R. French (2015), Journal of Financial Economics 116(1):1–22
Adds profitability and investment factors (M06A · 6A.12).
- On persistence in mutual fund performance verified
M. M. Carhart (1997), Journal of Finance 52(1):57–82
The four-factor model with momentum (M06A · 6A.12); persistence of fund performance explained by momentum and expenses (M06B · 6B.7).
- Betting against beta verified
A. Frazzini and L. H. Pedersen (2014), Journal of Financial Economics 111(1):1–25
The low-beta anomaly and leverage constraints (M06A · 6A.12).
- Quality minus junk verified
C. S. Asness, A. Frazzini and L. H. Pedersen (2019), Review of Accounting Studies 24(1):34–112
The quality factor (M06A · 6A.12).
- Four factor model in Indian equities market verified
S. K. Agarwalla, J. Jacob and J. R. Varma (2013, revised 2014), IIMA Working Paper 2013-09-05
Methodology paper for the IIMA Indian Fama–French–Momentum data library (M06A · 6A.12).
- Indian PEAD study (Gupta and Dhusia, 2021) verified
Gupta and Dhusia (2021), Trends in Economics and Management 15(37), DOI 10.13164/trends.2021.37.27
Secondary Indian evidence on post-earnings-announcement drift; read critically. Title not given in the notes.
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Agarwal and Sridharan (2013), IIM Bangalore working paper
Secondary Indian evidence on post-earnings-announcement drift; read critically. Title not given in the notes.
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US Securities and Exchange Commission, 11 Mar 2005
The regulatory response to market timing after the 2003 scandal (M06B · 6B.12.4); read with SEC press release 2004-33 (Bank of America settlement), https://www.sec.gov/news/press/2004-33.htm
- Mutual fund performance verified
W. F. Sharpe (1966), Journal of Business 39(1):119–138
The reward-to-variability (Sharpe) ratio, introduced to rank mutual funds (M06B · 6B.7).
- The performance of mutual funds in the period 1945–1964 verified
M. C. Jensen (1968), Journal of Finance 23(2):389–416
Jensen's alpha and the first large test of fund skill: funds did not beat buy-and-hold after costs (M06B · 6B.7).
- Mutual fund flows and performance in rational markets verified
J. B. Berk and R. C. Green (2004), Journal of Political Economy 112(6):1269–1295
Skill, decreasing returns to scale and competitive flows: why net alpha does not persist although managers are skilled. M06B Proposition 6B.7.1 is a linear version.
- Luck versus skill in the cross-section of mutual fund returns verified
E. F. Fama and K. R. French (2010), Journal of Finance 65(5):1915–1947
Bootstrap simulation of alpha t-statistics under zero true alpha; few funds cover their costs (M06B · 6B.7.2).
- How active is your fund manager? A new measure that predicts performance verified
K. J. M. Cremers and A. Petajisto (2009), Review of Financial Studies 22(9):3329–3365
Active share (M06B (6B.20)) and closet indexing.
- Measuring the true cost of active management by mutual funds unverified
R. M. Miller (2007), Journal of Investment Management 5(1):29–49
The active expense ratio of M06B (6B.33): what a fund charges for the part of the portfolio that differs from the index.
- Who cares about shareholders? Arbitrage-proofing mutual funds verified
E. Zitzewitz (2003), Journal of Law, Economics, and Organization 19(2):245–280
Stale-price arbitrage in US international funds and its dilution of long-term holders (56 bp a year in 1998–99, 114 bp in 2001); the background to the 2003 scandal (M06B · 6B.2, 6B.12.4).
- Payoff complementarities and financial fragility: evidence from mutual fund outflows verified
Q. Chen, I. Goldstein and W. Jiang (2010), Journal of Financial Economics 97(2):239–262
Why funds holding illiquid assets are prone to runs, with evidence; the model behind M06B Proposition 6B.10.2.
- The index premium and its hidden cost for index funds unverified
A. Petajisto (2011), Journal of Empirical Finance 18(2):271–288
The cost to index funds of trading at index-change prices pushed by anticipating traders (M06B · 6B.8).
- Inefficiencies in the pricing of exchange-traded funds verified
A. Petajisto (2017), Financial Analysts Journal 73(1):24–54
ETF premiums and discounts relative to NAV, largest for illiquid and international ETFs (M06B · 6B.9).
- Do ETFs increase volatility? verified
I. Ben-David, F. Franzoni and R. Moussawi (2018), Journal of Finance 73(6):2471–2535
ETF arbitrage transmits liquidity shocks to the underlying stocks: stocks with more ETF ownership are more volatile (M06B · 6B.9).
- A note on the suboptimality of dollar-cost averaging as an investment policy verified
G. M. Constantinides (1979), Journal of Financial and Quantitative Analysis 14(2):443–450
Why precommitted averaging is dominated by a policy that conditions on information (M06B Proposition 6B.6.2).
- The relation between forward prices and futures prices verified
J. C. Cox, J. E. Ingersoll and S. A. Ross (1981), Journal of Financial Economics 9(4):321–346
The source of M07 Props 7.5–7.6: forward and futures prices coincide under deterministic rates and differ with stochastic rates (7.2.3–7.2.4).
- Forward contracts and futures contracts verified
R. A. Jarrow and G. S. Oldfield (1981), Journal of Financial Economics 9(4):373–382
Companion to Cox–Ingersoll–Ross on the futures–forward gap (M07 · 7.2.4).
- Martingales and stochastic integrals in the theory of continuous trading verified
J. M. Harrison and S. R. Pliska (1981), Stochastic Processes and their Applications 11(3):215–260
The risk-neutral pricing principle used in M07 · 7.2.4 and the continuous-time martingale theory behind M08.
- The theory of hedging and speculation in commodity futures verified
L. L. Johnson (1960), Review of Economic Studies 27(3):139–151
Minimum-variance hedging (M07 · 7.6.2).
- The hedging performance of the new futures markets verified
L. H. Ederington (1979), Journal of Finance 34(1):157–170
Minimum-variance hedge ratio and R² as the measure of hedging effectiveness (M07 · 7.6.2).
- Metallgesellschaft and the economics of synthetic storage verified
C. L. Culp and M. H. Miller (1995), Journal of Applied Corporate Finance
The defence of MG's stack-and-roll hedge (M07 · 7.8.1).
- Maturity structure of a hedge matters: lessons from the Metallgesellschaft debacle verified
A. S. Mello and J. E. Parsons (1995), Journal of Applied Corporate Finance
The critique: the stack hedge created funding risk the firm could not carry (M07 · 7.8.1).
- Metallgesellschaft: a prudent hedger ruined, or a wildcatter on NYMEX? verified
S. C. Pirrong (1997), Journal of Futures Markets
Argues the one-for-one stack was a speculative position, not a hedge (M07 · 7.8.1).
- The Pricing of Commodity Contracts verified
F. Black (1976), Journal of Financial Economics 3(1–2):167–179
Black-76: options on futures, used for Nifty and MCX options in M08 · 8.8.
-
J. C. Cox, S. A. Ross and M. Rubinstein (1979), Journal of Financial Economics 7(3):229–263
The binomial tree of M08 · 8.3–8.4.
- Martingales and Arbitrage in Multiperiod Securities Markets verified
J. M. Harrison and D. M. Kreps (1979), Journal of Economic Theory 20(3):381–408
No arbitrage and the existence of an equivalent martingale measure (M08 · 8.3).
- The Calculation of Implied Variances from the Black–Scholes Model: A Note verified
S. Manaster and G. Koehler (1982), Journal of Finance 37(1):227–230
A starting point that guarantees Newton's method converges for implied volatility (M08 · 8.10).
- Binomial Models for Option Valuation – Examining and Improving Convergence verified
D. Leisen and M. Reimer (1996), Applied Mathematical Finance 3(4):319–346
A tree that removes most of the odd–even oscillation of CRR convergence (M08 · 8.4).
- Let's Be Rational verified
P. Jäckel (2015), Wilmott 2015(75):40–53
Implied volatility to machine precision in two iterations; the production method mentioned in M08 · 8.10.
-
US General Accounting Office
Official account of the 1998 recapitalisation, cited in M08 Case A.
- A Guide to Volatility and Variance Swaps verified
K. Demeterfi, E. Derman, M. Kamal and J. Zou (1999), Journal of Derivatives 6(4):9–32
Replicating a variance swap with a strip of options (M09 · 9.6). Also circulated as the Goldman Sachs Quantitative Strategies note "More Than You Ever Wanted to Know About Volatility Swaps".
- The Extreme Value Method for Estimating the Variance of the Rate of Return verified
M. Parkinson (1980), Journal of Business 53(1):61–65
The high–low range estimator of M09 · 9.2.2.
- On the Estimation of Security Price Volatilities from Historical Data verified
M. Garman and M. Klass (1980), Journal of Business 53(1):67–78
The OHLC estimator of M09 · 9.2.3.
- Estimating Variance from High, Low and Closing Prices verified
L. C. G. Rogers and S. Satchell (1991), Annals of Applied Probability 1(4):504–512
A drift-robust range estimator (M09 · 9.2.3).
- Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices verified
D. Yang and Q. Zhang (2000), Journal of Business 73(3):477–491
The estimator that also handles overnight gaps (M09 · 9.2.3).
- The Asymptotic Distribution of the Range of Sums of Independent Random Variables verified
W. Feller (1951), Annals of Mathematical Statistics 22(3):427–432
The distribution of the range of Brownian motion behind Parkinson's estimator (M09 · 9.2.2).
- Robustness of the Black and Scholes Formula verified
N. El Karoui, M. Jeanblanc-Picqué and S. Shreve (1998), Mathematical Finance 8(2):93–126
Hedging with a misspecified volatility: P&L depends on implied minus realised variance weighted by gamma (M09 · 9.3).
- Towards a Theory of Volatility Trading verified
P. Carr and D. Madan (1998), in R. Jarrow (ed.), Volatility, Risk Books
Delta-hedged P&L and the log-contract replication of variance (M09 · 9.3, 9.6).
- Which Free Lunch Would You Like Today, Sir? Delta Hedging, Volatility Arbitrage and Optimal Portfolios verified
R. Ahmad and P. Wilmott (2005), Wilmott Magazine, Nov 2005
Hedging at implied versus realised volatility and the resulting P&L paths (M09 · 9.3).
- When Is Time Continuous? verified
D. Bertsimas, L. Kogan and A. Lo (2000), Journal of Financial Economics 55(2):173–204
Hedging error from discrete rebalancing (M09 · 9.3).
- Delta-Hedged Gains and the Negative Market Volatility Risk Premium verified
G. Bakshi and N. Kapadia (2003), Review of Financial Studies 16(2):527–566
Delta-hedged long options lose on average: evidence for the variance risk premium (M09 · 9.4).
- Expected Option Returns verified
J. Coval and T. Shumway (2001), Journal of Finance 56(3):983–1009
Index option returns are too negative for the CAPM (M09 · 9.4).
- Expected Stock Returns and Variance Risk Premia verified
T. Bollerslev, G. Tauchen and H. Zhou (2009), Review of Financial Studies 22(11):4463–4492
The variance risk premium predicts equity returns (M09 · 9.4).
-
G. Sankar, S. Ramachandran and J. Lukose P J (2020), International Review of Economics & Finance 70:321–334
Indian evidence on the variance risk premium (M09 · 9.4).
- Prices of State-Contingent Claims Implicit in Option Prices verified
D. Breeden and R. Litzenberger (1978), Journal of Business 51(4):621–651
The risk-neutral density as the second strike-derivative of call prices (M09 · 9.5).
- Implied Binomial Trees verified
M. Rubinstein (1994), Journal of Finance 49(3):771–818
The post-1987 skew and trees fitted to it (M09 · 9.5).
- Does Net Buying Pressure Affect the Shape of Implied Volatility Functions? verified
N. Bollen and R. Whaley (2004), Journal of Finance 59(2):711–753
Demand for index puts shapes the skew (M09 · 9.5).
- Demand-Based Option Pricing verified
N. Gârleanu, L. H. Pedersen and A. Poteshman (2009), Review of Financial Studies 22(10):4259–4299
End-user demand moves option prices when dealers cannot hedge perfectly (M09 · 9.5).
- Regimes of Volatility verified
E. Derman (1999), Risk 12(4)
Sticky-strike, sticky-delta and sticky-implied-tree regimes of the smile (M09 · 9.5).
- Pricing with a Smile verified
B. Dupire (1994), Risk 7(1):18–20
The local-volatility formula of M09 · 9.5.
- A Closed-Form Solution for Options with Stochastic Volatility verified
S. Heston (1993), Review of Financial Studies 6(2):327–343
The Heston stochastic-volatility model (M09 · 9.5).
- Stocks as Lotteries verified
N. Barberis and M. Huang (2008), American Economic Review 98(5):2066–2100
Probability weighting makes investors overpay for lottery-like payoffs, such as far OTM options (M09 · 9.12.3).
- Option Pricing of Earnings Announcement Risks verified
A. Dubinsky, M. Johannes, A. Kaeck and N. J. Seeger (2019), Review of Financial Studies 32(2):646–687
Extracting the market's expected earnings-day move from the option term structure (M09A · 9A.10).
-
M. Avellaneda and M. D. Lipkin (2003), Quantitative Finance 3(6):417–425
Delta hedging by long-gamma dealers pins prices to strikes near expiry (M09A · 9A.6).
-
S. X. Ni, N. D. Pearson and A. M. Poteshman (2005), Journal of Financial Economics 78(1):49–87
Evidence that optionable stocks cluster at strikes on expiry (M09A · 9A.6).
- Pinning in the S&P 500 futures verified
B. Golez and J. C. Jackwerth (2012), Journal of Financial Economics 106(3):566–585
Pinning in an index futures market (M09A · 9A.6).
-
J. Pan and A. M. Poteshman (2006), Review of Financial Studies 19(3):871–908
The put–call ratio from opening buys on proprietary data predicts returns; public PCR does much less (M09A · 9A.4). Link is NBER WP 10925.
- Speculation and Economic Stability verified
N. Kaldor (1939), Review of Economic Studies 7(1):1–27
Origin of the convenience yield (M10 · 10.2).
- The Theory of Price of Storage verified
H. Working (1949), American Economic Review 39(6):1254–1262
The supply-of-storage curve: spreads as the price of storage (M10 · 10.2).
- The Supply of Storage verified
M. J. Brennan (1958), American Economic Review 48(1):50–72
Convenience yield falls as inventories rise (M10 · 10.2).
- On the Behaviour of Commodity Prices verified
A. Deaton and G. Laroque (1992), Review of Economic Studies 59(1):1–23
Storage with a non-negativity constraint generates skewed prices and occasional spikes; for depth on M10 · 10.2.
- Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage verified
E. F. Fama and K. R. French (1987), Journal of Business 60(1):55–73
Empirical test of the theory of storage across commodities (M10 · 10.2).
- The Strategic and Tactical Value of Commodity Futures verified
C. B. Erb and C. R. Harvey (2006), Financial Analysts Journal 62(2):69–97
Roll yield, not spot return, drives long-run commodity futures returns (M10 · 10.3).
- The Fundamentals of Commodity Futures Returns verified
G. Gorton, F. Hayashi and K. G. Rouwenhorst (2013), Review of Finance 17(1):35–105
Inventories, the futures basis and risk premiums: the inventory evidence for M10 · 10.2–10.3.
- The Economics of Exhaustible Resources verified
H. Hotelling (1931), Journal of Political Economy 39(2):137–175
The Hotelling rule of M10 · 10.4.
- Nonrenewable Resource Scarcity verified
J. A. Krautkraemer (1998), Journal of Economic Literature 36(4):2065–2107
Survey of how the Hotelling rule fares in the data (M10 · 10.4).
- Gibson's Paradox and the Gold Standard verified
R. B. Barsky and L. H. Summers (1988), Journal of Political Economy 96(3):528–550
Gold as a durable asset whose price moves inversely with real rates (M10 · 10.4, 10.6).
- Distribution of the Estimators for Autoregressive Time Series with a Unit Root verified
D. A. Dickey and W. A. Fuller (1979), JASA 74(366):427–431
The Dickey–Fuller unit-root test: the gold/silver ratio of M10 · 10.7 and the proofs of M13A · 13A.2.
-
A. Estrella and F. Mishkin (1998), Review of Economics and Statistics 80(1):45–61
The yield-curve slope as a recession predictor (M11 · 11.5).
- Forward and spot exchange rates verified
E. Fama (1984), Journal of Monetary Economics 14(3):319–338
The forward premium puzzle: high-interest currencies do not depreciate as UIP predicts (M11 · 11.9).
-
W. Du, A. Tepper and A. Verdelhan (2018), Journal of Finance 73(3):915–957
Persistent CIP deviations after 2008 and bank balance-sheet costs (M11 · 11.8).
- Carry Trades and Currency Crashes verified
M. Brunnermeier, S. Nagel and L. Pedersen (2008), NBER Macroeconomics Annual 23:313–348
Carry-trade returns are negatively skewed: up the stairs, down the elevator (M11 · 11.9).
- Tapering talk: The impact of expectations of reduced Federal Reserve security purchases on emerging markets verified
B. Eichengreen and P. Gupta (2015), Emerging Markets Review 25:1–15
The 2013 taper tantrum and India's exposure through its external balances (M11 case studies).
- The Purchasing Power Parity Puzzle verified
K. Rogoff (1996), Journal of Economic Literature 34(2):647–668
Real exchange rates revert with a half-life of years (M11 · 11.9). Citation checked 6 Nov 2026: JEL 34(2), June 1996, pp. 647–668 (RePEc record; publisher version on JSTOR).
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H. Neville, T. Draaisma, B. Funnell, C. R. Harvey and O. Van Hemert (2021), Journal of Portfolio Management 47(8):8–37; SSRN 3813202
Asset-class performance in inflationary regimes (M11 · 11.13): commodities had the strongest real returns, and cross-sectional momentum was the strongest equity factor. Journal citation checked 6 Nov 2026 (Duke scholars record); the working paper is SSRN 3813202.
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Hélène Rey (2013), Federal Reserve Bank of Kansas City Economic Policy Symposium (Jackson Hole); reissued as NBER WP 21162 (2015)
The global financial cycle limits monetary independence even under floating rates (M11 · 11.7). Citation checked 6 Nov 2026 against the Fed in Print record (fedinprint.org/item/fedkpr/21390).
- ICE FX Indexes Methodology (DXY) verified
ICE
The DXY as a geometric average of six currencies against the dollar (M11 · 11.10).
- Corporate Forecasts of Earnings Per Share and Stock Price Behavior: Empirical Test verified
J. Patell (1976), Journal of Accounting Research 14(2), from p. 246
The standardised-abnormal-return (Patell) test of M12 · 12.3.
- Event-study methodology under conditions of event-induced variance verified
E. Boehmer, J. Musumeci and A. Poulsen (1991), Journal of Financial Economics 30(2):253–272
The BMP test, robust to variance that rises on the event day (M12 · 12.3).
- Event Study Testing with Cross-sectional Correlation of Abnormal Returns verified
J. Kolari and S. Pynnönen (2010), Review of Financial Studies 23(11):3996–4025
Adjusting event-study tests when events cluster in calendar time (M12 · 12.3).
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M. Iacoviello and J. Tong (2026), Federal Reserve Board working paper
A geopolitical-risk index built with AI, the successor to the text-count GPR (M12 · 12.4); data at the same page.
- Efficient capital markets: a review of theory and empirical work verified
E. Fama (1970), Journal of Finance 25(2):383–417
The three forms of market efficiency (M13 · 13.1).
- On the impossibility of informationally efficient markets verified
S. Grossman and J. Stiglitz (1980), American Economic Review 70(3):393–408
Prices cannot be fully informative if information is costly: the Grossman–Stiglitz paradox of M13 · 13.1.
- A comprehensive 2022 look at the empirical performance of equity premium prediction verified
A. Goyal, I. Welch and A. Zafirov (2024), Review of Financial Studies 37(11):3490–3557
Update of Welch–Goyal with 29 newer variables: most fail out of sample (M13 · 13.3).
- Predictive regressions verified
R. F. Stambaugh (1999), Journal of Financial Economics 54(3):375–421
The small-sample bias of predictive regressions with persistent regressors (M13 · 13.3, Proposition 13.9).
- Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation verified
R. F. Engle (1982), Econometrica 50(4):987–1007
The ARCH model (M13 · 13.4).
- Generalized autoregressive conditional heteroskedasticity verified
T. Bollerslev (1986), Journal of Econometrics 31(3):307–327
The GARCH(1,1) model of M13 · 13.4.
- Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances verified
T. Bollerslev and J. Wooldridge (1992), Econometric Reviews 11(2):143–172
Robust standard errors for GARCH estimated under a wrong (normal) likelihood (M13 · 13.4).
- Stationarity and persistence in the GARCH(1,1) model verified
D. Nelson (1990), Econometric Theory 6(3):318–334
Strict stationarity of GARCH(1,1), including IGARCH (M13 · 13.4).
- Volatility forecast comparison using imperfect volatility proxies verified
A. Patton (2011), Journal of Econometrics 160(1):246–256
Which loss functions rank variance forecasts correctly against a noisy proxy (MSE and QLIKE) (M13 · 13.4).
- Dynamic linear models with Markov-switching verified
C.-J. Kim (1994), Journal of Econometrics 60(1–2):1–22
The Kim smoother for regime-switching models (M13 · 13.5).
- Verification of forecasts expressed in terms of probability verified
G. W. Brier (1950), Monthly Weather Review 78(1):1–3
The Brier score of M13 · 13.7.
- A new vector partition of the probability score verified
A. H. Murphy (1973), Journal of Applied Meteorology 12(4):595–600
The reliability–resolution–uncertainty decomposition of the Brier score (M13 · 13.7, Proposition 13.20).
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B. Mellers et al. (2014), Psychological Science 25(5):1106–1115
Good Judgment Project: training, teaming and tracking improve Brier scores (M13 · 13.8 and case studies). Summary: https://www.psychologicalscience.org/publications/observer/obsonline/predicting-uncertain-events-on-a-global-scale.html
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Ajay Pandey (2003), IIM Ahmedabad working paper (listed 3 Aug 2003)
Conditional models forecast five-day and monthly Nifty realised volatility poorly (M13 · 13.4). Title, author and PDF checked on the IIMA listing, 6 Nov 2026; the module reports it at abstract level, so read the paper before relying on details.
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Vivek Rajvanshi, Arijit Santra and Saunak Basu (March 2017), IIM Calcutta WPS No. 797
GARCH augmented with India VIX beats plain GARCH and implied volatility alone for Nifty 50 realised volatility (M13 · 13.4). Title, authors and date checked on the PDF's title page, 6 Nov 2026; reported at abstract level, so read the paper before relying on details.
- Realized Volatility and India VIX verified
Ashok Banerjee and Ritesh Kumar (November 2011), IIM Calcutta WPS No. 688
Another Indian comparison of implied (India VIX) and realised-volatility forecasts (M13 case studies). Title, authors and date checked on the PDF's title page, 6 Nov 2026; cited at abstract level.
- Testing for unit roots in autoregressive-moving average models of unknown order verified
S. E. Said and D. A. Dickey (1984), Biometrika 71(3):599–607
Justifies the augmented Dickey–Fuller test with a growing lag order (M13A · 13A.2).
-
J. G. MacKinnon (2010), Queen's Economics Department Working Paper 1227
Response-surface critical values for unit-root and Engle–Granger tests (M13A · 13A.2, 13A.5).
- Testing the random walk hypothesis: power versus frequency of observation verified
R. J. Shiller and P. Perron (1985), Economics Letters 18(4):381–386
Power of unit-root tests depends on the span of data, not the number of observations (M13A · 13A.2).
- Testing the null hypothesis of stationarity against the alternative of a unit root verified
D. Kwiatkowski, P. C. B. Phillips, P. Schmidt and Y. Shin (1992), Journal of Econometrics 54:159–178
The KPSS test, with stationarity as the null (M13A · 13A.2).
- Spurious regressions in econometrics verified
C. W. J. Granger and P. Newbold (1974), Journal of Econometrics 2(2):111–120
Regressing one random walk on another gives significant t-statistics by accident (M13A · 13A.3).
- Understanding spurious regressions in econometrics verified
P. C. B. Phillips (1986), Journal of Econometrics 33(3):311–340
The asymptotic theory of spurious regression (M13A · 13A.3).
- Asymptotic properties of residual based tests for cointegration verified
P. C. B. Phillips and S. Ouliaris (1990), Econometrica 58(1):165–193
Why Engle–Granger residual tests need their own critical values (M13A · 13A.5).
- Statistical analysis of cointegration vectors verified
S. Johansen (1988), Journal of Economic Dynamics and Control 12(2–3):231–254
The reduced-rank regression and trace test of M13A · 13A.6.
- Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models verified
S. Johansen (1991), Econometrica 59(6):1551–1580
The full Johansen framework with deterministic terms (M13A · 13A.6).
- A simple estimator of cointegrating vectors in higher order integrated systems verified
J. H. Stock and M. W. Watson (1993), Econometrica 61(4):783–820
Dynamic OLS: efficient estimation of the cointegrating vector.
- Statistical inference in instrumental variables regression with I(1) processes verified
P. C. B. Phillips and B. E. Hansen (1990), Review of Economic Studies 57(1):99–125
Fully modified OLS for cointegrating regressions.
- Estimation of common long-memory components in cointegrated systems verified
J. Gonzalo and C. W. J. Granger (1995), JBES 13(1):27–35
Permanent–transitory decomposition and price-discovery shares (M13A · 13A.4).
- One security, many markets: determining the contributions to price discovery verified
J. Hasbrouck (1995), Journal of Finance 50(4):1175–1199
Information shares: which market leads price discovery (M13A · 13A.4).
- Analytic solutions for optimal statistical arbitrage trading verified
W. K. Bertram (2010), Physica A 389(11):2234–2243, doi:10.1016/j.physa.2010.01.045
Optimal entry and exit bands for an OU spread and the expected cycle time (M13A · 13A.8).
- Optimal mean reversion trading with transaction costs and stop-loss exit verified
T. Leung and X. Li (2015), International Journal of Theoretical and Applied Finance 18(3)
Optimal stopping for OU spreads with costs and stop-losses (M13A · 13A.8).
- Statistical arbitrage in the US equities market verified
M. Avellaneda and J.-H. Lee (2010), Quantitative Finance 10(7):761–782
Factor-residual (PCA and ETF) statistical arbitrage with OU s-scores.
- Optimal properties of exponentially weighted forecasts verified
J. F. Muth (1960), JASA 55(290):299–306
The exponentially weighted average as the optimal (Kalman) forecast of a random walk plus noise (M13A · 13A.9).
- Tests of equality between sets of coefficients in two linear regressions verified
G. C. Chow (1960), Econometrica 28(3):591–605
The Chow test for a break at a known date (M13A · 13A.10).
- Tests of the hypothesis that a linear regression system obeys two separate regimes verified
R. E. Quandt (1960), JASA 55(290):324–330
The sup-F idea for a break at an unknown date (M13A · 13A.10).
- Tests for parameter instability and structural change with unknown change point verified
D. W. K. Andrews (1993), Econometrica 61(4):821–856
Asymptotic critical values for the sup-F test (M13A · 13A.10).
- Techniques for testing the constancy of regression relationships over time verified
R. L. Brown, J. Durbin and J. M. Evans (1975), JRSS B 37(2):149–192
The CUSUM and CUSUM-of-squares tests (M13A · 13A.10).
- Estimating and testing linear models with multiple structural changes verified
J. Bai and P. Perron (1998), Econometrica 66(1):47–78
Multiple breaks at unknown dates (M13A · 13A.10).
- Computation and analysis of multiple structural change models verified
J. Bai and P. Perron (2003), Journal of Applied Econometrics 18(1):1–22
The dynamic-programming algorithm for Bai–Perron (M13A · 13A.10).
- Residual-based tests for cointegration in models with regime shifts verified
A. W. Gregory and B. E. Hansen (1996), Journal of Econometrics 70(1):99–126
Cointegration tests that allow one break in the cointegrating vector (M13A · 13A.10).
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A. E. Khandani and A. W. Lo (2011), Journal of Financial Markets 14(1):1–46
The quant crash of August 2007: crowded mean-reversion strategies unwinding together, documented with factor and transactions data (M13A · 13A.13). The extended version of the authors' 2007 paper of the same name (Journal of Investment Management 5, 29–78, 2007; https://web.mit.edu/~alo/www/Papers/august07.html), which it supersedes; read this one.
- The limits of arbitrage verified
A. Shleifer and R. W. Vishny (1997), Journal of Finance 52(1):35–55
Arbitrageurs with outside capital are forced to cut positions exactly when mispricing widens.
- The properties of equally weighted risk contribution portfolios verified
S. Maillard, T. Roncalli and J. Teiletche (2010), Journal of Portfolio Management 36(4):60–70
Equal-risk-contribution portfolios sit between minimum variance and 1/N (M14 · 14.4).
- A well-conditioned estimator for large-dimensional covariance matrices verified
O. Ledoit and M. Wolf (2004), Journal of Multivariate Analysis 88(2):365–411
Shrinkage towards a scaled identity: the Ledoit–Wolf estimator of M14 · 14.3.
- Honey, I shrunk the sample covariance matrix verified
O. Ledoit and M. Wolf (2004), Journal of Portfolio Management 30(4):110–119
The practitioner version of covariance shrinkage (M14 · 14.3).
- The Markowitz optimization enigma: is "optimized" optimal? verified
R. Michaud (1989), Financial Analysts Journal 45(1):31–42
Mean–variance optimisers maximise estimation error (M14 · 14.2).
- Volatility-managed portfolios verified
A. Moreira and T. Muir (2017), Journal of Finance 72(4):1611–1644
Scaling exposure inversely to recent variance raises Sharpe ratios (M14 · 14.5).
- Optimal investment strategies for controlling drawdowns verified
S. Grossman and Z. Zhou (1993), Mathematical Finance 3(3):241–276
Optimal policy under a maximum-drawdown constraint: risk exposure proportional to the distance from the floor (M14 · 14.8).
- Advances in prospect theory verified
A. Tversky and D. Kahneman (1992), Journal of Risk and Uncertainty 5(4):297–323
Cumulative prospect theory, read with Kahneman and Tversky (1979) for M14 · 14.9.
- The disposition to sell winners too early and ride losers too long verified
H. Shefrin and M. Statman (1985), Journal of Finance 40(3):777–790
Names and explains the disposition effect (M14 · 14.9).
- Boys will be boys verified
B. Barber and T. Odean (2001), Quarterly Journal of Economics 116(1):261–292
Overconfidence: men trade more than women and earn less for it (M14 · 14.9).
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B. Hurst, Y. H. Ooi and L. H. Pedersen, Journal of Portfolio Management 44(1), 2017
Time-series momentum across futures markets since 1880; the evidence behind trend rules on commodity futures (Playbook 15.11, M04 · 4.3.2).