Juhani Linnainmaa

Juhani T. Linnainmaa

Associate Professor of Finance and PCL Faculty Scholar

NBER Faculty Research Fellow

University of Chicago Booth School of Business

5807 South Woodlawn Avenue

Chicago, IL 60637


Email: jlinnain [at] chicagobooth.edu

Tel: +1 (773) 834 3176

Curriculum Vitae



  1. Ball, Ray, Joseph Gerakos, Juhani Linnainmaa, and Valeri Nikolaev, 2015, Accruals, cash flows, and operating profitability in the cross section of stock returns, Journal of Financial Economics, forthcoming. [SSRN link]

A cash-based operating profitability measure (that excludes accruals) outperforms other measures of profitability and subsumes accruals in predicting the cross section of average returns. Firms with high accruals earn low average returns because they are less profitable on a cash basis.

Note: Fama and French (2015) compare our cash-based operating profitability factor against two alternative profitability factors, and find that the cash factor improves the description of average returns for many left hand side sorts.

Award: First prize in the academic competition at the Chicago Quantitative Alliance (CQA) Fall 2015 Conference.

  1. Foerster, Stephen, Juhani Linnainmaa, Brian Melzer, and Alessandro Previtero, 2015, Retail financial advice: Does one size fit all? Journal of Finance, forthcoming. [SSRN link]

Advisor fixed effects explain considerably more variation in portfolio risk and home bias than a broad set of investor attributes that includes risk tolerance, stage in the lifecycle and financial sophistication. An advisor's own asset allocation strongly predicts the allocations chosen on clients' behalf.

Award: 2015 CFA Society & Hillsdale Canadian Investment Research Award (announcement)

Media: Featured in Wall Street Journal ("Client Portfolios May Match Advisers’ Own Asset Allocation", December 12, 2014), Globe and Mail ("Make portfolio-building a priority to justify investment adviser fees," December 5, 2014; "Putting a number on the value of financial advice: 3%," June 14, 2015), Fiscal Times ("Expensive, one-size-fits-all advice," December 10, 2014), and Chicago Booth Capital Ideas ("Why financial advice isn't worth the fees," February 25, 2015)

  1. Linnainmaa, Juhani, Walter Torous, and James Yae, 2015, Reading the tea leaves: Model uncertainty, robust forecasts, and the autocorrelation of analysts' forecast errors, Journal of Financial Economics, forthcoming. [SSRN link]

We estimate that analysts' concerns for model misspecification explain approximately 60% of the autocorrelation in analysts' forecast errors. Our model of robust forecasting applies not only to analysts' forecasts but to all model-based forecasts.

  1. Keloharju, Matti, Juhani Linnainmaa, and Peter Nyberg, 2015, Return seasonalities, Journal of Finance, forthcoming. [SSRN link] [Internet Appendix] [AQR Insight Award Finalist 2015: Announcement / AQR Insight Award Slides]

We document return seasonalities in individual stock returns, portfolio returns, anomalies, commodities, international stock market indices, and at the daily frequency. These return seasonalities overwhelm unconditional differences in expected returns.

Note: If you try to replicate the result on long-lasting seasonalities in daily returns, please remember to account for market closures due to U.S. holidays. As the lag k grows, the likelihood that the days go out of sync increases; a regression at lag k=200, for example, is very unlikely a Monday-on-Monday (or Tuesday-on-Tuesday, and so forth) regression. You should "pad" the data with missing values so that there is an observation for every stock-day even when the market is closed. The fact that this alignment matters indicates that these regressions indeed pick up cross-sectional day-of-the-week seasonalities in average returns and not, e.g., autocorrelated innovations measurable in trading time.

  1. Ball, Ray, Joseph Gerakos, Juhani Linnainmaa, and Valeri Nikolaev, 2015, Deflating profitability, Journal of Financial Economics 117(2), 225-248 (lead article). [SSRN link]

An alternative measure of firm profits, operating profits, exhibits a far stronger link with expected returns than either net income or gross profit.

Note: The XSGA variable in Compustat adds to the SG&A reported by the company other items such as R&D expenses. This issue is discussed on p. 254 of Volume 5 of Compustat Manuals. You can recover the reported SG&A by subtracting XRD from XSGA.

Media: Featured in Forbes ("The Profitability Factor Redux: Super-Duel in Space," June 2, 2014)

  1. Gerakos, Joseph and Juhani Linnainmaa, 2014, Market reactions to tangible and intangible information revisited, Critical Finance Review 5, 135-163. [PDF] [SSRN link]

A decomposition of book-to-market ratio into stock and book returns creates a book return polluted by past book-to-market ratios, stock returns, net issuances, and dividends. Our results cast doubt on the argument that book-to-market forecasts returns because it is a good proxy for the intangible return.

  1. Linnainmaa, Juhani, 2013, Reverse Survivorship Bias, Journal of Finance 68(3), 789-813 (lead article). [PDF] [SSRN link] [Internet Appendix]

The distribution of estimated alphas is biased downwards if funds tend to disappear following poor performance. This paper estimates a structural model to correct for this "reverse survivorship bias."

Media: Mutual fund research featured in Time magazine ("The Triumph of Index Funds," September 18, 2014) and "The Big Question: Are successful active managers lucky or skilled?" (Capital Ideas, August 2014).

  1. Keloharju, Matti, Samuli Knüpfer, and Juhani Linnainmaa, 2012, Do investors buy what they know? Product market choices and investment decisions, Review of Financial Studies 25(10), 2921-2958 (lead article). [PDF] [SSRN link]

Individuals’ product market choices influence their investment decisions.

  1. Linnainmaa, Juhani and Gideon Saar, 2012, Lack of anonymity and the inference from order flow, Review of Financial Studies 25(5), 1414-1456. [PDF] [SSRN link]

We demonstrate that broker identity is a powerful signal about the identity of investors who initiate trades, and that the broker ID signal is important enough to affect prices.

  1. Grinblatt, Mark, Matti Keloharju, and Juhani Linnainmaa, 2012, IQ, trading behavior, and performance, Journal of Financial Economics 104(2), 339-362. Reprinted in Household Finance, M. Haliassos (ed.), The International Library of Critical Writings in Economics series, Edward Elgar Publishing (2015). [PDF] [SSRN link]

High-IQ investors are less subject to the disposition effect and more aggressive about tax-loss trading, and they exhibit superior market timing, stock-picking skill, and trade execution.

Award: Runner-up for Goldman Sachs International - Best Conference Paper Award at the 2010 European Finance Association Conference.

  1. Grinblatt, Mark, Matti Keloharju, and Juhani Linnainmaa, 2011, IQ and stock market participation, Journal of Finance 66(6), 2121-2164. Reprinted in Household Finance, M. Haliassos (ed.), The International Library of Critical Writings in Economics series, Edward Elgar Publishing (2015). [PDF] [Internet Appendix] [SSRN link]

Stock market participation is monotonically related to IQ, controlling for wealth, income, age, and other demographic and occupational information.

Media: Featured in Bloomberg Businessweek ("Smart Money Owns More Equities Says IQ Study of Who Buys Stocks," January 19, 2012) and New York Times ("What High-I.Q. Investors Do Differently," February 26, 2012)

Award: One of five papers awarded the "best finance papers of 2011" award by the Foundation for the Advancement of Finnish Securities Market.

  1. Linnainmaa, Juhani, 2011, Why do (some) households trade so much? Review of Financial Studies 24(5), 1630-1666. [PDF] [SSRN link]

When agents can learn about their abilities as active investors, they rationally "trade to learn" even if they expect to lose from active investing.

Award: One of five papers awarded the "best finance papers of 2011" award by the Foundation for the Advancement of Finnish Securities Market.

  1. Grinblatt, Mark and Juhani Linnainmaa, 2011, Jensen's Inequality, parameter uncertainty, and multi-period investment, Review of Asset Pricing Studies 1(1), 1-34 (lead article). [PDF] [SSRN link]

The proper application of Jensen’s inequality to the multi-period investment decision turns finance intuition on its head: multi-period investments with negative risk premia can be profitable, risk-averse investors can have infinite demand for risky securities, settings exist in which risk-averse investors should not diversify, and demand for mutual funds with negative alphas may be rational.

  1. Linnainmaa, Juhani, 2010, Do limit orders alter inferences about investor performance and behavior? Journal of Finance 65(4), 1473-1506. [PDF] [Internet Appendix] [SSRN link]

Investors' use of limit orders drives a wedge between investors' intentions and realized trades. Limit orders are contrarian; they are more likely to execute when there are news or asymmetric information; and they lose money when new information arrives to the market. When we try to infer investors' information sets or intentions from their realized trades, our inferences are biased. I call this bias the "limit order effect."

Award: Best finance paper 2010 award from the Foundation for the Advancement of Finnish Securities Market.

Media: Featured in the Chicago Booth Capital Ideas (October 2007) and the Economist Intelligence Unit.


Work in Progress

  1. Asset Manager Funds (with Joseph Gerakos and Adair Morse, February 2016)

Institutional investors paid asset managers average annual fees of $172 billion between 2000 and 2012. We show that asset managers outperformed their benchmarks by 96 basis points per year before fees, and by 49 basis points after fees. Estimates from a Sharpe (1992) model suggest that asset managers achieved outperformance through factor exposures ("smart beta"). If institutions had instead implemented a long-only mean-variance efficient portfolio over the same factors via institutional mutual funds, they would have earned just as a high, but no higher, Sharpe ratio as by delegating to asset managers. Liquid, low-cost ETFs are likely eroding the comparative advantage of asset managers. Because asset managers account for 29% of investable assets, the adding-up constraint implies that the average dollar of everyone else had a negative alpha of 49 basis points.

  1. The Misguided Beliefs of Financial Advisors (with Brian Melzer, and Alessandro Previtero)

A common view of retail finance is that rampant conflicts of interest explain the high cost of financial advice. Using detailed data on financial advisors and their clients, however, we show that most advisors invest their personal portfolios just like they advise their clients. They trade frequently, chase returns, and prefer expensive, actively managed funds over cheap index funds. Differences in advisors' beliefs affect not only their own investment choices, but also cause substantial variation in the quality and cost of their advice. Advisors do not hold expensive portfolios only to convince clients to do the same - their own performance would actually improve if they held exact copies of their clients' portfolios, and they exhibit similar trading behavior even after they leave the industry. This evidence suggests that many advisors offer well-meaning, but misguided, recommendations rather than self-serving ones. Eliminating conflicts of interest may therefore reduce the cost of advice by less than policymakers hope.

  1. The History of the Cross Section of Stock Returns (with Michael Roberts)

Using accounting data spanning the 20th century, we show that most accounting-based return anomalies are spurious. When we take anomalies out-of-sample by moving either backwards or forwards in time, their average returns decrease and volatilities increase. These patterns emerge because data-snooping works through t-values, and an anomaly's t-value is high if its average return is high or volatility low. The average anomaly's in-sample Sharpe ratio is biased upwards by a factor of three. The data-snooping problem is so severe that we would expect to reject even the true asset pricing model when tested using in-sample data. Our results suggest that asset pricing models should be tested using out-of-sample data or, if not not feasible, that the correct standard by which to judge a model is its ability to explain half of the in-sample alpha.

  1. Average returns, book-to-market, and changes in firm size (with Joseph Gerakos, February 2016, revise and resubmit at Review of Financial Studies, previous titles "Decomposing value" and "Dissecting factors")

Only those high B/M firms that have decreased in size earn the value premium. These firms follow conservative investment policies, while those high B/M firms that do not earn the value premium generate low cash flows. This difference explains why HML is redundant in some asset pricing models include profitability and investment factors, but not others. Profitability and investment factors subsume HML's ability to predict economic growth, implying that expected growth is high when profitable firms that invest conservatively earn high returns. Our result on the relation between the value premium and changes in firm size provides a testable restriction for theories of value: if a value premium within the model remains when controlling for changes in firm size, such a model is inconsistent with the data.

Award: Second prize in the academic competition at the Chicago Quantitative Alliance (CQA) Fall 2012 Conference.

  1. Learning and Stock Market Participation (November 2005)

This paper examines the impact of trading constraints on market participation when agents learn about their investment opportunities. The possibility of facing binding constraints in the future creates a feedback that can keep agents out of the market even if the risk premium is high. This effect arises with learning because the changes in investment opportunities are correlated with future realized outcomes: an agent will have a poor investment opportunity set precisely in those future states where her marginal utility is high. Non-participation arises also in an equilibrium model where agents resolve uncertainty about the cash flow covariance between tradable and non-tradable assets. These results suggest that learning and short-sale constraints can simultaneously generate limited participation, higher risk premium, and insignificant contemporaneous correlation between the stock return and the income of those who do not participate in the stock market. We conclude that a standard intertemporal hedging motive, generated by (i) learning about the parameters of the economy or by (ii) changes in the labor income dynamics, may account for agents' seemingly puzzling nonparticipation decisions without relying on non-standard preferences.

  1. The Individual Day Trader (November 2005)

This paper shows that individual day traders are reluctant to close losing day trades. They even sell other stocks from their portfolios to finance the unintended purchases. This disposition to ride losers has significant long-term welfare consequences. Day traders hurt their portfolios’ performance up to −6% in three months after a holdings change. The changes in individuals’ exposure to market-wide shocks cause this underperformance: individuals systematically migrate towards small technology stocks with low B/M ratios. We find a negative relation between day trading profits and long-term performance: active day traders have the highest day trading profits but they hurt their long-term performance the most. Our results suggest that behavioral biases can push investors towards portfolios they might feel uncomfortable holding under other circumstances.


Other Publications

  1. Linnainmaa, Juhani, 2009, Review of “The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. By Andrew W. Lo and Jasmina Hasanhodzic. New York: Bloomberg Press, 2009.” Journal of Economic Literature 47(4), 1141-1144. [PDF]