Before an Analyst Becomes an Analyst: Does Industry Experience Matter?

• Author: XI LIU,SINAN GOKKAYA,DANIEL BRADLEY
• Published date: 01 April 2017
• Date: 01 April 2017
• DOI: http://doi.org/10.1111/jofi.12466

THE JOURNAL OF FINANCE •VOL. LXXII, NO. 2 •APRIL 2017

Before an Analyst Becomes an Analyst: Does

Industry Experience Matter?

DANIEL BRADLEY, SINAN GOKKAYA, and XI LIU∗

ABSTRACT

Using hand-collected biographical information on financial analysts from 1983 to

2011, we find that analysts making forecasts on firms in industries related to their

preanalyst experience have better forecast accuracy,evoke stronger market reactions

to earning revisions, and are more likely to be named Institutional Investor all-stars.

Plausibly exogenous losses of analysts with related industry experience have real

financial market implications—changes in firms’ information asymmetry and price

reactions are significantly larger than those of other analysts. Overall, industry ex-

pertise acquired from preanalyst work experience is valuable to analysts, consistent

with the emphasis placed on their industry knowledge by institutional investors.

SELL-SIDE ANALYSTS ARE AMONG the most important information agents in cap-

ital markets. As a result, a large body of academic research has been devoted

to the question of what makes a good sell-side analyst. The literature shows

that a number of innate characteristics and external factors such as analysts’

forecasting experience, political views, portfolio complexity, and the prestige of

their brokerage house are related to analysts’ performance (Clement (1999),

Gilson et al. (2001), Malloy (2005), Jiang, Kumar, and Law (2016)). Of these

factors, practitioners indicate that industry knowledge is perhaps the most im-

portant quality an analyst can possess. Each October, Institutional Investor (II)

releases its annual all-star analyst rankings, which polls buy-side institutions

and ranks the top sell-side analysts in each industry. In addition to a list of

top analysts, II provides information on the qualities that respondents view

as most important. Industry knowledge has been consistently ranked the most

important trait. Corroborating II’s survey results, Brown et al. (2015) find that

sell-side analysts also believe that industry knowledge is the most important

characteristic related to their performance and career concerns.

∗Daniel Bradley is with the University of South Florida. Sinan Gokkaya and Xi Liu are with

Ohio University. We appreciate comments from John Banko, Jonathan Clarke, Diego Garcia,

Andy Fodor, Jacquelyn Humphrey, Ryan Huston, Russell Jame, Chris James, Avner Kalay, Andy

Naranjo, Jacob Oded, Sugata Ray, Jay Ritter, Dahlia Robinson, John Stowe, Geoff Warren, Fei

Xie, Xiaoyun Yu, Qiaoqiao Zhu, two anonymous referees, an anonymous Associate Editor, the

Editor (Kenneth Singleton), and seminar participants at the Australian National University, Ohio

University, Tel Aviv University, University of Florida, 2014 Western Finance Association, and

2014 Financial Management Association meetings. The authors do not have any potential conflicts

of interest, as identified in the JF Disclosure Policy. We are solely responsible for any errors or

omissions.

DOI: 10.1111/jofi.12466

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752 The Journal of Finance R

However, despite the widespread view that industry knowledge is critical to

an analyst’s job, there is little systematic evidence on the relation between in-

dustry knowledge and analyst performance, likely because industry knowledge

is inherently difficult to measure. In one attempt to empirically address the link

between analyst performance and industry specialization, Boni and Womack

(2006) find that analysts have superior ability in ranking individual stocks

within industries. In more recent work, Kadan et al. (2012) examine industry

recommendations made by strategy analysts that take a macroeconomic top-

down view of the overall industry and find that a portfolio of optimistic industry

recommendations earns significant positive abnormal returns, while portfolios

created based on negative industry recommendations earn negative abnormal

returns.

In this paper, we shed new light on the relation between analysts’ indus-

try knowledge and forecasting performance. Specifically, using a novel hand-

collected biographical data set, we extrapolate sell-side analysts’ preanalyst

industry experience from their previous employment history and match this

with their coverage portfolios to determine whether a covered firm is related to

the analyst’s preanalyst industry work experience. We then examine whether

industry knowledge acquired from preanalyst industry work experience pro-

vides sell-side analysts a competitive advantage by enabling them to better

interpret the factors that affect the operations, financial condition, and indus-

tries of the firms in their coverage portfolios above and beyond the factors

previously shown in the literature to be related to analyst performance.

To illustrate our empirical design, consider an analyst in our sample. Before

becoming an analyst, he worked at CBS Group for seven years as Director

of Strategic Planning. As an analyst at Bear Stearns, his coverage portfolio

included both firms that are in the entertainment/broadcasting industry that

are related to his previous work experience at CBS Group such as Comcast

Corporation, Cox Communications, Cox Radio, Young Broadcast, Walt Disney

Corporation, and Adelphia Communications and firms not in this industry and

hence unrelated to his previous work experience such as Hertz Corporation,

The Learning Company, and Avis Rent A Car among others. To distinguish an-

alysts’ general and firm-specific forecasting experience, we refer to preanalyst

work experience related to the industry of a covered firm as related experience.

When analysts make forecasts on firms operating in an industry that is un-

related to their preanalyst industry experience, we refer to this experience as

unrelated experience. Analysts without any prior industry experience are called

inexperienced analysts.1

For a sample of 112,973 earnings forecasts on 5,581 firms over the period

1983 to 2011, we find that the relative earnings accuracy of forecasts by an-

alysts with related experience is significantly better than that of analysts

with unrelated experience or of inexperienced analysts. Specifically, the mean

1Throughout the paper, we refer to analysts with related preanalyst industry experience as

industry expert analysts and analysts without related preanalyst industry experience as nonexpert

analysts.

Before an Analyst Becomes an Analyst 753

relative forecast accuracy of analysts with related industry experience is 3.6%

higher than that of other analysts after controlling for intertemporal variation

in task difficulty,general and firm-specific forecasting experience, and other fac-

tors shown to explain cross-sectional differences in earnings forecast accuracy.

To put this in perspective, the forecast performance of a sell-side analyst with

nine years of general forecasting experience (the 90th experience percentile) is

2.1% more accurate than that of an analyst with three years of such experience

(10th percentile). The relative accuracy of forecasts issued by industry-

experienced analysts on unrelated firms is not different, however, from that

of forecasts issued by inexperienced analysts.2

We next examine the impact of Regulation FD (Reg FD) on our analysis.

Cohen, Frazzinni, and Malloy (2010) find that analysts with educational links

to senior executives at covered firms performed better than nonconnected ana-

lysts pre-FD, but this effect vanished after Reg FD when selective disclosure to

analysts was prohibited, implying that these connections foster the transfer of

private information. Accordingly, one plausible mechanism driving our results

may be that industry work experience cultivates industry connections and the

flow of private information. We find, however, that related industry experi-

ence matters in both periods and the passage of Reg FD has not weakened the

economic or statistical impact of industry experience on forecast performance.

Therefore, while we cannot completely rule out the possibility that information

flow from social connections with industry networks may contribute to our re-

sults, private information flow is unlikely to be a primary explanation. Rather,

our evidence is in line with the view that preanalyst industry work experience

provides analysts with a fundamental understanding of the industry. This re-

sult is also consistent with the strong emphasis that buy-side institutions and

sell-side analysts continue to place on industry knowledge in the post-Reg FD

era (Brown et al. (2015)).3

Given the evidence of higher relative forecast accuracy, we also examine the

extent to which sell-side analysts’ preanalyst work experience leads to favor-

able career outcomes. We find that previous work experience incrementally

increases the likelihood of becoming an II all-star analyst, but only when the

analyst covers stocks related to her preanalyst industry work experience. In

particular, the odds of being elected to the all-star team are 75% higher for an-

alysts with related industry experience compared to analysts with unrelated

2Toensure our results are not sensitive to how analysts’ forecast performance is measured (i.e.,

the proportional mean absolute forecast error (PMAFE)) or the choice of econometric specification,

we rerun regressions with the unadjusted absolute forecast error (AFE) and include firm-year and

broker fixed effects. We further use Hong and Kubik’s (2003) relative performance metric, and

we also perform tests using the subsample of experienced analysts that make forecasts on both

industry-related and industry-unrelated firms and include analyst-year paired fixed effects. The

results remain unchanged.

3In separate analyses, we also examine the investment value of analysts’ buy and sell rec-

ommendations. Using a calendar time portfolio approach following Barber, Lehavy, and Trueman

(2005), we find that buy and sell recommendations issued by industry expert analysts yield superior

abnormal returns compared to those issued by other analysts.