Assessing the Predictability of Financial Analysts' Stock Price Recommendations

Assessing the Predictability of Financial Analysts’ Stock Price

Recommendations

A Case Study of the Oslo Stock Exchange

Pål-Christian S. Njølstad

Thesis submitted for the degree of Master of Philosophy in Economics

Department of Economics

Faculty of Social Sciences

UNIVERSITY OF OSLO

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Assessing the Predictability of Financial Analysts’ Stock Price

Recommendations

A Case Study of the Oslo Stock Exchange

Pål-Christian S. Njølstad

© 2017 Pål-Christian S. Njølstad

Assessing the Predictability of Financial Analysts’ Stock Price Recommendations

http://www.duo.uio.no/

Printed: Reprosentralen, Universitetet i Oslo

Preface

This thesis is submitted to the University of Oslo (UiO) as partial fulfillment of the degree of Master of Philosophy in Economics and as part of the course ECON4090 - Master’s Thesis. The work culminating in this report has been performed at the Department of Economics, Faculty of Social Sciences under the supervision of Professor Kjetil Storesletten. I am grateful for his support and guidance. Fur- thermore, I would like to thank the Norwegian School of Economics (NHH) for providing access to their Bloomberg Professional Service and Børsprosjektet databases. I am also indebted to Associate Professor Øyvind Salvesen at the Nor- wegian University of Science and Technology (NTNU) for his advice on statistical modeling, including, e.g., employing generalized least squares (GLS) when faced with heteroscedasticity and autocorrelation and, in particular, properly estimating the covariance matrices to do so. Lastly, I am thankful for McKinsey&Company’s support of my educational pursuits at UiO, concurrently with teaching me how to advice financial institutions on strategy. Nevertheless, all errors are my own.

I had the pleasure of spending six unforgettable weeks in Barcelona with Erle in the spring of 2017, part of which I was occupied with the work and writing of this thesis. I am forever grateful for her love and support. Although all its words are mine, this thesis is hers.

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Abstract

In this thesis, I assess the predictability of financial analysts’ stock price recom- mendations through a case study of the Oslo Stock Exchange (OSE). The foun- dation of this assessment is∼23 000 recommendations published to the Institu- tional Brokers’ Estimate System (I/B/E/S) between 1^st of January 2007 and 31^st of March 2017 associated with stocks composing the OBX Index¹. Using gen- eralized least squares (GLS) techniques, I, firstly, document financial analysts’

would-beraison d’êtreon the OSE: (i) significant positive (negative) multi-factor model adjusted excess return² associated with ’Buy’ (’Sell’) recommendations and (ii) significant increases in share turnover, both at market and broker level, in days subsequent to publication. Secondly, I find indications that these returns are likely reaped by the recommendation issuer’s clients and, in particular, insti- tutional investors: (i) significant above-average bought (sold) value volume asso- ciated with ’Buy’ (’Sell’) recommendations and (ii) significant increase in trade size, a symptom of institutional investor activity, for the same broker that issued the recommendation in days following its publication. Lastly, and contrary to the bandwidth these recommendations are granted in Norwegian financial news, I find that they likely have little / no systematic value to the general public: e.g., no sig- nificant long-term multi-factor model adjusted excess return post-publication, in conformance with the Efficient Market Hypothesis³.

1Stock market index with the 25 most liquid companies listed on the Oslo Stock Exchange, rotated semiannually.

2Carhart four-factor models (CFFM) used to estimate expected returns, subtracted from actual return to arrive at adjusted return. CFFM is an extension of the Fama–French three-factor model by including a momentum factor in addition to factors for market return, small market cap, and high book-to-market value stocks (Carhart,1997, p. 61).

3E.g., seeFama(1998).

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Contents

1 Introduction 3

1.1 Background, Context, and Motivation . . . 3

1.2 Research Questions and Goals . . . 7

1.3 Research Contributions . . . 10

1.4 Thesis Structure . . . 11

2 Literature Review and Research State-of-the-Art 13 2.1 Predictability of Financial Analysts’ Recommendations . . . 13

2.1.1 Short-Term Market Reaction . . . 15

2.1.2 Recommendation Beneficiaries . . . 16

2.1.3 Long-Term Predictive Value . . . 17

2.1.4 The Norwegian Market . . . 19

2.2 Asset Pricing Factor Models . . . 20

2.2.1 Capital Asset Pricing Model . . . 21

2.2.2 Fama–French Three-Factor Model . . . 22

2.2.3 Carhart Four-Factor Model . . . 23

2.3 Fama–MacBeth Regression . . . 24

2.4 Generalized Least Squares . . . 25

3 Data and Methods 29 3.1 Data Foundation . . . 29

3.1.1 Recommendations . . . 29

3.1.2 Issuer Characteristics . . . 34

3.1.3 Equity Prices, Indices, and Trading Statistics . . . 36

3.1.4 Broker Trading Activity . . . 37

3.1.5 Asset Pricing Data . . . 39

3.2 Research Methods . . . 39

3.2.1 Excess Return . . . 39

3.2.2 Trading Activity . . . 41

3.2.3 Generalized Least Squares Regressions . . . 44

3.2.4 Software and Tools . . . 46

4 Empirical Results and Discussion 47 4.1 Long-Term Predictability . . . 47

4.1.1 Recommendation and Target Price "Promises" . . . 49

4.1.2 Post-Recommendation Excess Stock Price Returns . . . . 51

4.2 Short-Term Market Reactions . . . 52

4.2.1 Intraday Stock Price Returns . . . 55

4.2.2 Intraday Trading Activities . . . 59

4.3 Market Actors to Benefit . . . 65

4.4 Analyst and Issuer Characteristic Differences . . . 73

4.4.1 Long-Term Predictability of Stock Price Return . . . 74

4.4.2 Short-Term Predictability of Stock Price Return . . . 76

4.4.3 Short-Term Predictability of Trading Activity . . . 79

5 Conclusion and Venues for Further Work 83

A Appendix 95

Chapter 1 Introduction

In this chapter, I introduce the research conducted within the scope of this thesis.

In Section1.1, the background and motivation of the work is presented. Section 1.2 lists and elaborates on the research questions and goals of my work. Subse- quently, I account specifically for the research contributions made in Section1.3.

And lastly, a brief outline of the remainder of the thesis is given in Section1.4.

1.1 Background, Context, and Motivation

This thesis concerns the financial analyst’s role in the allocation of economic re- sources on the stock exchange. With this, it seeks to understand if, how, and to whom financial analysts contribute in the buying and selling of stocks, e.g.: Do financial analysts have the faculties to systematically predict stock price move- ments in the short and long term? How does the market react to these predictions?

And who are ultimately the beneficiaries of these recommendations, if / when predictive?

There is considerate evidence that investors deviate from holding the market portfolio, as delineated by, e.g.,De Long et al.(1990, p. 704),Lease et al.(1974, p. 424). As the latter elaborates on, investors systematically fail to diversify by, e.g., holding a single or small number of stocks as opposed to the market. These deviations from the market portfolio, necessarily requires running decisioning on which assets to invest in and which to divest. With the proliferation of the Internet, and with it, overwhelming amounts of available information, processing relevant information to back these decisions can be both laborious and costly (Hong,2000, p. 192). Puzzling, yet robust, findings of security price underreaction to public