MARKET REACTION TO THE TONES OF EARNINGS CONFERENCE CALLS

Tonin, Joyce Menezes da Fonseca; Scherer, Luciano Marcio

doi:10.1590/S0034-759020220107x

Joyce Menezes da Fonseca Tonin jmftonin@uem.br

Universidade Estadual de Maringá, Departamento de Ciências Contábeis e Programa de Pós-graduação em Ciências Contábeis, Maringá, PR, Brasil

https://orcid.org/0000-0003-1371-1314

Luciano Marcio Scherer Lmscherer@ufpr.br

Universidade Federal do Paraná, Departamento de Ciências Contábeis e Programa de Pós-graduação em Contabilidade, Curitiba, PR, Brasil

https://orcid.org/0000-0002-6104-7860

jmftonin@uem.br

Lmscherer@ufpr.br

AUTHORS’ CONTRIBUTIONS

Joyce Menezes da Fonseca Tonin and Luciano Marcio Scherer worked on the conceptualization and theoretical-methodological approach as well as on data analysis, writing and final revision of the manuscript. The theoretical review and data collection was conducted by Joyce Menezes da Fonseca Tonin.

Variables	Description	Formula	Literature
BM_it	Variable that represents the Book-to-market indicator of company i in period t	$B M_{i t} = BOOK_VAL_PER_SH$	Price et al. (2012)Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012). Earnings conference calls and stock returns: The incremental informativeness of textual tone. Journal of Banking and Finance, 36(4), 992-1011. doi: 10.1016/j.jbankfin.2011.10.013 https://doi.org/10.1016/j.jbankfin.2011.... , Bannier, Pauls and Walter (2017)Bannier, C., Pauls, T., & Walter, A. (2017). CEO-speeches and stock returns. CFS Working Paper No. 583. doi: 10.2139/ssrn.3051151 https://doi.org/10.2139/ssrn.3051151... , and Brockman et al. (2017)Brockman, P., Li, X., & Price, S. M. (2017). Conference call tone and stock returns: Evidence from the Stock Exchange of Hong Kong. Asia-Pacific Journal of Financial Studies, 46, 667-685. doi: 10.1111/ajfs.12186 https://doi.org/10.1111/ajfs.12186... .
LEV_it	Variable that represents the leverage of company i in period t	$L E V_{i t} = \frac{B S_T O T_L I A B 2}{B S_T O T_A S S E T}$	Price et al. (2012)Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012). Earnings conference calls and stock returns: The incremental informativeness of textual tone. Journal of Banking and Finance, 36(4), 992-1011. doi: 10.1016/j.jbankfin.2011.10.013 https://doi.org/10.1016/j.jbankfin.2011.... , Bannier et al. (2017)Bannier, C., Pauls, T., & Walter, A. (2017). CEO-speeches and stock returns. CFS Working Paper No. 583. doi: 10.2139/ssrn.3051151 https://doi.org/10.2139/ssrn.3051151... , Brockman et al. (2015Brockman, P., Li, X., & Price, S. M. (2015). Differences in conference call tones: Managers vs. analysts. Financial Analysts Journal, 71(4), 24-42. doi: 10.2469/faj.v71.n4.1 https://doi.org/10.2469/faj.v71.n4.1... , 2017).
SIZE_it	Variable that represents the capitalization and market of company i in period t	$S I Z E_{i t} = \ln (T O_M K T_V A L)$	Price et al. (2012)Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012). Earnings conference calls and stock returns: The incremental informativeness of textual tone. Journal of Banking and Finance, 36(4), 992-1011. doi: 10.1016/j.jbankfin.2011.10.013 https://doi.org/10.1016/j.jbankfin.2011.... , Bannier et al. (2017)Bannier, C., Pauls, T., & Walter, A. (2017). CEO-speeches and stock returns. CFS Working Paper No. 583. doi: 10.2139/ssrn.3051151 https://doi.org/10.2139/ssrn.3051151... , Henry e Leone (2016)Henry, E., & Leone, A. J. (2016). Measuring qualitative information in capital markets research: Comparison of alternative methodologies to measure disclosure tone. The Accounting Review, 91(1), 153-178. doi: 10.2308/accr-51161 https://doi.org/10.2308/accr-51161... , and Brockman et al. (2017)Brockman, P., Li, X., & Price, S. M. (2017). Conference call tone and stock returns: Evidence from the Stock Exchange of Hong Kong. Asia-Pacific Journal of Financial Studies, 46, 667-685. doi: 10.1111/ajfs.12186 https://doi.org/10.1111/ajfs.12186... .
SUPR_it	Variable that represents the surprise in the results of company i in period t	$S U P R_{i t} = \frac{(E P S_{i t} - E P S_{i, t - 1})}{P_{i, t - 1}}$	Price et al. (2012)Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012). Earnings conference calls and stock returns: The incremental informativeness of textual tone. Journal of Banking and Finance, 36(4), 992-1011. doi: 10.1016/j.jbankfin.2011.10.013 https://doi.org/10.1016/j.jbankfin.2011.... , Bannier et al. (2017)Bannier, C., Pauls, T., & Walter, A. (2017). CEO-speeches and stock returns. CFS Working Paper No. 583. doi: 10.2139/ssrn.3051151 https://doi.org/10.2139/ssrn.3051151... , and Brockman et al. (2017)Brockman, P., Li, X., & Price, S. M. (2017). Conference call tone and stock returns: Evidence from the Stock Exchange of Hong Kong. Asia-Pacific Journal of Financial Studies, 46, 667-685. doi: 10.1111/ajfs.12186 https://doi.org/10.1111/ajfs.12186... .
LnAT_it	Variable that represents the total assets of company i in period t	$\ln (B S_T O T_A S S E T)$

Panel A: descriptive statistics for variable BHAR (0.1) and variables TONE (2010-17)
Statistics	Minimum	Maximum	Average	Standard Deviation	Variation Coefficient	Asymmetry	Kurtosis
BHAR (0,1)	-0.239	0.242	0.000	0.043	247.438	0.421	8.217
TONE^OVERAL	-0.714	0.818	0.042	0.235	5.623	-0.130	2.824
TONE^INT	-0.800	1.000	0.224	0.306	1.369	-0.363	2.867
TONE^QA	-1.000	0.700	-0.133	0.309	-2.322	-0.707	4.017
TONE^MANAGER	-0.733	0.846	0.168	0.265	1.579	0.124	2.978
TONE^ANALYST	-1.000	1.000	-0.099	0.281	-2.852	-0.301	4.354
TONE^CEO	-0.714	0.911	0.181	0.274	1.514	0.471	2.749
TONE^CFOIR	-0.867	0.938	0.117	0.294	2.509	-0.112	2.947
TONE^SELL	-0.833	0.750	-0.084	0.261	-3.116	0.082	3.097
TONE^BUY	-0.857	0.846	-0.031	0.210	-6.839	-0.678	6.706
Panel B: Descriptive statistics of words classified as positive and negative by the LM dictionary
Statistics	Minimum	Maximum	Average	Standard Deviation	Variation Coefficient	Asymmetry	Kurtosis
POS^INT	2	189	33.209	24.608	0.741	1.734	7.919
NEG^INT	0	126	19.068	13.181	0.691	2.041	11.589
POS^QA	0	286	36.227	28.268	0.780	1.452	8.734
NEG^QA	0	164	41.548	28.844	0.694	0.920	3.854
POS^MANAGER	1	339	58.409	38.390	0.657	1.479	7.048
NEG^MANAGER	2	203	38.657	22.932	0.593	1.472	7.554
POS^ANALYST	0	49	11.894	8.790	0.739	0.782	3.377
NEG^ANALYST	0	73	15.397	12.391	0.805	1.154	4.477
Panel C: Descriptive statistics of words classified as positive and negative, segregated by participant type
Statistics	Minimum	Maximum	Average	Standard Deviation	Variation Coefficient	Asymmetry	Kurtosis
POS^CEO	0	180	25.112	31.311	1.247	1.594	5.554
NEG^CEO	0	117	13.464	17.334	1.287	1.816	7.245
POS^CFOIR	0	121	24.026	20.921	0.871	1.504	5.778
NEG^CFOIR	0	126	18.097	15.732	0.869	1.539	6.959
POS^SELL	0	46	9.930	7.804	0.786	0.859	3.588
NEG^SELL	0	61	12.711	10.855	0.854	1.155	4.421
POS^BUY	0	15	1.249	2.310	1.849	2.356	9.227
NEG^BUY	0	39	1.670	3.205	1.920	3.593	26.643

Panel A: Pearson correlation between BHAR (0.1) and the TONE variables (2010-17)
VARIABLES	BHAR (0,1)	TONE^OVERALL	TONE^INT	TONE^QA	TONE^MANAGER	TONE^ANALYST
BHAR (0,1)	1
TONE^OVERALL	0.1147**	1
TONE^INT	0.1087**	0.7622**	1
TONE^QA	0.0723**	0.5867**	0.3055**	1
TONE^MANAGER	0.0926**	0.9475**	0.8270**	0.5453**	1
TONE^ANALYST	0.1137**	0.4759**	0.1751**	0.4779**	0.3265**	1
Panel B: Pearson correlation between BHAR (0.1) and control variables (2010-17)
VARIABLES	BHAR (0.1)	SIZE	BM	LnAT	SUPR	LEV
BHAR (0.1)	1
SIZE	-0.0604**	1
BM	0.0364	-0.0244	1
LnAT	-0.0814**	0.8578**	-0.3240**	1
SUPR	-0.0236	-0.0034	-0.0021	0.0061	1
LEV	0.0197	0.2501**	0.1610**	0.3376**	0.0086	1

Panel A: Estimation of models
Variables	Model 1	Model 2	Model 3	Model 4	Model 5
TONE^OVERALL	0.0188***	-	-	-	-
TONE^INT	-	0.0120***	-	-	-
POS^{INT (1)}	-	-	0.0148*	-	-
NEG^{INT (1)}	-	-	-0.0203	-	-
TONE^QA	-	0.0058	-	-	-
POS^{QA (1)}	-	-	0.0124	-	-
NEG^{QA (1)}	-	-	-0.0048	-	-
TONE^MANAGER	-	-	-	0.0089*	-
POS^{MANAGER (1)}	-	-	-	-	0.0054
NEG^{MANAGER (1)}	-	-	-	-	-0.0065
TONE^ANALYST	-	-	-	0.0132***	-
POS^{ANALYST (1)}	-	-	-	-	0.0847***
NEG^{ANALYST (1)}	-	-	-	-	-0.0363*
SIZE ⁽¹⁾	0.4870	0.5140	0.4480	0.5090	0.4570
BM⁽¹⁾	-0.0357	-0.0452	-0.0445	-0.0388	-0.0503
LnAT⁽¹⁾	-0.409*	-0.4520*	-0.4770**	-0.4140*	-0.4610*
SUPR⁽¹⁾	-0.4740	-0.4560	-0.4810	-0.4960	-0.4870
LEV⁽¹⁾	0.0171*	0.0168*	0.0171*	0.0164*	0.0139
constant	0.0099	0.0123	0.0159*	0.0104	0.0161
Panel B: Model specification tests and econometric tests
F Test
t-stat	1.59	1.56	1.58	1.71	1.72
p-value	0.0097	0.0131	0.0111	0.0034	0.0030
LM Test
t-stat	2.12	1.44	1.53	3.24	3.34
p-value	0.0728	0.1155	0.1077	0.0359	0.0338
Hausman Test
t-stat	5.15	-	-	7.56	12.15
p-value	0.5253	-	-	0.373	0.2049
Specification	POLS	POLS	POLS	POLS	POLS

Panel A: Estimation of models
Variables	Model 6			Model 7
Variables	POLS	FE	RE	POLS	FE	RE
TONE^CEO	0.0070	0.0065	0.0071	-	-	-
POS^{CEO (1)}	-	-	-	-0.0006	-0.0008	-0.0011
NEG^{CEO (1)}	-	-	-	-0.0041	-0.0022	-0.0044
TONE^CFOIR	0.0089*	0.0025	0.0073	-	-	-
POS^{CFOIR (1)}	-	-	-	0.0195**	0.0108	0.0179*
NEG^{CFOIR (1)}	-	-	-	-0.0199	-0.0824	-0.0168
TONE^SELL	0.0112**	0.0106*	0.0111**	-	-	-
POS^{SELL (1)}	-	-	-	0.0761***	0.0885***	0.0820***
NEG^{SELL (1)}	-	-	-	-0.0382*	-0.0560**	-0.0426**
TONE^BUY	0.0053	0.0108	0.0068	-	-	-
POS^{BUY (1)}	-	-	-	0.1720**	0.1900**	0.1800**
NEG^{BUY (1)}	-	-	-	-0.0384	-0.1250**	-0.621
SIZE⁽¹⁾	0.5020	0.1400	0.4600	0.3910	0.1400	0.3670
BM⁽¹⁾	-0.0393	-0.0176**	-0.0551	-0.0486	-0.1710**	-0.0617
LnAT⁽¹⁾	-0.3910*	-0.6130	-0.4060*	-0.4200*	-0.6320	-0.4300*
SUPR⁽¹⁾	-0.5150	-0.4830	-0.5000	-0.5480	-0.5300	-0.5410
LEV⁽¹⁾	0.0167*	0.3150	0.0185*	0.0143	0.0365	0.0166*
constant	0.0073	0.0422	0.0103	0.0134	0.0404	0.0149
Panel B: Model specification tests and econometric tests
F Test
t-stat	1.61			1.66
p-value	0.0082			0.0054
LM Test
t-stat	1.82			2.22
p-value	0.0884			0.0680
Hausman Test
t-stat	16.33			21.27
p-value	0.0603			0.0677

\begin{matrix} B H A R_{i t} = α_{0} + β_{13} T O N E^{C E O}_{i t} + β_{14} T O N E^{C F O I R}_{i t} + β_{19} T O N E^{S E L L}_{i t} \\ + β_{20} T O N E^{B U Y}_{i t} + γ_{k} C O N T R O L S^{K}_{i t} + ε_{i t} \end{matrix}

\begin{matrix} B H A R_{i t} = α_{0} + β_{15} P O S^{C E O}_{i t} + β_{16} N E G^{C E O}_{i t} + β_{17} P O S^{C F O I R}_{i t} \\ + β_{18} N E G^{C F O I R}_{i t} + β_{21} P O S^{S E L L}_{i t} + β_{22} N E G^{S E L L}_{i t} \\ + β_{23} P O S^{B U Y}_{i t} + β_{24} N E G^{B U Y}_{i t} + γ_{k} C O N T R O L S^{K}_{i t} + ε_{i t} \end{matrix}

\begin{matrix} B H A R_{i (τ_{1}, τ_{2})} = \prod_{t = 0}^{τ_{2}} (1 + A R_{i, t}) & c o m A R_{i, t} = R_{i . t} - (\hat{α_{i}} + \hat{β_{i}} R_{m t}) \end{matrix}

[1] jmftonin@uem.br

Brasil

Brasil

MARKET REACTION TO THE TONES OF EARNINGS CONFERENCE CALLS

ABSTRACT