Dois ensaios em finanças
| Ano de defesa: | 2016 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Não Informado pela instituição
|
| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Inglês: | |
| Link de acesso: | https://hdl.handle.net/10438/16639 |
Resumo: | We use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month. |
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Tessari, CristinaEscolas::EPGEFGVGlasman, Daniela KubudiVicente, José Valentim MachadoAlmeida, Caio Ibsen Rodrigues de2016-06-29T14:07:23Z2016-06-29T14:07:23Z2016-03-22TESSARI, Cristina. Dois ensaios em finanças. Dissertação (Mestrado em Economia) - FGV - Fundação Getúlio Vargas, Rio de Janeiro, 2016.https://hdl.handle.net/10438/16639We use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.In the first chapter, we test some stochastic volatility models using options on the S&P 500 index. First, we demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility process using the empirical structure function, or variogram. This result is consistent with findings of previous studies. The main contribution of our paper is to estimate the two time-scales in the volatility process simultaneously by using nonlinear weighted least-squares technique. To test the statistical significance of the rates of mean-reversion, we bootstrap pairs of residuals using the circular block bootstrap of Politis and Romano (1992). We choose the block-length according to the automatic procedure of Politis and White (2004). After that, we calculate a first-order correction to the Black-Scholes prices using three different first-order corrections: (i) a fast time scale correction; (ii) a slow time scale correction; and (iii) a multiscale (fast and slow) correction. To test the ability of our model to price options, we simulate options prices using five different specifications for the rates or mean-reversion. We did not find any evidence that these asymptotic models perform better, in terms of RMSE, than the Black-Scholes model. In the second chapter, we use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.porOption pricingStochastic volatilityIdiosyncratic skewnessIdiosyncratic volatilityPortfolio selectionMean reversionEconomiaDerivativos (Finanças)Risco (Economia)Mercado de opções - PreçosDois ensaios em finançasOption pricing under multiscale stochastic volatilityIdiosyncratic moments and the cross-section of stock returns in Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINALPDFPDFapplication/pdf1264081https://repositorio.fgv.br/bitstreams/dfa40ffb-0cfb-43c9-80d5-d076da4dad37/download14e65157457bfe8deea5353bb192a0afMD51LICENSElicense.txtlicense.txttext/plain; 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| dc.title.por.fl_str_mv |
Dois ensaios em finanças |
| dc.title.alternative.eng.fl_str_mv |
Option pricing under multiscale stochastic volatility Idiosyncratic moments and the cross-section of stock returns in Brazil |
| title |
Dois ensaios em finanças |
| spellingShingle |
Dois ensaios em finanças Tessari, Cristina Option pricing Stochastic volatility Idiosyncratic skewness Idiosyncratic volatility Portfolio selection Mean reversion Economia Derivativos (Finanças) Risco (Economia) Mercado de opções - Preços |
| title_short |
Dois ensaios em finanças |
| title_full |
Dois ensaios em finanças |
| title_fullStr |
Dois ensaios em finanças |
| title_full_unstemmed |
Dois ensaios em finanças |
| title_sort |
Dois ensaios em finanças |
| author |
Tessari, Cristina |
| author_facet |
Tessari, Cristina |
| author_role |
author |
| dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EPGE |
| dc.contributor.affiliation.none.fl_str_mv |
FGV |
| dc.contributor.member.none.fl_str_mv |
Glasman, Daniela Kubudi Vicente, José Valentim Machado |
| dc.contributor.author.fl_str_mv |
Tessari, Cristina |
| dc.contributor.advisor1.fl_str_mv |
Almeida, Caio Ibsen Rodrigues de |
| contributor_str_mv |
Almeida, Caio Ibsen Rodrigues de |
| dc.subject.eng.fl_str_mv |
Option pricing Stochastic volatility Idiosyncratic skewness Idiosyncratic volatility Portfolio selection Mean reversion |
| topic |
Option pricing Stochastic volatility Idiosyncratic skewness Idiosyncratic volatility Portfolio selection Mean reversion Economia Derivativos (Finanças) Risco (Economia) Mercado de opções - Preços |
| dc.subject.area.por.fl_str_mv |
Economia |
| dc.subject.bibliodata.por.fl_str_mv |
Derivativos (Finanças) Risco (Economia) Mercado de opções - Preços |
| description |
We use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month. |
| publishDate |
2016 |
| dc.date.accessioned.fl_str_mv |
2016-06-29T14:07:23Z |
| dc.date.available.fl_str_mv |
2016-06-29T14:07:23Z |
| dc.date.issued.fl_str_mv |
2016-03-22 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| format |
masterThesis |
| status_str |
publishedVersion |
| dc.identifier.citation.fl_str_mv |
TESSARI, Cristina. Dois ensaios em finanças. Dissertação (Mestrado em Economia) - FGV - Fundação Getúlio Vargas, Rio de Janeiro, 2016. |
| dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10438/16639 |
| identifier_str_mv |
TESSARI, Cristina. Dois ensaios em finanças. Dissertação (Mestrado em Economia) - FGV - Fundação Getúlio Vargas, Rio de Janeiro, 2016. |
| url |
https://hdl.handle.net/10438/16639 |
| dc.language.iso.fl_str_mv |
por |
| language |
por |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.source.none.fl_str_mv |
reponame:Repositório Institucional do FGV (FGV Repositório Digital) instname:Fundação Getulio Vargas (FGV) instacron:FGV |
| instname_str |
Fundação Getulio Vargas (FGV) |
| instacron_str |
FGV |
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FGV |
| reponame_str |
Repositório Institucional do FGV (FGV Repositório Digital) |
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Repositório Institucional do FGV (FGV Repositório Digital) |
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https://repositorio.fgv.br/bitstreams/dfa40ffb-0cfb-43c9-80d5-d076da4dad37/download https://repositorio.fgv.br/bitstreams/a2049bfa-5259-4bc3-b7c9-f26a3f7e8bec/download https://repositorio.fgv.br/bitstreams/0938be95-c0a1-4a2a-b7b6-e68e187bea0c/download https://repositorio.fgv.br/bitstreams/eaba69d4-9341-401f-8d6d-ac600c036930/download https://repositorio.fgv.br/bitstreams/01eb8845-81be-4447-a252-1272a780dfe2/download https://repositorio.fgv.br/bitstreams/3b0448f1-504c-4fd2-9a2b-b6e8126890a0/download |
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MD5 MD5 MD5 MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV) |
| repository.mail.fl_str_mv |
|
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1827842539946770432 |