Last updated November 2016
CAMILO BOTÍA
Carnegie Mellon University-Tepper School of Business
5000 Forbes Avenue
Pittsburgh, PA 15213
Mobile: +1 412 224 7236
[email protected]
www.andrew.cmu.edu/user/cbotiach/
EDUCATION
Carnegie Mellon University – Tepper School of Business Pittsburgh, PA
Ph.D. in Finance, Minor in Statistics (Expected May 2017)
M.Sc. in Finance (2012)
Universidad de los Andes Bogotá, Colombia
M.Sc. in Industrial Engineering, Cum Laude (2010)
B.S. in Industrial Engineering, Magna Cum Laude (2009)
B.S. in Mathematics, Magna Cum Laude (2008)
RESEARCH INTERESTS
Financial Intermediation, Financial Regulation, Asset Pricing
WORKING PAPERS
How Much Information Is Too Much Information? Lagged Disclosure, Bank Runs, and Risk
Taking (Job Market Paper)
I study the effects of disclosing financial information on the occurrence of bank runs and on
management risk-taking activities. The main trade-off is between managerial incentives for
risk taking, which disclosure disciplines, and the risk of bank runs, which disclosure may
trigger. I find that the main policy consideration is the growth rate of bank assets. If bank
assets grow sufficiently slowly, then the optimal policy is to disclose with a lag, in order to
balance managerial risk taking and bank runs. When bank assets have high-growth rates, a
disclosure lag increases the occurrence of runs and decreases bank value.
Presented at: Carnegie Mellon University, London Business School TADC 2016, Olin School of
Business professional development workshop June 2016, Society for the Advancement of
Economic Theory meetings 2016 and European Finance Meetings Doctoral Tutorial 2016.
Release of information and Discount Window Lending
I study how the release of discount window information affects the provision of managerial
incentives and whether the disclosure could trigger bank runs. I propose a model in which
banks suffer adverse shocks that require cash infusion in order to continue operating and
assets are subject to moral hazard. The bank is financed by depositors that can withdraw
money at any time, introducing a collective action problem. I provide conditions that
Last updated November 2016
characterize whether disclosure or confidentiality of discount window borrowings maximizes
the NPV of bank projects. The main result suggests that disclosure is a better policy when
moral hazard is serious relative to the size of the liquidity shock, because it allows a contract
that induces the banker to behave. Secrecy is a better tool when the moral hazard is small
relative to the liquidity shock, because a run is avoided.
Presented at: Carnegie Mellon University
Bank Runs and Contingent Capital (Work in Progress)
Presented at: Carnegie Mellon University
University Endowments, Performance and Asset Allocation (Work in Progress)
HONORS AND AWARDS
GSA/Provost Conference Funding Award. Carnegie Mellon University, 2016
AFA Doctoral Student Travel Grant. Boston, January 2015
Doctoral Research Grant. Tepper School of Business, summer 2015
William Larimer Mellon Fellowship, Carnegie Mellon University, 2010-2015
RELEVANT CONFERENCE INVITATIONS
Presented at the 2016 EFA Doctoral Tutorial (BI), 2016 SAET meetings (IMPA), and 2016 TransAtlantic Doctoral Conference (LBS)
ACADEMIC EXPERIENCE
Research Assistant (2013-2015), Carnegie Mellon University
Richard Green (Winter 2015), Burton Hollifield (Summer and Fall 2013)
Instructor, Regression Analysis (Summer 2013), Carnegie Mellon University
Teaching Assistant (2012-2016), Carnegie Mellon University
Graduate: Financial Optimization (MBA and MSCF), Data Mining (MBA), Time Series
(MBA), Asset Management (MSCF), Financial Economics (MSCF), Econometrics (PhD),
Mathematics for Economists (PhD)
Research Assistant (2007), Universidad de los Andes
Supervisor René Meziat
OTHER WORK EXPERIENCE
Professional at the Research and Analysis Group, Foreign Reserves Department (2008 –
2010), Banco de la República (Central Bank), Colombia
ADDITIONAL INFORMATION
Passed level III of the CFA program (2012)
Last updated November 2016
Languages: English, Spanish
Programming: MATLAB, R, STATA, VBA, Mathematica, SAS. Familiar with C/C++
REFERENCE LETTERS
Reference letters can be requested from Lawrence Rapp, Associate Director of Ph.D. Student
Services, by phone +1 412 268 1319, or e-mail [email protected]