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Decentralizing Money: Bitcoin Prices and Blockchain Security

Emiliano S. Pagnotta
Review of Financial Studies 2022 35(2), 866-907
We address the determination of bitcoin prices and decentralized security. Users forecast the transactional and resale values of holdings, pricing the risk of systemic attacks. Miners contribute resources to protect against attackers and compete for block rewards. Bitcoin’s design leads to multiple equilibria: the same blockchain technology is consistent with sharply different price and security levels. Bitcoin’s monetary policy can lead to welfare losses and deviations from quantity theory. Price-security feedback amplifies fundamental shocks’ volatility impact and leads to boom and busts unconnected to fundamentals. We characterize how viability versus fiat currency depends on bitcoin’s relative acceptability and inflation protection.

Chasing Private Information

Marcin Kacperczyk; Emiliano S. Pagnotta
Review of Financial Studies 2019 32(12), 4997-5047
[Using over 5,000 trades unequivocally based on nonpublic information about firm fundamentals, we find that asymmetric information proxies display abnormal values on days with informed trading. Volatility and volume are abnormally high, whereas illiquidity is low, in equity and option markets. Daily returns reflect the sign of private signals, but bidask spreads are lower when informed investors trade. Market makers’ learning under event uncertainty and limit orders help explain these findings. The cross-section of information duration indicates that traders select days with high uninformed volume. Evidence from the U.S. SEC Whistleblower Reward Program and the FINRA involvement addresses selection concerns.]

Competing on Speed

Emiliano S. Pagnotta; Thomas Philippon
Econometrica 2018 86(3), 1067-1115 open access
We analyze trading speed and fragmentation in asset markets. In our model, trading venues make technological investments and compete for investors who choose where and how much to trade. Faster venues charge higher fees and attract speed-sensitive investors. Competition among venues increases investor participation, trading volume, and allocative e ffi ciency, but entry and fragmentation can be excessive, and speeds are generically ine ffi cient. Regulations that protect transaction prices (e.g., Securities and Exchange Commission trade-through rule) lead to greater fragmentation. Our model sheds light on the experience of European and U.S. markets since the implementation of Markets in Financial Instruments Directive and Regulation National Markets System.

Chasing Private Information

Marcin Kacperczyk; Emiliano S. Pagnotta
Review of Financial Studies 2019 32(12), 4997-5047
Using over 5,000 trades unequivocally based on nonpublic information about firm fundamentals, we find that asymmetric information proxies display abnormal values on days with informed trading. Volatility and volume are abnormally high, whereas illiquidity is low, in equity and option markets. Daily returns reflect the sign of private signals, but bid-ask spreads are lower when informed investors trade. Market makers’ learning under event uncertainty and limit orders help explain these findings. The cross-section of information duration indicates that traders select days with high uninformed volume. Evidence from the U.S. SEC Whistleblower Reward Program and the FINRA involvement addresses selection concerns. Received January 11, 2017; editorial decision December 17, 2018 by Editor Andrew Karolyi.

Legal Risk and Insider Trading

Marcin Kacperczyk; Emiliano S. Pagnotta
Journal of Finance 2024 79(1), 305-355 open access
Do illegal insiders internalize legal risk? We address this question with hand‐collected data from 530 SEC (the U.S. Securities and Exchange Commission) investigations. Using two plausibly exogenous shocks to expected penalties, we show that insiders trade less aggressively and earlier and concentrate on tips of greater value when facing a higher risk. The results match the predictions of a model where an insider internalizes the impact of trades on prices and the likelihood of prosecution and anticipates penalties in proportion to trade profits. Our findings lend support to the effectiveness of U.S. regulations' deterrence and the long‐standing hypothesis that insider trading enforcement can hamper price informativeness.

Nonstandard Errors

Albert J. Menkveld; Anna Dreber; Felix Holzmeister; Jürgen Huber; Magnus Johannesson; Michael Kirchler; SEBASTIAN NEUSÜß; Michael Razen; Utz Weitzel; DAVID ABAD-DÍAZ; Menachem Abudy; Tobias Adrian; Yacine Aït-Sahalia; Olivier Akmansoy; Jamie Alcock; Vitali Alexeev; Arash Aloosh; LIVIA AMATO; Diego Amaya; James J. Angel; ALEJANDRO T. AVETIKIAN; AMADEUS BACH; EDWIN BAIDOO; GAETAN BAKALLI; LI BAO; Andrea Barbon; OKSANA BASHCHENKO; Parampreet Christopher Bindra; Geir Høidal Bjønnes; Jeffrey R. Black; Bernard S. Black; DIMITAR BOGOEV; SANTIAGO BOHORQUEZ CORREA; Oleg Bondarenko; CHARLES S. BOS; Ciril Bosch-Rosa; ELIE BOURI; Christian T. Brownlees; ANNA CALAMIA; Viet Nga Cao; Gunther Capelle-Blancard; LAURA M. CAPERA ROMERO; Massimiliano Caporin; Allen Carrion; TOLGA CASKURLU; Bidisha Chakrabarty; Jian Chen; Mikhail Chernov; WILLIAM CHEUNG; LUDWIG B. CHINCARINI; Tarun Chordia; SHEUNG-CHI CHOW; BENJAMIN CLAPHAM; Jean-Edouard Colliard; Carole Comerton-Forde; EDWARD CURRAN; THONG DAO; WALE DARE; Ryan J. Davies; RICCARDO DE BLASIS; GIANLUCA F. DE NARD; Fany Declerck; OLEG DEEV; Hans Degryse; SOLOMON Y. DEKU; CHRISTOPHE DESAGRE; Mathijs A. van Dijk; Chukwuma Dim; Thomas Dimpfl; YUN JIANG DONG; PHILIP A. DRUMMOND; Tom L. Dudda; TEODOR DUEVSKI; Ariadna Dumitrescu; Teodor Dyakov; Anne Haubo Dyhrberg; Michał Dzieliński; ASLI EKSI; Izidin El Kalak; Saskia ter Ellen; Nicolas Eugster; Martin D. D. Evans; Michael Farrell; ESTER FELEZ-VINAS; Gerardo Ferrara; EL MEHDI FERROUHI; Andrea Flori; JONATHAN T. FLUHARTY-JAIDEE; Sean Foley; Kingsley Y. L. Fong; Thierry Foucault; TATIANA FRANUS; Francesco A. Franzoni; Bart Frijns; MICHAEL FRÖMMEL; SERVANNA M. FU; Sascha Füllbrunn; BAOQING GAN; GE GAO; Thomas Gehrig; ROLAND GEMAYEL; DIRK GERRITSEN; Javier Gil-Bazo; Dudley Gilder; Lawrence R. Glosten; THOMAS GOMEZ; Arseny Gorbenko; Joachim Grammig; Vincent Grégoire; Ufuk Güçbilmez; Björn Hagströmer; JULIEN HAMBUCKERS; ERIK HAPNES; Jeffrey H. Harris; Lawrence Harris; SIMON HARTMANN; JEAN-BAPTISTE HASSE; Nikolaus Hautsch; XUE-ZHONG (TONY) HE; Davidson Heath; SIMON HEDIGER; Terrence Hendershott; Ann Marie Hibbert; Erik Hjalmarsson; Seth A. Hoelscher; Peter Hoffmann; Craig W. Holden; Alex R. Horenstein; Wenqian Huang; DA HUANG; Christophe Hurlin; KONRAD ILCZUK; ALEXEY IVASHCHENKO; Subramanian R. Iyer; Hossein Jahanshahloo; NAJI JALKH; Charles M. Jones; SIMON JURKATIS; Petri Jylhä; ANDREAS T. KAECK; GABRIEL KAISER; ARZÉ KARAM; Egle Karmaziene; BERNHARD KASSNER; Markku Kaustia; EKATERINA KAZAK; Fearghal Kearney; Vincent van Kervel; SAAD A. KHAN; MARTA K. KHOMYN; Tony Klein; OLGA KLEIN; Alexander Klos; Michael Koetter; Aleksey Kolokolov; Robert A. Korajczyk; Roman Kozhan; Jan P. Krahnen; PAUL KUHLE; Amy Kwan; QUENTIN LAJAUNIE; F. Y. Eric C. Lam; Marie Lambert; Hugues Langlois; JENS LAUSEN; Tobias Lauter; Markus Leippold; VLADIMIR LEVIN; YIJIE LI; HUI LI; CHEE YOONG LIEW; THOMAS LINDNER; Oliver Linton; JIACHENG LIU; Anqi Liu; Guillermo Llorente; Matthijs Lof; ARIEL LOHR; FRANCIS LONGSTAFF; Alejandro Lopez-Lira; Shawn Mankad; NICOLA MANO; ALEXIS MARCHAL; Charles Martineau; Francesco Mazzola; Debrah Meloso; MICHAEL G. MI; Roxana Mihet; Vijay Mohan; Sophie Moinas; DAVID MOORE; Liangyi Mu; Dmitriy Muravyev; Dermot Murphy; GABOR NESZVEDA; CHRISTIAN NEUMEIER; Ulf Nielsson; Mahendrarajah Nimalendran; Sven Nolte; LARS L. NORDEN; Peter O’Neill; Khaled Obaid; BERNT A. ØDEGAARD; Per Östberg; EMILIANO PAGNOTTA; Marcus Painter; Stefan Palan; IMON J. PALIT; Andreas Park; Roberto Pascual; Paolo Pasquariello; Ľuboš Pástor; VINAY PA℡; Andrew J. Patton; Neil D. Pearson; Loriana Pelizzon; MICHELE PELLI; Matthias Pelster; Christophe Pérignon; CAMERON PFIFFER; Richard Philip; TOMÁŠ PLÍHAL; PUNEET PRAKASH; OLIVER-ALEXANDER PRESS; TINA PRODROMOU; Marcel Prokopczuk; Talis Putnins; YA QIAN; GAURAV RAIZADA; David Rakowski; Angelo Ranaldo; Luca Regis; Stefan Reitz; Thomas Renault; REX W. RENJIE; Roberto Renò; Steven J. Riddiough; Kalle Rinne; PAUL RINTAMÄKI; Ryan Riordan; THOMAS RITTMANNSBERGER; IÑAKI RODRÍGUEZ LONGARELA; Dominik Roesch; LAVINIA ROGNONE; Brian Roseman; Ioanid Roşu; Saurabh Roy; NICOLAS RUDOLF; STEPHEN R. RUSH; Khaladdin Rzayev; ALEKSANDRA A. RZEŹNIK; Anthony Sanford; Harikumar Sankaran; Asani Sarkar; Lucio Sarno; Olivier Scaillet; STEFAN SCHARNOWSKI; KLAUS R. SCHENK-HOPPÉ; ANDREA SCHERTLER; MICHAEL SCHNEIDER; FLORIAN SCHROEDER; Norman Schürhoff; Philipp Schuster; MARCO A. SCHWARZ; Mark S. Seasholes; Norman J. Seeger; Or Shachar; Andriy Shkilko; JESSICA SHUI; MARIO SIKIC; Giorgia Simion; Lee A. Smales; Paul Söderlind; Elvira Sojli; Konstantin Sokolov; JANTJE SÖNKSEN; Laima Spokeviciute; Denitsa Stefanova; Marti G. Subrahmanyam; BARNABAS SZASZI; Oleksandr Talavera; Yuehua Tang; Nick Taylor; Wing Wah Tham; Erik Theissen; Julian Thimme; Ian Tonks; Hai Tran; Luca Trapin; Anders B. Trolle; M. ANDREEA VADUVA; Giorgio Valente; Robert A. Van Ness; Aurelio Vasquez; Thanos Verousis; Patrick Verwijmeren; ANDERS VILHELMSSON; Grigory Vilkov; Vladimir Vladimirov; SEBASTIAN VOGEL; Stefan Voigt; Wolf Wagner; THOMAS WALTHER; Patrick Weiss; Michel van der Wel; Ingrid M. Werner; P. Joakim Westerholm; Christian Westheide; HANS C. WIKA; Evert Wipplinger; Michael Wolf; Christian C. P. Wolff; LEONARD WOLK; WING-KEUNG WONG; Jan Wrampelmeyer; Zhen-Xing Wu; Shuo Xia; Dacheng Xiu; KE XU; CAIHONG XU; Pradeep K. Yadav; JOSÉ YAGÜE; Cheng Yan; Antti Yang; Woongsun Yoo; WENJIA YU; YIHE YU; Shihao Yu; Bart Z. Yueshen; Darya Yuferova; MARCIN ZAMOJSKI; Abalfazl Zareei; STEFAN M. ZEISBERGER; LU ZHANG; S. Sarah Zhang; Xiaoyu Zhang; LU ZHAO; Zhuo Zhong; Z. IVY ZHOU; CHEN ZHOU; XINGYU S. ZHU; Marius Zoican; REMCO ZWINKELS
Journal of Finance 2024 79(3), 2339-2390 open access
In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.