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Data, Digital Risks, and Financial Markets.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data, Digital Risks, and Financial Markets./
作者:	Balasubramanian, Anirudha.
面頁冊數:	1 online resource (177 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-03, Section: A.
Contained By:	Dissertations Abstracts International84-03A.
標題:	Prices. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29288670click for full text (PQDT)
ISBN:	9798845436672

Data, Digital Risks, and Financial Markets.
Balasubramanian, Anirudha.

Data, Digital Risks, and Financial Markets. - 1 online resource (177 pages)

Source: Dissertations Abstracts International, Volume: 84-03, Section: A.

Thesis (Ph.D.)--Stanford University, 2022.

Includes bibliographical references

Big data and pervasive digitization have transformed both the risks corporations face and the methods used to insure against them. What does this mean for the existence and efficiency of markets for risk-sharing and speculation? In my dissertation, Data, Digital Risks, and Financial Markets, I model algorithmic approaches, data dimensionality, and novel hazards to modernize our understanding of insurability, information aggregation, and optimal regulation in financial markets.The dissertation consists of three chapters. The first chapter studies the equilibrium coexistence, in financial markets, of traders using high-dimensional datasets and algorithmic strategies. The second chapter describes the extent to which insurance in markets for new or nonstationary risks exists and when government data policy can help. The third chapter argues how insurance availability might actually worsen ransomware, a pressing new cyberrisk, and presents sublimit caps as a practical regulatory measure.Trading with High-Dimensional Data. In chapter 1 (written jointly with Yilin (David) Yang), we study a trading game with agents who face a high-dimensional estimation problem. When agents face a curse of dimensionality, we show there exists an approximate equilibrium where all agents employ purely algorithmic forecasts and do not learn from price. Such an equilibrium matches survey evidence about modern trading, implies suboptimality in price as a predictor, and explains trading volume spikes on earnings dates.Data Paucity in New Insurance Markets. In chapter 2, I study how insurance markets for new or nonstationary risks can be tiny even when those risks are massive. Data paucity creates undiversifiable "model uncertainty" and when insurers penalize this uncertainty, they offer contracts with policy limits and (sometimes) deductibles if at all (even without moral hazard and adverse selection). Anonymized datasharing and relaxed antitrust policy may help in these contexts.Insurance against Ranswomare. In chapter 3, I show how increased cyberinsurance availability can increase the frequency and severity of ransomware attacks. Even accounting for the cybersecurity improvements insurers bring their customers, higher coverage (sub)limits may harm social welfare. While that does not mean the presence of cyberinsurers is welfare-negative, it means that regulatory sublimit caps for ransomware coverage - an enforceable policy, unlike ransom payment bans - can enhance social welfare relative to a regulation-free benchmark.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798845436672Subjects--Topical Terms:

652651
Prices.
Index Terms--Genre/Form:

542853
Electronic books.

Data, Digital Risks, and Financial Markets.
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500 $a Source: Dissertations Abstracts International, Volume: 84-03, Section: A.
500 $a Advisor: Reiss, Peter; Skrzypacz, Andrzej; Ostrovsky, Michael; Bent, Stacey F.
502 $a Thesis (Ph.D.)--Stanford University, 2022.
504 $a Includes bibliographical references
520 $a Big data and pervasive digitization have transformed both the risks corporations face and the methods used to insure against them. What does this mean for the existence and efficiency of markets for risk-sharing and speculation? In my dissertation, Data, Digital Risks, and Financial Markets, I model algorithmic approaches, data dimensionality, and novel hazards to modernize our understanding of insurability, information aggregation, and optimal regulation in financial markets.The dissertation consists of three chapters. The first chapter studies the equilibrium coexistence, in financial markets, of traders using high-dimensional datasets and algorithmic strategies. The second chapter describes the extent to which insurance in markets for new or nonstationary risks exists and when government data policy can help. The third chapter argues how insurance availability might actually worsen ransomware, a pressing new cyberrisk, and presents sublimit caps as a practical regulatory measure.Trading with High-Dimensional Data. In chapter 1 (written jointly with Yilin (David) Yang), we study a trading game with agents who face a high-dimensional estimation problem. When agents face a curse of dimensionality, we show there exists an approximate equilibrium where all agents employ purely algorithmic forecasts and do not learn from price. Such an equilibrium matches survey evidence about modern trading, implies suboptimality in price as a predictor, and explains trading volume spikes on earnings dates.Data Paucity in New Insurance Markets. In chapter 2, I study how insurance markets for new or nonstationary risks can be tiny even when those risks are massive. Data paucity creates undiversifiable "model uncertainty" and when insurers penalize this uncertainty, they offer contracts with policy limits and (sometimes) deductibles if at all (even without moral hazard and adverse selection). Anonymized datasharing and relaxed antitrust policy may help in these contexts.Insurance against Ranswomare. In chapter 3, I show how increased cyberinsurance availability can increase the frequency and severity of ransomware attacks. Even accounting for the cybersecurity improvements insurers bring their customers, higher coverage (sub)limits may harm social welfare. While that does not mean the presence of cyberinsurers is welfare-negative, it means that regulatory sublimit caps for ransomware coverage - an enforceable policy, unlike ransom payment bans - can enhance social welfare relative to a regulation-free benchmark.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
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650 4 $a Investments. $3 566987
650 4 $a Algorithms. $3 536374
650 4 $a Optimization techniques. $3 3681622
650 4 $a Computer science. $3 523869
650 4 $a Finance. $3 542899
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773 0 $t Dissertations Abstracts International $g 84-03A.
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