![Michael Pang](data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="%231b1b1b" class="bi bi-person-fill" viewBox="0 0 16 16"><path d="M3 14s-1 0-1-1 1-4 6-4 6 3 6 4-1 1-1 1zm5-6a3 3 0 1 0 0-6 3 3 0 0 0 0 6"/></svg>)
Michael Pang
Analyst-Equity bei
Aquatic Capital Management LLC
Profil
Michael Pang is currently a Quantitative Researcher at Aquatic Capital Management LLC, a position held since 2020.
Mr. Pang completed an undergraduate degree at The University of Waterloo in 2020.
Aktive Positionen von Michael Pang
| Unternehmen | Position | Beginn |
|---|---|---|
Aquatic Capital Management LLC
 Aquatic Capital Management LLC Investment ManagersFinance Aquatic’s Funds seek long-term positive returns that are uncorrelated, over time, with traditional asset classes. In seeking to achieve this objective, the firm intends to employ quantitative investment and trading strategies. These quantitative strategies arise from the systematic application of mathematical, statistical, machine-learning and other models to historical and real-time data to discover persistent patterns in the evolution of market prices, asset volatilities, trading costs, and other relevant fundamental and economic data. | Analyst-Equity | 01.01.2020 |
Ausbildung von Michael Pang
Erfahrungen
Besetzte Positionen
Aktive
Inaktive
Börsennotierte Unternehmen
Private Unternehmen
Beziehungen
71
Beziehungen ersten Grades
2
Unternehmen ersten Grades
Herr
Frau
Aufsichtsräte
Führungskräfte
Unternehmensverbindungen
| Private Unternehmen | 2 |
|---|---|
The University of Waterloo
 The University of Waterloo Other Consumer ServicesConsumer Services Functions as a College/University | Consumer Services |
Aquatic Capital Management LLC
Aquatic Capital Management LLC Investment ManagersFinance Aquatic’s Funds seek long-term positive returns that are uncorrelated, over time, with traditional asset classes. In seeking to achieve this objective, the firm intends to employ quantitative investment and trading strategies. These quantitative strategies arise from the systematic application of mathematical, statistical, machine-learning and other models to historical and real-time data to discover persistent patterns in the evolution of market prices, asset volatilities, trading costs, and other relevant fundamental and economic data. | Finance |
