Profil
James Rhodes est directeur de la technologie chez Morningstar, Inc. M. Rhodes occupait auparavant le poste de directeur de la technologie de Rocaton Investment Advisors LLC. Il est titulaire d'un diplôme de premier cycle du Muhlenberg College et d'un diplôme de deuxième cycle de l'Université Carnegie Mellon.
Postes actifs de James Rhodes
| Sociétés | Poste | Début |
|---|
Anciens postes connus de James Rhodes
| Sociétés | Poste | Fin |
|---|---|---|
| MORNINGSTAR, INC. | Directeur Technique/Scientifique/R&D | - |
Rocaton Investment Advisors LLC
Rocaton Investment Advisors LLC Investment ManagersFinance Rocaton develops its asset allocation recommendations through the use of proprietary risk, return and correlation assumptions to assess the expected risk and expected return of different asset mixes over a variety of market environments. Specifically, the firm often utilizes a Monte Carlo portfolio optimization process to forecast risk and return inputs over different scenarios. Recommended allocations are generally based on forecasted risk and forecasted return characteristics, including expected volatility and correlation of returns, liquidity and transaction costs, as well as on client objectives. | Directeur Technique/Scientifique/R&D | 01/09/2016 |
Formation de James Rhodes
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Sociétés liées
| Entreprise privées | 4 |
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Carnegie Mellon University
Carnegie Mellon University Other Consumer ServicesConsumer Services Functions as a College/University | Consumer Services |
Morningstar, Inc.
Morningstar, Inc. Financial Publishing/ServicesCommercial Services Operates as a investment insights company that provides investment and wealth management & credit rating services | Commercial Services |
Muhlenberg College
Muhlenberg College Other Consumer ServicesConsumer Services Functions as a College/University | Consumer Services |
Rocaton Investment Advisors LLC
Rocaton Investment Advisors LLC Investment ManagersFinance Rocaton develops its asset allocation recommendations through the use of proprietary risk, return and correlation assumptions to assess the expected risk and expected return of different asset mixes over a variety of market environments. Specifically, the firm often utilizes a Monte Carlo portfolio optimization process to forecast risk and return inputs over different scenarios. Recommended allocations are generally based on forecasted risk and forecasted return characteristics, including expected volatility and correlation of returns, liquidity and transaction costs, as well as on client objectives. | Finance |
















