Profile
James Rhodes is Chief Technology Officer for Morningstar, Inc. Mr. Rhodes previously occupied the position of Chief Technology Officer of Rocaton Investment Advisors LLC. He received an undergraduate degree from Muhlenberg College and a graduate degree from Carnegie Mellon University.
James Rhodes active positions
| Companies | Position | Start |
|---|
Former positions of James Rhodes
| Companies | Position | End |
|---|---|---|
| MORNINGSTAR, INC. | Chief Tech/Sci/R&D Officer | - |
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. | Chief Tech/Sci/R&D Officer | 2016-08-31 |
Training of James Rhodes
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Inactive
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1st degree companies
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Executives
Linked companies
| Private companies | 4 |
|---|---|
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 |
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