Senior Investment Analyst

Job Duties

It is expected the candidate can use these in conjunction with a deep understanding of financial markets to estimate long‑term variables to generate expected returns (10%). Strong knowledge of financial theory, especially long‑run cash flow models and present value relations, and the ability to translate stock‑based theories and models to broader asset classes (10%). Expert in estimating equity expected returns using supply side framework, with proven contributions to this area (15%).

Knowledge of fundamental demand side equity models, with the ability to use present value relations to decompose risk premiums into supply side estimations of the equity risk premiums (10%). Expert in equity index aggregation methodologies, including ability to construct fundamentals based on unique Morningstar data and variables. This includes strong knowledge of industry best practices and techniques for producing robust aggregate data to use in our investment processes (15%).

Expert knowledge in econometrics techniques and the ability to develop complex models. This includes, but is not limited to, strong knowledge of multivariate unit roots and structural break, with the expectation of proven contribution to this body of knowledge. Other areas with expected strengths include Markov regime switching models, trend and cycle decomposition, and estimation of latent variables (10%). Expert in time series, cross‑sectional and panel methodologies for conducting back‑test studies and research (5%).

Strong knowledge of structural macroeconomics, including ability to identify and analyze the effects of different types of economic shocks, such as supply and demand shocks, using SVAR models (5%). Strong knowledge of fixed income models and term structure models and the ability to apply these concepts to equities and other asset classes (5%). Strong knowledge of foreign exchange models, including purchasing power parity models (5%).

Understanding of cross‑asset class interactions and ability to model joint events using multivariate distributions. This includes the ability to create simulations using copulas and marginal distributions (5%). Strong understanding of portfolio variance decomposition and the ability to impose diagonal restrictions to capture bottom‑up risk information from Morningstar equity analysts (5%). Remote work requests will be considered consistent with company policy.

This position requires a Bachelor's degree in Business Analytics, Finance, Economics, Mathematics, or a related analytical field, or foreign equivalent and 3 years of relevant investment experience in Associate Analyst (Multi Asset Research), Financial Product Specialist, or related position. Also, must have Chartered Financial Analyst (CFA) credential.

This position also requires experience with investments, especially expertise in and knowledge of financial theory and the ability to link this to empirical and practical applications, including estimating expected returns and asset allocation. Experience with advanced return and fundamental decompositions using knowledge of asset pricing theory. Experience of advanced econometrics and use in daily workflow. Experience using Python, R, Matlab, Morningstar Direct, Morningstar Direct API in Python, Pitchbook, Office 365 tools relevant to industry database.

Experience in creating expected return models and estimates for public markets. Experience in creating expected return models for assets with non‑observable returns. Experience in estimating latent variables, including but not limited to state‑space models and Bayesian Markov Chain Monte Carlo methods. Expertise in creating fundamental equity indices and fundamental ratios. Expertise in asset class…