
Over the last 13 years, I have had the opportunity to start and grow a model driven credit portfolio and help build a comprehensive investment process from the creation of alpha and risk models to the construction and implementation of daily portfolios and periodic attributions of desk performance. I have helped make continuous improvements across all components of the process by looking to combine my experience of conducting fundamental research in the High Yield Credit market with my aptitude for quantitative methods.
During this time, I have learnt that a systematic process not only captures alpha potential for all the securities in a defined universe, but also helps create insights for market volatility, dispersion and sector level factors. I am motivated to work with a small research team to design, research and manage innovative portfolios based on systematic processes.
I believe that with the addition of certain Bayesian type techniques to the systematic approach, we may be able to build a more general framework across many asset classes. Since a fundamental research process has been at the core of my work, I would also be able to perform credit analysis in the public and private markets and strive to bring systematic elements to research.
· Launched and managed a market neutral, long-short strategy comprising ~ 300 HY and IG corporate bonds selected from a universe of ~1000 credits for 13 years.
· Delivered consistent, positive returns on a gross notional base ~ $1.5– $4 bn and a net notional base of ~ -$100mm– $300 mm bn over this time, with positive annual returns in 11 years (cumulative ~$340 mm- ex-capital costs) and negative annual returns in 2 years (~ -$28 mm in 2018 and in 2022). Positive returns were weighted towards more volatile, high dispersion years.
· Combined market information around company fundamentals (e.g. earnings and other economic announcements), individual security price changes and the cross-sectional dispersion of security returns with the output derived from the quantitative model to assess adverse-risk selection biases and evaluate optimal risk constraints; and generated model-consistent yet cost effective and robust desk portfolios.
· Collaborated with the research team to constantly evaluate strategy risk and implementation shortfall. Provided specific inputs to improve upon the alpha and the risk models.
· Developed a proprietary framework to identify market regimes based on momentum and reversal states, that was used both for factor-timing and to optimally vary portfolio risk exposures.
· Researched firm-specific financial statement variables in conjunction with price momentum to identify tail risk of a corporate credit that may not be completely captured by the model-estimated risk.
· Partnered with in-house credit traders to achieve efficient trade execution.
· Built a fundamental understanding of the cyclical sectors including Energy, Basic Materials and Consumer by engaging with street analysts, and monitored risk and alpha-signal changes to help manage hedge-fund and benchmark-relative long-only credit portfolios.
· Assisted in the building of the CDS Long-Short (2004), CDO (2004) and Equity Long-Short (2007) strategies; created checklists for analysts to assess integrity of data, robustness of signals and out-of-model risks.
· Developed two innovative alpha-signals for the quantitative models: one based on good growth and bad growth of a firm and the other based on a firm’s cash flow momentum.