About Equities
Our expertise in equities is underpinned by our ability to transform theoretical, academic research into real investment strategies and solutions. Over the last 25 years, we have demonstrated this through a successful track record in risk-managed, alpha-seeking and ESG-tilted equity portfolios.
Our history in equities
1995
Minimum variance research project, based on Prof. R.A. Haugen’s research
1997
Launch of first live minimum variance portfolio (Swiss equities)
2000
Fundamental quality indicators embedded in the process alongside quantitative optimisation
2004
First integration of ESG filters
2006
Liquidity-at-risk model, allowing better liquidity and lower trading cost
2010
First strategy using equity and derivatives
2011
Development of a proprietary statistical alpha-seeking risk model
2014
Launch of a alpha-seeking equity strategy
2016
Proprietary CO2/climate risk analysis methodology
2019
Machine learning model, allowing better detection of stocks with increased downside risk
Integration of ESG scores into all equity and fixed income investments
2020
Adaptative risk management framework using macroeconomic Nowcasters
Launch of Climate model
2021
Adherence to SASB reporting standards
2022
Launch of Unigestion Climate Transition Fund
Our equity capabilities
Holistic risk management
We have one of the longest track records in the industry of running risk-managed equity portfolios. Our equity investment philosophy is anchored in the belief that the best way to make money in the long run is not to lose it.
ESG and sustainability
We believe that investing in well-governed businesses with responsible practices can make a positive contribution to the long-term risk adjusted performance of our clients’ portfolios. We integrate ESG factors into our investment process using our ‘four pillars’ approach, covering norm-based exclusion, worst-in-class screening, portfolio guidelines and active stewardship.
Active multifactor portfolios
We start from academic research on proven equity risk premia such as Value, Momentum and Quality, then apply proprietary analysis to improve their risk-adjusted return characteristics. We then utilise an active, macroeconomically-informed weighting scheme to produce an efficient all-weather multifactor portfolio.
Latest Videos
In this series of videos, specialists from our Equities team take a detailed look at ESG, from how we screen our investment universe through to how it is integrated into our strategies and its impact on performance.
Core competencies
Risk modelling
We measure and decompose risks using a suite of advanced quantitative models. This includes statistical stock price analysis and top-down Nowcaster indicators on macro, valuation and sentiment. As a consequence, our portfolios are able to exhibit convincing capital protection characteristics and a consistent behaviour across market regimes.
Style Factors
We harvest the return of equity risk premia: Value, Momentum, Quality and Low-Risk. Our definition of style premia risk combines rigorous empirical research and fundamental expertise. Their variance is assessed with our unified macro risk-based allocation framework. This process enables us to best capture academically proven sources of return in an optimal way.
Adaptive Allocation
We adapt our equity portfolio style allocation to macro, sentiment and valuation indicators. This framework blends a risk-based strategic allocation with a dynamic one using a series of Nowcaster and Newscaster indicators on macro, valuation and sentiment to ensure our performance remains robust across market regimes.
ESG
We integrate ESG factors using our four pillars approach, comprising a suite of indicators and processes. This covers norm-based exclusions, worst-in-class screening, portfolio guidelines and active engagement. As a result, our equity portfolios’ ESG metrics are significantly superior to corresponding market indices.
Fundamental Research
We uncover fundamental risks and opportunity sets using a framework which analyses stocks, sectors, countries and themes. Our qualitative appraisal complements the quantitative approach with a forward-looking view and acts as a safety net, improving on the weaknesses of quantitative models.
Machine Learning
We estimate expected returns using a supervised machine learning algorithm (Tree-based regression) to uncover complex non-linear relationships between 100+ predictors and stocks returns. This repeatable, unemotional process evolves over time to act as an additional alpha driver for our portfolios.
The Team
The Equities team is 22 strong and organised around the following five groups:
- Portfolio Managers – responsible for portfolio construction, investment decisions, day-to-day portfolio monitoring and the enhancement of the management process through research projects.
- Client Portfolio Managers – combine portfolio management roles including input into the decision making process and customisation of existing strategies to client needs.
- Fundamental Analysts – responsible for performing qualitative/fundamental analysis on equities, with an aim of identifying and monitoring critical fundamental risk factors.
- Quantitative Analysts – responsible for conducting quantitative research and developing the proprietary risk analysis tools used by the team.
- Traders – responsible for the efficient implementation of strategies with regard to portfolio manager’s execution policies, as well as developing models to predict and reduce market impact while trading.
Composites & Funds
Composites
Past performance is no guide to the future, the value of investments can fall as well as rise, there is no guarantee that your initial investment will be returned. The content of this page constitutes neither investment advice nor recommendation. It represents no offer, solicitation or suggestion of suitability to subscribe in the investment vehicles it refers to. Please contact your professional adviser or consultant before making an investment decision. Please refer to the KIIDs, the Fund offering documents, and the latest Annual and Semi Annual Reports before investing. Before investing, investors should obtain and read a copy of the prospectus and the KIIDs. Where possible we aim to disclose the material risks pertinent to this document, and as such these should be noted on the individual document pages. A complete list of all the applicable risks can be found in the Fund prospectus. There is no guarantee that the investment objective of the Fund will be achieved. The NAV is not guaranteed and may fall as well as rise, depending on investment performance, and exchange rate fluctuations. Some of the investment strategies described or alluded to herein may be construed as high risk and not readily realisable investments, which may experience substantial and sudden losses including total loss of investment. These are not suitable for all types of investors. Data and graphical information herein are for information only and may have been derived from third party sources. Unigestion takes reasonable steps to verify, but does not guarantee, the accuracy and completeness of this information. As a result, no representation or warranty, expressed or implied, is or will be made by Unigestion in this respect and no responsibility or liability is or will be accepted. All information provided here is subject to change without notice. It should only be considered current as of the date of publication without regard to the date on which you may access the information. Rates of exchange may cause the value of investments to go up or down. An investment with Unigestion, like all investments, contains risks, including total loss for the investor.
