This report shows public data only. Is this your organisation? If so, login here to view your full report.

Matarin Capital Management (Delisted)

PRI reporting framework 2020

You are in Direct - Listed Equity Incorporation » ESG incorporation in actively managed listed equities » Implementation processes » (A) Implementation: Screening

A) 実施:スクリーニング

LEI 04. Types of screening applied

04.1. 組織内でアクティブ運用している上場株式に適用するスクリーニングの種類を記載し、説明してください。




For Matarin’s Patience Premium strategies, we are screening out “Worst in Class” ESG stocks based upon controversies around their activities, products, governance, or practices and performance.

We have designed an approach to fossil free investment that focuses on fossil fuel guzzlers, as well as the energy sector.

We are also offering customized negative screens for customers, based upon their requests.



Matarin’s Patience Premium strategies are designed to hold the “Best In Class” Patience Premium stocks, based upon our proprietary scoring system, which includes ESG factors




We offer customized norms-based screening upon client request.

04.2. スクリーニング基準が変更された場合に顧客や受益者に通知する方法について説明してください。

Matarin communicates any changes to our model to clients through monthly and/or quarterly account reviews. 

LEI 05. Processes to ensure screening is based on robust analysis

05.1. スクリーニングが徹底した分析に基づいていることを確実にするために、組織が使用しているプロセスを選択してください。

05.2. ESGスクリーニング戦略の一環で包括的なESG調査の対象となるアクティブ上場株式ポートフォリオの割合を示してください。

05.3. 第三者のESG評価がスクリーニング目的で更新される頻度を示してください。

05.4. 組織のESGスクリーニングを構築するための組織内リサーチを精査する頻度を示してください。

05.5. 補足情報 [任意]

“Robust analysis” of all of the variables which go into our investment process is the basis of our very existence at Matarin!

Our investment processes are time tested. They have worked successfully for over 30 years, and have added significant value to client portfolios over that time.  On a shorter term basis, we perform portfolio attribution analyses regularly and are cognizant of which factors are working in the portfolio and which are not in any given period of time. 

In addition, we continuously perform simulations using new factors to determine if different factors in different weights might have a positive impact on returns for a given level of risk. As quantitative investors, we have many tools available to us to perform this work.

The creation of our investment strategies included numerous simulations to test the efficacy of our stock selection model to predict expected returns, i.e., stock alphas.  Additionally, these simulations tested various portfolio construction considerations such as contribution to risk from:  stock, industry and sector weights; exposure to macro factors such as interest rates and oil prices; and “blind” statistical factors.  The simulation process allows Matarin to both evaluate different input combinations, e.g., constraints on relative sector weights, and understand the interaction among alphas, risk, and transaction costs.  This understanding is especially important as it is essential to the efficient construction of optimal portfolios aimed at achieving various levels of risk, given a specific return objective; or achieving various levels of returns given a specific target for risk.

Matarin’s simulation process is used to test the efficacy of each and every potential factor we might include in our “alpha” or risk models, including ESG factors.   This process includes:

  • Appropriately lagging data so as to avoid any “look ahead” bias in developing factors.
  • Eliminating stocks from the universe which did not meet specific capitalization and/or liquidity criteria.
  • Establishing a targeted predicted tracking error range.  This allows Matarin to increase portfolio risk exposure, as warranted by market opportunities, without creating unnecessary portfolio turnover due to an automatic rebalancing to a single fixed risk target.
  • At purchase, capping stock weights at 1.2% to achieve diversification of stock specific risk.  Additionally, allowing stock weights to rise to a maximum of 2.0%, thus avoiding unnecessary transaction costs from forced rebalancing.
  • Constraining non-blind risk factors, within “common sense” limits, ensuring all quantifiable risk exposures are intended and compensated with expected excess returns.
  • Constraining sector and industry weights, within a specified range, thus avoiding excessive risk exposure and ensuring portfolio excess returns are generated largely from stock specific risks resulting from stock selection.
  • Rigorously analyzing simulation results to ensure that portfolio turnover rates, characteristics, holdings, and constraints were as anticipated, ex ante.
  • Estimating and evaluating simulated returns and risks during two distinct time periods to ensure consistency of outcome and similarity of distribution patterns across time and different market environments.

Matarin’s investment objective is to provide realistically achievable excess returns while controlling for portfolio risks and, in particular, downside risk.  Throughout the simulation process we sought a portfolio construction scenario that afforded a high information ratio, but also one in which downside volatility was dampened.  One of Matarin’s firm objectives is for clients to have sufficient confidence in our process to remain invested during those inevitable periods of challenging markets.  And, ideally, to invest further during such times so as to realize the upside potential as performance of both the portfolio and the market once again improves.  Through our simulation process we have been mindful of this firm objective and have selected an optimal combination of stock alphas and risk parameters to deliver consistency of results with lower volatility.

Matarin’s process for factor creation is dynamic.  Markets are not static and the determinants of future investment returns can vary in influence.  Consequently, our proprietary factors and their weights will evolve as both our thinking and model development adapt to changing market environments.

The starting point for research into new factors is typically an insight regarding what may be predictive of stock prices going forward.  These insights can originate from a variety of sources; a book, academic research, financial periodicals, or even by a comment made by Warren Buffet one year at his annual meeting.  We care little about the source of the ideas, we care more about the quality of the insights and how best to quantify them.  We do not buy any factors from external sources, nor do we rely on sell-side research to aid in the determination of industry or stock specific weights.  All of the value-added insights housed within the models are our own. 

Once each factor has been quantified, they are tested historically to determine how well they performed relative to other factors, and how they interact with other factors.  Our investment team tests only those insights it believes has “Future Investment Merit”…not necessarily those ideas which have worked best in the past, but those they believe are likely to be most predictive of stock prices going forward.  We are not looking to build the top performing back-test, but instead are focused on building a model that will excel in the real world going forward.  The development and testing of these indicators are “assigned” to whoever is most interested in performing them.  Factors are included in the model once they have been thoroughly vetted and agreed to by all members of the investment team.

The process of defining, testing and then using a factor in our models is most definitely “rigorous”. ESG factors are handled in exactly the same way, and with as much care as any financial factor we might be inclined to use in our process. 

LEI 06. Processes to ensure fund criteria are not breached (Private)