CrossBorder Capital implements a proprietary risk-based approach that employs a systematic quantitative model.
This is designed to more easily integrate into your investment process by providing an extra level of screening. Our methodology and evaluations have been independently studied and verified by Dassault Systemes, the risk consultants.
Traffic light warning systems and data heat maps visually display alerts to clients. We monitor and separately publish data on three key risk channels: (1) liquidity risk; (2) forex risk and (3) market exposure risk. These are combined into a Composite Risk Index, which is published, within 10 days of each month-end.
To assess risk, CrossBorder Capital tracks capital flows, watches Central Banks and digs into credit markets. The methodology derives from a comprehensive study of flow of funds data and incorporates our belief is that changes in the sources of funds (i.e. financial flows) are often more important than the uses of funds (i.e. economic spending categories). This is true by definition at major inflections in the funding cycle, which we measure through our monthly GLI™ (Global Liquidity Indexes). These indexes comprise measures of Central Bank, Private Sector and net Cross-Border capital flows: we sample more than 30 data series for each of 80 economies World-wide, covering banks, Central Banks, shadow banks, corporations, households and foreign investors to unambiguously assess liquidity conditions.
Our conclusions are expressed in three ways: (1) credit markets depend on the ability to re-finance positions (liquidity/re-financing risk) and are therefore determined by the volume of liquidity; (2) forex markets depend upon the quality as well as the quantity of liquidity, and specifically on the difference between our indexes of Private Sector and Central Bank Liquidity (forex risk), and (3) investment performance depends, in part, on both these credit risk and forex risk factors as well as a third factor market exposure risk, which measures the extent that existing portfolios are skewed, or not, towards risk assets and therefore implicitly includes greater or less default risk and maturity risk.
In summary, liquidity risk is most important for bond and credit markets; forex risk determines currency markets, and exposure risk is key for risk assets, such as equities and credits. These risk factors are optimally combined using machine-learning technology into a Composite Risk Index.
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