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Design your portfolio and manage your risks using data science
Access a wide range of exposures, including ESG passive investments
The machine learning engine uses Bayesian forecasting to rank the probability of outperformance for each fund in your portfolio
Repeatable, rules-based framework that reduces reliance of guesswork
Portfolio Advisory
Bespoke Asset Allocation Services
Twenty20 Systematic iBasket
After the recent bouts of market turbulence,
how good were your risk adjusted returns?
Algo-Chain currently provides the research and Model Portfolio weightings to a number of Discretionary Fund Managers and in the link above we show an example of a Model Portfolio that is designed to be weatherproof. In this particular case, the model employs a carefully calibrated momentum signal across a range of asset classes.
One important question to ask is – now that we are heading into unchartered territory – how will your portfolio perform in a market crash and how can you make it more robust to unforeseen events? Is the lack of transparency of active funds holding you back from applying a more scientific approach to fund selection and asset allocation?
Last, but not least, with the underperformance of many active managers, the key question to ask is – on a risk adjusted basis, how good was your portfolio’s performance after fees? At Algo-Chain we have developed a set of tools that show the range of performances for a certain risk level. It also allows us to provide insights into how to improve an investor’s performance and weatherproof the portfolio.
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