Investment Matters
Join Darren as he speaks about algorithmic trading with Ivan Scherman, the Portfolio Manager of the Ausbiz Capital GroWise Fund. Ivan explains how technology and data-driven, rules-based, strategies seek signals and exploit patterns across global markets. His approach trades thousands of assets and runs around 200 independent strategies, aiming for uncorrelated returns that reduce systemic risk and smooth portfolio volatility. Why investors should watch: A rare insight into how institutional-grade algorithmic strategies work and how they are now available to retail investors to help improve diversification, reduce volatility, and enhance long-term portfolio returns. Want to learn more: https://www.investmentmarkets.com.au/ For more information on Ausbiz GroWise Capital Fund: https://www.investmentmarkets.com.au/listings/ausbiz-capital-growise-fund-ausbiz-capital-investments-698e71e5424d9a649939758c Disclaimer These podcasts are for informational and promotional purposes only. Any comments made or information provided does not consider the appropriateness for you having regard to your particular objectives, personal/financial situation and needs. Before investing you should consider independent professional financial advice. No comments made or information provided constitutes advice, an invitation, or an offer to buy any security or other financial product or engage in any investment activity. All securities and financial products involve risks. Past performance of any product is not a reliable indication of future performance. Read carefully the governing documents of a product’s offering such as its PDS, TMD or information memorandum. InvestmentMarkets does not vet, endorse or recommend any product that is the subject of these podcasts and is only facilitating the exposure of the product. These podcasts were made at a particular date in time and therefore relevant facts, the economic environment, governing documentation and the law upon which they were based may change after that date such that the accuracy and reliability of their content may be affected.
19 episodios
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