Our Investment Philosophy
Our Investment Philosophy
Our investment philosophy is based on the belief that financial markets are complex, dynamic and exhibit self-reinforcing behaviour which manifests through feedback loops. These feedback loops lead to market complacency and market stress, as evident in tail risk events such as the Asian Financial Crisis, the Dotcom Bubble and the Global Financial Crisis.
Systems that depict feedback loop characteristics are typically chaotic in nature. Chaotic systems are challenging to understand through conventional statistical techniques, often mistakenly characterised as random events.
Alpha Vista believes that chaotic systems within financial markets can be understood if underlying patterns of behaviour – which are inherent in the data – can be discovered. Once discovered, pattern recognition enables the definition of regime states associated with market biases.
The combination of data science, AI-based analytics and distributed computation technology is the means by which complex chaotic systems can be analysed in real-time to identify opportunities for alpha generation and risk mitigation.
Our approach
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DATA DRIVEN
We capture and analyse vast volumes of financial market data at highly granular levels to identify patterns and order within chaotic systems for regime analysis
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SYSTEMATIC EXECUTION
With automated signal being generated throughout the day, we have streamlined trade execution through a systematic process with connections to multiple counterparties to source liquidity and be able to execute on size.
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ADVANCED ENGINEERING
Our technology infrastructure and platform is the backbone of our business. Ingesting streaming (live) data at the millisecond timescale enables low-latency real-time analysis.
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AGILE COLLABORATION
To encourage the cross pollination of ideas and the development of innovative solutions for our clients, we engage through multi-disciplinary teams that operate daily in an agile environment.
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AI ANALYTICS
Our AI and algorithms adapt dynamically to changes in the behaviour and shape of patterns in data, transforming these into information-rich signals that support investment strategy, asset allocation and risk management decision making.