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At Quantfish we use mathematical modeling, machine learning and extensive research to forecast anticipated future market behavior with a statistically significant degree of confidence. We design our own proprietary trading systems and endeavor to capitalize on opportunities in the financial markets as and when they arise.

About Quantfish

Portfolios

Quantfish diversified & leveraged private equity funds (Portfolios are auto-updated twice daily)

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Markets

Futures & Forex markets we actively trade (Trading performance are auto-updated twice daily)

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Research Lab

A collection of quantitative research tools, Latest market analysis and Trading strategy optimizations

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Expertise

Our skillset include Software development, Data science, Machine learning and Quantitative analysis

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Why Quantfish?

The word ‘quant’ is derived from quantitative, which essentially means working with numbers, whereas ‘fish’ refers to the fishing for, or extracting of ‘alpha’ in the markets. Alpha (α) is a term used in investing to describe an investment strategy’s ability to beat the market.

We do not utilize fundamental data, market sentiment, or any non-quantifiable input to inform our trading models. Quantfish trading is purely data-driven and uses advanced statistical and mathematical models based on large sets of historic price data to establish the probability of certain future market movements. A lot of computational power and extensive research is required to design & develop successful models, and we use only state-of-the-art hardware and software to aid the process.

Our private equity portfolios consist of major indices as well as forex pairs combined with the least amount of correlation to ensure optimum diversification within each fund. To further enhance diversification to allow for smoother equity curves, our strategies are optimized to perform well in bull and bear markets and make use of trend following, breakout and mean reversion principles.

Testing and Trading Software

We do not utilize any 3rd party software such as Tradestation or Amibroker to test or trade our strategies. Our proprietary system trading software (AlphaWOLF) has been meticulously developed ‘in-house’ from the ground up over several years. AlphaWOLF software connects directly with our broker’s API and allows us to easily design and deploy new strategies, as well as portfolio level backtesting, optimization, visualization and fully automated live trading.

Our software’s trading ‘engine’ is used for strategy testing, optimization as well as live trading. Using the exact same ‘engine’ for all these applications has many advantages. It reduces errors and discrepancies and replicates live trading as close as possible compared to historic test results. Spread variation and slippage during live trading might still slightly deviate from historic testing results, but these are simulated during testing and optimization to imitate live trading within a 3% margin of error. [ More Info ]

Private Equity Funds




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Quantfish Expertise

Data Science

Data Science

Machine Learning

Machine Learning

Quantitative Analysis

Quantitative Analysis

Algorithmic Trading

Algorithmic Trading

Investment Models

Investment Models

Private Equity Funds

Private Equity Funds

Artificial Intelligence

Artificial Intelligence

Reinforcement Learning

Reinforcement Learning

Evolutionary Computing

Evolutionary Computing

Software Development

Software Development

Mobile Applications

Mobile Applications

API Integration

API Integration

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Technologies:

  • Machine Learning
    Machine learning is a method of teaching computers to learn and make decisions on their own, without explicit programming. It involves feeding a computer large amounts of data and using algorithms to automatically learn patterns and make decisions. There are several types of machine learning, including supervised learning and unsupervised learning. It has been applied in a wide range of fields, including computer science, economics, and finance and can be utilized in the creation of investment models and algo-trading strategies.
    Quant.fish Research
  • Quantitative Analysis
    Quantitative analysis is a method of using mathematical and statistical techniques to understand and analyze data. It is commonly used in finance, economics, and other fields to model and make predictions about real-world systems. Quantitative analysts use tools such as statistical software, programming languages, and mathematical models to analyze data and make informed decisions. The goal of quantitative analysis is to use data to support or refute hypotheses, understand trends and relationships, and make accurate predictions about future outcomes.
    Quant.fish Research
  • Data Science
    Data science is a field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data scientists apply techniques from a range of fields, including statistics, machine learning, and computer science, to analyze and interpret complex data. They use this data to solve real-world problems, make data-driven decisions, and communicate their findings to others. Data science is a interdisciplinary field that spans a wide range of industries, including finance and technology.
    Quant.fish Research
  • Software Development
    Software development is the process of designing, creating, testing, and maintaining software applications. It involves a range of activities, including requirements gathering, design, coding, testing, and deployment. Software developers use programming languages and tools to write, test, and debug code, and often work in teams to develop complex software systems. Software development can be done using a variety of approaches, such as the traditional Waterfall model, or more modern Agile methodologies.
    Quant.fish Research
  • Reinforcement Learning
    Reinforcement learning is a type of machine learning in which an agent learns to interact with its environment in order to maximize a reward. The agent receives feedback in the form of rewards or punishments for its actions, and uses this feedback to improve its strategy for interacting with the environment. Reinforcement learning algorithms, together with neural networks, can be used to solve a wide range of problems, including financial investment models and optimization of algorithmic trading strategies.
    Quant.fish Research
  • Statistical Analysis
    Statistical analysis is the process of using statistical techniques to summarize, analyze, and interpret data. It involves the collection and organization of data, the selection of appropriate statistical tests, and the interpretation of results. Statistical analysis is used to describe and understand data, make predictions about future outcomes, and test hypotheses. It is a fundamental tool in fields such as finance, economics, and the natural and social sciences, and is used to inform decision-making and guide policy.
    Quant.fish Research
  • Evolutionary Computing
    Evolutionary computing is a branch of artificial intelligence that involves the use of evolutionary algorithms to optimize solutions to problems. These algorithms are inspired by natural evolution and use techniques such as selection, crossover, and mutation to generate solutions to a given problem. Evolutionary computing algorithms such as 'genetic algorithms' and others are often used to solve problems that are difficult or impossible to solve using traditional algorithms, due to the complexity or size of the problem space.
    Quant.fish Research