Banner Multi Strategy

Inception Date

October 1997

October 1997

Objective

Long-term capital appreciation

Universe

  • Macro: 100+ futures and forwards
  • Equity/Credit: 5,000+ securities

Quantitative Strategies

  • Technical Macro
  • Fundamental Macro
  • Technical Equity/Credit
  • Fundamental Equity/Credit

Objective

Long-term capital appreciation

Quantitative Strategies

  • Technical Macro
  • Fundamental Macro
  • Technical Equity/Credit
  • Fundamental Equity/Credit

Universe

  • Macro: 100+ futures and forwards
  • Equity/Credit: 5,000+ securities

Quantitative Multi-Strategy Approach

Long-term indicative risk allocations.

Key Features

Research-driven

Broadest expression of Winton’s proprietary research and investment management capabilities.

Dynamic

Trades an evolving portfolio of quantitative strategies, powered by technical and fundamental signals.

Diversified

Takes long and short positions in 100+ futures and forwards markets and 5,000+ equity/credit securities.

Past Performance

Source: BarclayHedge, Ltd. and Winton Capital Management. Past performance is not indicative of future results. Multi-Strategy performance is based on the oldest and largest account trading the strategy at the respective time and net of 1% management and 20% performance fees from inception to 31 March 2017; 0.9% management and 16% performance fees from 1 April 2017. No representation is being made that any account will or is likely to achieve profits or losses similar to those being shown. Performance of other accounts which started at different times may differ from the performance shown in the chart. Data to 31 August 2018.

Related Research

The Scientific Method Applied to Investing

The aim of statistical inference, whether it is in investment strategy development or medical research is not to say what would have been most effective in the past, but to make a statement about what will hold in the future. For valid inferences, we need to avoid bias in our conclusions.

Winton's research process has been designed to manage selection bias and avoid other common quantitative investment pitfalls. Here we describe the causes of such bias and some of the tools that can help us yield valid conclusions.

Testing Our Strategy for Testing Our Strategies

We have a well-defined process for testing and screening signals that has been honed over the past two decades through a combination of trial, error, and careful thought. Our research process is designed to answer the question: does a trading strategy work? But does our research process work?

In a carefully designed experiment, 26 research-approved trading strategies were shown, on average, to have genuine forecasting skill. This is an encouraging result for both the profitability of these systems and Winton's research methods.

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