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LFIS Capital

Liquid Alt / Relative Value strategies

Absolute return

LFIS' expertise in implied parameters is rooted in its quantitative research capabilities and long-standing equity derivatives background. The team focuses on analysing and managing market-implied variables such as volatility, correlation, repo and dividends, which form a rich universe for relative value and derivatives carry strategies.

This expertise can be deployed through dedicated mandates, managed accounts or tailored Quantitative Investment Strategies (“QIS”), depending on each client's objectives and constraints. Portfolio construction may also be complemented with linear long/short quantitative investment strategies across equities, rates, foreign exchange and commodities.

By combining quantitative analysis, derivatives expertise and disciplined implementation, LFIS seeks to capture dislocations across instruments, maturities and asset classes, while adapting each solution to investors' risk profiles, liquidity requirements and portfolio objectives.

Focus on Dispersion

LFIS Dispersion strategy has been part of our portfolios since 2015. LFIS' dispersion expertise is based on the observation that equity index volatility and single-stock volatility can be driven by different structural flows.

Institutional investors often hedge portfolios by buying index options, which can create a premium in index implied volatility. At the same time, structured products issuance can create selling pressure on single-stock volatility. These dynamics may create relative value opportunities between index volatility and single-stock volatility.

A dispersion strategy seeks to capture the correlation premium embedded in equity volatility markets, where implied correlation can trade at a premium relative to realized correlation. LFIS focuses on market-neutral implementations, with an emphasis on vega-flat structures using volatility swaps where appropriate, in order to reduce path dependency, improve neutrality and retain convexity.

  • Equity volatility and implied correlation analysis
  • Index volatility versus single-stock volatility relative value
  • Dispersion portfolio construction
  • Vega-flat implementation
  • Volatility swaps and derivatives execution
  • Market-neutral risk management
  • Monitoring of realised correlation, sector rotation and earnings-driven dispersion

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