KyperXCapital
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Approach

Systematic discipline, discretionary context.

Models excel at processing large amounts of market data consistently. Human judgement is applied to macro, sector and regime interpretation. The strategy is built as three layers, each with a separate job.

Strategy stack

Three layers, built from the core up.

The systematic core is always running. Thematic conviction decides where research-led exposure sits. The risk and hedge overlay engages when conditions call for it.

Exploded viewDashed: conditional
Strategy stackThree layers drawn as an exploded stack. The systematic core is the base, thematic conviction sits above it, and the risk and hedge overlay is the top layer, drawn dashed because it engages conditionally.LAYER 03 · CONDITIONALRisk & hedge overlayLAYER 02 · RESEARCH-LEDThematic convictionLAYER 01 · ALWAYS ONSystematic coreEXPOSURE IS BUILT FROM THE CORE UP

Signal to position

How a signal becomes a position.

Signals are combined into a score, the market regime is classified, and position size is set against a volatility budget. Exposure limits apply before anything reaches the portfolio. Discretionary context informs the regime and sizing steps.

ProcessDirection of flow only
From signal to positionMomentum, volatility, liquidity and correlation inputs feed a signal engine. The engine feeds regime classification, then position sizing, then exposure limits, then the portfolio. A dashed discretionary overlay of macro, sector and geopolitical context informs regime classification and position sizing.MomentumTREND PERSISTENCEVolatilityREALISED · IMPLIEDLiquidityDEPTH · FLOWSCorrelationCROSS-ASSET STRUCTURESignal engineMULTI-FACTOR SCORERegimeTREND × VOLATILITYPosition sizingVOLATILITY BUDGETPortfolioEXCHANGE-TRADEDEXPOSURELIMITSDiscretionary overlayMACRO · SECTOR · GEOPOLITICAL CONTEXTINPUTS

Dashed: discretionary input. The diagram shows the order of steps, not volume or speed.

Thematic conviction

Where research sets the map.

Targeted exposure to high-conviction growth areas with strong earnings elasticity and secular tailwinds. These are the sectors the research covers, not a list of holdings.

Theme

AI infrastructure

Compute, networking and the build-out behind AI adoption, where earnings respond strongly to capital expenditure cycles.

  • Capital expenditure cycles
  • Supply-chain concentration
  • Policy and export controls
Theme

Semiconductors

Design, equipment and manufacturing in a cyclical industry with long innovation runways and geopolitical exposure.

  • Inventory and pricing cycles
  • US–China and supply-chain shifts
  • Earnings elasticity
Theme

Biopharma innovation

Innovation-driven healthcare, where scientific and regulatory catalysts create discrete re-rating events.

  • Clinical and regulatory catalysts
  • Pipeline concentration
  • Event-driven volatility

Implementation

What the strategy trades, and how.

Instruments
Listed equities, ETFs and index products, with exchange-traded options and futures. Positions are held in the underlying instruments; no CFDs are used.
Markets
Liquid, exchange-traded markets, chosen so that positions can be adjusted as regimes change.
Timing
Entry and exit signals are refined with intraday volatility analytics and cross-asset correlation patterns. Execution rules avoid crowded, fragile flows.
Sizing
Position size is calibrated to volatility and liquidity, with strict limits per instrument, sector and theme.
Macro context
Interest-rate cycles, inflation and liquidity conditions inform risk-on and risk-off posture. Geopolitical catalysts, including US–China dynamics, supply-chain shifts and regulatory themes, inform sector and regional allocation.
Liquidity
Exchange-traded instruments support daily to weekly liquidity at strategy level. Investor liquidity terms are set out in the investment terms.