Statistical Arbitrage, Pairs Trading

Implement a high-frequency statistical arbitrage pairs trading strategy using Z-score thresholds on cointegrated assets. Discover entry/exit logic and market ap

Published · Updated · Methodology: Arbitrage

Part of: Mean Reversion

  • Methodology: Arbitrage
  • Content type: strategy
  • Timeframes: High-frequency
  • Markets: Cryptocurrencies, Stocks (potentially applicable)

Source video

Decoded from: Un sistema real de alta frecuencia rentable by Hispatrading Magazine — watch the original

Strategy overview

Statistical arbitrage and pairs trading treat the *relationship* between two historically linked instruments as the tradeable object: the position is long one and short the other, and the bet is on their spread reverting rather than on either instrument going up or down. That single structural choice explains most of what this catalog entry looks like. There is no directional forecast to indicate, and no overlay to read — the signal lives in a synthetic series constructed from two price streams, so an empty indicator list here is descriptive rather than missing data. It also means the usual one-chart, one-symbol framing sits awkwardly around a method whose minimum unit is a pair.

The source is "Un sistema real de alta frecuencia rentable" from Hispatrading Magazine, a Spanish-language publication aimed at quantitative and systematic traders rather than a retail chart-reading audience. The load-bearing word in that title is *real*: the pitch is not that statistical arbitrage works in principle — that has been academic common ground for decades — but that a live, running implementation exists, which is precisely the claim a viewer cannot verify from the outside. The high-frequency classification is not decoration either. Spread divergences in a well-behaved pair are small by construction, so the return comes from repetition, which pushes commissions, spreads and slippage from a rounding error into the middle of the edge itself.

What this page cannot reconstruct is the part that decides everything: which instruments form the pair, how the relationship is measured and re-estimated, and what divergence counts as wide enough to act on. No rule set was extracted from this video and no chapter markers were recorded, so those choices stay with the source. Worth carrying into any version of this idea: a pair relationship is a statistical claim with an expiry date, sensitive to crowding and to the regime that produced it, so a profitability statement about such a system is always stamped to a period rather than a permanent property.

Topics

statistical arbitrage · pairs trading · arbitrage strategy · high-frequency trading · z-score trading · cointegration strategy · cryptocurrency arbitrage · crypto trading strategy · trading strategy · pine script · tradingview strategy · algorithmic trading

Frequently asked questions

What is statistical arbitrage or pairs trading?

It is a relative-value approach: two instruments with a historical statistical relationship are traded against each other — long one, short the other — so the position profits from their spread converging rather than from the market moving in a particular direction.

Why are no indicators listed for this strategy?

Because the signal is not a chart overlay. Pairs trading derives its input from a synthetic series built out of two price streams — the spread and how far it has drifted from its usual behaviour — so there is nothing standard to plot on a single instrument's chart.

Why is this classified as a high-frequency strategy?

In statistical arbitrage the individual divergences are usually small, so results depend on capturing many of them. That makes trade frequency structural rather than stylistic, and it puts execution costs — commissions, spreads, slippage — inside the edge rather than alongside it.

What does this entry cover, and what does it not?

It covers the concept and the framing of a Spanish-language video from Hispatrading Magazine on a live high-frequency system. No rule set was extracted from this source, so pair selection, the divergence measure and the entry and exit thresholds are not available here — Strategy Decoder only publishes the structure it can actually extract from a video, and does not fill the gaps by inference.

About this strategy page

This trading strategy was decoded by Strategy Decoder's AI from a public YouTube trading video and turned into a structured, reviewable specification. In the interactive app this page shows the full entry and exit logic, risk management settings, the indicators involved with their parameters, AlgoWizard-compatible logic and a Pine Script export ready for TradingView backtesting — plus an automated backtest verdict when one has been computed for this strategy.

Strategy Decoder catalogs 2,229 decoded strategies. Each one is extracted with confidence scoring, cross-linked to the indicators it uses, and kept up to date as new videos are processed daily. Load this page with JavaScript enabled to use the interactive tools, or start from the strategy explorer to filter by methodology, market and timeframe.

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