Pair Trading Qant Maney

What it does:

Scans a fixed list of assets (24-hour US stock pairs from the Pepperstone brokerage) on the chosen timeframe.

For each pair and for various periods (Period1…Period100 ABOVE) it:

Calculates a regression model between the two assets (and, if desired, using the US500 index as a normalizer).

Generates the residual (spread) of this relationship, its mean, standard deviation, correlation, and betas (B1 and B2).

Applies an ADF test to the residual (cointegration/stationarity).

Calculates the Z-score of the current residual (how many standard deviations it is away from the mean).

Only pairs that meet the filters are included in the table.

Attach the indicator to the chart, adjust inputs (periods, Z-score limit, ADF, normalizer usage, etc.). Click on “START SCANNER”: it performs all tests and populates the table with the pairs that gave a signal. Click on a line in the table: The indicator shows the pair details (Z-Score, ADF, betas, correlation, average, lot ratio). It draws the residual chart (candle or line mode) with average and 2σ and 3σ bands, allowing you to adjust the period and window shift. It calculates an A/B lot ratio (with a vol-neutral option, adjusting for asset deviations). Typical operational rules (suggested by the indicator): When the Z-Score is high positive (above the limit): the pair is “stretched”; the idea is to sell the expensive asset and buy the cheap one, in the proportion indicated in the panel. When the Z-score is very negative: the pair is "cheap"; you reverse the positions (buy the one below the average and sell the one above). You can save the selected pair in the SAVED panel to create a watchlist of recurring opportunities.


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Ben Mati Mulatya
The Hybrid Metaheuristic Algorithm (HMA) is a cutting-edge optimization approach that combines the strengths of genetic algorithms with the best features of population-based algorithms. Its high-speed computation ensures unparalleled accuracy and efficient search capabilities, significantly reducing the total time required for optimization while identifying optimal solutions in fewer iterations. HMA outperforms all known population optimization algorithms in both speed and accuracy. Use Cases AO
***** Ana ticaret XAUUSD'dir. Teste yaparsa, XAUUSD'e ayarlanma tavsiye ediliyor. Diğer ticaret hedefleri faydallığını garanti edemez****** Teste ihtiyacınız olursa, lütfen bir mesaj bırakın (gördüğüm anda cevap vereceğim). Çalışma sonuçlarını korumak için belirli parametreler girmeli. Sistemin öntanımlı parametreleri ekran fotoğrafında gösterilen etkileri ulaşamaz! Teste ihtiyacınız olursa, lütfen bir mesaj bırakın (gördüğüm anda cevap vereceğim). Çalışma sonuçlarını korumak için belirli par
Bu ürün 3 yıldır geliştirilmektedir. MQL5 programlama dilinde her türlü Yapay Zeka ve makine öğrenimi kodlarıyla çalışmak için en gelişmiş kod tabanıdır. MetaTrader 5'te birçok yapay zeka destekli ticaret robotu ve gösterge oluşturmak için kullanılmıştır. Bu, MQL5 için makine öğrenimi üzerine ücretsiz ve açık kaynaklı bir projenin premium sürümüdür. Bağlantı burada:  https://github.com/MegaJoctan/MALE5 . Ücretsiz sürüm daha az özelliğe sahiptir, belgelenmemiştir ve düzenli olarak bakım görmez. S
Shawrie
Kevin Kipkoech
This Pine Script implements a Gaussian Channel + Stochastic RSI Strategy for TradingView . It calculates a Gaussian Weighted Moving Average (GWMA) and its standard deviation to form an upper and lower channel. A Stochastic RSI is also computed to determine momentum. A long position is entered when the price closes above the upper Gaussian band and the Stoch RSI K-line crosses above D-line . The position is exited when the price falls back below the upper band. The script includes commission, cap
Yazarın diğer ürünleri
Scan a fixed list of assets (Ibovespa) in the chosen timeframe (TimeFrame). For each pair and for various periods. Calculate a regression model between the two assets (and, if desired, using the bova11 index as a normalizer). Generate the spread of this relationship, its mean, standard deviation, speculative deviation, and betas (B1 and B2). Apply an ADF test without exclusion (cointegration/stationarity). Calculate the Z-score of the current exclusion (how many standard deviations are away from
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