@tacoboutruru: I would’ve stayed home….

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Thursday 17 September 2026 19:01:54 GMT

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Dude_in _A_hyundai :

Me i” if you Excuse me” 🚶

2026-09-18 03:14:01

1

itsjustchristina04 :

Your facial expressions always crack me up!!

2026-09-17 23:59:09

1

Angelsstyle :

Sorry

2026-09-18 01:50:40

1

jess66280 :

2026-09-17 21:44:57

2

Christian Antonio :

Same 🤣

2026-09-17 19:14:43

1

Silverio C Hernández :

2026-09-18 10:14:39

0

jokrs_kid :

2026-09-17 20:37:56

1

theoglostin88 :

sorry

2026-09-18 01:50:00

1

Justine Marie :

2026-09-17 21:54:31

1

Honestly 🫠 :

2026-09-17 19:27:06

1

Marissafloress :

2026-09-17 19:22:50

1

LISAMARIE ❤️ :

😂😂😂

2026-09-17 19:41:54

1

mrNYCin210 :

😂😂😂

2026-09-17 19:04:53

1

Eloy Rodriguez :

❤️❤️❤️

2026-09-18 06:04:09

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🥣 Uma receitinha leve e deliciosa para quem está buscando opções para incluir na rotina de emagrecimento! 😋💚 ⚠️ Créditos e conteúdo: @nutrizangada 📌 O e-book mencionado no vídeo é da Nutri Zangada. Gostou da receita? Salva para fazer depois! ❤️ #emagrecimento #receitasaudavel #receitafit #reeducacaoalimentar #dieta

🥣 Uma receitinha leve e deliciosa para quem está buscando opções para incluir na rotina de emagrecimento! 😋💚 ⚠️ Créditos e conteúdo: @nutrizangada 📌 O e-book mencionado no vídeo é da Nutri Zangada. Gostou da receita? Salva para fazer depois! ❤️ #emagrecimento #receitasaudavel #receitafit #reeducacaoalimentar #dieta

How do you pick your indicators? Let's build a formula. Every systematic strategy is a function of the past path. Rough path theory gives that path a canonical description, its signature: the sequence of iterated integrals, where level one is the increment, level two the areas swept, against time the shape of the trend and between two assets the lead-lag, and higher levels finer shape shrinking like 1/n!. Hambly and Lyons (2010, Annals of Mathematics) proved the signature determines the path, and a universal approximation theorem says any continuous function of the path is, to any precision, a linear combination of signature terms. So every indicator, moving-average crossovers, RSI, Bollinger bands, even the Kalman filter, can be approximated arbitrarily well by a linear combination of signature terms. Futter, Horvath and Wiese (Quantitative Finance, 2025) make this a portfolio method. Regressing a MACD momentum strategy with a sigmoid, on the TLT ETF, onto the signature recovers it with R² of 66% at order 1, 89% at order 3 and 98% at order 11. Because the strategy is linear in the signature, the mean-variance optimum is closed-form: the weight vector is proportional to the inverse covariance of the terms' profit attributions times those attributions, both read off the expected lead-lag signature, with no neural network and no gradient descent. At order zero it is exactly Markowitz; each order adds path dependence and, because the criterion is over a horizon, a built-in drawdown control. For two assets, one signal and time at order two, that is 21 terms. The limits, from the paper: the expected signature is noisy to estimate and robustness is left to future work; the covariance needs signature terms of order six for an order-two strategy; market impact is not modelled; the real-data evidence is a three-ETF frontier and one momentum replication. Libraries: signatory, esig, iisignature. Futter, O., Horvath, B. & Wiese, M. (2025). Signature Trading: A Path-Dependent Extension of the Mean-Variance Framework with Exogenous Signals. Quantitative Finance, 25(2). arXiv 2308.15135. #finance #quant #machinelearning #roughpaths #algotrading

How do you pick your indicators? Let's build a formula. Every systematic strategy is a function of the past path. Rough path theory gives that path a canonical description, its signature: the sequence of iterated integrals, where level one is the increment, level two the areas swept, against time the shape of the trend and between two assets the lead-lag, and higher levels finer shape shrinking like 1/n!. Hambly and Lyons (2010, Annals of Mathematics) proved the signature determines the path, and a universal approximation theorem says any continuous function of the path is, to any precision, a linear combination of signature terms. So every indicator, moving-average crossovers, RSI, Bollinger bands, even the Kalman filter, can be approximated arbitrarily well by a linear combination of signature terms. Futter, Horvath and Wiese (Quantitative Finance, 2025) make this a portfolio method. Regressing a MACD momentum strategy with a sigmoid, on the TLT ETF, onto the signature recovers it with R² of 66% at order 1, 89% at order 3 and 98% at order 11. Because the strategy is linear in the signature, the mean-variance optimum is closed-form: the weight vector is proportional to the inverse covariance of the terms' profit attributions times those attributions, both read off the expected lead-lag signature, with no neural network and no gradient descent. At order zero it is exactly Markowitz; each order adds path dependence and, because the criterion is over a horizon, a built-in drawdown control. For two assets, one signal and time at order two, that is 21 terms. The limits, from the paper: the expected signature is noisy to estimate and robustness is left to future work; the covariance needs signature terms of order six for an order-two strategy; market impact is not modelled; the real-data evidence is a three-ETF frontier and one momentum replication. Libraries: signatory, esig, iisignature. Futter, O., Horvath, B. & Wiese, M. (2025). Signature Trading: A Path-Dependent Extension of the Mean-Variance Framework with Exogenous Signals. Quantitative Finance, 25(2). arXiv 2308.15135. #finance #quant #machinelearning #roughpaths #algotrading

مأذيت احد #ترند #اكسبلورر #tiktok #هواجيس #قصيد

مأذيت احد #ترند #اكسبلورر #tiktok #هواجيس #قصيد

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