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Trading View - Option Chain Experimental Indicator that shows CE/PE Ltp, Volume, Traded Value (Ltp x Volume) for the chart timeframe Once OI data is available on Trading View , OI data will be added as well. Link [ Animation - Traded Value per min.

I Luv Markets

8,984 subscribers

46,583 Aufrufe • vor 2 Jahren •via X (Twitter)

Finanzen Wissenschaft & Technologie Bildung

Anya Rossi• Live Now

Private livecam show

11 Kommentare

Profilbild von Keshav Arora

Keshav Aroravor 2 Jahren

Ek hi Dil hai Kitni baar jeetoge sir 🙏

Profilbild von blackswan

blackswanvor 2 Jahren

Oh wow this looks cool 👌

Profilbild von Aniket jain

Aniket jainvor 2 Jahren

What are benefit of it 🤔

Profilbild von AKM

AKMvor 2 Jahren

Great work 👍

Profilbild von TradingAlgo

TradingAlgovor 2 Jahren

This looks 🔥

Profilbild von Arghya Ray

Arghya Rayvor 2 Jahren

Excellent

Profilbild von Mr. आत्मनिर्भर बेरोजगार

Mr. आत्मनिर्भर बेरोजगारvor 2 Jahren

Very nice

Profilbild von Aman Jain🫰🏻

Aman Jain🫰🏻vor 2 Jahren

Kya baate hai Sir. Ek number

Profilbild von Shivam Pardeshi

Shivam Pardeshivor 2 Jahren

Damn 🙌🏻

Profilbild von Rajesh.D

Rajesh.Dvor 2 Jahren

It's only for bank nifty??

Profilbild von I Luv Markets

I Luv Marketsvor 2 Jahren

Go to Inputs and adjust the Ref Strike and Expiry Date

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Initial balance: 51 USD 💸 Total Traded Volume: 25600 USD 🏦 Trading time: 3:21 hours ⏰ PNL: not important for this demonstration but you can see it in the video. What's interesting is that I paid 5.12 USD in fees in 3 hours, if I have 5 fees or rebates will be all profit 🤖

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President Trump's investment accounts made 3,642 transactions between Jan. 6 and March 30, a pace of about 63 per trading day, according to a financial disclosure form filed in May,. The president traded between $212 million and $695 million in stocks and other securities over the first three months of the year — an unprecedented sum for a sitting president – and the sheer volume of the trades, and the timing of certain transactions, has prompted accusations of insider trading and conflicts of interest from Democrats and ethics experts. CBS News extracted and analyzed the data to compile an interactive dashboard below, that is available in the linked article. Jo Ling Kent

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Olivia

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jhey ʕ•ᴥ•ʔ

251,813 Aufrufe • vor 2 Jahren

VIKINGS JERSEY GIVEAWAY on VikesNow! Never done a giveaway before, so let’s change that. If Jordan Addison is traded in a package that nets the #Vikings a 2nd Round Pick*, I will give away a jersey (the $130 one on NFL Shop) of the winner’s choice and have it shipped directly to them. I will honor this offer if he’s traded for a 2nd Round Pick in 2026 BEFORE the Draft (obviously), and if he is traded AFTER the draft for a 2027 2nd Rounder, I will honor that as well. The jersey will be given away a bit later in the offseason. If Addison is not traded, I’ll go ahead and give one away anyway, just a little bit later before the 2026 season begins. A few simple requirements: - Must be following BREVY BRIGHTLIGHTS - Must be subscribed to the VikesNow YouTube channel (link below) - Must retweet this post anytime between now and the release of the final 53-man roster. Winner will be chosen at random with proof at time of drawing. #SKOL #SweatBloodTears

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BREVY BRIGHTLIGHTS

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OKX Integrates Chainlink To Unlock $80 Trillion RWA Opportunity On X Layer OKX officially adopts Chainlink to anchor the Real-World Asset (RWA) infrastructure on its X Layer network. The integration provides the high-speed data feeds and cross-chain interoperability necessary to capture an estimated $80T in tokenized global markets. As a "Chainlink Scale" member, X Layer is now positioned as a primary destination for sovereign institutional-grade asset migration. The collaboration enables developers to build advanced decentralized applications that bridge legacy financial value with the "AI Agent Economy" on X Layer.

OKX Integrates Chainlink To Unlock $80 Trillion RWA Opportunity On X Layer OKX officially adopts Chainlink to anchor the Real-World Asset (RWA) infrastructure on its X Layer network. The integration provides the high-speed data feeds and cross-chain interoperability necessary to capture an estimated $80T in tokenized global markets. As a "Chainlink Scale" member, X Layer is now positioned as a primary destination for sovereign institutional-grade asset migration. The collaboration enables developers to build advanced decentralized applications that bridge legacy financial value with the "AI Agent Economy" on X Layer.

BSCN

16,358 Aufrufe • vor 28 Tagen

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Prints 👑

18,729 Aufrufe • vor 10 Monaten

“We’re shifting to production deployments.” Having worked with well over 40 institutions globally at Chainlink Labs, Niki Ariyasinghe shares his insights on the rapidly evolving landscape for tokenized assets: 1. Leading banks are preparing for the tokenization opportunity Following successful pilots on testnets, premier financial institutions are launching production deployments live on mainnet. This provides a blockchain-based foundation to support trillions of dollars worth of tokenized assets. 2. Real volume is already moving onto these platforms Broadridge’s blockchain-based repo platform already has “over $70B of transaction value that goes through that platform every day.” This level of transaction volume for RWAs will expand and replicate across an array of verticals. Unlocking the full capabilities of these tokenized assets requires a single platform that securely provides all data, compute, and cross-chain requirements: #Chainlink.

“We’re shifting to production deployments.” Having worked with well over 40 institutions globally at Chainlink Labs, Niki Ariyasinghe shares his insights on the rapidly evolving landscape for tokenized assets: 1. Leading banks are preparing for the tokenization opportunity Following successful pilots on testnets, premier financial institutions are launching production deployments live on mainnet. This provides a blockchain-based foundation to support trillions of dollars worth of tokenized assets. 2. Real volume is already moving onto these platforms Broadridge’s blockchain-based repo platform already has “over $70B of transaction value that goes through that platform every day.” This level of transaction volume for RWAs will expand and replicate across an array of verticals. Unlocking the full capabilities of these tokenized assets requires a single platform that securely provides all data, compute, and cross-chain requirements: #Chainlink.

Chainlink

197,084 Aufrufe • vor 2 Jahren

I recently came across this video of an analyst claiming a specific Situational Analysis pattern, with more than 90% accuracy. Instead of taking it at face value, I fed the video and years of historical Nifty data into Gemini AI. By the time my coffee was ready, the AI backtested 20+ years of data. ✅ Scenario 1 - If the high price on Friday is lower than the high price on Thursday. The low price reached on Friday will be revisited during the regular trading session on Monday. Accuracy of this condition is 57.2%. Not 90% as mentioned by the expert, but a statistically significant advantage you can actually build a strategy around. ❌ Scenario 2: If the high price on Wednesday is lower than the high price on Monday. The low price reached on Wednesday will be revisited on Thursday. A literal 50.8% accuracy only. We live in an era where you can validate any trading idea instantly.

I recently came across this video of an analyst claiming a specific Situational Analysis pattern, with more than 90% accuracy. Instead of taking it at face value, I fed the video and years of historical Nifty data into Gemini AI. By the time my coffee was ready, the AI backtested 20+ years of data. ✅ Scenario 1 - If the high price on Friday is lower than the high price on Thursday. The low price reached on Friday will be revisited during the regular trading session on Monday. Accuracy of this condition is 57.2%. Not 90% as mentioned by the expert, but a statistically significant advantage you can actually build a strategy around. ❌ Scenario 2: If the high price on Wednesday is lower than the high price on Monday. The low price reached on Wednesday will be revisited on Thursday. A literal 50.8% accuracy only. We live in an era where you can validate any trading idea instantly.

Kirubakaran Rajendran

32,780 Aufrufe • vor 5 Monaten

The 2008 financial crisis led to the creation of Bitcoin because toxic assets were created by a poorly managed financial system that left society with the costs. We have an opportunity to build a better financial system that is cryptographically guaranteed, transparent, and gives control of risk over to the parties that it affects most. Our work on Chainlink and CCIP seeks to accelerate the speed at which this world happens on-chain. From secure data delivery to decentralized compute and now cross-chain interoperability, Chainlink is protecting dApps and their end users to deliver the true value of smart contracts and DeFi: a fair, transparent and largely derisked global financial system. As CCIP becomes the most widely used connectivity standard, we will initially see two largely separate on-chain networks of value: one for institutional/bank chains and the existing public blockchain DeFi ecosystem. CCIP will eventually merge these two large ecosystems into a single on-chain financial system that secures the world’s value on the Internet of Contracts. Presentation: Slides:

The 2008 financial crisis led to the creation of Bitcoin because toxic assets were created by a poorly managed financial system that left society with the costs. We have an opportunity to build a better financial system that is cryptographically guaranteed, transparent, and gives control of risk over to the parties that it affects most. Our work on Chainlink and CCIP seeks to accelerate the speed at which this world happens on-chain. From secure data delivery to decentralized compute and now cross-chain interoperability, Chainlink is protecting dApps and their end users to deliver the true value of smart contracts and DeFi: a fair, transparent and largely derisked global financial system. As CCIP becomes the most widely used connectivity standard, we will initially see two largely separate on-chain networks of value: one for institutional/bank chains and the existing public blockchain DeFi ecosystem. CCIP will eventually merge these two large ecosystems into a single on-chain financial system that secures the world’s value on the Internet of Contracts. Presentation: Slides:

Sergey Nazarov

181,990 Aufrufe • vor 3 Jahren

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MIT defines an algorithm in one sentence that changes how you think about trading "a computational procedure that takes an input and produces an output through a well-defined sequence of steps" that's it. not AI. not machine learning. not a black box a set of rules that takes data in and spits a decision out every quant strategy ever built is just an algorithm Citadel's execution system that routes 40% of US equity volume is an algorithm Renaissance's Medallion Fund running millions of trades per year is an algorithm Jane Street's market making engine processing $26 trillion annually is an algorithm input: market data rules: mathematical conditions output: trade or no trade the difference between a quant desk and a retail trader is not the data it's that one side wrote down their rules precisely enough for a machine to execute them retail says "if RSI is low and the chart looks good, i'll probably buy" a quant desk says "if RSI 1.5, buy 0.3% of NAV" same logic. one is a feeling. the other is an algorithm the feeling can't be tested, can't be repeated, can't be measured the algorithm can be backtested across 10,000 trades and you know exactly when it works and when it doesn't > this lecture: MIT, free, 70 seconds > algorithmic trading volume: 60-75% of all US equity trades > Jane Street, Citadel, Two Sigma: every trade is algorithmically executed > tools to build your own: Python, free data, a laptop you don't need a faster computer or better data you need to write your strategy down precisely enough that a machine could run it without you that's the whole leap. from intuition to algorithm full breakdown in the video below

delost

23,905 Aufrufe • vor 25 Tagen

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

84,686 Aufrufe • vor 1 Jahr