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Portfolio Management: All The Ways AI Is Transforming Modern Asset Strategies

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Manage episode 414775534 series 3474148
Innhold levert av HackerNoon. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av HackerNoon eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/portfolio-management-all-the-ways-ai-is-transforming-modern-asset-strategies.
The industry was highly impacted by AI in recent years, as machine learning and artificial intelligence have made predictive analytics more accurate.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #artificial-intelligence, #asset-management, #fintech, #modern-asset-strategies, #portfolion-management, #ai-integration, #future-of-finance, #hackernoon-top-story, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.
This story was written by: @kustarev. Learn more about this writer by checking @kustarev's about page, and for more stories, please visit hackernoon.com.
The rise of AI has significantly impacted various industries, and the finance industry is among those most affected. In recent decades, AI has been implemented in different sectors of the finance industry. In the back office, ML algorithms are used to find anomalies in execution logs, detect suspicious transactions, and manage risks, leading to increased efficiency and security. In the front office, AI helps segment customers, automate customer support processes, and optimize derivatives pricing. However, the most intriguing aspect is AI's capabilities for the buy-side of finance — identifying predictive signals amid market noise by analyzing significant amounts of data as quickly as possible. Fields of application for AI include portfolio optimization, fundamental analysis, textual analysis, trading activities, investment advisory services, risk management, etc. Examples of implemented techniques and tools are machine learning algorithms, natural language processing, quantitative trading strategies, and explainable AI (XAI), among others.

  continue reading

170 episoder

Artwork
iconDel
 
Manage episode 414775534 series 3474148
Innhold levert av HackerNoon. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av HackerNoon eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/portfolio-management-all-the-ways-ai-is-transforming-modern-asset-strategies.
The industry was highly impacted by AI in recent years, as machine learning and artificial intelligence have made predictive analytics more accurate.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #artificial-intelligence, #asset-management, #fintech, #modern-asset-strategies, #portfolion-management, #ai-integration, #future-of-finance, #hackernoon-top-story, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.
This story was written by: @kustarev. Learn more about this writer by checking @kustarev's about page, and for more stories, please visit hackernoon.com.
The rise of AI has significantly impacted various industries, and the finance industry is among those most affected. In recent decades, AI has been implemented in different sectors of the finance industry. In the back office, ML algorithms are used to find anomalies in execution logs, detect suspicious transactions, and manage risks, leading to increased efficiency and security. In the front office, AI helps segment customers, automate customer support processes, and optimize derivatives pricing. However, the most intriguing aspect is AI's capabilities for the buy-side of finance — identifying predictive signals amid market noise by analyzing significant amounts of data as quickly as possible. Fields of application for AI include portfolio optimization, fundamental analysis, textual analysis, trading activities, investment advisory services, risk management, etc. Examples of implemented techniques and tools are machine learning algorithms, natural language processing, quantitative trading strategies, and explainable AI (XAI), among others.

  continue reading

170 episoder

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