Mizuho Americas, a subsidiary business of the Japan-based Mizuho Financial Group, Inc, has announced today that it has selected Quantifi, a fintech provider of risk, analytics and trading solutions, to support its expanding equity derivatives platform.
Mizuho stated that it was looking for an independent pricing and structuring solution to supplement risk measurement on its price structured equity notes and derivative positions.
Quantifi will complement Mizuho America’s existing internal process, providing additional pricing models to validate its internal models.
Mizuho said that it selected Quantifi due to the depth of its equity analytics and flexibility of its technology. Additionally, Mizuho stated that it chose the fintech
Fintech
Financial Technology (fintech) is defined as ay technology that is geared towards automating and enhancing the delivery and application of financial services. The origin of the term fintechs can be traced back to the 1990s where it was primarily used as a back-end system technology for renowned financial institutions. However, it has since grown outside the business sector with an increased focus upon consumer services.What Purpose Do Fintechs Serve?The main purpose of fintechs would be to supply a technological service that not only simplifies but also aids consumers, business operators, and networks.This is done by optimizing business processes and financial operations through the implementation of specialized software, algorithms, and automated computing processes. Transitioning from the roots of the financial sector, fintech providers can be found through a multitude of industries such as retail banking, education, cryptocurrencies, insurance, nonprofit, and more. While fintechs cover a vast array of business sectors, it can be broken down into four classifications which are as followed: Business-to-business for banks, Business-to-business for banking business clients, business-to-consumers for small businesses, and consumers. More recently, fintechs presence has become increasingly apparent within the trading sector, primarily for cryptocurrencies and blockchain technology.The creation and use of Bitcoin can also be contributed to innovations brought upon by fintechs while smart contracts through blockchain technology have simplified and automated contracts between buyers and sellers. As a whole, fintechs applications are growing more diverse with a consumer-centric focus while its applications continue to innovate the trading and cryptocurrency sectors through automated technologies and business practices.
Financial Technology (fintech) is defined as ay technology that is geared towards automating and enhancing the delivery and application of financial services. The origin of the term fintechs can be traced back to the 1990s where it was primarily used as a back-end system technology for renowned financial institutions. However, it has since grown outside the business sector with an increased focus upon consumer services.What Purpose Do Fintechs Serve?The main purpose of fintechs would be to supply a technological service that not only simplifies but also aids consumers, business operators, and networks.This is done by optimizing business processes and financial operations through the implementation of specialized software, algorithms, and automated computing processes. Transitioning from the roots of the financial sector, fintech providers can be found through a multitude of industries such as retail banking, education, cryptocurrencies, insurance, nonprofit, and more. While fintechs cover a vast array of business sectors, it can be broken down into four classifications which are as followed: Business-to-business for banks, Business-to-business for banking business clients, business-to-consumers for small businesses, and consumers. More recently, fintechs presence has become increasingly apparent within the trading sector, primarily for cryptocurrencies and blockchain technology.The creation and use of Bitcoin can also be contributed to innovations brought upon by fintechs while smart contracts through blockchain technology have simplified and automated contracts between buyers and sellers. As a whole, fintechs applications are growing more diverse with a consumer-centric focus while its applications continue to innovate the trading and cryptocurrency sectors through automated technologies and business practices.
Read this Term company because of its responsive service and extensive model library to help supplement its proprietary, in-house technology.
With Quantifi, Mizuho Americas will enhance its access to accurate and fast pricing and analytics
Analytics
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Read this Term and seamlessly integrate them with its other internal processes. By selecting Quantifi, Mizuho Americas has saved on development time and resources and now can focus on its core business.
Rohan Douglas, the CEO of Quantifi, stated: “We are delighted to be providing Mizuho Americas, one of the premier investment banks, with technology and support for its equity derivatives business. We look forward to partnering with Mizuho Americas to help it expand its equity offering.”
Enhancing Asset and Wealth Management Accessibility
The deal underscores Mizuho Americas’ commitment to enhance its investment bank offering and develop a suite of solutions for customers in the alternative investment market.
In December last year, Mizuho made a strategic investment in M-Service, a leading player in Vietnam’s digital payment sector. Mizuho acquired about 7.5% shares of M-Service to help the firm in its growth.
Last month, Mizuho Americas signed an agreement to acquire Dallas-based Capstone Partners, a leading middle-market placement agent focused on advisory and fundraising services to private equity, credit, real assets and infrastructure investment companies. With the merger, Mizuho wants to reinforce its capital raising and distribution capabilities through Capstone’s global network of over 1,500 Limited Partners across Asia, Europe and the US with expanded opportunities for cross-selling complementary investment banking solutions.
In October last year, Mizuho hired three senior bankers to enable expansion of its Americas platform across banking, equities, fixed income and futures in support of its customers.
Mizuho Americas, a subsidiary business of the Japan-based Mizuho Financial Group, Inc, has announced today that it has selected Quantifi, a fintech provider of risk, analytics and trading solutions, to support its expanding equity derivatives platform.
Mizuho stated that it was looking for an independent pricing and structuring solution to supplement risk measurement on its price structured equity notes and derivative positions.
Quantifi will complement Mizuho America’s existing internal process, providing additional pricing models to validate its internal models.
Mizuho said that it selected Quantifi due to the depth of its equity analytics and flexibility of its technology. Additionally, Mizuho stated that it chose the fintech
Fintech
Financial Technology (fintech) is defined as ay technology that is geared towards automating and enhancing the delivery and application of financial services. The origin of the term fintechs can be traced back to the 1990s where it was primarily used as a back-end system technology for renowned financial institutions. However, it has since grown outside the business sector with an increased focus upon consumer services.What Purpose Do Fintechs Serve?The main purpose of fintechs would be to supply a technological service that not only simplifies but also aids consumers, business operators, and networks.This is done by optimizing business processes and financial operations through the implementation of specialized software, algorithms, and automated computing processes. Transitioning from the roots of the financial sector, fintech providers can be found through a multitude of industries such as retail banking, education, cryptocurrencies, insurance, nonprofit, and more. While fintechs cover a vast array of business sectors, it can be broken down into four classifications which are as followed: Business-to-business for banks, Business-to-business for banking business clients, business-to-consumers for small businesses, and consumers. More recently, fintechs presence has become increasingly apparent within the trading sector, primarily for cryptocurrencies and blockchain technology.The creation and use of Bitcoin can also be contributed to innovations brought upon by fintechs while smart contracts through blockchain technology have simplified and automated contracts between buyers and sellers. As a whole, fintechs applications are growing more diverse with a consumer-centric focus while its applications continue to innovate the trading and cryptocurrency sectors through automated technologies and business practices.
Financial Technology (fintech) is defined as ay technology that is geared towards automating and enhancing the delivery and application of financial services. The origin of the term fintechs can be traced back to the 1990s where it was primarily used as a back-end system technology for renowned financial institutions. However, it has since grown outside the business sector with an increased focus upon consumer services.What Purpose Do Fintechs Serve?The main purpose of fintechs would be to supply a technological service that not only simplifies but also aids consumers, business operators, and networks.This is done by optimizing business processes and financial operations through the implementation of specialized software, algorithms, and automated computing processes. Transitioning from the roots of the financial sector, fintech providers can be found through a multitude of industries such as retail banking, education, cryptocurrencies, insurance, nonprofit, and more. While fintechs cover a vast array of business sectors, it can be broken down into four classifications which are as followed: Business-to-business for banks, Business-to-business for banking business clients, business-to-consumers for small businesses, and consumers. More recently, fintechs presence has become increasingly apparent within the trading sector, primarily for cryptocurrencies and blockchain technology.The creation and use of Bitcoin can also be contributed to innovations brought upon by fintechs while smart contracts through blockchain technology have simplified and automated contracts between buyers and sellers. As a whole, fintechs applications are growing more diverse with a consumer-centric focus while its applications continue to innovate the trading and cryptocurrency sectors through automated technologies and business practices.
Read this Term company because of its responsive service and extensive model library to help supplement its proprietary, in-house technology.
With Quantifi, Mizuho Americas will enhance its access to accurate and fast pricing and analytics
Analytics
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Read this Term and seamlessly integrate them with its other internal processes. By selecting Quantifi, Mizuho Americas has saved on development time and resources and now can focus on its core business.
Rohan Douglas, the CEO of Quantifi, stated: “We are delighted to be providing Mizuho Americas, one of the premier investment banks, with technology and support for its equity derivatives business. We look forward to partnering with Mizuho Americas to help it expand its equity offering.”
Enhancing Asset and Wealth Management Accessibility
The deal underscores Mizuho Americas’ commitment to enhance its investment bank offering and develop a suite of solutions for customers in the alternative investment market.
In December last year, Mizuho made a strategic investment in M-Service, a leading player in Vietnam’s digital payment sector. Mizuho acquired about 7.5% shares of M-Service to help the firm in its growth.
Last month, Mizuho Americas signed an agreement to acquire Dallas-based Capstone Partners, a leading middle-market placement agent focused on advisory and fundraising services to private equity, credit, real assets and infrastructure investment companies. With the merger, Mizuho wants to reinforce its capital raising and distribution capabilities through Capstone’s global network of over 1,500 Limited Partners across Asia, Europe and the US with expanded opportunities for cross-selling complementary investment banking solutions.
In October last year, Mizuho hired three senior bankers to enable expansion of its Americas platform across banking, equities, fixed income and futures in support of its customers.
Source: https://www.financemagnates.com/fintech/mizuho-americas-taps-quantifi-to-support-its-growing-equity-derivatives-platform/