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While the whole world is talking about machines taking over the financial markets, QuantInsti is busy prepping the next generation of algorithmic and quantitative traders to meet the challenges of coming decades
Mumbai (Maharashtra): While the whole world is talking about machines taking over the financial markets, QuantInsti is busy prepping the next generation of algorithmic and quantitative traders to meet the challenges of coming decades.
How to make sense of statistics, econometrics, financial computing and trading strategies by using advanced techniques of deep learning and artificial intelligence? Quantra has a solution.
A student report of Stanford University based on the application of deep learning to algorithmic trading displayed 81 percent successful trade and a 66 percent of directional accuracy on the application of deep learning based trading strategy on a test data set. The report said, 'Deep Learning models with multiple layers have been shown as a promising architecture that can be suitable for predicting financial time series data.'
Anthony Antenucci, VP of global business development at Intelenet Global Services, said, "It wasn't long before statisticians at Wall Street got in the game and realised that applying machine learning programs (AI models) to investment trading applications, they could effectively crunch millions upon millions of data points in real time and capture information that current statistical models couldn't."
Quantra by QuantInsti is believed to be one of the most advanced self-paced learning interactive platforms when it comes to algorithmic and quantitative trading. Started in early 2017, Quantra has been the go-to learning platform for algorithmic and quantitative trading enthusiasts across 130 countries.
Currently, the platform hosts 16 specialised courses with some of them authored by well know industry practitioners including the likes of Dr. E. P. Chan. Quantra recently launched two new courses 'Neural Networks for Trading' and 'Decision Trees for Trading' which aim to empower traders with the advanced trading techniques.
The self-paced learning programmes are the new avenue being explored by a lot of aspiring algorithmic traders which offers open and paid learning material with a practical approach. A great opportunity for aspiring traders to get hands-on learning experience.
"A very interesting and exciting platform. I had a lot of fun following the concepts presented and the Python coding for the same. I am glad I found Quantra that has so many interesting courses in the area of Algorithmic Trading," said Dan Comescu, Director of Firmware Engineering, Econis-Labs LLC, USA.
The innovative learning approach, interactive exercises, and credible certifications make it easy to efficiently accelerate the learning curve. Quantra has also partnered with some of the leading financial institutes to create more awareness in this domain.
"E-learning programmes have been well received by students around the world considering the convenience to practice and value that is derived from them. With the growing potential of automation in financial markets, there is a high demand for skilled resources, we want to create an e-learning hub that will groom professionals to keep up with technology and enhance their skills. Quantra is the foundation of one such initiative in the form of a knowledge-based marketplace which caters to aspiring quantitative and algorithmic traders across the world," said Nitesh Khandelwal, Director and Co-founder, QuantInsti.
Traditional traders are now turning their path to the algorithmic way. Platforms like Quantra are making sure that the masses are educated about the changing landscape in the algorithmic trading world by means of their learning programmes, it makes easier for people to acquire the required skill set.
There are ample of case studies from Quantra that prove professionals are no longer afraid of changing their field anymore, people with no finance, technology or programming related background are trying their hands on algorithmic trading.
In the quest to seek the elusive alpha, techniques related to machine learning, data analytics, decision tree, sentiment analysis and neural networks are being used to model trading strategies. A new financial world is being built on these concepts.
The algorithmic and quantitative trading domain now offers some of the most appealing career opportunities. No wonder that most of the trading across the trading destinations globally have been moving towards automation.

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