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#QuantInsti ALGO NEWSLETTER

May 2017 Edition

Multi-Strategy Portfolios: Combining Quantitative Strategies Effectively

 

Register for this one-of-a-kind webinar which will explain how to combine different quantitative strategies to create a multi-strategy portfolio. The webinar session outline includes how to quantitatively classify strategies, characteristics of strategy distribution types, multiple strategy examples, strategies as investable assets and portfolio optimization.

 

Can I Be A Quant In My 40s?

 

This month’s newsletter highlights the journey of a 40-year-old professional who decided to change the course of his career to pursue his passion for quantitative trading. Catch our conversation with QuantInsti’s alumnus, Mr. V Sankar Narayanan and get inspired!

Trading in the Flow with Ferenc Meszaros (Register here)

 

Join chief system developer and graduate finance lecturer Ferenc Meszaros, as he dives into semi-automated trading strategies based on the proven concepts of regression to the mean, noise filtering, and higher timeframe context. Join us May 30th.

Featured Alumnus

 
 

Batch No. 27

Mr. Ankit Handa has been successfully placed by QuantInsti’s placement cell with National Commodity and Derivatives Exchange Ltd. (NCDEX) as a Quantitative modeling and research (QMS) Associate in Mumbai. Ankit holds a MBA from Great Lakes Institute of Management and Bachelors in Engineering.

Featured Alumnus

 
 

Batch No. 32

 

Mr. Mohammed Shamim has been successfully placed by QuantInsti’s placement cell with PRB Securities as a Trading Strategist in Kolkata, India. Shamim holds a MSc. Global Business Management from ESC Rennes School of Business, France and a Bachelor of Management Studies.

Latest on QuantInsti's #AlgoBlog

 
Trading Strategy
 
 

The article explains the step-by-step backtesting of the “52-Weeks High Effect in Stocks” trading strategy using R programming. The strategy paper has been sourced from the Quantpedia site where you can explore other trading strategies as well.

 
Trading using Machine Learning in Python
 
 

How to trade using machine learning in python? This blog will explain machine learning that can help with new tool to generate more alpha with one such module. Learn how to create hyper-parameters, data splitting, making predictions and more!

This article covers some of the R programming best practices that can be implemented by programmers to improve code readability, consistency, and repeatability. The article was featured on R-bloggers in their “Most visited articles of the week” and also in the “Recent popular posts” list.