Jan

27

2019

Python Algo Trading Market Neutral Hedge Fund Strategy

smack 27 Jan 2019 13:13 LEARNING » e-learning - Tutorial

Python Algo Trading Market Neutral Hedge Fund Strategy
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 06:50 Hours | Lec: 43 | 1.08 GB | Language: English | Sub: English [Auto-generated]



Hands on Python guide to developing your own market neutral long short hedge fund strategy with sentiment analysis.



What you'll learn
Build a market neutral long short strategy from scratch
Incorporate sentiment analysis as a factor in their strategy
Learn to critically review any trading strategies
Learn and apply Quant Equity work flow in to their strategy development process

Requirements
Students will need intermediate Python knowledge
Some basic understanding of finance would be helpful

Description
Update 23 Aug 2017: Do note that Quantopian platform will no longer support third party broker integration. Please see their website under forum. The title of the post is "Phasing Out Brokerage Integrations".

This course provides you with the tools that top hedge funds used. These institutional tools include but are not limited to market data, fundamental data, sentiment analysis data, and more. All FREE. Yes, you read that right. FREE. Did I say Python codes are provided as well?

In this course, you will learn to design, develop, and test long short hedge funds strategy incorporating sentiment analysis, one of the hottest research area in finance, in a systematic and scientific manner. You will be able to assess your strategy and evaluate the strength and weaknesses, improve and finally at your own wish go-live.

You will get a detailed tour of the investment process of the quantitative investment world, one used by Professional Quant on a daily basis. The course will cover all the key areas such as sourcing data and making data-driven investment, defining trading universe suitable for your trading strategy, search and discovery of the elusive alpha, combining multiple alpha, follow by portfolio construction, and trading.

The hedge fund market has seen massive adoption of data-drive, quantitative approach. In an article published in Wired Technology in Apr 2017, it states:

"There was $38 billion of institutional investment into algorithmically driven hedge funds in the first quarter of 2016 alone. In October 2016, one of the biggest players, Renaissance Technologies, which has $60 billion under management, announced that it received $7 billion in investment the previous year."

"The time will come when no human investment manager will be able to beat the computer," David Siegel, the co-founder of quantitative fund Two Sigma, which manages $35 billion, told an investment conference in 2015.

The time to take action is now. Look forward to seeing you inside!

This course is for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation for any security; nor does it constitute an offer to provide investment advisory. Nothing contained herein constitutes investment advice or offers any opinion with respect to the suitability of any security, and any views expressed herein should not be taken as advice to buy, sell, or hold any security or as an endorsement of any security or company. Any views expressed and data illustrated herein were prepared based upon information, believed to be reliable, available at the time of publication. No guarantees have been made as to their accuracy or completeness. All information is subject to change and may quickly become unreliable for various reasons, including changes in market conditions or economic circumstances.

Who this course is for?
Anyone who is interested in developing algorithmic and systematic trading
Anyone who is interested in extracting alpha in one of the hottest area in finance
Those who are looking to break into the Hedge Fund industry
Those who are interested to apply big data and data science in finance
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Python Algo Trading Market Neutral Hedge Fund Strategy




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