Welcome back to the Algorithmic Trading Conference series. Part 2 of this series will cover a summary of the presentations given by Quantpedia, Vauban, and Quantinsti. Part 1 of the Algorithmic Trading Conference series can be found here. Also check out the video for Part 2 here.
About Quantpedia and Team
Quantpedia (founded 2011) is an independent research company that processes financial academic research into potential ideas for quantitative and algorithmic trading strategies. Radovan Vajtko, current CEO, started his tenure at Quantpedia in 2015 and along with his team, has grown the company into one of the most prominent quantitative research companies in the world. Prior to Quantpedia, Radovan managed around $300 Million for Tatra Asset Management company (AUM > $2 Billion), the biggest asset management company in Slovakia for several years.
Purpose of Academic Research
“The best course of action is to fundamentally understand anomalies which are described in academic research and then explore their functioning beyond the scope of the research paper” - Radovan Vajtko
Tens of thousands of research papers on quantitative finance and algorithmic trading are published every year and professionals like academia professors, PhDs, universities asset management companies and other financial institutions play a key role in the same to establish their credibility or attract more investors. Publishing these papers became a common tactic after the crisis in 2008, as it helped wealth management companies establish trust with potential customers by providing them transparency and an incentive to provide capital. Once a strategy is published, several entities try to implement similar strategies by deriving inspiration from it and this often decreases the profitability of the strategy.
Vauban, founded by Remy Astie and Ulric Musset, is a wealth container platform frequently known as an asset-holding legal entity. Vauban’s main purpose is to automate and digitise the structuring as well as the launching of various investment vehicles. From initial structuring to NAV calculation, the platform helps individuals set-up and deploy complex legal entities such as Funds and SPVs in hours with a few clicks.
Launching a fund
"Apart from a couple of million dollars and a good proven track record, a key factor in successfully launching a hedge fund is the handling of its operations and the formation of its legal infrastructure." - Remy Astie, Co-founder of Vauban
Due to the heavy regulation in the financial sector, the operations and administrative tasks while launching a new fund, take up the time equivalent of a full-time job. Ideally the team behind the fund should be focused on the fundraising and attracting investors rather than the operations of the business. A fund usually charges a certain amount of management fee to its investors but as investors increase, so do expenses such as accounting fees, back-office administration fees, and legal fees to set up domestic as well as international entities. This proportionally makes it difficult to grow the net returns of the fund and this is exactly where both founders of Vauban saw an opportunity for a venture.
Quantinsti is an online learning platform for algorithmic and quantitative trading. They provide programs and resources for algorithmic traders on all levels of expertise, including a program that helps intermediate traders adapt to a professional level of trading. Quantinsti additionally developed Blueshift, a platform that supports strategy research, backtesting, live trading and has built-in financial data.
How Blueshift helps Algo traders
“Now when I say any, that means any trading ideas you have, can be translated into a series of logical statements” - Prodipta Ghosh, Vice President of Quantinsti
Blueshift’s workspace contains existing trading strategy templates, backtesting data and tools for scheduling functions that can run at a specific time. The platform is user-friendly to beginner programmers as well as professionals who wish to work with TensorFlow, Visual Studio Code and other advanced tools. The platform also supports “Visual programming”, or “programming without code” for non-programmers or traders who want to build strategies without Python. It incorporates functions in the workspace that give the user the ability to define their own risk management techniques, developing alpha, and an automatic ability to shut down the strategy if it produces a certain amount of capital drawdown.
Thank you to those who participated in the conference, we hope you found it informative and valuable. Again we welcome any new Alpaca users and look forward to hosting more events in the future. To get involved more with the Alpaca community, please visit the Alpaca Forum and our Community Slack!
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