Quantitative Finance

Quantitative Finance or Mathematical Finance is applied mathematics with a strong focus on the financial markets. In Quant Finance, especially quant finance for trading firms, the quant seeks to use numerical models from market prices, company or asset fundamental data, and alternative data to develop new trading or investment models. The goal is to provide a new trading model.

CloudQuant provides quantitive financial enthusiast and professionals with free tools to develop new trading models. These crowd researchers develop the trading models and work with quantitative traders to execute the trading strategy. The quant is paid based on a license agreement where the trading strategy receives an allocation and they retain their own intellectual property (the algo.)

Posts

Algo Trading powered by Alternative Data Sets

Conversations: Effects of Alternative Data Sets on Trading Algorithms

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What effect can alternative data sets have on trading algorithms? We asked a few of our teammates and systematic traders what the effect of alternative data sets is on trading algos. We thought we could spread some insight as to why our alternative…
Quantamental alternative data

Conversations: Learning Python within CloudQuant

What was your experience like learning Python within CloudQuant? We asked our portfolio managers and product management teammates who code in Python to explain their starting experiences in programming with Python with CloudQuant. We wanted to share with everyone what encouraged them to keep learning throughout the years. Everyone here codes as part of their job. This includes the CEO all the way down to the interns. We rely on our Backtesting Engine to ensure that trading algorithms work well before committing money to the automated trading strategies. But we also use JupyterLab in our daily work. We generate our reports, monitor our systems, and do all sorts of tasks in Python. Python has overtaken the spreadsheet in CloudQuant.
John "Morgan" Slade

Quants discuss evaluating and adapting their models - Including CloudQuant

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In January, Morgan Slade participated in a Panel Discussion for Quantitative Fund Managers and how they are adapting their model.
New York

Meet The Niche Manager – Quantitative Managers. January 26, 2018

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CloudQuant will be participating in the Peltz International seminar Meet the Niche Manager on January 26, 2018 in New York.
www.futuresradioshow.com

Futures Radio Show interviews Morgan Slade December 12, 2017

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CloudQuant's CEO was interviewed by Anthony Crudele of Futures Radios show to discuss topic including Artificial Intelligence, Machine Learning, and Deep Learning applied to algorithmic trading. Alternative datasets are a major topic of discussion. People are saying that data is being created faster than ever before. That really isn't true. What is really happening is that data is being captured and stored at a faster rate than ever before. Vendors are now making AltData available for traders to change the way that they interact with the markets. This applies to futures and stocks with the popularity of Deep Learning in algorithmic trading strategy development.
RSI

Technical Analysis Library (TA-LIB) for Python Backtesting

Anyone who has ever worked on developing a trading strategy from scratch knows the huge amount of difficulty that is required to get your logic right. ... TA-LIB Turbo-Charges Your Research Loop: TA-Lib is widely used by quantitative researchers and software engineers developing automated trading systems and charts. This freely available tool allows you to gather information on over 200 stock market indicators.
Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence for December 11, 2017

AI & ML news covering Hedge Funds, Career, Fraud Detection, Vineyards/Winemaking, Quanthouse, Apple, Quantitative Brokers, and more
Morgan Slade, Python Data Scientist and Trader

QuantNews Interview with CEO Morgan Slade

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With over 20 years of experience as a trader, portfolio manager, executive, and entrepreneur, Morgan Slade is now the CEO of CloudQuant, a cloud based quantitative strategy incubator and systematic investment fund. He has built quantitative trading businesses at some of the world’s largest hedge funds and Investment Banks ...
Open, Close, High, Low

Share Ordering Demo using Market, Limit, and Midpoint Peg Orders

The CloudQuantAI github repository holds the share_ordering_demo tutorial/code that demonstrates ways to buy and sell stocks in the CloudQuant backtesting engine using Market, Limit, and Midpoint Peg Order types. There is no single "right way" to do any of these. You will have to think carefully about
Quantitative Strategies and Capital for Trading

Industry News: Machine Learning and Artificial Intelligence for November 27, 2017

AI & ML news covering: UBS, UK Workforce, Smart AI Chips, BlackRock, FINTECH Workflow management, CITIC, Aquila Capital, Investment Bankers, ...