Quantitative Trading

Quantitative trading utilizes trading strategies based on quantitative analysis to systematically identify trading opportunities and to execute trades as identified. A Quant trader may work for the buy side or sell side of the trading industry. Buy side quants are looking to trade for investment purposes. These trades typically seek to make a profit from either short-term price movements (alpha) or from longer-term investment returns (beta.) Sell side quants provide quantitative trading in their brokerage activities. The sell side algos are typically accumulation type strategies (i.e. volume weighted average pricing – VWAP) that help investors get the best price for their overall order.

Quantitative trading techniques include high-frequency trading, sentiment analysis trading, and statistical arbitrage.

Quantitative trading is not synonymous with High-Frequency Trading (HFT) even though all HFT firms employ some form of algorithmic trading.

CloudQuant utilizes crowd researchers to provide the quantitative analysis that is then used by our quantitive traders.


Quantamental alternative data

The Rise of Quants in Trading and Financial Markets

Cloud computing and access to industrial grade investment and data science tools are changing the playing field for quantitative trading firms. CloudQuant's CEO Morgan Slade participated in a panel at Stocktoberfest West in October 2017. This has raised the discussion of quantamental investment and data science techniques. This is the merger of technology, investment management, and data science.
Bullish Turn of Events for Sprint - S by Theodore Kekstadt

Bullish Turn Of Events For - $S: TA-LIB Three Outside Strategy

This stock has been on a negative slide for months, and every bounce has been one to sell into. The outlook is different for this current turn in direction. A “Three Outside Up” Japanese Candlestick reversal pattern... Source code for signal links included.
Improved Breakout Strategy

Industry News: Machine Learning and Artificial Intelligence News November 13, 2017

AI & ML news covering: the creative process, improving skills, ETFs, Risk, Supervised Learning, RiskGenius, Robo Cops, Fears, NVidia, Quickbooks, SEC Edgar ...
John "Morgan" Slade

Open Source Meets Quant Trading - Futures Industry Association

Recording of October 17-19, 2017 Future Industry Associations EXPO panel discussion on Open Source Meets Quant Trading.
Trading Strategy Scorecard from CloudQuant

52 Traders Interviews Morgan Slade

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The podcast on Massive 30,000 Trades Daily, High-Frequency Quant Trading with Morgan Slade including an interesting breakout trading strategy.
Trend Analysis in a Candlestick Market Data Chart

ZigZag Strategy Suggestion from Quora

A suggested a Zig-Zag trading strategy that bounces back and forth on the stock market to make small profits. Testing shows the strategy wouldn't work.
World Market Access

Futures Radio Show from FIA Expo 2017

An interview by Anthony Crudele of Futures Radio Show discussing the success of the Trading Strategy Incubator, crowd researching, and algorithmic trading.
Crowdsourcing Algorithmic Research

CloudQuant at FIA Expo in Chicago: perfect storm for open source revolution in quant trading

The impact of machine learning and open source resources on quant trading could be described as explosive. At FIA Expo in Chicago, CloudQuant’s CEO Morgan Slade will be discussing how that’s translating into opportunity for a wider variety of participants.

Backtest Visualization on CloudQuant

The Quantitative Strategy Backtest ScoreCard is saving time for crowd researchers who are able to visualize the results of multi-day backtests quickly, even as the backtest is running.
chicago cityscape and sears tower

Built in Chicago: Wanna try your hand at high-frequency trading? There's an app for that

Built in Chicago discusses CloudQuant, a Chicago-based algorithmic trading startup, lets anyone try their hand at devising their own strategies.