Trading Strategy

A trading strategy is a plan (often implemented in an algorithm) that defines when a trader will place orders to enter and exit an investment. Trading strategies range from simple sets of rules that an individual follows all the way to highly complicated applied artificial intelligence computer systems.

Many successful trading strategies go beyond orders to buy and sell. They often include risk management, hedging, and money management.


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 …
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.
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.
Quantitative Strategy, Trading, and Algo Development Industry News

Quantitative Trading and Data Science in the News August 28, 2017

Quantitative Trading and Data Science in the News August 28 2017: CloudQuant opens door to crowd algo traders, RBC AI pilot, RBC pilots AI-based financial insight tools, AI focussed Chip, Momentum trading guide…

CloudQuant Launches with Unprecedented Risk Capital Allocation to Crowd Researcher

CloudQuant, the trading strategy incubator, has launched its crowd research platform by licensing and allocating risk capital to a trading algorithm. The algorithm licensor will receive a direct share of the strategy’s monthly net trading profits.
Daily ROIC Prior to improvements

Improving A Trading Strategy

TD Sequential is a technical indicator for stock trading developed by Thomas R. DeMark in the 1990s. It uses bar plot of stocks to generate trading signals. … Several elements could be modified in this strategy. Whether to include the countdown stage, the choice of the number of bars in the setup stage and countdown stage, the parameters that help to decide when to exit and the size of the trade will affect strategy performance. In addition, we could use information other than price to decide whether the signal should be traded.