Technical Analysis

Technical analysis is a trading analysis technique used to evaluate stocks (or other financial instruments) in order to predict future price changes. This is accomplished by analyzing statistics gathered from trading activity (last trades, bid/ask prices, volume, etc.) Technical analysts focus on market data charts to forecast future price changes.

Many crowd researchers at CloudQuant use TA-Lib to assist in their use of Technical Indicators.

Posts

Facebook drop 19%, July 2018

$FB Decline 19%- What did the Social and technical analysis show? – July 26 2018

$FB’s 19% drop was preceded by TA-LIB and Social Market Analytics indicators to sell. The $120 Billion drop in market cap could have been an opportunity to short sell before the market close the previous night.
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Three Inside Up Technical Pattern shown on $IBM Jan 2, 2018

TA-LIB Three Inside Up Buy Signal – $IBM

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IBM, the 100-year-old company, is wedging into a tight trade, but it looks like the Bulls are gearing to press a move higher. Just before year-end, the stock set a Three Inside Up Japanese candlestick pattern setting the stage for a rally. Source code using TA-LIB and Python included.
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Harami Sell Signal on Google Dec 20, 2017

Harami Sell Signal with Three Inside Down Demonstrated on $GOOG

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December 19, 2017 Monday Google pressed new highs, but Tuesday closed out the day with a Harami Sell signal. Watch out for today. A negative close today boosts the negative outlook with the emergence of a Three Inside Down pattern. In this event, it will most likely mean that there will be a “little coal in Google stockholders stockings for Christmas”.
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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.
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Candlestick market data chart

Understanding Candlestick Bars & Market Data for Beginning Algo Programmers

In this video, we introduce you to Candlestick Bars, a store of Historic Market Data, how to access that data via Pythons Lists and how pointers work in lists.
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Catalent Inc. – $CTLT – Bearish Engulfing Sell Signal

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There was a fresh sell signal for Catalent Inc. stock this week. The recent rally has been put on hold with the emergence of a Bearish Engulfing signal. More selling pressure is expected to develop as the market degrades from the steep upward slope it has been trending on. This post shows a trading signal and has algo source code links.
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$GE – Short Term Buy Signal – Piercing the Line

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Technical analysis shows a piercing the line trading signal. This post includes links to source code show how to capture this signal with TA-LIB
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Bullish Turn of Events for Sprint - S by Theodore Kekstadt

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

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

Medium.com

The Patient Chart Pattern Trader

“Although HFT and algo trading dominate market activity nowadays to the tune of about 80% of transaction volume, there are still a number of old school chart pattern traders around. This is evident from social media messages where these traders post charts with patterns, such as head and shoulders, triangles, trendlines, double tops and bottoms, just to name a few. Although some of those chart traders aim to only teach their “art” to new traders, some are obviously patient enough to trade with it.” 
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“Chart pattern trading is a style that is more suitable for recreational trading rather than professional. This is one reason it was never considered seriously by the majority of hedge funds. In addition to requiring patience, slow chart pattern formations offer enough time for detection and competition is high at diminishing returns.”
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“The conclusion is that chart trading was a style for patient traders during times when everything was slow, from data collection, to chart drawing, to analysis and to executive trades. Nowadays the word is faster by several orders of magnitude. Good chart traders could obviously survive the new dynamics but the expectation should be low given dominance of algos. At the same time, learning that old style of trading is more interesting in the context of studying the reasons it is no longer applicable to the markets.”
See what Michael Harris has to say about it on Medium.com
Note: CloudQuant has seen many chart pattern traders bring their discipline of trading and analysis to their python based algorithms.
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