Viewing posts from August, 2019
CryptoTheorem group releases Bitcoin Bubble Index and Crypto Bubble Index.
According to Google Trends, the word "sentiment analyis" has been gaining steady traction over the past 5 years. Sentiment refers to the attitude expressed by an individual regarding a certain topic.
Ever noticed how things in crypto get really exciting, people start making crazy predictions, and suddenly at its highest point, everything turns for the worst?
A lot of investors mention the word "sentiment". But do you really know what is means, and how you can use it wisely as a trader? In short, Market sentiment is the feeling or tone of the market, or its crowd psychology, as revealed through the activity and price movement of the securities traded in that market.
First, you can build a very basic strategy that simply buys when sentiment is superb, holds, and sells once sentiment gets into negatives. To mimic this, You can write a simple strategy, which just do this. If the cryptocurrency sentiment analysis signal is at 100, the strongest possible positive, then a buy is initiated, using 10% of the portfolio's available cash, and a stop-loss of 0.5% is set. This means that we would be invested in up to 10 assets at any one time. We could try to make the strategy a bit smarter by dynamically adjusting investment size according to available investments, but we'll keep it basic for now. After buying, the strategy holds the asset until sentiment hits -1 or lower, and then a sell is initiated.
Every day, millions of news are generated, and all these news are produced by humans in natural language. These news contain the information that can help on the field of decision making, algorithmic trading and risk management. Consider one piece of news may trigger a cryptocurrency price explosion. Or a hiding trend may be buried in a huge pile of news data. For now, these works are often done by professional analysts. But the task become harder and harder as soaring flows of news. That's why we need the automated and quantitative news analysis.
Technical Analysis is the process of using charts and indicators based on the price and volume to predict the future movements of financial assets
The automated analysis of textual data and its application in business analytics holds great promise for providing decision-makers with information from a sheer endless stream of news available online. Recent advances in computing have led to exciting new tools in the areas on Natural Language Processing. Sentiment Analysis and Machine Learning that can be used to make sense from an ever growing number of online sources. In a series of blog posts we will be looking at the basic concept of sentiment analysis in general and in the context of cryptocurrency trading, offer a behind-the-scenes view into Derivative Lab's very own efforts in building a sentiment engine, introduce a number of case studies and provide a glimpse into the future of machine learning and Artificial Intelligence (AI).
Tick-by-tick Sentiment data can allow us to identify entry points throughout the day when there are spike in Sentiment. These spikes can be caused by the release of good or bad news that will drive trading and price movement.