Linear Gauge Guide

Key Understandings

News sentiment vs trader sentiment

• News sentiment is a big data / alternative data set derived from the vast volume of news published related to the financial markets and key themes affecting them e.g. Brexit, Trump
• Trader sentiment is a small data set derived from client positions.

News sentiment often precedes market movement

• By knowing what the sentiment is now, users can pre-empt how the market might react.

News volume is a proxy for market volatility

User Benefits

• By understanding current market sentiment traders can better anticipate market reactions.
• Data visualisation - intuitive, engaging tools to aid decision making and confidence.
• MT4 EA - research and trade within your own MT4 for faster execution
• Hourly / Daily data to suit trading styles.
• Multi-asset

Linear Gauge Components

What is included and how it works

Displayed Data

News sentiment is calculated using a lexicon-based algorithm that is able to extract 9 sentiment types (emotions), 2 further metrics based on the volume of news received and 1 additional identifier based on entity recognition from News Text.

The sentiment score that is presented in the Linear Gauge is called the “Feel Good Factor” and shows the ratio between general positivity and general negativity in the news towards a selected instrument. It is calculated using the Exponential Moving Average technique and the goal of it is to accentuate the movement of the sentiment in the most recent period, so that any changes could be visually captured. 

The goal of this sentiment score is to show how much more bullish or bearish (or stronger vs. weaker) the current reading is vs. historical average for a given asset.

Presentation

The news sentiment data is presented in the form of a linear chart. The scores range from -1.0 (very bearish) to 1.0 (very bullish). Neutral score is depicted by 0.

The granularity of the data can be either Hourly or Daily, which simply indicates the amount and the period of news articles processed to generate the score.