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Market sentiment, also known as investor attention, is the general prevailing attitude of investors as to anticipated price development in a market. [1] This attitude is the accumulation of a variety of fundamental and technical factors, including price history, economic reports, seasonal factors, and national and world events.
At any given time, investors face a deluge of sentiment data from indicators like investor surveys, market volatility readings such as the VIX , options market gauges like the put/call ratio ...
A market trend is a perceived tendency of the financial markets to move in a particular direction over time. [1] Analysts classify these trends as secular for long time-frames, primary for medium time-frames, and secondary for short time-frames. [2]
In finance the put/call ratio (or put-call ratio, PCR) is a technical indicator demonstrating investor sentiment. [1] The ratio represents a proportion between all the put options and all the call options purchased on any given day. The put/call ratio can be calculated for any individual stock, as well as for any index, or can be aggregated. [2]
If the market is directionless (undecided), prices may fluctuate greatly around this level until a price breakout develops. Trading above or below the pivot point indicates the overall market sentiment. It is a leading indicator providing advanced signaling of potentially new market highs or lows within a given time frame. [5]
Even after the stock market’s post-election rally came to a screeching halt on Wednesday when the Federal Reserve signaled a hard line on interest rates, the S&P 500 remains up since Trump’s win.
China's services PMI survey results on Tuesday also boosted risk sentiment in the world's second-largest economy, they added. China's benchmark CSI 300 Index closed 2.5% higher, while Hong Kong's ...
The Gated Three-Tower Transformer (GT3) is a transformer-based model designed to integrate numerical market data with textual information from social sources to enhance the accuracy of stock market predictions. [12] Since NNs require training and can have a large parameter space; it is useful to optimize the network for optimal predictive ability.