A version of the Sentiment Ratio applied to EURUSD H1 has been automatically updating twitter feed @TSSMarkets.
Automated trade signals will be updating the account as from 2020-08-17.
The Sentiment Ratio indicator gauges current Market Sentiment between -100% and 100%, where lower than -40% is considered Bearish and higher than 40% Bullish. The channel between the two is considered Neutral.
The indicator has been particularly effective on H4 charts when used to confirm the direction of potential trading signals. On shorter term charts, when the indicator crosses -40 or 40 back to Neutral, it can be effective when indicating potential swings; for example, a sell signal when the indicator crosses below 40 and a buy signal when the indicator crosses above -40.
The Multi Trendlines indicator automatically draws the dominant trendlines on the current chart.
The indicator looks for the 5 best Up trends and the 5 best Down trends as at the current price, drawing each trendline if filter conditions are met.
The price relative to the trendline values can be incorporated into automated trading strategies or used as a tool for manual trading.
Algorithmic trading of the currency markets using the proprietary Trendline Syncing System (TSS).
Positions are based on the best entry and exit points in the rhythmic
movements of trending markets, evaluated across multiple timeframes, applying
aggregated Analyst pull ratios, Sentiment Ratio analysis, and economic news
event actuals versus forecasts.
The Foreign Exchange Market is the optimum asset class in which to balance a healthy Risk/Reward ratio in all economic and political conditions. Trading by investors adds to market depth and decreases the costs of businesses, pension funds and consumers to exchange money. In normal circumstances, market currency price adjustments are a natural and necessary safety valve to an economy. Ethically (and also from a risk management perspective) we do not trade non-stable currencies.
Our investment approach is to execute strategy plans formulated by special configurations of the TSS model, which creates automated algorithmic trades and ensures positions are implemented accurately in the currency markets 24 hours a day.
Over the past year I have experimented with three different methods of trading in the currency markets: computer automated algorithmic trading, human manual trading and semi-automated algorithmic trading.
Purely automated trading - using pattern recognition and data mining - has proven to be very unsuccessful, which is is to be expected, as it is highly unlikely that there exists a magic formula for technical analysis that can be applied at all times. If such a thing existed, the designer of the magic money box would quickly become the richest person in history, given the trillions of dollars that pass through the financial markets every day. Successful automated algorithms in the markets compete on speed of response to price imperfections between markets and to variances between market expectations and economic data announcements.
Manual trading has had variable returns, yielding a slight net gain, but this is no guarantee of future performance due to the lack of a reusable fully codified strategy.
The most successful method is the hybrid combination of a human and a machine working together in real-time, which has performed very well over the testing time period. The human (me) innovates and modifies ideas from large volumes of data processed by the algorithm, as directed by me. The semi-automated algorithm then dispassionately executes the trading plan exactly in the lifespan of the strategy, monitoring every market tick instantly every moment of every day.