Ultimate Major Contextual Dashboard (Multi-Asset)Overview : The Ultimate Major Dashboard is a performance-optimized market overview tool designed to provide a consolidated snapshot of the 7 major Forex pairs and Gold. It aggregates correlation, trend, momentum, and volatility data into a single, clean table, allowing users to view broader market context without switching charts.
Technical Logic & Components : This indicator utilizes a modular function to analyze EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD, and XAUUSD across four key dimensions:
Intermarket Correlation (Pearson Coefficient): Uses ta.correlation() to compare each asset against the symbol currently on your main chart.
Logic: Values above 0.7 (Dark Green) suggest a strong positive relationship, while values below -0.7 (Dark Red) suggest inverse behavior. This is calculated over a rolling 50-period window to balance stability with current market sensitivity.
Trend Bias (EMA-200): Evaluates the long-term trend by checking price position relative to the 200-period Exponential Moving Average.
Visuals: An upward arrow (⬆) indicates price is above the EMA; a downward arrow (⬇) indicates it is below.
Momentum (RSI-14): Calculates the Relative Strength Index. The dashboard automatically highlights readings above 70 (OB) or below 30 (OS) to help identify potential momentum extremes.
Volatility (ATR-14): Displays the Average True Range as a reference for the current active range of each market, helping users compare volatility levels across the majors.
How to Interpret the Dashboard
Asset Alignment: Correlation values help identify when pairs are moving in "unison" versus when a specific currency is diverging from the group.
Directional Context: Combining the Trend (EMA) and Momentum (RSI) columns provides a quick view of whether a market is trending strongly or reaching an exhaustion point.
Volatility Benchmarking: The ATR values offer perspective on which pairs are currently the most active, assisting in market comparison based on volatility preference.
Data Handling & Customization
Multi-Symbol Sync: Data is fetched using request.security(). The calculations are synchronized with the chart's current bar state for real-time accuracy.
Dynamic TF: Users can select the analysis timeframe (60, 240, D, W) via the settings menu.
Flexibility: The dashboard position can be toggled between all four corners of the chart to avoid overlapping with price action.
Disclaimer
This tool is provided for analytical and educational purposes only. It does not generate trading signals and should not be considered financial advice.
Intermarket
TFPS_EngineLibrary "TFPS_Engine"
f_calculate_lead_lag(series1, series2, length, max_lag)
Parameters:
series1 (float)
series2 (float)
length (int)
max_lag (int)
f_calculate_pressure_score(spx_ticker, vix_ticker, dxy_ticker, us10y_ticker, benchmark_source, trend_lookback, score_smoothing, use_dynamic_weights, corr_lookback, w_spx, w_vix, w_dxy, w_us10y, zscore_lookback, max_lag)
Parameters:
spx_ticker (string)
vix_ticker (string)
dxy_ticker (string)
us10y_ticker (string)
benchmark_source (float)
trend_lookback (int)
score_smoothing (simple int)
use_dynamic_weights (bool)
corr_lookback (int)
w_spx (float)
w_vix (float)
w_dxy (float)
w_us10y (float)
zscore_lookback (int)
max_lag (int)
LeadLagOutput
Fields:
best_lag (series int)
max_corr (series float)
TFPS_Output
Fields:
historical_score (series float)
smoothed_score (series float)
z_score (series float)
regime_signal (series int)
lead_lag_bars (series int)
lead_lag_corr (series float)
weight_spx (series float)
weight_vix (series float)
weight_dxy (series float)
weight_us10y (series float)
Strength Comparison @joshuuuexample:
if you want to find the stronger/weaker pair between eurusd and gbpusd, what you can do is check the eurgbp charts. if eurgbp is bullish, that means, that longs longs on eurusd are better than on gbpusd.
Unfortunately, there is no such thing to compare for example usoil with ukoil, or us100 with us500.
That's where this indicator comes in handy. You can choose whatever two symbols you want, that are supported by tradingview and you will get a chart, which shows symbol1/symbol2.
Now you can use normal market structure, or the ema option, to find out the stronger symbol.
This can also help predicting the so called SMT Divergences, taught by ICT.
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
Correlation with Matrix TableCorrelation coefficient is a measure of the strength of the relationship between two values. It can be useful for market analysis, cryptocurrencies, forex and much more.
Since it "describes the degree to which two series tend to deviate from their moving average values" (1), first of all you have to set the length of these moving averages. You can also retrieve the values from another timeframe, and choose whether or not to ignore the gaps.
After selecting the reference ticker, which is not dependent from the chart you are on, you can choose up to eight other tickers to relate to it. The provided matrix table will then give you a deeper insight through all of the correlations between the chosen symbols.
Correlation values are scored on a scale from 1 to -1
A value of 1 means the correlation between the values is perfect.
A value of 0 means that there is no correlation at all.
A value of -1 indicates that the correlation is perfectly opposite.
For a better view at a glance, eight level colors are available and it is possible to modify them at will. You can even change level ranges by setting their threshold values. The background color of the matrix's cells will change accordingly to all of these choices.
The default threshold values, commonly used in statistics, are as follows:
None to weak correlation: 0 - 0.3
Weak to moderate correlation: 0.3 - 0.5
Moderate to high correlation: 0.5 - 0.7
High to perfect correlation: 0.7 - 1
Remember to be careful about spurious correlations, which are strong correlations without a real causal relationship.
(1) www.tradingview.com
USDJPY Assumption v1Based on the "logical trading" post of Charles Cornley (thanks!).
Indicator States:
Very Bullish (Lime) = USD trend rising and JPY trend falling and Gold trend falling and US 10Y Bond trend falling and
Dow Jones trend rising and Nasdaq trend rising and Russell 2000 trend rising and
S&P 500 trend rising and Nikkei 225 trend rising
Bullish (Green) = USD trend rising and JPY trend falling
Bearish (Red) = USD trend falling and JPY trend rising
