Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster
Plain-English overview
This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism.
What Monte Carlo is and why quants rely on it
• Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve.
• Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon.
• Core strengths in quant finance .
– Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?”
– Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic.
– Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess.
• Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.”
How this indicator builds its probability cone
1) Seasonal pattern discovery
The script builds two day-of-year maps as new data arrives:
• A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information.
• A volatility map that tracks the typical absolute return for the same calendar day.
It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day.
2) Choice of randomness engine
You can pick how the future shocks are generated:
• Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock.
• Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution.
Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands.
3) Volatility scaling to current conditions
Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa.
4) Many futures, summarized by percentiles
The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles:
• 5th and 95th → approximate 95% band (outer cone).
• 16th and 84th → approximate 68% band (inner cone).
• 50th → the median or “expected path.”
These are drawn as polylines so you can immediately see central tendency and dispersion.
5) A historical overlay (optional)
Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward.
Inputs you control and how to think about them
Monte Carlo Simulation
• Price Series for Calculation . The source series, typically close.
• Enable Probability Forecasts . Master switch for simulation and drawing.
• Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon.
• Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty.
• Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice).
• Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history.
• Volatility Scaling . On by default so the cone respects today’s range context.
Plotting & UI
• Probability Cone . Plots the outer and inner percentile envelopes.
• Expected Path . Plots the median line through the cone.
• Historical Overlay . Dotted seasonal-only projection for context.
• Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts.
What appears on your chart
• A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band.
• A median path (default blue) running through the center of the cone.
• An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent.
• Optional historical seasonal path drawn as dotted segments for the next 30 bars.
How to use it in trading
1) Position sizing and stop logic
The cone translates “volatility plus seasonality” into distances.
• Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play.
• Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable.
• If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality.
2) Entry timing with seasonal bias
When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system.
3) Target selection
Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive.
4) Scenario planning & “what-ifs”
Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through.
5) Options and vol tactics
• When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate.
• When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics.
Reading the probability cone like a pro
• Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite.
• Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained.
• Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone.
• Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst.
Methodological notes (what the code actually does)
• Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price.
• Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives.
• Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable.
• Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation.
• Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better.
• Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones.
• Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive.
• Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history.
Strengths and limitations
• Strengths :
– Probabilistic thinking replaces single-point guessing.
– Seasonality adds a small but meaningful directional bias that many markets exhibit.
– Volatility scaling adapts to the current regime so the cone stays realistic.
• Limitations :
– Seasonality can break around structural changes, policy shifts, or one-off events.
– The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision.
– The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts.
– Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories.
Tuning guide
• Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets.
• Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes.
• Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong.
• Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence.
Workflow examples
• Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band.
• Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated.
• Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range.
Good habits
• Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality.
• Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt.
• Validate seasonality for your symbol and timeframe; not every market has strong calendar effects.
Summary
The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
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FEDFUNDS Rate Divergence Oscillator [BackQuant]FEDFUNDS Rate Divergence Oscillator
1. Concept and Rationale
The United States Federal Funds Rate is the anchor around which global dollar liquidity and risk-free yield expectations revolve. When the Fed hikes, borrowing costs rise, liquidity tightens and most risk assets encounter head-winds. When it cuts, liquidity expands, speculative appetite often recovers. Bitcoin, a 24-hour permissionless asset sometimes described as “digital gold with venture-capital-like convexity,” is particularly sensitive to macro-liquidity swings.
The FED Divergence Oscillator quantifies the behavioural gap between short-term monetary policy (proxied by the effective Fed Funds Rate) and Bitcoin’s own percentage price change. By converting each series into identical rate-of-change units, subtracting them, then optionally smoothing the result, the script produces a single bounded-yet-dynamic line that tells you, at a glance, whether Bitcoin is outperforming or underperforming the policy backdrop—and by how much.
2. Data Pipeline
• Fed Funds Rate – Pulled directly from the FRED database via the ticker “FRED:FEDFUNDS,” sampled at daily frequency to synchronise with crypto closes.
• Bitcoin Price – By default the script forces a daily timeframe so that both series share time alignment, although you can disable that and plot the oscillator on intraday charts if you prefer.
• User Source Flexibility – The BTC series is not hard-wired; you can select any exchange-specific symbol or even swap BTC for another crypto or risk asset whose interaction with the Fed rate you wish to study.
3. Math under the Hood
(1) Rate of Change (ROC) – Both the Fed rate and BTC close are converted to percent return over a user-chosen lookback (default 30 bars). This means a cut from 5.25 percent to 5.00 percent feeds in as –4.76 percent, while a climb from 25 000 to 30 000 USD in BTC over the same window converts to +20 percent.
(2) Divergence Construction – The script subtracts the Fed ROC from the BTC ROC. Positive values show BTC appreciating faster than policy is tightening (or falling slower than the rate is cutting); negative values show the opposite.
(3) Optional Smoothing – Macro series are noisy. Toggle “Apply Smoothing” to calm the line with your preferred moving-average flavour: SMA, EMA, DEMA, TEMA, RMA, WMA or Hull. The default EMA-25 removes day-to-day whips while keeping turning points alive.
(4) Dynamic Colour Mapping – Rather than using a single hue, the oscillator line employs a gradient where deep greens represent strong bullish divergence and dark reds flag sharp bearish divergence. This heat-map approach lets you gauge intensity without squinting at numbers.
(5) Threshold Grid – Five horizontal guides create a structured regime map:
• Lower Extreme (–50 pct) and Upper Extreme (+50 pct) identify panic capitulations and euphoria blow-offs.
• Oversold (–20 pct) and Overbought (+20 pct) act as early warning alarms.
• Zero Line demarcates neutral alignment.
4. Chart Furniture and User Interface
• Oscillator fill with a secondary DEMA-30 “shader” offers depth perception: fat ribbons often precede high-volatility macro shifts.
• Optional bar-colouring paints candles green when the oscillator is above zero and red below, handy for visual correlation.
• Background tints when the line breaches extreme zones, making macro inflection weeks pop out in the replay bar.
• Everything—line width, thresholds, colours—can be customised so the indicator blends into any template.
5. Interpretation Guide
Macro Liquidity Pulse
• When the oscillator spends weeks above +20 while the Fed is still raising rates, Bitcoin is signalling liquidity tolerance or an anticipatory pivot view. That condition often marks the embryonic phase of major bull cycles (e.g., March 2020 rebound).
• Sustained prints below –20 while the Fed is already dovish indicate risk aversion or idiosyncratic crypto stress—think exchange scandals or broad flight to safety.
Regime Transition Signals
• Bullish cross through zero after a long sub-zero stint shows Bitcoin regaining upward escape velocity versus policy.
• Bearish cross under zero during a hiking cycle tells you monetary tightening has finally started to bite.
Momentum Exhaustion and Mean-Reversion
• Touches of +50 (or –50) come rarely; they are statistically stretched events. Fade strategies either taking profits or hedging have historically enjoyed positive expectancy.
• Inside-bar candlestick patterns or lower-timeframe bearish engulfings simultaneously with an extreme overbought print make high-probability short scalp setups, especially near weekly resistance. The same logic mirrors for oversold.
Pair Trading / Relative Value
• Combine the oscillator with spreads like BTC versus Nasdaq 100. When both the FED Divergence oscillator and the BTC–NDQ relative-strength line roll south together, the cross-asset confirmation amplifies conviction in a mean-reversion short.
• Swap BTC for miners, altcoins or high-beta equities to test who is the divergence leader.
Event-Driven Tactics
• FOMC days: plot the oscillator on an hourly chart (disable ‘Force Daily TF’). Watch for micro-structural spikes that resolve in the first hour after the statement; rapid flips across zero can front-run post-FOMC swings.
• CPI and NFP prints: extremes reached into the release often mean positioning is one-sided. A reversion toward neutral in the first 24 hours is common.
6. Alerts Suite
Pre-bundled conditions let you automate workflows:
• Bullish / Bearish zero crosses – queue spot or futures entries.
• Standard OB / OS – notify for first contact with actionable zones.
• Extreme OB / OS – prime time to review hedges, take profits or build contrarian swing positions.
7. Parameter Playground
• Shorten ROC Lookback to 14 for tactical traders; lengthen to 90 for macro investors.
• Raise extreme thresholds (for example ±80) when plotting on altcoins that exhibit higher volatility than BTC.
• Try HMA smoothing for responsive yet smooth curves on intraday charts.
• Colour-blind users can easily swap bull and bear palette selections for preferred contrasts.
8. Limitations and Best Practices
• The Fed Funds series is step-wise; it only changes on meeting days. Rapid BTC oscillations in between may dominate the calculation. Keep that perspective when interpreting very high-frequency signals.
• Divergence does not equal causation. Crypto-native catalysts (ETF approvals, hack headlines) can overwhelm macro links temporarily.
• Use in conjunction with classical confirmation tools—order-flow footprints, market-profile ledges, or simple price action to avoid “pure-indicator” traps.
9. Final Thoughts
The FEDFUNDS Rate Divergence Oscillator distills an entire macro narrative monetary policy versus risk sentiment into a single colourful heartbeat. It will not magically predict every pivot, yet it excels at framing market context, spotting stretches and timing regime changes. Treat it as a strategic compass rather than a tactical sniper scope, combine it with sound risk management and multi-factor confirmation, and you will possess a robust edge anchored in the world’s most influential interest-rate benchmark.
Trade consciously, stay adaptive, and let the policy-price tension guide your roadmap.
Economy RadarEconomy Radar — Key US Macro Indicators Visualized
A handy tool for traders and investors to monitor major US economic data in one chart.
Includes:
Inflation: CPI, PCE, yearly %, expectations
Monetary policy: Fed funds rate, M2 money supply
Labor market: Unemployment, jobless claims, consumer sentiment
Economy & markets: GDP, 10Y yield, US Dollar Index (DXY)
Options:
Toggle indicators on/off
Customizable colors
Tooltips explain each metric (in Russian & English)
Perfect for spotting economic cycles and supporting trading decisions.
Add to your chart and get a clear macro picture instantly!
HL2 Moving Average with BandsThis indicator is designed to assist traders in identifying potential trade entries and exits for S&P 500 (ES) and Nasdaq-100 (NQ) futures. It calculates a Simple Moving Average (SMA) based on the HL2 value (average of high and low prices) of the current candle over a user-defined lookback period (default: 200 periods). The indicator plots this SMA as a blue line, providing a smoothed reference for price trends.
Additionally, it includes upper and lower bands calculated as a percentage (default: 0.5%) above and below the SMA, plotted as green and red lines, respectively. These bands act as dynamic thresholds to identify overbought or oversold conditions. The indicator generates trade signals based on price action relative to these bands:
Long Entry: A green upward triangle is plotted below the candle when the close crosses above the upper band, signaling a potential buy.
Close Long: A red square is plotted above the candle when the close crosses back below the upper band, indicating an exit for the long position.
Short Entry: A red downward triangle is plotted above the candle when the close crosses below the lower band, signaling a potential sell.
Close Short: A green square is plotted below the candle when the close crosses back above the lower band, indicating an exit for the short position.
The script is customizable, allowing users to adjust the SMA length and band percentage to suit their trading style or market conditions. It is plotted as an overlay on the price chart for easy integration with other technical analysis tools.
Recommended Time Frame and Settings for Trading S&P 500 and Nasdaq-100 Futures
Based on research and market dynamics for S&P 500 (ES) and Nasdaq-100 (NQ) futures, the 5-minute chart is recommended as the optimal time frame for day trading with this indicator. This time frame strikes a balance between capturing intraday trends and filtering out excessive noise, which is critical for futures trading due to their high volatility and leverage. The 5-minute chart aligns well with periods of high liquidity and volatility, such as the U.S. market open (9:30 AM–11:00 AM EST) and the afternoon session (2:00 PM–4:00 PM EST), when institutional traders are most active.
Why 5-minute? It allows traders to react to short-term price movements while avoiding the rapid fluctuations of 1-minute charts, which can be prone to false signals in choppy markets. It also provides enough data points to make the SMA and bands meaningful without the lag associated with longer time frames like 15-minute or hourly charts.
Recommended Settings
SMA Length: Set to 200 periods. This longer lookback period smooths the HL2 data, reducing noise and providing a reliable trend reference for the 5-minute chart. A 200-period SMA helps identify significant trend shifts without being overly sensitive to minor price fluctuations.
Band Percentage: 0.5% is more suitable for the volatility of ES and NQ futures on a 5-minute chart, as it generates fewer but higher-probability signals. Wider bands (e.g., 1%) may miss short-term opportunities, while narrower bands (e.g., 0.1%) may produce excessive false signals.
Trading Session Recommendations
Futures markets for ES and NQ are open nearly 24 hours (Sunday 6:00 PM EST to Friday 5:00 PM EST, with a daily break from 4:00 PM–5:00 PM EST), but not all hours are equally optimal due to varying liquidity and volatility. The best times to trade with this indicator are:
U.S. Market Open (9:30 AM–11:00 AM EST): This period is characterized by high volume and volatility, driven by the opening of U.S. equity markets and economic data releases (e.g., 8:30 AM EST reports like CPI or GDP). The indicator’s signals are more reliable during this window due to strong order flow and price momentum.
Afternoon Session (2:00 PM–4:00 PM EST): After the lunchtime lull, volume picks up as institutional traders return, and news or FOMC announcements often drive price action. The indicator can capture breakout moves as prices test the upper or lower bands.
Pre-Market (7:30 AM–9:30 AM EST): For traders comfortable with lower liquidity, this period can offer opportunities, especially around 8:30 AM EST economic releases. However, use tighter risk management due to wider spreads and potential volatility spikes.
Additional Tips
Avoid Low-Volume Periods: Steer clear of trading during low-liquidity hours, such as the overnight session (11:00 PM–3:00 AM EST), when spreads widen and price movements can be erratic, leading to false signals from the indicator.
Combine with Other Tools: Enhance the indicator’s effectiveness by pairing it with support/resistance levels, Fibonacci retracements, or volume analysis to confirm signals. For example, a long entry signal above the upper band is stronger if it coincides with a breakout above a key resistance level.
Risk Management: Given the leverage in futures (e.g., Micro E-mini contracts require ~$1,200 margin for ES), use tight stop-losses (e.g., below the lower band for longs or above the upper band for shorts) to manage risk. Aim for a risk-reward ratio of at least 1:2.
Test Settings: Backtest the indicator on a demo account to optimize the SMA length and band percentage for your specific trading style and risk tolerance. Micro E-mini contracts (MES for S&P 500, MNQ for Nasdaq-100) are ideal for testing due to their lower capital requirements.
Why These Settings and Time Frame?
The 5-minute chart with a 200-period SMA and 0.5% bands is tailored for the volatility and liquidity of ES and NQ futures during peak trading hours. The longer SMA period ensures the indicator captures meaningful trends, while the 0.5% bands are tight enough to signal actionable breakouts but wide enough to avoid excessive whipsaws. Trading during high-volume sessions maximizes the likelihood of valid signals, as institutional participation drives clearer price action.
By focusing on these settings and time frames, traders can leverage the indicator to capitalize on the dynamic price movements of S&P 500 and Nasdaq-100 futures while managing the inherent risks of these markets.
UB Short Signal (10Y Yield Future Spike)"This indicator identifies short opportunities on UB futures based on inverse correlation with 10Y Yield Futures. A macro trading tool to be used with additional confirmations."
🎯 Indicator Strategy
This tool generates sell signals for Ultra Bond (UB) futures when:
The Micro 10-Year Yield Future shows an upward spike (> adjustable threshold)
Trading volume is significant (false signal filter)
Inverse correlation is confirmed (UB falls when 10Y rises)
⚙️ Parameters
Spike Threshold: Sensitivity adjustment (e.g., 0.08% for swing trading)
Minimum Volume: Default 100 (optimized for Micro 10Y contracts)
📊 Recent Backtest
06/15/2024: +0.10% spike → UB dropped -0.3% within 15 minutes
06/18/2024: Valid signal post-CPI release
⚠️ Disclaimer
Analytical tool only – not financial advice
Must be combined with proper risk management
Climax Volume FilterThis script helps filter out volume spikes caused by sudden market events (e.g. CPI, FOMC), which can distort volume-based analysis.
It identifies and optionally smooths or excludes high “climax” candles to provide a clearer view of natural volume trends during pullbacks and consolidations.
Use it to:
• Avoid misreading volume during news events
• Improve your reading of exhaustion vs. continuation
• Support better entry timing during flag or FVG setups
CAPE / Shiller PE Ratio - cristianhkrThe Cyclically Adjusted Price-to-Earnings Ratio (CAPE Ratio), also known as the Shiller P/E Ratio, is a long-term valuation measure for stocks. It was developed by Robert Shiller and smooths out earnings fluctuations by using an inflation-adjusted average of the last 10 years of earnings.
This TradingView Pine Script indicator calculates the CAPE Ratio for a specific stock by:
Fetching historical Earnings Per Share (EPS) data using request.earnings().
Adjusting the EPS for inflation by dividing it by the Consumer Price Index (CPI).
Computing the 10-year (40-quarter) moving average of the inflation-adjusted EPS.
Calculating the CAPE Ratio as (Stock Price) / (10-year Average EPS adjusted for inflation).
Plotting the CAPE Ratio on the chart with a reference line at CAPE = 20, a historically significant threshold.
TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals.
Global Inflation Indicator🔹 Overview:
The Global Inflation Indicator is a macro-analysis tool designed to track and compare inflation trends across major economies. It pulls Consumer Price Index (CPI) data from multiple regions, helping traders and investors analyze how inflation impacts global markets, particularly gold, forex, and commodities.
📊 Key Features:
✅ Tracks inflation in six major economies:
🇺🇸 USA (CPIAUCSL) – Key driver for USD and gold prices
🇪🇺 Eurozone (CPHPTT01EZM659N) – Euro inflation impact
🇬🇧 United Kingdom (GBRCPIALLMINMEI) – GBP & economic trends
🇨🇳 China (CHNCPIALLMINMEI) – Emerging market impact
🇯🇵 Japan (JPNCPIALLMINMEI) – Yen & inflation control policies
🇮🇳 India (INDCPIALLMINMEI) – Key gold-consuming economy
✅ Real-time Inflation Trends:
Provides a visual comparison of inflation levels in different regions.
Helps traders identify inflationary cycles & their effect on global assets.
✅ Macro-Driven Trading Decisions:
Gold & Forex Correlation: High inflation may increase demand for gold.
Interest Rate Expectations: Central banks respond to inflation shifts.
Currency Strength: Inflation impacts USD, EUR, GBP, JPY, CNY, INR.
📉 How to Use It:
Gold traders can assess inflation trends to predict potential price movements.
Forex traders can compare inflation effects on major currency pairs (EUR/USD, USD/JPY, GBP/USD, etc.).
Stock investors can evaluate how inflation affects central bank policies and interest rates.
📌 Conclusion:
The Global Inflation Indicator is a powerful tool for macroeconomic analysis, providing real-time insights into global inflation trends. By integrating this indicator into your gold, forex, and commodity trading strategies, you can make more informed investment decisions in response to economic changes.
Global M2 Index Percentage### **Global M2 Index Percentage**
**Description:**
The **Global M2 Index Percentage** is a custom indicator designed to track and visualize the global money supply (M2) in a normalized percentage format. It aggregates M2 data from major economies (e.g., the US, EU, China, Japan, and the UK) and adjusts for exchange rates to provide a comprehensive view of global liquidity. This indicator helps traders and investors understand the broader macroeconomic environment, identify trends in money supply, and make informed decisions based on global liquidity conditions.
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### **How It Works:**
1. **Data Aggregation**:
- The indicator collects M2 data from key economies and adjusts it using exchange rates to calculate a global M2 value.
- The formula for global M2 is:
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2. **Normalization**:
- The global M2 value is normalized into a percentage (0% to 100%) based on its range over a user-defined period (default: 13 weeks).
- The formula for normalization is:
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3. **Visualization**:
- The indicator plots the M2 Index as a line chart.
- Key reference levels are highlighted:
- **10% (Red Line)**: Oversold level (low liquidity).
- **50% (Black Line)**: Neutral level.
- **80% (Green Line)**: Overbought level (high liquidity).
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### **How to Use the Indicator:**
#### **1. Understanding the M2 Index:**
- **Below 10%**: Indicates extremely low liquidity, which may signal economic contraction or tight monetary policy.
- **Above 80%**: Indicates high liquidity, which may signal loose monetary policy or potential inflationary pressures.
- **Between 10% and 80%**: Represents a neutral to moderate liquidity environment.
#### **2. Trading Strategies:**
- **Long-Term Investing**:
- Use the M2 Index to assess global liquidity trends.
- **High M2 Index (e.g., >80%)**: Consider investing in risk assets (stocks, commodities) as liquidity supports growth.
- **Low M2 Index (e.g., <10%)**: Shift to defensive assets (bonds, gold) as liquidity tightens.
- **Short-Term Trading**:
- Combine the M2 Index with technical indicators (e.g., RSI, MACD) for timing entries and exits.
- **M2 Index Rising + RSI Oversold**: Potential buying opportunity.
- **M2 Index Falling + RSI Overbought**: Potential selling opportunity.
#### **3. Macroeconomic Analysis**:
- Use the M2 Index to monitor the impact of central bank policies (e.g., quantitative easing, rate hikes).
- Correlate the M2 Index with inflation data (CPI, PPI) to anticipate inflationary or deflationary trends.
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### **Key Features:**
- **Customizable Timeframe**: Adjust the lookback period (e.g., 13 weeks, 26 weeks) to suit your trading style.
- **Multi-Economy Data**: Aggregates M2 data from the US, EU, China, Japan, and the UK for a global perspective.
- **Normalized Output**: Converts raw M2 data into an easy-to-interpret percentage format.
- **Reference Levels**: Includes key levels (10%, 50%, 80%) for quick analysis.
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### **Example Use Case:**
- **Scenario**: The M2 Index rises from 49% to 62% over two weeks.
- **Interpretation**: Global liquidity is increasing, potentially due to central bank stimulus.
- **Action**:
- **Long-Term**: Increase exposure to equities and commodities.
- **Short-Term**: Look for buying opportunities in oversold assets (e.g., RSI < 30).
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### **Why Use the Global M2 Index Percentage?**
- **Macro Insights**: Understand the broader economic environment and its impact on financial markets.
- **Risk Management**: Identify periods of high or low liquidity to adjust your portfolio accordingly.
- **Enhanced Timing**: Combine with technical analysis for better entry and exit points.
---
### **Conclusion:**
The **Global M2 Index Percentage** is a powerful tool for traders and investors seeking to incorporate macroeconomic data into their strategies. By tracking global liquidity trends, this indicator helps you make informed decisions, whether you're trading short-term or planning long-term investments. Add it to your TradingView charts today and gain a deeper understanding of the global money supply!
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**Disclaimer**: This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and consult with a professional before making investment decisions.
[Forex Fondamental Overview SGM]Fundamental analysis tool designed for currency trading in financial markets. The script generates a dashboard that displays key economic indicators for two selected currencies. Here is what makes this script particularly interesting for a trader:
1. Direct comparison between two currencies: The script allows you to choose two currencies (from a predefined list) and directly compare their key economic indicators such as interest rate, GDP growth, debt-to-GDP ratio, unemployment rate, inflation (CPI and PPI), and the services and manufacturing PMI indices. This gives you immediate insight into the economic strengths and weaknesses of each currency, which is crucial for making informed trading decisions.
2. Automatic data updating: Indicator values are updated automatically using security requests (request.security) that pull the most recent data available. This means you don't need to manually update data or check multiple sources; the script takes care of that for you.
3. Currency Relative Strength Calculation: The script calculates a strength index for each currency based on its economic indicators, and then it determines a relative strength index for the currency pair. This allows you to quickly see which currency is currently strongest, providing a basis for "buy strength, sell weakness" trading strategies.
4. Intuitive visualization: Results are presented in clear tables with colored indicators, making the information quickly digestible. For example, the background color changes depending on the relative strength of the currency pair, giving you an immediate visual signal of the overall trend.
5. Adaptability to different trading strategies: Whether you are a swing trader, a day trader, or a scalper, understanding the economic state of currencies can help you align your trading positions with underlying macroeconomic trends. This script gives you this information without requiring detailed economic analysis on your part.
In short, this script is a powerful tool for any Forex trader who wants to integrate fundamental analysis into their trading routine without bothering with the complexity of tracking and analyzing a multitude of economic indicators manually.
Temporal Value Tracker: Inception-to-Present Inflation Lens!What we're looking at here is a chart that does more than just display the price of gold. It offers us a time-traveling perspective on value. The blue line, that's our nominal price—it's the straightforward market price of gold over time. But it's the red line that takes us on a deeper journey. This line adjusts the nominal price for inflation, showing us the real purchasing power of gold.
Now, when we talk about 'real value,' we're not just philosophizing. We're anchoring our prices to a point in time when the journey began—let's say when gold trading started on the markets, or any inception point we choose. By 'shadowing' certain years—say, from the 1970s when the gold standard was abandoned—we can adjust this chart to reflect what the inflation-adjusted price means since that key moment in history.
By doing so, we're effectively isolating our view to start from that pivotal year, giving us insight into how gold, or indeed any asset, has held up against the backdrop of economic changes, policy shifts, and the inevitable rise in the cost of living. If you're analyzing a stock index like the S&P 500, you might begin your inflation-adjusted view from the index's inception date, which allows you to measure the true growth of the market basket from the moment it started.
This adjustment isn't just academic. It influences how we perceive value and growth. Consider a period where the nominal price skyrockets. We might toast to our brilliance in investment! But if the inflation-adjusted line lags, what we're seeing is nominal growth without real gains. On the other hand, if our red line outpaces the blue even during stagnant market periods, we're witnessing real growth—our asset is outperforming the eroding effects of inflation.
Every asset class can be evaluated this way. Stocks, bonds, real estate—they all have their historical narratives, and inflation adjustment tells us if these stories are tales of genuine growth or illusions masked by inflation.
So, as informed traders and investors, we need to keep our eyes on this inflation-adjusted line. It's our measure against the silent thief that is inflation. It ensures we're not just keeping up with the Joneses of the market, but actually outpacing them, building real wealth over time
1995-Present - Inflation and Purchasing PowerGood day, everyone! Today, we're going to look at a chart that's a bit different from the usual price charts we analyse. This isn't just any chart; it's a lens into the past, adjusted for the reality of inflation—a concept we often hear about but seldom see directly applied to our trading charts.
What we have here is an 'Inflation Adjusted Price' indicator on TradingView, and it's doing something quite special. It's showing us the price of our asset, let's say the S&P 500, not just in today's dollars, but in the dollars of 1995. Why 1995, you ask? Well, it's the starting point we've chosen to measure how much actual buying power has changed since then.
So, every point on this red line we see represents what the S&P 500's value would be if we stripped away the effects of inflation. This is the price in terms of what your money could actually buy you back in 1995.
As traders and investors, we're always looking at prices going up and thinking, 'Great! My investment is growing!' But the real question we should ask is, 'Is my money growing in real terms? Can it buy me more than it did last year, or five, ten, or twenty-five years ago?'
This chart tells us exactly that. If the red line is above the actual price, it means that the S&P 500 has not just grown in nominal terms, but it has actually outpaced inflation. Your investment has grown in real terms; it can buy you more now than it could back in 1995.
On the flip side, if the red line is below the actual price, that's a sign that while the nominal price might be up, the real value, the purchasing power, hasn't grown as much or could even have fallen.
This view is crucial, especially for the long-term investors among us. It gives us a reality check on our investments and savings. Are we truly growing our wealth, or are we just keeping up with the cost of living? This indicator answers that.
Remember, the true measure of financial growth is not just the numbers on a chart. It's what you can do with those numbers—how much bread, or eggs, or yes, even houses, you can buy with your hard-earned money
BTC Purchasing Power 2009-20XX! Hello, today I'm going to show you something that shifts our perspective on Bitcoin's value, not just in nominal terms, but adjusted for the real buying power over the years. This Pine Script TAS developed for TradingView does exactly that by taking into account inflation rates from 2009 to the present.
As you know, inflation erodes the purchasing power of money. That $100 in 2009 does not buy you the same amount in goods or services today. The same concept applies to Bitcoin. While we often look at its price in terms of dollars, pounds, or euros, it's crucial to understand what that price really means in terms of purchasing power.
What this script does is adjust the price of Bitcoin for cumulative inflation since 2009, allowing us to see not just how the nominal price has changed, but how its value as a means of purchasing goods and services has evolved.
For example, if we see Bitcoin's price at $60,000 today, that number might seem high compared to its early years. However, when we adjust this price for inflation, we might find that in terms of 2009's purchasing power, the effective price might be somewhat lower. This adjusted price gives us a more accurate reflection of Bitcoin's true value over time.
This script plots two lines on the chart:
The Original BTC Price: This is the unadjusted price of Bitcoin as we typically see it.
BTC Purchasing Power: This line shows Bitcoin's price adjusted for inflation, reflecting how many goods or services Bitcoin could buy at that point in time compared to 2009.
By comparing these lines, we can observe periods where Bitcoin's purchasing power significantly increased, even if the nominal price was not at its peak. This can help us identify moments when Bitcoin was undervalued or overvalued in real terms.
This analysis is crucial for long-term investors and traders who want to understand Bitcoin's value beyond the surface-level price movements. It helps us appreciate Bitcoin's potential as a store of value, especially in contexts where traditional currencies are losing purchasing power due to inflation.
Remember, investing is not just about riding price waves; it's about understanding the underlying value. And that's precisely what this script helps us to uncover
Multi VWAP from Gaps [MW]Multi VWAP from Gaps
Introduction
The Multi VWAP from Gaps tool extends the concept of using the Anchored Volume Weighted Average Price, popularized by its founder, Brian Shannon, founder of AlphaTrends. It creates automatic AVWAPS for anchor points originating at the biggest gaps of the week, month, quarter and year. Currently, most standard VWAP tools allow users to place custom anchored VWAPs, but the routine of doing this for every equity being watched can become cumbersome. This tool makes that process multi-times easier. Considering that large gaps can represent a shift in market structure, this tool provides unique and immediate insight into how past daily price gaps can and have affected price action.
Settings
LABEL SETTINGS
Show Biggest Gap of Week | Month | Quarter : Toggle labels that identify the location of the biggest gaps for the selected time period.
Show Big Labels : Toggle labels from showing the date and gap size to just showing a single letter (W/M/Q/Y) designating the time period that the gap is from.
Hide All Labels : Turn labels off and on.
MAX VWAP LINES
Max Weekly | Monthly | Quarterly | Yearly Lines : How many VWAP lines, starting from today, should be shown for the specified time period. Max: 5
SHOW VWAP LINES
Show Weekly | Monthly | Quarterly | Yearly Lines : This feature allows you to remove lines for the specified time period.
Calculations
This indicator does not provide buy or sell signals. It is simply the VWAP calculated starting from an “anchor point”, or start time. It is calculated by the summation of Price x Volume / Volume for the period starting at the anchor point.
How to Interpret
According to Brian Shannon, VWAP is an objective measure of what the average trader has paid for a particular equity over a given period, and is the value that large institutional investors frequently use as a trade signal. Therefore, by definition, when the price is above an AVWAP, buyers are in control for that period of time. Likewise, if the price is below the AVWAP, sellers are in control for that period of time.
VWAPs that coincide with important events, such as FOMC meetings, CPI reports, earnings reports, have added significance. In many cases, these events can cause gaps to happen in day-to-day price movement, and can affect market structure going forward.
Practically speaking, price action can tend to change direction when a significant VWAP is hit, voiding buy and sell signals. Like moving averages, this indicator can show, in real-time, how a buy or sell signal should be interpreted. A significant AVWAP line is a point of interest, and can serve as strong support or resistance, because large institutions may be using those values for entries or exits. For a great analysis of how to use AVWAP, visit the AlphaTrends channel on Youtube here or you can buy Brian Shannon’s “Anchored VWAP” book on Amazon.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Additionally, in order to build the VWAP calculations, past data is needed that may not be available on shorter timeframes. The workaround is that for some longer-term VWAP lines on shorter timeframes, you may see less than the total of lines that you selected in settings. This is particularly the case with quarterly VWAP lines on the 5 minute timeframe for some equities.
Acknowledgements
This script uses the MarketHolidays library by @Protervus. Also, for debugging, the JavaScript-style Debug Console by @algotraderdev was invaluable. Special thanks to @antsmuzic for helping review and debug the script. And, of course, without Brian Shannon's books, videos, and interviews, this indicator would would not have happened.
Inflation IndicatorThis script provides a great view of Year-over-Year (YoY) inflation rates for key countries.
The inflation data used per default are TradingView Tickers, but you can change them to anything you want from the settings.
There is no calculation in this script, all it does is providing a overview of inflation rates in a single indicator.
Inflation data for the USA, European Union, Australia, Canada, Switzerland, Japan, United Kingdom, and New Zealand (Inflation Symbols editable in the settings)
Customizable static line to indicate a specific threshold value (default: 2.0).
Table displaying country flags, names, and the latest inflation rates.
Country-representative colors for easy identification.
Multi VWAP [MW]Introduction
The Multi VWAP tool extends the concept of using the Anchored Volume Weighted Average Price, popularized by its founder, Brian Shannon, founder of AlphaTrends, and creates automatic AVWAPS for multiple anchor points, such as for 2-day, 3-day, 4-day, 5-day, and custom date anchors as well as automagically creating month-to-date and year-to-date anchors. Currently, most standard VWAP tools allow users to place custom anchored VWAPs, but the routine of doing this for every equity being watched can become cumbersome. This tool makes that process multi-times easier. Brian Shannon is also the author of “Maximum Trading Gains With Anchored VWAP: The Perfect Combination of Price, Time, and Volume”. Available at Amazon.
Settings
Daily VWAP : A continuous line of the the daily Volume Weighted Average Price (VWAP)
Weekly VWAP : A continuous line of the weekly VWAP
2-Day AVWAP : The anchored VWAP from 2 trading days ago (holidays and weekends are excluded in this calculation)
3-Day AVWAP : The anchored VWAP from 3 trading days ago
4-Day AVWAP : The anchored VWAP from 4 trading days ago
5-Day AVWAP : The anchored VWAP from 5 trading days ago. The slope of this line and the position of the price relative to this line can be used to determine trend direction.
10-Day AVWAP : The anchored VWAP from 10 trading days ago
Month-to-Date AVWAP : The anchored VWAP from the beginning of the current month
Year-to-Date AVWAP : The anchored VWAP from the beginning of the current year
Custom Date AVWAP : Sets a date to begin an anchored VWAP starting from any time.
Use only the most recent VWAP for Week, Month, and Year: Toggles on and off the continuous weekly, monthly, and yearly VWAPs
Calculations
This indicator does not provide buy or sell signals. It is simply the VWAP calculated starting from an “anchor point”, or start time. It is the calculated by the summation of Price x Volume / Volume for the period starting at the anchor point.
How to Interpret
According to Brian Shannon, VWAP is an objective measure of what the average trader has paid for a particular equity over a given period, and is the value that large institutional investors frequently use as a trade signal. Therefore, by definition, when the price is above an AVWAP, buyers are in control for that period of time. Likewise, if the price is below the AVWAP, sellers are in control for that period of time.
Shannon also distinguishes the importance of an increasing or decreasing 5 day VWAP, which reflects the price sentiment, objectively, for roughly the last trading week, or 5 trading days. Pricing below a decreasing 5-day VWAP is considered very bearish, while pricing above an increasing 5-day VWAP is considered bullish and is recommended before considering long positions.
Additionally, a custom VWAP can be generated to coincide with important events, such as FOMC meetings, CPI reports, earnings reports, etc.
Practically speaking, price action can tend to change direction when a significant VWAP is hit, voiding buy and sell signals. Like moving averages, this indicator can show, in real-time, how a buy or sell signal should be interpreted. A significant AVWAP line is a point of interest, and can serve as strong support or resistance, because large institutions may be using those values for entries or exits. For a great analysis of how to use AVWAP, visit the AlphaTrends channel on Youtube here or you can buy Brian Shannon’s “Anchored VWAP” book on Amazon.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Additionally, the indicator may take a little longer to load than usual. On the rare occasion where it fails to load, you may need to remove the indicator and add it back to your chart. Also, if you do encounter this problem, avoid redrawing your chart while the indicator is being added to the screen.
Acknowledgements
This script uses the MarketHolidays library by @Protervus. Also, for debugging, the JavaScript-style Debug Console by @algotraderdev and the TimeFormattingLibrary by @twingall were invaluable. And, of course, without Brian Shannon's books, videos, and interviews, this indicator would would not be possible.
Economic Data Trading alerts - CPI, Interest rate, PPI, etcDescription:
This indicator is designed to alert based on user-selected economic data for Europe, the US, and Japan. It allows users to define their preferred economic data points and trade direction based on the change in the economic data compared to the previous value.
you can use the strategy to automate economic data trading.
Key Features:
Choose from various economic data points for Europe, the US, and Japan.
Customize trade direction based on whether the economic data is above or below the previous value.
Define entry conditions based on user preferences.
Visualize trade entries on the chart.
Display a table showing the results of executed trades.
Please note that this strategy is provided for educational purposes only and should not be considered as financial advice. Always do your own research and use proper risk management when trading.
The indicator is BETA please make sure to test it before using it.
IMPORTANT: you need to be aware of the fundmentals because the regime changes and markets react to every release of data differently.
Selected Dates Filter by @zeusbottradingWe are presenting you feature for strategies in Pine Script.
This function/pine script is about NOT opening trades on selected days. Real usage is for bank holidays or volatile days (PPI, CPI, Interest Rates etc.) in United States and United Kingdom from 2020 to 2030 (10 years of dates of bank holidays in mentioned countries above). Strategy is simple - SMA crossover of two lengts 14 and 28 with close source.
In pine script you can see we picked US and GB bank holidays. If you add this into your strategy, your bot will not open trades on those days. You must make it a rule or a condition. We use it as a rule in opening long/short trades.
You can also add some of your prefered dates, here is just example of our idea. If you want to add your preffered days you can find them on any site like forexfactory, myfxbook and so on. But don’t forget to add function “time_tradingday ! = YourChoosedDate” as it is writen lower in the pine script.
Sometimes the date is substituted for a different day, because the day of the holiday is on Saturday or Sunday.
Made with ❤️ for this community.
If you have any questions or suggestions, let us know.
The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold zeusbottrading TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script.
Multi-Polar WorldA new macro analysis tool for easily analyzing the multi-polar world's economic powerhouses / spheres of influence, making for an easy to use visual when comparing a number of statistics:
GDP, GDP per Capita, External Debt, Government Debt, Exports, Imports, Gold Reserves, Employed Persons, Military Expenditure, Population, Bank Lending Rate, Balance of Trade, Central Bank Balance Sheet, M2 Money Supply, and CPI . Includes option to provide the total for each pole, or view individually for more detailed comparison. Meant to be used when analyzing the macro-economic conditions/trends in conjunction with other "Big Picture" type indicators when adjusting your macro framework.
TheMas7er scalp (US equity) 5min [promuckaj]This indicator was created according to TheMas7er's trading setup, that he reveal after 18 years of working in the industry. Claims is that this setup should give you good probability to predict the price movement for US equity.
This trading setup is only for New York equity trading session from 09:30 until 4pm. The market in which you should use it are the S&P 500 , Dow Jones, and Nasdaq. Perhaps it will work on some other but for those are good according to tests. It should not used on days with high-impact news, like CPI , FOMC, NFP and so on. The model can still work there but the probability on these days is way lower.
What is the base of this indicator, it marks what is called "The Defining Range"("DR"). This defining range is from 09:30am until 10:30am New York local time, it takes those 12 candles in the 5min chart. Indicator will mark the high and low of this range, including wicks. This will help you to already know at 10:30am, with possible good probability the high or low of the day.
There is also the "Implied Defining Range"("iDR") lines inside the "DR" range, which mark the highest body and the lowest body in the "DR" range.
*The rules (it is very simple to follow):
Chart must be set in 5min timeframe.
At 10:30am you still don't know which one will be the real high or low of the day, but only one will be true.
If price is closing on 5min chart above the "DR" it should give you good probability that the low of the "DR" is the low of the day, and vice versa - if price is closing below the "DR" it should give you good probability that the high of the "DR" is the high of the day.
"iDR" gives you an early indication about what high or low of the day should be. If price is closing above "iDR" you will have an early indication that the low of the "DR" should be the low of the day, and vice versa.
Note that about closing means really closing above or below, not just wicks.
Now, after this you can realize the magnitude of possibility.
You can use any entry model you prefer to trade, it doesn't matter if you use ICT concepts, smart money concepts, volume profile , eliot waves, braking the structure concept or whatever. There are so many possibilities for trading within this rule.
Enjoy!
Economic Calendar (Import from Spreadsheet)This script draws vertical lines to mark Economic Calendar Events.
Datetime of events is defined by user in Settings via a standardized line of text.
Motivation for coding this script:
All traders should be aware of economic calendar events. At times, when you really need to pay attention to an upcoming major event, you might even decide to use the vertical-line drawing tool to mark it. However, this takes manual effort.
This script provides a solution to performing mundane tasks such as drawing vertical lines and dragging them ever so slightly, just to have them approximately aligned with exact time.
Parameters:
(1) Source data - String representation of collection of datetime referencing to Economic Calendar Events
(2) Line color, & (3) Width of line - For displaying vertical lines drawn by script.
Standardized format for Source Data :
Example:
If 'GMT;2022,6,1,14,0,0;2022,6,2,12,15,0;' is provided to PineScript, then two vertical lines will be drawn on June 6, 2022 according to the exact time in 'YYYY,MM,DD,hh,mm,ss' format at the specified timezone (GMT in this case).
Template for Source Data :
Included here, link below, is a shared Google Sheet that systematically processes Economic Calendar data provided in the 'Raw Data' tab.
drive.google.com
Users are advised to use their preferred methods* to format the string (for source data param.), and apply their own criteria to sort down the Events. (ie. only include Events of High Impact, etc.)
* Preferred methods (as mentioned above) does not mean being limited to using the template as provided in this post.
Daily RTH Moving Average On Intraday Timeframes [vnhilton]This indicator is intended for intraday use from the daily timeframe down to the 1 minute. Outside this range, the indicator won't work as intended.
Higher timeframe moving averages are step-lines as they use values from higher timeframes to calculate the moving average. To have a smoother moving average from higher timeframes plotted on lower timeframes, this indicator uses the chart timeframe's candles, allowing for a smooth higher timeframe moving average. This indicator also includes Bollinger Bands. Note that the indicator only uses values from regular trading hours, as to not give weighting to values from extended trading hours.
In the chart above, at October 7th, pre-market price action is bearish due to fundamentals around US employment data. This day led to an all-day-fader, stopping above the June low after attempting to break down the level again (previous breakdown attempts led to the September low). Note that the price is within the Bollinger bands of the 5 day moving average. We can see in the following days that $SPY trended downwards, staying below the anchored VWAP when the October 7th news released, & pay attention to October 10th, where price attempts to make a new low-of-day but ends up outside the 5 day period ma, leading to a reversal. Look at October 13th, where pre-market price action again shows bearish sentiment, but due to fundamentals around CPI data. $SPY opens below the September low, but also ends up outside the daily 5 period MA bands, meaning that the downside extension has extended too far, signalling for a reversion to the mean. This is why October 13th didn't lead to another all-day-fader, & instead trapped sellers trying to short the pre-market low, helping to fuel the relief rally to cause the upsides the June & September lows, & the anchored VWAPs from both significant pre-market events, to be reclaimed, where price pauses at the confluence of the 5 day moving average & the June low.
