Goldprediction — Indicators and Strategies

Aurum DCX AVE Gold and Silver Strategy Summary in one paragraph Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter. Scope and intent • Markets. Gold and silver futures or spot, other liquid commodities, major indices • Timeframes. Five minutes to one day. Defaults to 30min for swing pace • Default demo used in this publication. TVC:GOLD on 30m • Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias • Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings • Testability. Each component has a named input. Entry names L and S are visible in the list of trades • Portable yardstick. Weekly ATR for stops and R multiples for targets • Open source. Method and implementation are disclosed for community review Method overview in plain language You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope. Base measures • Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE • Return basis. Not required Components • Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window • Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat • DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens • Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band Fusion rule • All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled Signal rule • Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish • Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish • Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band Inputs with guidance Setup • Symbol. Default TVC:GOLD (Correlation Asset for internal logic) • Signal timeframe. Blank follows the chart • Confirm timeframe. Default 1 day used by the bias block Directional Convexity Index • DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier • DCX rise bars. Typical 3 to 6. Higher demands continuation • DCX entry threshold. Typical 15 to 35. Higher avoids soft moves • Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape • Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence Adaptive Volatility Envelope • AVE window. Typical 24 to 48. Higher smooths more • Midline type. ALMA or HMA or EMA per preference • TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions • Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR • Base envelope mult. Typical 1.4 to 2.2. Width of bands • Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands Intermarket Bias • Use DXY bias. Default ON • DXY timeframe. Default 1 day • DXY trend window. Typical 10 to 50 Risk • Risk percent per trade. Reporting field. Keep live risk near one to two percent • Weekly ATR. Default 14. Basis for stops • Stop ATR weekly mult. Typical 1.5 to 3.0 • Take profit R multiple. Typical 1.5 to 3.0 • Trail with AVE band. Optional. OFF by default Properties visible in this publication • Initial capital. 20000 • Base currency. USD • request.security lookahead off everywhere • Commission. 0.03 percent • Slippage. 5 ticks • Default order size method percent of equity with value 3% of the total capital available • Pyramiding 0 • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Realism and responsible publication • No performance claims. Past results never guarantee future outcomes • Shapes can move while a bar forms and settle on close • Strategies use standard candles for signals and orders only Honest limitations and failure modes • Economic releases and thin liquidity can break assumptions behind the expansion logic • Gap heavy symbols may prefer a longer ATR window • Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands • Session time follows the exchange of the chart and can change symbol to symbol • Symbol sensitivity is expected. Use the gates and length inputs to find stable settings Open source reuse and credits • None Mode Public open source. Source is visible and free to reuse within TradingView House Rules Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.

Hazel nut BB Strategy, volume base- lite version Hazel nut BB Strategy, volume base — lite version Having knowledge and information in financial markets is only useful when a trader operates with a well-defined trading strategy. Trading strategies assist in capital management, profit-taking, and reducing potential losses. This strategy is built upon the core principle of supply and demand dynamics. Alongside this foundation, one of the widely used technical tools — the Bollinger Bands — is employed to structure a framework for profit management and risk control. In this strategy, the interaction of these tools is explained in detail. A key point to note is that for calculating buy and sell volumes, a lower timeframe function is used. When applied with a tick-level resolution, this provides the most precise measurement of buyer/seller flows. However, this comes with a limitation of reduced historical depth. Users should be aware of this trade-off: if precise tick-level data is required, shorter timeframes should be considered to extend historical coverage . The strategy offers multiple configuration options. Nevertheless, it should be treated strictly as a supportive tool rather than a standalone trading system. Decisions must integrate personal analysis and other instruments. For example, in highly volatile assets with narrow ranges, it is recommended to adjust profit-taking and stop-loss percentages to smaller values. ◉ Volume Settings • Buyer and seller volume (up/down volume) are requested from a lower timeframe, with an option to override the automatic resolution. • A global lookback period is applied to calculate moving averages and cumulative sums of buy/sell/delta volumes. • Ratios of buyers/sellers to total volume are derived both on the current bar and across the lookback window. ◉ Bollinger Band • Bands are computed using configurable moving averages (SMA, EMA, RMA, WMA, VWMA). • Inputs allow control of length, standard deviation multiplier, and offset. • The basis, upper, and lower bands are plotted, with a shaded background between them. ◉ Progress & Proximity • Relative position of the price to the Bollinger basis is expressed as percentages (qPlus/qMinus). • “Near band” conditions are triggered when price progress toward the upper or lower band exceeds a user-defined threshold (%). • A signed score (sScore) represents how far the close has moved above or below the basis relative to band width. ◉ Info Table • Optional compact table summarizing: • - Upper/lower band margins • - Buyer/seller volumes with moving averages • - Delta and cumulative delta • - Buyer/seller ratios per bar and across the window • - Money flow values (buy/sell/delta × price) for bar-level and summed periods • The table is neutral-colored and resizable for different chart layouts. ◉ Zone Event Gate • Tracks entry into and exit from “near band” zones. • Arming logic: a side is armed when price enters a band proximity zone. • Trigger logic: on exit, a trade event is generated if cumulative buyer or seller volume dominates over a configurable window. ◉ Trading Logic • Orders are placed only on zone-exit events, conditional on volume dominance. • Position sizing is defined as a fixed percentage of strategy equity. • Long entries occur when leaving the lower zone with buyer dominance; short entries occur when leaving the upper zone with seller dominance. ◉ Exit Rules • Open positions are managed by a strict priority sequence: • 1. Stop-loss (% of entry price) • 2. Take-profit (% of entry price) • 3. Opposite-side event (zone exit with dominance in the other direction) • Stop-loss and take-profit levels are configurable ◉ Notes • This lite version is intended to demonstrate the interaction of Bollinger Bands and volume-based dominance logic. • It provides a framework to observe how price reacts at band boundaries under varying buy/sell pressure, and how zone exits can be systematically converted into entry/exit signals. When configuring this strategy, it is essential to carefully review the settings within the Strategy Tester. Ensure that the chosen parameters and historical data options are correctly aligned with the intended use. Accurate back testing depends on applying proper configurations for historical reference. The figure below illustrates sample result and configuration type.

SuperTrade ST1 Strategy Overview The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk. This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency. How It Works This strategy leverages three key components: Supertrend Indicator A trend-following indicator based on Average True Range (ATR). Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility. 200-period Exponential Moving Average (EMA) Filter Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends. Helps filter out counter-trend entries during market pullbacks or ranges. ATR-Based Stop Loss and Take Profit Each trade uses the ATR to calculate volatility-adjusted exit levels. Stop Loss: 1× ATR below entry. Take Profit: 4× ATR above entry (1:4 R:R). This asymmetry ensures that even with a lower win rate, the strategy can remain profitable. Entry Conditions A long trade is triggered when: Supertrend flips from bearish to bullish (trend reversal). Price closes above the Supertrend line. Price is above the 200 EMA (bullish market bias). Exit Logic Once a long position is entered: Stop loss is set 1 ATR below entry. Take profit is set 4 ATR above entry. The strategy automatically exits the position on either target. Backtest Settings This strategy is configured for realistic backtesting, including: $10,000 account size 2% equity risk per trade 0.1% commission 1 tick slippage These settings aim to simulate real-world conditions and avoid overly optimistic results. How to Use Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals. Works best in clearly trending markets (especially in crypto, stocks, indices). Can be paired with alerts for live trading or analysis. Important Notes This version is long-only by design. No short positions are executed. Ideal for swing traders or position traders seeking asymmetric returns. Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.