Sigmoid Allocation Indicator & DashboardTL;DR This sigmoid-based allocation indicator tells you percentage of your portfolio to invest based on how much the market has dropped.
Market at all-time high? → Stay defensive, invest less (e.g., 30%)
Market crashed hard? → Get aggressive, invest more (e.g., 100%)
The "sigmoid" part just means the transition between these two extremes follows a smooth S-shaped curve.
Description
This indicator is a sigmoid-based allocation system that dynamically adjusts a portfolio exposure based on market drawdown.
It compares multiple steepness curves (K values) to find your optimal risk profile for leveraged ETF strategies, but it can also be used to scale in-out from stocks, crypto and to understand whether to use leverage or not.
The Sigmoid Allocation Dashboard helps you to dynamically adjust a portfolio allocation based on how much a market has dropped from its all-time high.
I've implemented it using a sigmoid (S-curve) function, that dynamically calculates the optimal allocation percentages. Depending on the market conditions, the S curves transition between defensive and aggressive allocations.
The Math Behind It (if you are a geek like me)
This indicator uses the sigmoid function to create smooth S-curve transitions:
α(D) = α_min + (α_max - α_min) × σ(k × (D - D_mid))
Where:
σ(x) = 1 / (1 + e^(-x)) ← Standard sigmoid function
You can also check it here:
// Sigmoid function: σ(x) = 1 / (1 + e^(-x))
sigmoid(float x) =>
1.0 / (1.0 + math.exp(-x))
// Alpha calculation: α(D) = α_min + (α_max - α_min) × σ(k × (D - D_mid))
calcAlpha(float drawdown, float k, float a_min, float a_max, float d_midpoint) =>
sig_input = k * (drawdown - d_midpoint) / 100.0
a_min + (a_max - a_min) * sigmoid(sig_input)
User parameters (you can tweak this):
Allocation Min (%): Your baseline allocation when markets are at ATH (default: 30%)
Allocation Max (%): Your maximum allocation during deep drawdowns (default: 100%)
D_mid (%): The drawdown level where you want to be at the midpoint (default: 25%)
Why do I like sigmoid and not a linear line?
Unlike linear models, the sigmoid creates "floors" and "ceilings" for your allocation. It transitions smoothly, no sudden jumps, and you never exceed your defined min/max bounds.
Understand the K Values (Steepness)
The K parameter controls how quickly your allocation shifts from defensive to aggressive.
Lower K (for example K=5) will give you a gradual transition, but at 0% drawdown you are already at a 46% allocation.
A higher like (like K=40) will give you a sharp transition, but at 0% drawdown you are close to the minimum allocation. On the other hand, a higher K will give close to 100% allocation when the markets are at new lows.
The example below illustrates this well, then the S&P 500 reached new lows in October 2022:
Different K values will affect the sigmoid curves (and you allocations differently). The chart below illustrates well how K affects the sigmoid curves:
Read the Dashboard
The main dashboard shows:
Current drawdown from ATH
Allocation % for each K value
Suggested action (Defensive → MAX LONG)
Use the Reference Chart
The static reference panel shows what your allocation would be at various drawdown levels (0%, 10%, 20%, 30%, 40%, 50%), helping you plan ahead.
Identify Zones
The color-coded chart background shows:
- 🟢 Green Zone: Aggressive positioning - "Buy the Dip"
- 🟡 Yellow Zone: Transition zone - Scaling in/out
- 🔴 Red Zone: Defensive positioning - Protect ya gains
Use Cases
Use case 1: Leveraged ETF Portfolio Management (this is my main use case)
When holding leveraged ETFs like TQQQ or UPRO, volatility makes it important to:
- Reduce exposure near all-time highs (when crashes hurt most)
- Increase exposure during drawdowns (when recovery potential is highest)
Example Strategy:
- At ATH: Hold 30% TQQQ, 70% cash/bonds or other uncorrelated assets
- At 25% drawdown: Hold 65% TQQQ, 35% cash/bonds
- At 40%+ drawdown: Hold 100% TQQQ
Use case 2: Diversified Leveraged Portfolio
Compare different K values for different assets:
- Use K = 10 for broad market (QQQ/SPY exposure via TQQQ/UPRO)
- Use K = 25 for sector bets (TECL, SOXL, TMF) that you want to scale into faster
Use case 3: Systematic Rebalancing Signals
Use the alerts to trigger rebalancing:
- Alert when K3 allocation crosses above 90% (time to add)
- Alert when drawdown exceeds your D_mid threshold
- Alert when market returns to within 5% of ATH
Tips for Best Results
It works best in longer time frames
Adjust the ATR lookback window
Match your risk tolerance level
I use this for index investing and stocks and haven't tried with crypto
Thanks for using the indicator and let me know if you have any feedback :)
- Henrique Centieiro
포트폴리오 관리
BTC Fundamental Value Hypothesis [OmegaTools]BTC Fundamental Value Hypothesis is a macro-valuation and regime-detection model designed to contextualize Bitcoin’s price through relative market-cap comparisons against major capital reservoirs: Gold, Silver, the Altcoin market, and large-cap equities. Instead of relying on traditional on-chain metrics or purely technical signals, this tool frames BTC as an asset competing for global liquidity and “store-of-value mindshare”, then estimates an implied fair value based on how BTC historically coexists (or diverges) from these benchmark universes.
Core concept: relative market-cap anchoring
The indicator builds a reference-based fair price by translating external market capitalizations into implied BTC valuation using a dominance framework. In practice, you choose one or more reference universes (Gold, Silver, Altcoins, Stocks). For each selected universe, the script computes how large BTC “should be” relative to that universe (dominance ratio), and converts that into an implied BTC price. The final fair price is the average of the implied prices from the enabled universes.
Two dominance modes: automatic vs manual
1. Automatic Dominance % (default)
When enabled, the model estimates dominance ratios dynamically using a 252-period simple moving average of BTC market cap divided by each reference market cap. This produces an adaptive baseline that follows structural changes over time and reduces sensitivity to short-term spikes.
2. Manual Dominance %
If you prefer a discretionary macro thesis, you can directly input dominance parameters for each reference universe. This is useful when you want to stress-test scenarios (e.g., “BTC should converge toward X% of Gold’s market cap”) or align the model with a specific long-term adoption narrative.
Reference universes and data construction
- BTC market cap: pulled from CRYPTOCAP:BTC.
- Gold and Silver market caps: derived from the corresponding futures symbols (GC1!, SI1!) multiplied by an assumed total above-ground quantity (constant tonnage converted to troy ounces). This provides a practical and tradable proxy for spot valuation context.
- Altcoin market cap: pulled from CRYPTOCAP:TOTAL2 (total crypto market excluding BTC).
- Stocks market cap proxy (Σ3): a deliberately conservative equity benchmark built from three mega-cap stocks (AAPL, MSFT, AMZN) using total shares outstanding (request.financial) multiplied by price. This avoids index licensing complexity while still tracking a meaningful slice of global equity beta/liquidity.
Valuation output: overvalued vs undervalued (log-based)
The valuation readout is expressed as a percentage derived from the logarithmic distance between BTC price and the model’s fair price. This choice makes valuation comparable across long time horizons and reduces distortion during exponential growth phases. A positive valuation indicates BTC trading below the model’s implied value (undervalued), while a negative valuation indicates trading above it (overvalued).
Oscillator: relative momentum and regime confirmation
In addition to fair value, the indicator includes a momentum differential oscillator built from RSI(50):
- BTC RSI is compared to the average RSI of the selected reference universes.
- The oscillator highlights when BTC strength is leading or lagging the broader macro benchmarks.
- Color is rendered through a gradient to provide immediate regime readability (risk-on vs risk-off behavior, expansion vs contraction phases).
Visualization and UI components
- Fair Price overlay: the computed fair price is plotted directly on the BTC chart for immediate comparison with spot price action.
- Valuation shading: the area between price and fair price is filled to visually emphasize dislocation and potential mean-reversion zones.
- Oscillator panel: a zero-centered oscillator with filled bands helps you identify persistent trend regimes versus transitional conditions.
- Summary table: a right-side table displays the current valuation (over/under) and, when Automatic mode is enabled, the live dominance ratios used in the model (BTC/GOLD, BTC/SILVER, BTC/ALTC, BTC/STOCKS).
How to use it (practical workflows)
- Macro valuation context: use fair price as a structural anchor to assess whether BTC is trading at a premium or discount relative to external liquidity baselines.
- Regime filtering: combine valuation with the oscillator to distinguish “cheap but weak” from “cheap and strengthening” (and the inverse for tops).
- Mean-reversion mapping: large, persistent deviations from fair value often highlight speculative extremes or capitulation zones; this can support systematic entries/exits, position sizing, or hedging decisions.
- Scenario analysis: switch to Manual Dominance % to model adoption outcomes, policy-driven shifts, or multi-year re-rating assumptions.
Important notes and limitations (read before use)
- This is a hypothesis-driven macro model, not a literal intrinsic value calculation. Results depend on dominance assumptions, proxies, and data availability.
- Gold/Silver market caps are approximations based on futures pricing and fixed supply constants; real-world supply dynamics, above-ground estimates, and spot/futures basis can differ.
- The Stocks (Σ3) benchmark is a proxy and intentionally not “the whole market”. It is designed to represent a large-cap liquidity reference, not total equity capitalization.
- Always validate signals with additional context (market structure, volatility regime, risk management rules). This indicator is best used as a macro layer in a broader decision framework.
Designed for clarity, macro discipline, and repeatability
BTC Fundamental Value Hypothesis by OmegaTools is built for traders and investors who want a clean, data-driven way to interpret BTC through the lens of competing asset classes and capital flows. It is particularly effective on higher timeframes (Daily/Weekly) where macro relationships are more stable and valuation signals are less noisy.
© OmegaTools, Eros
Mission Control Dashboard (AI, Crypto, Liquidity) FASTCONCEPT Price is a lagging indicator. Liquidity is a leading indicator. "Mission Control Dashboard (AI, Crypto, Liquidity) FAST" is a sophisticated macroeconomic dashboard designed to audit the "plumbing" of the financial system in real-time. Unlike standard indicators that rely solely on price action, this tool pulls data from the Federal Reserve (FRED), Treasury Statements, Corporate Financials (10-K/10-Q), and On-Chain Stablecoin metrics to visualize the structural flows driving the market.
THE "UNIFIED FIELD" SOLVER One of the hardest challenges in cross-asset scripting is "Time Dilation"—synchronizing 24/7 Crypto markets (Bitcoin) with Mon-Fri Traditional markets (Stocks/Bonds).
Standard scripts fail on weekends, showing mismatched data.
This engine uses a Weekly Anchor system. It calculates all momentum and liquidity metrics based on "Week-to-Date" or "Month-Ago" anchors. This ensures that a "Liquidity Drain" looks identical whether you are viewing a Bitcoin chart on Saturday or an Apple chart on Monday.
THE CHRONOS LOGIC The dashboard is sorted by Time Sensitivity (Speed of impact), from fast-twitch tactical signals to slow-moving structural fundamentals.
1. TACTICAL (Reacts in 24–48h)
Stablecoin Flight: Measures the immediate flow of capital from Volatile Assets to Stablecoins (USDT/USDC). A spike (>0.5%) indicates fear/sidelining.
Liquidity Alpha: Calculates the efficiency of capital. It subtracts "Friction" (Dollar Strength + Yields) from "Flow" (Liquidity Beta). High Alpha means money is flowing easily into risk assets.
Alt Euphoria: Tracks the overheating of the Altcoin market (TOTAL3). Green indicates sustainable growth; Red (>45%) warns of a "blow-off top."
Retail FOMO: A sentiment gauge comparing Coinbase Stock ( NASDAQ:COIN ) performance vs. Bitcoin ( CRYPTOCAP:BTC ). When Retail outperforms the Asset, local tops often follow.
2. LIQUIDITY & MACRO (Reacts in 1–4 Weeks)
Debt Wall (10Y): The Rate-of-Change of the US 10-Year Treasury Yield. Spiking yields act as gravity on risk assets.
Liquidity Beta: The raw "Quantity of Money." Tracks the 4-week change in Net Liquidity (Fed Balance Sheet - TGA + Stablecoins).
TGA Balance: The Critical Monitor. Tracks the Treasury General Account. When the TGA rises (Red), the government is draining liquidity from the banking system. When it falls (Green), it releases cash.
Note: This script includes an auto-scaler to handle TGA data in both Billions and Millions.
3. STRUCTURAL (Reacts in 3–12 Months)
AI Capex (YoY & QoQ): The "Floor" of the 2025/2026 cycle. Tracks the Capital Expenditure of the Hyperscalers (MSFT, GOOGL, AMZN, META). As long as this remains high (>30%), the infrastructure boom supports the tech narrative.
PMI Manufacturing: Tracks the ISM Manufacturing cycle. Contraction (<50) often forces Fed intervention.
Micron Inventory: A lead indicator for the hardware cycle.
HOW TO USE
Status Colors: The traffic light system helps you assess risk at a glance.
🟢 GREEN (Healthy): Flow is positive, friction is low, fundamentals are strong.
🔴 RED (Danger): Liquidity is draining (TGA spike), yields are shock-rising, or FOMO is excessive.
Zero Configuration: The script auto-detects asset classes and scales units (Billions/Trillions) automatically.
DATA SOURCES
Federal Reserve Economic Data (FRED)
Daily Treasury Statement (DTS)
CryptoCap (TradingView)
Nasdaq/Corporate Financials
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. Macro data feeds are subject to reporting delays.
Manual PNL TrackerEnter your USD position size, direction and entry price to track it realtime in the chart without needing to use TV brokers for it.
Asset Drift ModelThis Asset Drift Model is a statistical tool designed to detect whether an asset exhibits a systematic directional tendency in its historical returns. Unlike traditional momentum indicators that react to price movements, this indicator performs a formal hypothesis test to determine if the observed drift is statistically significant, economically meaningful, and structurally stable across time. The result is a classification that helps traders understand whether historical evidence supports a directional bias in the asset.
The core question the indicator answers is simple: Has this asset shown a reliable tendency to move in one direction over the past three years, and is that tendency strong enough to matter?
What is drift and why does it matter
In financial economics, drift refers to the expected rate of return of an asset over time. The concept originates from the geometric Brownian motion model, which describes asset prices as following a random walk with an added drift component (Black and Scholes, 1973). If drift is zero, price movements are purely random. If drift is positive, the asset tends to appreciate over time. If negative, it tends to depreciate.
The existence of drift has profound implications for trading strategy. Eugene Fama's Efficient Market Hypothesis (Fama, 1970) suggests that in efficient markets, risk-adjusted drift should be minimal because prices already reflect all available information. However, decades of empirical research have documented persistent anomalies. Jegadeesh and Titman (1993) demonstrated that stocks with positive past returns continue to outperform, a phenomenon known as momentum. DeBondt and Thaler (1985) found evidence of long-term mean reversion. These findings suggest that drift is not constant and can vary across assets and time periods.
For practitioners, understanding drift is fundamental. A positive drift implies that long positions have a statistical edge over time. A negative drift suggests short positions may be advantageous. No detectable drift means the asset behaves more like a random walk, where directional strategies have no inherent advantage.
How professionals use drift analysis
Institutional investors and hedge funds have long incorporated drift analysis into their systematic strategies. Quantitative funds typically estimate drift as part of their alpha generation process, using it to tilt portfolios toward assets with favorable expected returns (Grinold and Kahn, 2000).
The challenge lies not in calculating drift but in determining whether observed drift is genuine or merely statistical noise. A naive approach might conclude that any positive average return indicates positive drift. However, financial returns are noisy, and short samples can produce misleading estimates. This is why professional quants rely on formal statistical inference.
The standard approach involves testing the null hypothesis that expected returns equal zero against the alternative that they differ from zero. The test statistic is typically a t-ratio: the sample mean divided by its standard error. However, financial returns often exhibit serial correlation and heteroskedasticity, which invalidate simple standard errors. To address this, practitioners use heteroskedasticity and autocorrelation consistent standard errors, commonly known as HAC or Newey-West standard errors (Newey and West, 1987).
Beyond statistical significance, professional investors also consider economic significance. A statistically significant drift of 0.5 percent annually may not justify trading costs. Conversely, a large drift that fails to reach statistical significance due to high volatility may still inform portfolio construction. The most robust conclusions require both statistical and economic thresholds to be met.
Methodology
The Asset Drift Model implements a rigorous inference framework designed to minimize false positives while detecting genuine drift.
Return calculation
The indicator uses logarithmic returns over non-overlapping 60-day periods. Non-overlapping returns are essential because overlapping returns introduce artificial autocorrelation that biases variance estimates (Richardson and Stock, 1989). Using 60-day horizons rather than daily returns reduces noise and captures medium-term drift relevant for position traders.
The sample window spans 756 trading days, approximately three years of data. This provides 12 independent observations for the full sample and 6 observations per half-sample for structural stability testing.
Statistical inference
The indicator calculates the t-statistic for the null hypothesis that mean returns equal zero. To account for potential residual autocorrelation, it applies a simplified HAC correction with one lag, appropriate for non-overlapping returns where autocorrelation is minimal by construction.
Statistical significance requires the absolute t-statistic to exceed 2.0, corresponding to approximately 95 percent confidence. This threshold follows conventional practice in financial econometrics (Campbell, Lo, and MacKinlay, 1997).
Power analysis
A critical but often overlooked aspect of hypothesis testing is statistical power: the probability of detecting drift when it exists. With small samples, even substantial drift may fail to reach significance due to high standard errors. The indicator calculates the minimum detectable effect at 95 percent confidence and requires observed drift to exceed this threshold. This prevents classifying assets as having no drift when the test simply lacks power to detect it.
Robustness checks
The indicator applies multiple robustness checks before classifying drift as genuine.
First, the sign test examines whether the proportion of positive returns differs significantly from 50 percent. This non-parametric test is robust to distributional assumptions and verifies that the mean is not driven by outliers.
Second, mean-median agreement ensures that the mean and median returns share the same sign. Divergence indicates skewness that could distort inference.
Third, structural stability splits the sample into two halves and requires consistent signs of both means and t-statistics across sub-periods. This addresses the concern that drift may be an artifact of a specific regime rather than a persistent characteristic (Andrews, 1993).
Fourth, the variance ratio test detects mean-reverting behavior. Lo and MacKinlay (1988) showed that if returns follow a random walk, the variance of multi-period returns should scale linearly with the horizon. A variance ratio significantly below one indicates mean reversion, which contradicts persistent drift. The indicator blocks drift classification when significant mean reversion is detected.
Classification system
Based on these tests, the indicator classifies assets into three categories.
Strong evidence indicates that all criteria are met: statistical significance, economic significance (at least 3 percent annualized drift), adequate power, and all robustness checks pass. This classification suggests the asset has exhibited reliable directional tendency that is both statistically robust and economically meaningful.
Weak evidence indicates statistical significance without economic significance. The drift is detectable but small, typically below 3 percent annually. Such assets may still have directional tendency but the magnitude may not justify concentrated positioning.
No evidence indicates insufficient statistical support for drift. This does not prove the asset is driftless; it means the available data cannot distinguish drift from random variation. The indicator provides the specific reason for rejection, such as failed power analysis, inconsistent sub-samples, or detected mean reversion.
Dashboard explanation
The dashboard displays all relevant statistics for transparency.
Classification shows the current drift assessment: Positive Drift, Negative Drift, Positive (weak), Negative (weak), or No Drift.
Evidence indicates the strength of evidence: Strong, Weak, or None, with the specific reason for rejection if applicable.
Inference shows whether the sample is sufficient for analysis. Blocked indicates fewer than 10 observations. Heuristic indicates 10 to 19 observations, where asymptotic approximations are less reliable. Allowed indicates 20 or more observations with reliable inference.
The t-statistics for full sample and both half-samples show the test statistics and sample sizes. Double asterisks denote significance at the 5 percent level.
Power displays OK if observed drift exceeds the minimum detectable effect, or shows the MDE threshold if power is insufficient.
Sign Test shows the z-statistic for the proportion test. An asterisk indicates significance at 10 percent.
Mean equals Median indicates agreement between central tendency measures.
Struct(m) shows structural stability of means across half-samples, including the standardized level deviation.
Struct(t) shows whether t-statistics have consistent signs across half-samples.
VR Test shows the variance ratio and its z-statistic. An asterisk indicates the ratio differs significantly from one.
Econ. Sig. indicates whether drift exceeds the 3 percent annual threshold.
Drift (ann.) shows the annualized drift estimate.
Regime indicates whether the asset exhibits mean-reverting behavior based on the variance ratio test.
Practical applications for traders
For discretionary traders, the indicator provides a quantitative foundation for directional bias decisions. Rather than relying on intuition or simple price trends, traders can assess whether historical evidence supports their directional thesis.
For systematic traders, the indicator can serve as a regime filter. Trend-following strategies may perform better on assets with detectable positive drift, while mean-reversion strategies may suit assets where drift is absent or the variance ratio indicates mean reversion.
For portfolio construction, drift analysis helps identify assets where long-only exposure has historical justification versus assets requiring more balanced or tactical positioning.
Limitations
This indicator performs retrospective analysis and does not predict future returns. Past drift does not guarantee future drift. Markets evolve, regimes change, and historical patterns may not persist.
The three-year sample window captures medium-term tendencies but may miss shorter regime changes or longer structural shifts. The 60-day return horizon suits position traders but may not reflect intraday or weekly dynamics.
Small samples yield heuristic rather than statistically robust results. The indicator flags such cases but users should interpret them with appropriate caution.
References
Andrews, D.W.K. (1993) Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4).
Black, F. and Scholes, M. (1973) The pricing of options and corporate liabilities. Journal of Political Economy, 81(3).
Campbell, J.Y., Lo, A.W. and MacKinlay, A.C. (1997) The econometrics of financial markets. Princeton: Princeton University Press.
DeBondt, W.F.M. and Thaler, R. (1985) Does the stock market overreact? Journal of Finance, 40(3).
Fama, E.F. (1970) Efficient capital markets: a review of theory and empirical work. Journal of Finance, 25(2).
Grinold, R.C. and Kahn, R.N. (2000) Active portfolio management. 2nd ed. New York: McGraw-Hill.
Jegadeesh, N. and Titman, S. (1993) Returns to buying winners and selling losers. Journal of Finance, 48(1).
Lo, A.W. and MacKinlay, A.C. (1988) Stock market prices do not follow random walks. Review of Financial Studies, 1(1).
Newey, W.K. and West, K.D. (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3).
Richardson, M. and Stock, J.H. (1989) Drawing inferences from statistics based on multiyear asset returns. Journal of Financial Economics, 25(2).
Time Anchored FX LevelFX-Anchored Price Level
This indicator anchors a historical price at a specific date and time, and optionally links that anchor to a secondary FX rate to create a dynamic, currency-aware price level.
Thus, e.g. one visualize a past BTCEUR price on a BTCUSD chart now.
At the selected timestamp, the script captures the chart price using the chosen timeframe and price source.
If a secondary ticker is provided (for example, an FX rate), the anchored value is fixed in that secondary currency and then converted back to the chart currency on every bar. The result is a moving level that reflects changes in the exchange rate over time.
If no secondary ticker is set, the indicator behaves as a classic time-anchored price level and plots a constant historical price.
Key features
* Anchor a price to an exact date and time (string input with optional hour offset)
* Optional secondary ticker for FX or cross-rate conversion
* Dynamic level plotted as a series (updates like a moving average)
* User-selectable calculation timeframe and price source (Open, Close, etc.)
* Visual anchor marker at the original timestamp
* Last-bar price label for clear readability
Typical use cases
* FX buyback or re-entry levels after converting proceeds into another currency
* Evaluating historical prices in constant-currency terms
* Comparing past executions to current market conditions
* Anchoring risk or valuation levels across time and exchange rates
This tool is designed for traders who need precise, time-anchored reference levels that remain meaningful as currencies and markets evolve.
BTC - Standard of Living BenchmarkerOVERVIEW
Most traders track their wealth in USD or EUR — currencies that are structurally designed to lose value. This is a "Money Illusion." To understand if you are truly becoming wealthier, you must measure your Bitcoin not against fiat, but against the Standard of Living assets you eventually want to buy.
The Standard of Living Benchmarker is a macro-ratio engine that swaps the denominator of your chart. It answers the only question that matters for long-term wealth: "Is my Bitcoin stack gaining ground against the real world?"
THE "Stuff" BENCHMARKS
I have pre-selected four critical pillars of a high standard of living (that can be switched/cycled in the settings window):
• Gold: The historical baseline for "Hard Money" (TVC:GOLD).
• Equities: The primary engine of global productivity (S&P 500).
• Real Estate: Measured via the Vanguard Real Estate ETF (VNQ).
• Energy: The fundamental cost of human progress (Crude Oil).
THE CORE CALCULATION
The calculation is a simple, non-manipulated ratio:
• The Formula: Ratio = BTC_Price / Asset_Price
• This means: We are looking at the direct barter-rate between Bitcoin and the asset. For example, when the "Energy" mode is selected, the chart doesn't show dollars; it shows exactly how many Barrels of Oil one single Bitcoin can buy at today's close.
THE LIFESTYLE BASKET (The 5th Denominator)
Individual ratios tell you how Bitcoin is doing against one asset, but life isn't lived in a single asset. To solve this, I introduced the Lifestyle Basket .
What is a "Lifestyle Share"? A synthetic "Life Token" that represents a diversified slice of human prosperity. It is an equal-weighted basket consisting of:
• 25% Gold (Inflation Hedge)
• 25% S&P 500 (Global Growth)
• 25% Real Estate (Shelter)
• 25% Crude Oil (Energy/Consumption)
HOW TO READ THE CHART
• How to interpret the ratio: If the dashboard shows that 1 BTC buys 50 Lifestyle Shares , it means your Bitcoin stack has the purchasing power to acquire 50 equal units of the world's most critical assets.
• The Purchasing Power Line (Orange): When this line moves UP, Bitcoin is outperforming the real world. You are getting "wealthier" in a tangible sense. When it moves DOWN, your Bitcoin is losing purchasing power against that specific asset class.
• The Opportunity Zones: We plot a 200-day Mean with Standard Deviation bands.
• Upper Band (Red): Bitcoin is historically "Expensive" compared to the asset. This has historically been a high-probability zone to swap BTC for "Stuff" (Real Estate, Gold, etc.).
• Lower Band (Green): Bitcoin is "Cheap" compared to the asset. This is the zone where "Stuff" should be sold to acquire more Bitcoin.
WHY THIS IS "FRESH"
Unlike standard indicators that use RSI or MACD to find price momentum, this is a Macro-Audit . It ignores the noise of the US Dollar and focuses on the Ratio of Reality . It allows the "Infinite Hodler" to know when they are overextended in Bitcoin and when it is mathematically time to diversify into hard real-world assets.
DISCLAIMER
This script is for educational and macro-analytical purposes only. It does not constitute financial advice. Benchmarks are proxies for asset classes and may not reflect individual local prices (e.g., local real estate).
Tags: bitcoin, macro, gold, realestate, oil, benchmark, purchasing power, wealth, satoshi, Rob Maths, robmaths, Rob_Maths
Titan V40.0 Optimal Portfolio ManagerTitan V40.0 Optimal Portfolio Manager
This script serves as a complete portfolio management ecosystem designed to professionalize your entire investment process. It is built to replace emotional guesswork with a structured, mathematically driven workflow that guides you from discovering broad market trends to calculating the exact dollar amount you should allocate to each asset. Whether you are managing a crypto portfolio, a stock watchlist, or a diversified mix of assets, Titan V40.0 acts as your personal "Portfolio Architect," helping you build a scientifically weighted portfolio that adapts dynamically to market conditions.
How the 4-Step Workflow Operates
The system is organized into four distinct operational modes that you cycle through as you analyze the market. You simply change the "Active Workflow Step" in the settings to progress through the analysis.
You begin with the Macro Scout, which is designed to show you where capital is flowing in the broader economy. This mode scans 15 major sectors—ranging from Technology and Energy to Gold and Crypto—and ranks them by relative strength. This high-level view allows you to instantly identify which sectors are leading the market and which are lagging, ensuring you are always fishing in the right pond.
Once you have identified a leading sector, you move to the Deep Dive mode. This tool allows you to select a specific target sector, such as Semiconductors or Precious Metals, and instantly scans a pre-loaded internal library of the top 20 assets within that industry. It ranks these assets based on performance and safety, allowing you to quickly cherry-pick the top three to five winners that are outperforming their peers.
After identifying your potential winners, you proceed to the Favorites Monitor. This step allows you to build a focused "bench" of your top candidates. by inputting your chosen winners from the Deep Dive into the Favorites slots in the settings, you create a dedicated watchlist. This separates the signal from the noise, letting you monitor the Buy, Hold, or Sell status of your specific targets in real-time without the distraction of the rest of the market.
The final and most powerful phase is Reallocation. This is where the script functions as a true Portfolio Architect. In this step, you input your current portfolio holdings alongside your new favorites. The script treats this combined list as a single "unified pool" of candidates, scoring every asset purely on its current merit regardless of whether you already own it or not. It then generates a clear Action Plan. If an asset has a strong trend and a high score, it issues a BUY or ADD signal with a specific target dollar amount based on your total equity. If an asset is stable but not a screaming buy, it issues a MAINTAIN signal to hold your position. If a trend has broken, it issues an EXIT signal, advising you to cut the position to zero to protect capital.
Smart Logic Under the Hood
What makes Titan V40.0 unique is its "Regime Awareness." The system automatically detects if the broad market is in a Risk-On (Bull) or Risk-Off (Bear) state using a global proxy like SPY or BTC. In a Risk-On regime, the system is aggressive, allowing capital to be fully deployed into high-performing assets. In a Risk-Off regime, the system automatically forces a "Cash Drag," mathematically reducing allocation targets to keep a larger portion of your portfolio in cash for safety.
Furthermore, the scoring engine uses Risk-Adjusted math. It does not simply chase high returns; it actively penalizes volatility. A stock that is rising steadily will be ranked higher than a stock that is wildly erratic, even if their total returns are similar. This ensures that your "Maintenance" positions—assets you hold that are doing okay but not spectacular—still receive a proper allocation target, preventing you from being forced to sell good assets prematurely while ensuring you are effectively positioned for the highest probability of return.
Reflation Proxy: (QQQ/GSG) vs QQQ (Base-100)This indicator builds a single “reflation impulse” line by standardizing the QQQ/GSG ratio (growth equities vs commodities) and comparing it to QQQ over the same Base-100 lookback window. The result highlights when commodities are catching up to or outperforming growth (reflation/broadening impulse) versus when growth is dominating real assets (disinflation/duration regime). The main line is smoothed with a user-defined EMA and includes three configurable control EMAs (21/50/100 by default). Rising readings generally reflect growth leadership; a rollover into a sustained decline tends to mark reflation pressure building under the surface.
Risk Management◼ Turtle Trading Risk Management
This script helps you size your position and manage your risk, using volatility, based on Turtle Trading Strategy.
If volatility is high, size will be smaller, if volatility is low, size will be larger.
It uses N=20 days, daily ATR (customisable), to calculate volatility.
If the account is in drawdown, reduces risk amount as per Turtle Trading rules.
You can display the full table, or a smaller compact table
Calculadora CFDs v1.2 - 2026MT5 Lot & Margin Calculator for CFDs (Multi-Asset)
General Description
This tool is designed for CFD traders using platforms like MetaTrader 5 who need a fast and accurate way to calculate lot size (volume) before entering the market. The calculator solves the issue of varying contract sizes across different assets (Oil, Natural Gas, Gold, Forex, etc.) and precisely calculates the margin withheld by the broker.
Key Features:
Customizable Database: Pre-configure up to 20 different assets with their respective Contract Sizes. Once set, the script automatically detects the chart's ticker and applies the saved parameters.
Note: To find the correct Contract Size, go to MT5, right-click on the asset, select "Specification," and look for the "Contract Size" value.
Exact Margin Management: Calculate exactly how many lots to enter in MT5 based on the specific USD amount you want the broker to set aside as collateral (Margin). This value is fully adjustable in the settings.
Smart Leverage Logic: Includes automated logic for standard 2026 industry leverage levels (1:50 Forex, 1:10 Energies/Metals, 1:15 Cash Indices, 1:2 Crypto), with a manual override option.
High-Contrast Visualization: A clean and professional table interface with adjustable positioning on the chart (Top Right/Left, Bottom Right/Left).
Real-Time Data: All calculations are performed using the live price and data source of the ticker currently displayed on your chart.
Instructions for Use:
In the "Inputs" tab, enter your frequent tickers (e.g., XTIUSD, NAT.GAS) and their contract sizes according to your broker's specifications.
Define the "Margin to Retain" (the amount in USD you wish to use as collateral for the trade).
The indicator will instantly display the MT5 LOT size to enter into your trading terminal.
Use the "Save as Default" option in the settings to ensure your 20 assets remain saved for future sessions.
Indian Equities Theme Tracker [EWT] - Sector Rotation HeatmapIdentify where the "Smart Money" is flowing in the Indian Markets.
The Indian Equities Theme Tracker is a powerful visual dashboard designed for NSE traders and investors to monitor sector rotation and relative strength in real-time. By tracking the most liquid Exchange Traded Funds (ETFs), this tool provides a birds-eye view of the Indian economy—from core benchmarks like Nifty 50 and Nifty 500 to high-growth themes like Defence, EV, Tourism, and Energy.
In modern markets, capital doesn't move into all stocks at once; it rotates between sectors. This script helps you spot the leaders and laggards across five different timeframes, ensuring you are always positioned in the strongest themes.
🚀 Key Features :
23+ Essential Themes: Tracks Broad Market, Market Caps (Mid/Small), Sectors (IT, Bank, Auto, Metal), and Narratives (Defence, Tourism, EV, Energy).
Dynamic Performance Sorting: Automatically reorders the table based on your selected lookback (1 Day, 1 Week, 1 Month, 3 Months, or YTD).
Heatmap Logic: Intuitive color coding helps you instantly identify extreme bullishness or bearishness across the board.
Liquidity Focused: Uses the most liquid NSE ETFs (BeES and equivalent) to ensure the data is accurate and reflects tradeable prices.
Pro UI Design: A clean, professional dashboard that can be positioned anywhere on your chart without cluttering your price action analysis.
📊 Themes Included :
Benchmarks: Nifty 500, Nifty 50, Nifty Next 50.
Market Caps: Midcap 150, Smallcap 250.
Sectors: Private & PSU Banks, IT, Pharma, Healthcare, FMCG, Auto, Metals, Infra, Realty.
Thematic/Narratives: Defence, Tourism, Energy, EV & New Age Automotive, Consumption.
Safe Havens: Gold & Silver.
🛠️ How to use :
Timeframe: Switch to the Daily (D) timeframe for the best results.
Settings: Use the inputs to change the table position (Top/Middle/Bottom) and the sorting criteria.
Strategy: Look for themes that are consistently at the top of the "1 Month" and "3 Month" lists—these are your structural leaders. Use "1 Day" to spot quick tactical bounces.
Disclaimer: This indicator is for educational and informational purposes only and does not constitute financial advice. Always perform your own due diligence.
TASC 2026.02 Portfolio Diversification█ OVERVIEW
This indicator is a simplified framework for analyzing hypothetical portfolios, based on the concepts in the February 2026 edition of the TASC Traders' Tips , "Foundational Portfolio Design, Not Stock-Picking”. It requests datasets for spread symbols that represent weighted combinations of user-selected or predefined instruments, compares the returns in the data to those of a selected benchmark, and calculates risk-related metrics.
█ CONCEPTS
One of the core concepts of portfolio design is diversification. A diversified portfolio distributes market exposure across multiple, ideally uncorrelated, instruments to reduce potential risks. Investors often diversify their portfolios by allocating capital to instruments from different classes, sectors, or regions rather than investing in only a single instrument or multiple related instruments.
As described in the article, the motivation behind creating diversified portfolios is simple:
"No single position should have the capacity to sink the entire portfolio."
This indicator estimates a portfolio's performance by requesting combined price data for spread symbols from user inputs or predefined options, and then analyzing the data's annual arithmetic returns alongside those of a specified benchmark instrument. It displays the returns of the spread and the benchmark in a table at the bottom left.
The indicator also displays the following metrics described in the article in a table at the bottom right of the pane for additional performance information:
Max drawdown: The maximum drop in the portfolio's value from a local peak.
Standard deviation: The dispersion of portfolio values relative to their mean.
Sharpe ratio: The ratio of excess returns in an investment compared to a hypothetical risk-free rate of return.
Pain index: A measure of risk based on the depth, duration, and frequency of losses. The metric in this script considers only the bars where drawdown is nonzero.
Ulcer index: A measure of downside risk based on the root mean square of drawdowns. The metric in this script considers only the bars where drawdown is nonzero.
Correlation: The Pearson correlation coefficient between the returns of the hypothetical portfolio and those of a selected benchmark.
The first five metrics are direct risk measures. The correlation metric helps assess whether the hypothetical portfolio closely follows the broader market. High correlation with a broad benchmark might indicate an elevated sensitivity to systematic risk.
█ USAGE
Users can select a combination of up to 10 symbols with specific weights to construct a hypothetical portfolio to analyze. Alternatively, users can select a predefined combination of symbols and weights based on the article's examples of optimized portfolios for different levels of risk tolerance.
The script plots the calculated returns from the selected combination and the benchmark instrument for visual comparison. It also generates tables to compare returns and display risk metrics.
Note: This indicator is intended to provide a simplified demonstration of portfolio concepts, and some metric calculations differ slightly from those in the article. The script does not produce any signals, and the calculated metrics are estimates intended for EOD timeframes such as 1D. If the hypothetical portfolio consists of instruments with different sessions, we recommend using 1W or a higher timeframe.
█ INPUTS
Benchmark: The symbol of the instrument to compare against the hypothetical portfolio.
Portfolio Type: Choose between named options for predefined portfolio configurations based on risk profiles outlined in the article. To create a custom portfolio from up to 10 symbols, select "Custom" and adjust the 10 sets of inputs below.
Risk-free rate: The hypothetical annual risk-free rate for the Sharpe ratio.
Periods per year: If not zero, the script uses the value as the number of bars per year for annualization, which affects Sharpe ratio and standard deviation metrics.
Display Toggles: The display for the returns and metrics tables can be toggled on or off.
Theme TrackerTheme Tracker is a clean, at-a-glance theme rotation dashboard built to help you quickly identify where money is flowing—and where it’s leaving—across the market’s most important macro, sector, and industry themes.
Instead of bouncing between dozens of charts, Theme Tracker tracks a curated basket of 40 major theme ETFs and displays their relative performance across multiple timeframes, so you can instantly spot leadership, momentum shifts, and early rotation.
What it shows
For each theme ETF, the table displays performance over:
1 Day
1 Week
1 Month
3 Months
Year to Date (YTD)
Themes are ranked automatically by the timeframe you choose, allowing you to focus on what matters most in the current market regime—short-term momentum, intermediate rotation, or longer-term trend leadership.
Why it’s useful
Market leaders change. Rotation happens quietly at first, then suddenly.
Theme Tracker helps you:
Find the strongest themes fast (the “winners” attracting capital)
Spot weakening themes early (distribution and risk-off rotation)
Confirm market tone by comparing offensive vs defensive leadership
Generate trade ideas by focusing on the themes that are already being bid up
Avoid laggards by seeing what’s consistently underperforming across timeframes
When a theme is strong across multiple timeframes, that’s often where momentum traders and institutions are concentrating exposure. When it’s weak across timeframes, that’s often where capital is exiting.
How to use it
1) Choose your sort timeframe
Use the Sort setting (1D / 1W / 1M / 3M / YTD) to rank themes based on your trading horizon.
2) Look for alignment
Strong across all columns = sustained leadership
Strong short-term, weak long-term = potential bounce / rotation attempt
Weak short-term, strong long-term = possible pullback in a leader
Weak across the board = consistent capital outflow
3) Pair with your chartwork
Use the strongest themes as a shortlist for deeper chart analysis, setups, and relative strength confirmation.
Visual design
The table uses clear formatting and heat-style shading to make it easy to read quickly. Green tones highlight strength; red tones highlight weakness—so you can interpret rotation in seconds without overthinking.
If you trade momentum, relative strength, or market structure, Theme Tracker gives you one of the simplest edges available: knowing what’s leading right now. Track the best-performing themes, identify emerging rotation, and stay aligned with the areas of the market where capital is actually moving.
Momentum Screener: 1M/3M/52W HighThis script is a specialized momentum-tracking tool designed to identify "Stage 2" breakout candidates and high-growth stocks. It filters for three specific technical strengths simultaneously, ensuring you are only looking at tickers with both short-term explosive growth and long-term trend confirmation.
AuditLens - Profit Quality Analyzer📊 AuditLens - Profit Quality Analyzer
Ever wonder if a company's profits are real or just accounting tricks?
This indicator helps you spot potential earnings manipulation by analyzing the gap between reported profits and actual cash generation.
━━━━━━━━━━━━━━━━━━━━━━━━
🔍 WHAT IT DOES
━━━━━━━━━━━━━━━━━━━━━━━━
Calculates the "Divergence Ratio":
(Net Income - Operating Cash Flow) / Total Assets
• Positive divergence = Profits NOT backed by cash (risky)
• Negative divergence = Cash exceeds profits (healthy "cash cow")
━━━━━━━━━━━━━━━━━━━━━━━━
🚦 SIGNAL GUIDE
━━━━━━━━━━━━━━━━━━━━━━━━
🔴 RED FLAG (>10%): High risk - possible aggressive revenue recognition
🟠 ORANGE: Divergence trending up for 3+ quarters
🟡 YELLOW: Divergence trending up for 2+ quarters
🟢 GREEN (<-5%): "Cash Cow" - strong cash generation
✅ HEALTHY (0 to -5%): Normal profit quality
━━━━━━━━━━━━━━━━━━━━━━━━
📈 HOW TO USE
━━━━━━━━━━━━━━━━━━━━━━━━
1. Add to any stock chart
2. Check the summary table (top right)
3. Look for RED FLAGS before buying
4. Prefer stocks with negative divergence (cash cows)
━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ FAMOUS EXAMPLES
━━━━━━━━━━━━━━━━━━━━━━━━
• Enron (2001): Showed profits but burned cash → Bankruptcy
• Wirecard (2020): €1.9B "cash" that didn't exist → Fraud
• Luckin Coffee (2020): Fake revenue, no cash backing → Delisted
This indicator would have flagged all of them.
━━━━━━━━━━━━━━━━━━━━━━━━
🔗 FULL VERSION
━━━━━━━━━━━━━━━━━━━━━━━━
Want more detailed analysis with:
• 6 advanced audit rules
• Historical trend analysis
• Receivables & Inventory checks
• Detailed reports for any stock
👉 Try the full version FREE: auditlens-check.netlify.app
━━━━━━━━━━━━━━━━━━━━━━━━
📚 THE LOGIC
━━━━━━━━━━━━━━━━━━━━━━━━
Based on forensic accounting principles:
- Companies can manipulate earnings (accruals)
- But cash flow is harder to fake
- Big gap between the two = potential red flag
This is NOT financial advice. Always do your own research.
━━━━━━━━━━━━━━━━━━━━━━━━
Built by AuditLens team 🔍
Questions? DM or comment below.
JOBJABB - Risk Management Calculator1. Script Title (ชื่อสคริปต์)
JOBJABB - Risk Management Calculator
2. Description (รายละเอียดสคริปต์)
JOBJABB - Risk Management Calculator is a minimalist tool designed for traders who prioritize professional risk management. It calculates the optimal Lot Size based on your account balance and desired risk percentage, specifically optimized for Gold (XAUUSD) and Forex markets.
Key Features:
Automatic Lot Calculation: Instant position sizing for accurate risk control.
Gold & Forex Optimized: Built-in logic for different contract sizes (100 for Gold, 100k for Forex).
Multi-RR Targets: Automatically calculates TP prices for Risk-to-Reward ratios of 1:2, 1:3, and 1:5.
Minimalist Design: Clean black-and-white UI that won't clutter your chart.
Smart Alerts: Get notified when price hits Entry, SL, or TP levels.
JOBJABB - Risk Management Calculator คือเครื่องมือคำนวณขนาดไม้ (Lot Size) สไตล์ Minimalist ที่เน้นความเรียบง่ายแต่ทรงพลัง ออกแบบมาเพื่อช่วยให้เทรดเดอร์ควบคุมความเสี่ยงได้อย่างแม่นยำ โดยเฉพาะในตลาดทองคำ (XAUUSD) และ Forex
ฟีเจอร์หลัก:
คำนวณ Lot อัตโนมัติ: คำนวณจากเงินทุนและ % ความเสี่ยง ไม่ต้องกดเครื่องคิดเลขเอง
แม่นยำสำหรับทองคำ: รองรับค่า Contract Size ของทองคำ (100) และ Forex (100,000)
เป้าหมายกำไร (TP): แสดงราคาระดับ TP 1:2, 1:3 และ 1:5 ให้ทันที
ดีไซน์สะอาดตา: โทนขาว-ดำ อ่านง่าย ไม่รบกวนการวิเคราะห์กราฟ
ระบบแจ้งเตือน: แจ้งเตือนเมื่อราคาถึงจุด Entry, Stop Loss และ TP
3. How to Setup (วิธีการใช้งาน)
Risk Settings: Input your Account Balance and the % Risk you want to take per trade.
Trade Config: * Choose Direction (Buy or Sell).
Select Asset Type (Gold or Forex).
Set your Entry Price and Stop Loss Price.
Execution: Use the Recommended LOT shown in the table to open your position.
Alerts: Create an alert by selecting this script and choosing "Any alert() function call".
Elite Risk-On/Risk-Off Oscillator (6 pairs) The Elite Risk-On / Risk-Off Oscillator is a market-regime indicator designed to determine whether conditions favor aggressive risk-taking or defensive capital preservation rather than to predict price direction.
It combines six carefully selected relative-strength pairs that measure risk appetite across the most important parts of the market:
IEI/HYG (credit stress, weighted most heavily because credit often leads equities)
SPHB/SPLV (equity risk appetite via high-beta versus low-volatility stocks)
IWM/SPY (liquidity and growth sensitivity through small-caps versus large-caps)
MTUM/QUAL (trend durability versus balance-sheet quality)
XLY/XLP (consumer cyclicality, wants versus needs)
EEM/SPY (global risk and dollar-sensitive capital flows)
Each pair is evaluated using relative performance against a moving-average and slope filter to classify it as risk-on (+1), neutral (0), or risk-off (-1), with defensive ratios inverted so that positive readings always indicate risk-on conditions; the weighted signals are then aggregated, normalized to a -100 to +100 scale, and smoothed into a single oscillator. Readings above approximately +40 indicate a supportive risk-on environment where trends are more likely to persist, readings between -40 and +40 reflect transitional or choppy conditions with lower conviction, and readings below -40 signal a risk-off regime where capital preservation and defense should be prioritized.
The indicator is intended as a context and position-sizing tool, helping traders align strategy aggressiveness with underlying market conditions rather than relying on forecasts or narratives.
XAUUSD Lot Size Calculator1. What This Indicator Does
This tool is a Visual Risk Management System. Instead of using a calculator on your phone or switching tabs, it allows you to calculate the exact lot size for your trade directly on the TradingView chart by dragging lines.
It automates the math for:
Lot Size: How big your position should be to risk exactly X% of your account.
Take Profit: Where your target should be based on your Risk-to-Reward ratio.
Safety Checks: It warns you if your stop loss is too tight for the minimum lot size (0.01).
2. Visual Features
🔴 The Red Line (Stop Loss): This is your interactive line. You can grab it with your mouse and drag it to your desired invalidation point (e.g., below a support wick).
🟢 The Green Line (Take Profit): This line moves automatically. You cannot drag it. It calculates where your Take Profit must be to satisfy your Risk:Reward ratio (Default 1:1) based on where you placed the Red line.
⚫ The Info Table: A high-contrast black box in the corner that displays your calculated Lot Size, Risk amount, and Trade direction (Long/Short).
3. How to Use It (Step-by-Step)
Step 1: Initial Setup
When you first add the indicator to the chart, you need to tell it about your account:
Double-click the Black Table (or the Red Line) to open Settings.
Inputs Tab:
Account Balance: Enter your current trading balance (e.g., 10,000).
Risk %: Enter how much you want to lose per trade (e.g., 1.0%).
Contract Size: Keep this at 100 for Gold (XAUUSD) or standard Forex pairs.
Risk : Reward Ratio: Set your target (e.g., 1.0 for 1:1, or 2.0 for 1:2).
Step 2: Planning a Trade
Look at the chart and identify where you want to enter (current price) and where you want your Stop Loss.
Find the Red Line on your chart. (If you don't see it, go to Settings and change "Stop Loss Level" to a price near the current candle).
Click and Drag the Red Line to your specific Stop Loss price.
Step 3: Reading the Signals
Direction: If you drag the Red Line below the price, the table shows LONG. If you drag it above, it shows SHORT.
Lot Size: Read the big green number in the table (e.g., 0.55). This is the exact lot size you should enter in your broker.
TP Target: Look at the Green Line on the chart. That is your exit price.
Step 4: The "Orange Warning"
If you place your Stop Loss very close to the entry, or if your account is small, the math might suggest a lot size smaller than is possible (e.g., 0.004).
The table text will turn ORANGE.
The Lot Size will stick to 0.01 (the minimum).
The "Risk ($)" row will show you the actual risk. (Example: Instead of risking your desired $100, you might be forced to risk $105 because you can't trade smaller than 0.01 lots).
StopLoss Calculator ... Manual or Chart Entry, EUR or perc. RiskStop-Loss Calculator for manual or chart entry, EUR or % risk. Works for long & short positions on all timeframes. Entry and stop-loss lines are fully customizable. Use at your own risk.
Stop-Loss Rechner für manuellen oder Chart-Einstieg, Risiko in EUR oder %. Funktioniert für Long- & Short-Positionen in allen Timeframes. Entry- und Stop-Loss-Linien sind vollständig anpassbar. Nutzung auf eigenes Risiko.
Stop-Loss Calculator – Manual or Chart Entry, EUR or % Risk
This indicator calculates the optimal stop-loss price for trades based on the selected entry, position size, and risk tolerance. You can choose between manual entry or using the current chart price, and define risk as either a fixed amount (EUR) or a percentage of your capital. It works for both long and short positions and is compatible with all timeframes.
The script plots the entry and stop-loss levels, with colors and line styles fully customizable.
How to Use
Entry Selection: Choose between the chart’s current price or a manual entry price.
Position Size: Enter the number of units/shares/contracts you are trading.
Risk Mode: Select Absolute (EUR) or Percent (%). Enter the corresponding value.
Direction: Choose Long or Short.
Stop-Loss: The script automatically calculates and displays the stop-loss line.
BTC - Satoshis Altcoin Graveyard OVERVIEW
The Satoshi's Altcoin Graveyard (SAG) is a macro-statistical engine designed to solve the problem of Survivorship Bias . It is a well-known phenomenon in the crypto markets that the "Top 10" list is in a constant state of flux. If you look at historical data from CoinMarketCap (CMC) year by year, you will see a revolving door of projects that once seemed "too big to fail" disappearing into obscurity. Meanwhile, Bitcoin has remained the undisputed #1 since inception.
While most traders have a "gut feeling" that Altcoins eventually depreciate against Bitcoin, I believe in measuring it and drawing it on a chart for better visibility. By locking in specific "Cohorts" of market leaders from the past, we can track their inevitable decay through the Satoshi Sieve .
THE 13-COIN STATISTICAL BUCKET
To ensure an objective, non-biased audit, each cohort (we look at 2018, 2020 and 2022) is constructed using a fixed market-cap methodology from the snapshot date (excluding stablecoins):
• The Core: The Top 10 non-stablecoin assets at that time by Marketcap.
• The Risk Alpha: Representative samples from the Top #25, #50, and #100 ranks. (By including lower-ranked "riskier" alts, we capture the full statistical decay of the market, not just the "Blue Chips.")
TECHNICAL ARCHITECTURE
This script is engineered to push the boundaries of the Pine Script engine. TradingView enforces a hard limit of 40 unique data requests . By tracking 3 cohorts of 13 assets plus the Bitcoin base, this indicator utilizes exactly 40/40 requests , providing the maximum possible data density in a single chart window.
THE SPS CONCEPT (Survival Probability Score)
The SPS measures the Breadth of Survival . It answers: "How many coins from this year (the year of the snapshot) are actually outperforming BTC?"
We use a binary logic system to determine if a coin is "Winning" or "Losing" against the only benchmark that matters: Bitcoin.
• The Status Formula: Status = Current_Alt_BTC_Ratio >= Entry_Alt_BTC_Ratio ? 1 : 0 . This means: Every single day, at the Daily Close , the script compares the current Alt/BTC ratio to the fixed ratio from the snapshot date. If the coin is worth more in Bitcoin today than it was back then, it is assigned a "1" (a Win). If it has lost value against Bitcoin, it gets a "0" (a Loss).
• The SPS Line: SPS Line = (Sum of 'Wins' / 13) * 100 This means: We add up all the "Winners" for that specific day and turn it into a percentage. For example, if the Aqua line is at 7.69% on your chart, it confirms that on that day , exactly 1 out of the 13 coins was successfully beating Bitcoin, while the other 12 were underperforming.
THE PERFORMANCE MATRIX
In the top-right corner, we provide a Weighted Portfolio Simulation . This answers the financial question: "If I swapped 1 BTC into an equal-weight basket of these 13 coins on the snapshot day, what is my BTC value today?".
• Value < 1.0 BTC: You lost purchasing power compared to holding Bitcoin.
• Value > 1.0 BTC: You successfully achieved "Alpha" over the benchmark.
HOW TO READ THE CHART
• The Waterfall: Lines generally trend downward as the "Satoshi Sieve" filters out assets that cannot maintain their BTC-relative value.
• Dynamic Winners: We dynamically print the names of the current survivors at the tip of each line. If a cohort shows "None," the graveyard is full.
HOW TO READ THE MATRIX
• The BTC Target: Any portfolio value in the matrix below 1.0 BTC represents a failed altcoin rotation.
• Class of 2018: A portfolio value near 0.15 BTC at the current date, means a 85% loss rate.
• Class of 2020: A portfolio value near 0.77 BTC at the current date, means an approx 20 % loss rate.
• Class of 2022: A portfolio value near 0.31 BTC at the current date, means an approx 70% loss rate.
DIFFERENCE FROM AN ALTCOIN INDEX
Standard Altcoin Indexes (like my ALSI Index ) "rebalance" by removing losers and adding new winners. This is deceptive. The Altcoin Graveyard never rebalances . It forces you to watch the "losers" decay, providing a realistic look at the long-term opportunity cost of "Buy and Hold" for anything other than Bitcoin.
CONCLUSION
The data revealed by the Satoshi Sieve leads to a singular, sobering "Lesson Learned": Picking the right coin to outperform Bitcoin is not just difficult—it is statistically improbable over a long-term horizon.
While the "Risk-Reward" of altcoins is often marketed as having higher upside, the Altcoin Graveyard proves that for the vast majority of assets, the reward does not justify the risk of total portfolio erosion in BTC terms.
• The Mathematical Odds: If you picked a Top 10 coin in 2018, your chance of outperforming BTC today is effectively 0%.
• The Rotation Trap: Most investors "HODL" these assets into the graveyard, hoping for a return to previous ATHs that never comes because the liquidity has already moved on to the next "Class" of winners.
The final conclusion is clear: Diversification into altcoins is often just a slow-motion transfer of wealth back to Bitcoin. If you cannot identify the 1-out-of-13 that survives the Sieve, your best risk-adjusted move has historically been to simply hold the benchmark.
DISCLAIMER
This script is for educational purposes only. It does not constitute financial advice. It is a mathematical study of historical opportunity cost and survivorship bias.
Tags
bitcoin, btc, satoshis graveyard, altseason, dominance, total3, rotation, cycle, index, alsi, Rob Maths, robmaths
Satoshi Frame Risk FrameSatoshi Frame Risk Frame
Trade with structure, not emotion.
Satoshi Frame – Risk Frame is a minimalist capital and risk management tool designed for traders who value discipline over hype.
This indicator helps you:
Calculate position size based on fixed risk
Control margin usage with leverage awareness
Visualize risk before entering any trade
Stay consistent across different market conditions
Built for futures and leveraged trading, Risk Frame focuses on one rule only:
Protect your capital first. Profits come later.
This is the first public release by Satoshi Frame —
a framework, not a signal .
Lot Size & Risk Calculator All Pairs NEWLot Size & Risk Calculator All Pairs NEW
Description
Professional risk and position size calculator for traders working with various financial instruments.
Main difference from standard indicators:
Standard risk calculators only show basic Risk/Reward for the entire position. But in real trading, we often close positions partially at different take-profit levels, and the final Risk/Reward changes significantly with this approach! This indicator calculates weighted Risk/Reward taking into account position distribution across multiple take-profit levels.
Main features:
- Support for 4 instrument types: Forex, XAUUSD (gold), BTCUSD (bitcoin), US100 (NASDAQ index)
- Automatic position size calculation based on risk and stop-loss distance
- Multiple take-profit levels with customizable closing percentages
- Weighted Risk/Reward calculation considering position distribution
- Ability to adjust position distribution between take-profits to optimize final profit
- Display of total percentage growth of deposit from all take-profit levels
- 2 visualization options: colored fill between levels or lines
- Informative results panel in table format
Settings by groups:
Core Settings
- Currency: select instrument type (Forex, XAUUSD, BTCUSD, US100)
- Account Balance: trading account size in dollars
- Risk %: risk percentage from deposit (0.1-100%)
- Use Custom Contract Sizes: manual contract size configuration
Point Value Settings
- Use automatic point value calculation: automatic point value calculation
- Manual point value: manual point value input (for non-standard contracts)
Levels
- Entry Price: entry price (confirmation required on first use)
- Stop Price: stop-loss price
- Take-Profit Prices: take-profit prices (up to 3 levels)
- TP Close %: percentage of position closed at each take-profit level
Dashboard
- Show Targets Profit: display profit from take-profit levels
- Label Size: text size in the table
- Dashboard Position: table position on the chart
How to use:
Step 1: Initial setup (when first adding)
1. Enter entry price (Entry Price) - confirmation window will appear (click on desired bar)
2. Then enter stop-loss price (Stop Price) (click on desired bar)
3. Add first take-profit (TP1) (click on desired bar)
4. Second and third take-profits are added through checkboxes (click on the settings gear icon to open them)
Step 2: Instrument selection and risk configuration
1. In "Core" group, select your instrument type
2. Set account balance and risk percentage
Step 3: Position distribution configuration
1. Set TP Close % for each take-profit level (e.g.: TP1 - 33%, TP2 - 33%, TP3 - 34%)
2. Experiment with distribution! By changing closing percentages, you can:
- Increase/decrease final Risk/Reward
- Optimize risk/profit ratio
- Find the most comfortable position distribution for you
Step 4: Results analysis
1. Results table will show:
- Calculated position size (lots/contracts)
- Risk in monetary terms
- Risk/Reward for each take-profit level
- Weighted R:R considering position distribution
- Total potential profit from all take-profits
- Percentage growth of deposit - total profit percentage from all take-profit levels
Key features:
Position distribution adjustment
You can easily find optimal position distribution between take-profits:
- Aggressive approach: higher percentage on distant take-profit (higher profit potential)
- Conservative approach: higher percentage on near take-profit (faster profit taking)
- Balanced: even distribution for risk reduction
Weighted Risk/Reward
The indicator calculates not just simple R:R for the entire position, but weighted value that considers:
- Position distribution between take-profits
- Different distances to each take-profit level
- Closing percentage at each level
Results visualization
- Colored fill shows risk and profit zones
- Labels at levels display specific profit/loss values
- Results table contains all key metrics
Creation story
This indicator was created based on the original calculator by @Algoryze As a trader, I lacked the ability to see real Risk/Reward when partially closing positions and a convenient tool for selecting optimal position distribution between take-profit levels. I improved the indicator by adding:
- Weighted Risk/Reward calculation
- Ability to adjust closing percentage at each take-profit
- Display of total percentage growth of deposit
- Improved interface and visualization
I hope this tool will be useful to other traders who use strategies with partial position closing!
Important notes:
1. When first adding the indicator, be sure to enter prices in order: Entry → Stop → TP1
2. TP2 and TP3 are added through input fields (no confirmation required)
3. Closing percentages are automatically normalized if the sum is not 100%
4. Experiment with position distribution to find optimal risk/profit ratio
5. For different instruments, add separate copies of the indicator in different tabs
Support
For questions and suggestions, leave comments in the indicator publication on TradingView.
---
Important: All calculations are provided for informational purposes only. Trading involves risks, trade responsibly. The indicator helps with calculations but does not guarantee profit.
