OCM Pi Cycle Top IndicatorOCM Pi Cycle Top Indicator
This overlay indicator is a visual implementation of the Pi Cycle Top strategy, a historically effective method for identifying major Bitcoin market cycle tops. The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs within 3 days.
It tracks the crossover between two key moving averages:
A 111-day simple moving average (SMA)
A 2x multiple of the 350-day SMA
When the 111-day SMA crosses below the doubled 350-day SMA, the indicator flags a potential market top, marking it on the chart above the current price. This has historically aligned closely with previous Bitcoin macro peaks.
The indicator is designed for daily timeframes but allows for custom resolution input, making it flexible for backtesting. It also continuously plots both moving averages so traders can visually monitor the crossover dynamics in real-time.
⏰ Timeframes to be used on:
Daily
Weekly
Educational
OCM SOPR Z-ScoreOCM SOPR Z-Score
This indicator measures the Spent Output Profit Ratio (SOPR) for Bitcoin, smoothed as a Z-Score. SOPR is a key on-chain metric used to assess market profit-taking behaviour by comparing the price at which coins were sold to the price at which they were acquired. Values above 1 indicate profits being realized, while values below 1 suggest selling at a loss.
The indicator features a heatmap-style colour gradient reflecting the SOPR value intensity, making it easier to visually identify shifts in market sentiment. Subtle background highlights appear when the SOPR crosses upper or lower threshold levels, configurable to highlight overbought or oversold profit-taking extremes. This tool offers a straightforward way to monitor when the market may be topping or bottoming based on realized profit trends.
⏰ Timeframes to be used on:
Daily
Weekly
OCM Net Unrealized Profit/Loss (NUPL)OCM Net Unrealized Profit/Loss (NUPL)
This indicator tracks Bitcoin’s Net Unrealized Profit/Loss (NUPL), a key on-chain metric that reflects the difference between unrealised profits and losses across all market participants. By mapping this ratio, the indicator highlights prevailing market sentiment and investor psychology, segmented into distinct emotional zones ranging from capitulation to euphoria. Each zone is visually distinguished by dynamic colour coding, offering an intuitive way to gauge whether the market is dominated by fear, hope, or greed.
Thresholds for these sentiment zones are configurable, allowing you to tailor sensitivity to different market environments. The plotted NUPL line, combined with reference levels and background highlights for extreme conditions, provides a comprehensive tool to anticipate potential market turning points.
⏰ Timeframes to be used on:
Daily
Weekly
Beta -> The New SystemBeta → The New System 📊
Calculate and visualize your asset’s sensitivity to a benchmark over a rolling lookback period.
What is Beta? 🤔
Beta measures how much your asset moves in relation to a chosen benchmark. A Beta of 1 means it moves in perfect sync; above 1 means it’s more volatile (amplified moves), and below 1 means it’s less volatile (dampened moves). By tracking Beta you see if your asset is a risky rocket or a stable ship compared to the market. 🚀⚓️
Indicator Inputs ⚙️
Lookback Period ⏳
Number of bars (e.g. days) over which to compute rolling averages, covariance, and variance.
Benchmark Symbol 🏷️
The ticker of the market or index you want to compare against (e.g. BTCUSD, ETHUSD, an index).
How It Works 🧮
Fetch prices for both your asset and the benchmark at each bar.
Compute returns by calculating the percentage change from bar to bar.
Smooth returns with a simple moving average over the lookback period to get mean asset and benchmark returns.
Calculate covariance between asset and benchmark returns to see how they move together.
Calculate variance of the benchmark returns to measure its own volatility.
Divide covariance by variance (with a check to avoid division by zero)—that ratio is your Beta.
Plot & Interpretation 🎨
Line Color
Always blue for Beta, emphasizing volatility comparison.
Reference Line
A dashed gray line at Beta = 1 marks “market-level” sensitivity.
Reading Beta
β > 1 🟥
Asset tends to exaggerate benchmark moves—higher upside potential but larger downside risk.
β = 1 🟩
Asset moves in lockstep with your benchmark.
β < 1 🟦
Asset smooths out benchmark swings—less risk but also muted returns.
Pro Tips 💡
Combine Alpha + Beta: high Beta with positive Alpha can be great in up-markets but painful in drawdowns.
Monitor Beta shifts: a sudden jump could signal a regime change or new correlation dynamics.
Test different benchmarks: small-cap altcoins may track a broader crypto index differently than they track Bitcoin.
By keeping an eye on Beta in real time, you’ll understand not just how much you’re making, but how much market risk you’re taking on every trade.
OCM MVRV Z-ScoreOCM MVRV Z-Score
This indicator visualises the Market-Value-to-Realised-Value (MVRV) ratio, a widely used metric to assess Bitcoin market cycles by comparing the market capitalisation against the realised capitalisation. It offers two modes: a standard ratio and a statistically normalised Z-Score variant, enhancing sensitivity to deviations from historical norms. The script applies a gradient colour scheme that dynamically reflects the MVRV value’s relative position within defined overbought and oversold thresholds, allowing you to easily spot cyclical extremes and potential reversal zones.
Critical top and bottom lines are plotted for reference, including an adjustable neutral line, providing further context to Bitcoin's valuation state. This indicator is designed to help you identify periods of market euphoria or distress, making it a robust tool for timing entries and exits within broader market cycles.
⏰ Timeframes to be used on:
Daily
Weekly
OCM 200D MA HeatmapOCM 200D MA Heatmap
This tool visualises Bitcoin’s percentage deviation from its 200-day simple moving average, a long-term reference often associated with deep value zones and cyclical overheats. Each candle is overlaid with a colour-coded dot, with hues shifting according to fixed deviation thresholds. Cooler colours signal periods of market undervaluation, while warmer tones indicate stretched or euphoric price conditions.
The 200D MA line can be optionally displayed, offering a clean view of the long-term trend. Designed as a macro lens for investors and cycle-focused traders, this heatmap distils complex cycle dynamics into an immediate visual signal.
⏰ Timeframes to be used on:
- Daily
- Weekly
SG AlgoThis Indicator is designed to help traders identify high-quality trade opportunities with minimal noise.
Features ✨
Visualizes dynamic market structure with customizable Trend and Control lines.
Highlights key price zones known as Entry Boxes, where potential trade setups may occur.
Displays precise Buy and Sell signals based on internal confluence of trend and price action.
Intuitive color-coded cues and visual markers for quick decision-making.
Built-in alert system for real-time notifications to keep you ahead of market moves.
Suitable for both intraday scalping and longer-term position trading — all without clutter or distractions.
How to Use Buy and Sell Signals 📈📉
This indicator provides clear Buy and Sell signals based on trend behavior and key price zones:
Buy Signal 🟢: When the system indicates a buy, consider entering a long position just above the current price action.
Place your stop loss 🛑 slightly below a major support level (called the Control level) to manage risk.
Sell Signal 🔴: When a sell signal appears, consider entering a short position just below the current price action.
Place your stop loss 🛑 slightly above the Control level to limit losses.
Alternative Entry Method: Breakouts Relative to Trend 🚀📉
You may also choose to trade breakouts:
Buy on Breakout 🚀: Enter long when price breaks above and CLOSES a CANDLE the main trend level, indicating bullish momentum.
Use the Control level below as your stop loss area 🛑.
Sell on Breakdown 📉: Enter short when price breaks below the main trend level, signaling bearish momentum.
Use the Control level above as your stop loss area 🛑.
✅ Entry:
Buy Setup: When a green triangle appears below a candle (Entry Box Confirmed Buy), it signals a potential bullish entry. Consider entering at the close of the signal candle or on a small retracement into the candle body.
Sell Setup: When a red triangle appears above a candle (Entry Box Confirmed Sell), it signals a potential bearish entry. Consider entering at the close of the signal candle or on a slight pullback.
📍Stop-Loss Placement:
For Buys: Place your stop-loss just below the recent swing low or the bottom of the green “Entry Box” zone.
For Sells: Place your stop-loss just above the recent swing high or the top of the red “Entry Box” zone.
🎯 Optional Take-Profit Strategy:
Use a 1:2 or 1:3 risk-reward ratio. RISK 1%
⚠️⚠️ For educational purposes only. Not financial advice.
Use responsibly. Always test and confirm your setups.⚠️⚠️
Multi-Timeframe RSI AlertsThis Pine Script generates alerts based on the Relative Strength Index (RSI) values across two different timeframes — 30-minute and 5-minute. It's designed to help traders identify momentum shifts for both bullish and bearish scenarios.
Omega Ratio -> The NeW SystemOmega Ratio → The NeW System 🚀
Calculate and visualize a smoothed Omega Ratio to measure upside vs. downside performance relative to a target return.
What is the Omega Ratio? 🤔
The Omega Ratio compares the total gains above a specified target return to the total losses below that target. Unlike other risk metrics that focus on volatility alone, Omega shows you how much reward you’re getting for every unit of shortfall risk. A higher Omega means your upside outweighs downside more attractively.
Indicator Inputs ⚙️
Source 📊: the price series to calculate returns from (e.g. close price).
Calculation Period 📆: number of bars over which returns are compared to the target. Longer periods smooth out fluctuations; shorter periods react faster to changing market conditions.
Target Return per Period (%) 🎯: the minimum return you aim for each bar (e.g. 0.1% per day).
Smoothing Period (EMA) 🔄: how many periods to apply an exponential moving average to the raw Omega Ratio, reducing noise and highlighting the trend.
Strong Threshold 🟢: above this value the line turns green, signaling strong upside vs. downside performance (default: 1.0).
Weak Threshold 🔴: below this value the line turns red, warning that losses outweigh gains relative to your target (default: 0.5).
How the Indicator Works 🧮
Calculate periodic returns by comparing each bar’s price to the previous bar.
Convert your target percentage into a decimal per period.
Accumulate gains above the target by summing every time the return exceeds the target amount.
Accumulate losses below the target by summing the shortfall whenever the return falls short of that target.
Form the raw Omega Ratio by dividing total gains above target by total losses below target. If there are no losses below the target, Omega is undefined (and we handle that gracefully).
Smooth with EMA to filter out spikes and reveal the underlying strength or weakness of the ratio.
Plot & Interpretation 🎨
Dynamic Line Color
🟢 Green when the smoothed Omega Ratio exceeds the Strong Threshold, indicating your asset is delivering more reward above target than risk below it.
🔴 Red when it falls below the Weak Threshold, warning that downside shortfalls dominate.
⚪ Gray between thresholds, suggesting a balanced but unimpressive performance.
Threshold Lines
A dashed green line marks the Strong Threshold.
A dashed red line marks the Weak Threshold.
Pro Tips 💡
An Omega above 1 means you’re gaining more above your target than losing below it—a positive sign.
An Omega below 1 warns that losses are outweighing gains relative to your goal.
Adjust the Target Return to fit your trading style: a higher target demands more “elite” performance, while a low target (even 0%) shows you pure upside vs. downside balance.
Use this indicator to instantly see whether an asset is consistently beating your expectations or struggling to hold ground—helping you make more informed entry and exit decisions.
Sortino Ratio -> The NeW SystemSortino Ratio → The NeW System 🚀
Calculate and visualize an annualized, smoothed Sortino Ratio that focuses on downside volatility.
What is the Sortino Ratio? 🤔
The Sortino Ratio is a risk-adjusted performance metric like the Sharpe Ratio, but it only penalizes returns below a chosen benchmark (usually the risk-free rate). By isolating “bad” volatility—periods when your returns dip under that minimum—it shows you how well an asset rewards you for downside risk alone. 📉
Indicator Inputs ⚙️
Source 📊: the price series to calculate returns from (e.g. close price).
Calculation Period 📆: the number of days/bars used to compute average returns and downside volatility. Longer periods smooth out noise; shorter periods react faster.
Annual Risk-Free Rate (%) 💰: the minimum acceptable yearly return, converted internally to a per-bar rate. In crypto, you might set this to zero.
Smoothing Period (EMA) 🔄: how many periods to apply an exponential moving average to the raw Sortino Ratio, reducing spikes and making trends clearer.
Strong Threshold 🟢: above this level the line turns green, signaling robust downside-risk-adjusted performance.
Weak Threshold 🔴: below this level the line turns red, warning of underperformance relative to downside risk.
How the Indicator Works 🧮
Compute periodic returns by comparing each bar’s price to the prior bar.
Convert annual risk-free rate to a per-bar rate (divide by 365 for daily bars).
Calculate average return over the chosen period.
Measure downside deviation by squaring only the shortfalls below the risk-free rate, averaging them, and then taking the square root.
Form the raw Sortino Ratio by subtracting the per-bar risk-free rate from the average return, dividing by downside deviation, and annualizing. If downside deviation is zero, it defaults to zero to avoid errors.
Smooth with EMA to filter noise and highlight the underlying trend.
Plot & Interpretation 🎨
Line Color
🟢 Green when the smoothed Sortino Ratio ≥ Strong Threshold (strong downside-risk-adjusted returns).
🔴 Red when ≤ Weak Threshold (weak or negative performance).
⚪ Gray between thresholds (neutral zone).
Threshold Lines
Dashed green line at the Strong Threshold.
Dashed red line at the Weak Threshold.
Pro Tips 💡
A Sortino Ratio around 1 means returns match downside risk on a 1:1 basis—generally acceptable -> Long Term.
Below 0 indicates returns haven’t beaten your minimum acceptable rate.
Above 2 signals excellent downside-risk-adjusted performance—even in volatile markets like crypto, values slightly below 2 can still be strong -> Long Term.
Use this system to spot when an asset’s returns aren’t just high, but safely high—helping you trade with confidence and minimize nasty drawdowns! 🎯
Sharpe Ratio -> The NeW SystemSharpe Ratio → The NeW System 📈
Calculate and visualize an annualized, smoothed Sharpe Ratio based on daily returns.
What is the Sharpe Ratio? 🤔
The Sharpe Ratio measures risk-adjusted return by dividing the average return by its volatility. A higher Sharpe means you’re earning more reward per unit of risk. In crypto, we assume a 0% risk-free rate.
Indicator Inputs ⚙️
Source
The price series to use (default: close).
Sharpe Rolling Period
Number of days for the rolling average and volatility calculation.
Smoothing Period (EMA)
How many periods to smooth the raw Sharpe with an exponential moving average.
Strong Threshold 🔥
Sharpe ≥ this value shows a “strong” signal in green.
Weak Threshold ❄️
Sharpe ≤ this value shows a “weak” signal in red.
How It Works 🧮
Daily Returns – Calculate the percentage change in price from one day to the next.
Rolling Average – Smooth those daily returns over the chosen Sharpe period.
Rolling Volatility – Compute the standard deviation of daily returns over the same period.
Raw Sharpe – Divide the rolling average by the rolling volatility (with zero-volatility guard).
EMA Smoothing – Apply an EMA to the raw Sharpe to reduce noise.
Annualization – Multiply the smoothed daily Sharpe by √365 to get a yearlyized figure.
Plot & Interpretation 🎨
Line Color
🟢 Green when annualized Sharpe ≥ Strong Threshold (strong risk-adjusted performance)
🔴 Red when annualized Sharpe ≤ Weak Threshold (weak or negative performance)
⚪ Gray when between the thresholds (neutral zone)
Threshold Lines
A dashed green line marks the Strong Threshold.
A dashed red line marks the Weak Threshold.
Pro Tips 💡
A Sharpe around 1 is generally acceptable -> Long term.
Below 0 means you’re losing per unit of risk on average.
Above 2 is excellent—although in crypto, slightly lower values can still signal strength -> Long term.
Use this system to spot when an asset’s risk-adjusted returns are heating up (🔥) or cooling off (❄️), so you can time your trades more effectively!
EPT-DB:EMA Trend Table + Stoch RSIThe script attached is a simple table that tells you some directions with 9/20 EMA crosses.
If the the 1hour,2hour,4hour are all one direction, trades on any time frame below will only display buy or sell with those as a measure of confluence.
If you would like help making your own trading dashboard, let me know.
I have also attached RSI, those will flash green and red on their respective oversold levels.
JPMorgan G7 Volatility IndexThe JPMorgan G7 Volatility Index: Scientific Analysis and Professional Applications
Introduction
The JPMorgan G7 Volatility Index (G7VOL) represents a sophisticated metric for monitoring currency market volatility across major developed economies. This indicator functions as an approximation of JPMorgan's proprietary volatility indices, providing traders and investors with a normalized measurement of cross-currency volatility conditions (Clark, 2019).
Theoretical Foundation
Currency volatility is fundamentally defined as "the statistical measure of the dispersion of returns for a given security or market index" (Hull, 2018, p.127). In the context of G7 currencies, this volatility measurement becomes particularly significant due to the economic importance of these nations, which collectively represent more than 50% of global nominal GDP (IMF, 2022).
According to Menkhoff et al. (2012, p.685), "currency volatility serves as a global risk factor that affects expected returns across different asset classes." This finding underscores the importance of monitoring G7 currency volatility as a proxy for global financial conditions.
Methodology
The G7VOL indicator employs a multi-step calculation process:
Individual volatility calculation for seven major currency pairs using standard deviation normalized by price (Lo, 2002)
- Weighted-average combination of these volatilities to form a composite index
- Normalization against historical bands to create a standardized scale
- Visual representation through dynamic coloring that reflects current market conditions
The mathematical foundation follows the volatility calculation methodology proposed by Bollerslev et al. (2018):
Volatility = σ(returns) / price × 100
Where σ represents standard deviation calculated over a specified timeframe, typically 20 periods as recommended by the Bank for International Settlements (BIS, 2020).
Professional Applications
Professional traders and institutional investors employ the G7VOL indicator in several key ways:
1. Risk Management Signaling
According to research by Adrian and Brunnermeier (2016), elevated currency volatility often precedes broader market stress. When the G7VOL breaches its high volatility threshold (typically 1.5 times the 100-period average), portfolio managers frequently reduce risk exposure across asset classes. As noted by Borio (2019, p.17), "currency volatility spikes have historically preceded equity market corrections by 2-7 trading days."
2. Counter-Cyclical Investment Strategy
Low G7 volatility periods (readings below the lower band) tend to coincide with what Shin (2017) describes as "risk-on" environments. Professional investors often use these signals to increase allocations to higher-beta assets and emerging markets. Campbell et al. (2021) found that G7 volatility in the lowest quintile historically preceded emerging market outperformance by an average of 3.7% over subsequent quarters.
3. Regime Identification
The normalized volatility framework enables identification of distinct market regimes:
- Readings above 1.0: Crisis/high volatility regime
- Readings between -0.5 and 0.5: Normal volatility regime
- Readings below -1.0: Unusually calm markets
According to Rey (2015), these regimes have significant implications for global monetary policy transmission mechanisms and cross-border capital flows.
Interpretation and Trading Applications
G7 currency volatility serves as a barometer for global financial conditions due to these currencies' centrality in international trade and reserve status. As noted by Gagnon and Ihrig (2021, p.423), "G7 currency volatility captures both trade-related uncertainty and broader financial market risk appetites."
Professional traders apply this indicator in multiple contexts:
- Leading indicator: Research from the Federal Reserve Board (Powell, 2020) suggests G7 volatility often leads VIX movements by 1-3 days, providing advance warning of broader market volatility.
- Correlation shifts: During periods of elevated G7 volatility, cross-asset correlations typically increase what Brunnermeier and Pedersen (2009) term "correlation breakdown during stress periods." This phenomenon informs portfolio diversification strategies.
- Carry trade timing: Currency carry strategies perform best during low volatility regimes as documented by Lustig et al. (2011). The G7VOL indicator provides objective thresholds for initiating or exiting such positions.
References
Adrian, T. and Brunnermeier, M.K. (2016) 'CoVaR', American Economic Review, 106(7), pp.1705-1741.
Bank for International Settlements (2020) Monitoring Volatility in Foreign Exchange Markets. BIS Quarterly Review, December 2020.
Bollerslev, T., Patton, A.J. and Quaedvlieg, R. (2018) 'Modeling and forecasting (un)reliable realized volatilities', Journal of Econometrics, 204(1), pp.112-130.
Borio, C. (2019) 'Monetary policy in the grip of a pincer movement', BIS Working Papers, No. 706.
Brunnermeier, M.K. and Pedersen, L.H. (2009) 'Market liquidity and funding liquidity', Review of Financial Studies, 22(6), pp.2201-2238.
Campbell, J.Y., Sunderam, A. and Viceira, L.M. (2021) 'Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds', Critical Finance Review, 10(2), pp.303-336.
Clark, J. (2019) 'Currency Volatility and Macro Fundamentals', JPMorgan Global FX Research Quarterly, Fall 2019.
Gagnon, J.E. and Ihrig, J. (2021) 'What drives foreign exchange markets?', International Finance, 24(3), pp.414-428.
Hull, J.C. (2018) Options, Futures, and Other Derivatives. 10th edn. London: Pearson.
International Monetary Fund (2022) World Economic Outlook Database. Washington, DC: IMF.
Lo, A.W. (2002) 'The statistics of Sharpe ratios', Financial Analysts Journal, 58(4), pp.36-52.
Lustig, H., Roussanov, N. and Verdelhan, A. (2011) 'Common risk factors in currency markets', Review of Financial Studies, 24(11), pp.3731-3777.
Menkhoff, L., Sarno, L., Schmeling, M. and Schrimpf, A. (2012) 'Carry trades and global foreign exchange volatility', Journal of Finance, 67(2), pp.681-718.
Powell, J. (2020) Monetary Policy and Price Stability. Speech at Jackson Hole Economic Symposium, August 27, 2020.
Rey, H. (2015) 'Dilemma not trilemma: The global financial cycle and monetary policy independence', NBER Working Paper No. 21162.
Shin, H.S. (2017) 'The bank/capital markets nexus goes global', Bank for International Settlements Speech, January 15, 2017.
Elle MTF Execution MapThe Elle MTF Execution Map is a precision-built, multi-timeframe TradingView indicator designed for traders who align the Daily, 1-Hour, and 5-Minute charts. This script simplifies your execution process by visually marking key market zones and confluences — so you can stop overthinking and start trading with clarity.
Whether you're a price action trader or still developing your strategy, this tool helps you stay disciplined, focused, and confident in your decisions.
Features:
Automatic High Timeframe Zones
Daily and 1-Hour highs and lows automatically plotted on the 5-minute chart
Clean color-coded zone levels to anchor your bias
Engulfing Candle Detection
Bullish and bearish engulfing candles are highlighted only when they form near HTF zones
Helps you time entries based on price reaction, not emotion
Fair Value Gap (FVG) Highlighting
FVGs are auto-detected and shown as translucent boxes
Only appear near zones to reduce noise and increase precision
Zone-Only Logic for Clean Charts
All signals (engulfing candles and FVGs) require proximity to HTF zones
No overfitting. No clutter. Just what matters.
Built for the Trader Who Executes with Intention
Perfect for intraday scalpers, prop firm traders, and anyone using price action structure
Designed for use with live sessions, journaling, and trade recaps
Clean 0DTE Spread Strikes (PST, Only 1 Label Active)Credit Spread Made Easy. This provides the potential entry spread for the spy as well as the qqq. This is based on ATR and IV.
1m EMA Background ColorEntry Color background indicator where when the 5 ema 1 min timeframe is above the 21 ema 1 min timeframe background is green and when 5 is below the 21 it is red. this can be used for long or short trading
New York Open MarkerNEW YORK OPEN MARKER
This indicator highlights two key time points: the New York Open at 9:30 AM and the 10:00 AM NY time.
For many traders, the NY Open is a crucial session. Manually marking these candles every day can be repetitive and time-consuming — this tool automates that process.
When enabled, it will:
- Mark 9:30 AM NY Time with a Blue marker.
- Mark 10:00 AM NY Time with a Red marker.
You can easily toggle the indicator on or off, customize the labels, or even hide them entirely. The marker colors are also fully adjustable to match your chart style.
This tool is especially handy during backtesting, helping you quickly identify these critical candles without scanning the chart manually.
Rolling 4-Year CAGRCalculates rolling 4-year CAGR on day, week, or month chart.
Can change timeframe to any number of years.
-Jesse Myers
