Global OECD CLI Diffusion Index YoY vs MoMThe Global OECD Composite Leading Indicators (CLI) Diffusion Index is used to gauge the health and directional momentum of the global economy and anticipate changes in economic conditions. It usually leads turning points in the economy by 6 - 9 months.
How to read: Above 50% signals economic expansion across the included countries. Below 50% signals economic contraction.
The diffusion index component specifically shows the proportion of countries with positive economic growth signals compared to those with negative or neutral signals.
The OECD CLI aggregates data from several leading economic indicators including order books, building permits, and consumer and business sentiment. It tracks the economic momentum and turning points in the business cycle across 38 OECD member countries and several other Non-OECD member countries.
Educational
CCI Threshold StrategyThe CCI Threshold Strategy is a trading approach that utilizes the Commodity Channel Index (CCI) as a momentum indicator to identify potential buy and sell signals in financial markets. The CCI is particularly effective in detecting overbought and oversold conditions, providing traders with insights into possible price reversals. This strategy is designed for use in various financial instruments, including stocks, commodities, and forex, and aims to capitalize on price movements driven by market sentiment.
Commodity Channel Index (CCI)
The CCI was developed by Donald Lambert in the 1980s and is primarily used to measure the deviation of a security's price from its average price over a specified period.
The formula for CCI is as follows:
CCI=(TypicalPrice−SMA)×0.015MeanDeviation
CCI=MeanDeviation(TypicalPrice−SMA)×0.015
where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average of the Typical Price
Mean Deviation = Average of the absolute deviations from the SMA
The CCI oscillates around a zero line, with values above +100 indicating overbought conditions and values below -100 indicating oversold conditions (Lambert, 1980).
Strategy Logic
The CCI Threshold Strategy operates on the following principles:
Input Parameters:
Lookback Period: The number of periods used to calculate the CCI. A common choice is 9, as it balances responsiveness and noise.
Buy Threshold: Typically set at -90, indicating a potential oversold condition where a price reversal is likely.
Stop Loss and Take Profit: The strategy allows for risk management through customizable stop loss and take profit points.
Entry Conditions:
A long position is initiated when the CCI falls below the buy threshold of -90, indicating potential oversold levels. This condition suggests that the asset may be undervalued and due for a price increase.
Exit Conditions:
The long position is closed when the closing price exceeds the highest price of the previous day, indicating a bullish reversal. Additionally, if the stop loss or take profit thresholds are hit, the position will be exited accordingly.
Risk Management:
The strategy incorporates optional stop loss and take profit mechanisms, which can be toggled on or off based on trader preference. This allows for flexibility in risk management, aligning with individual risk tolerances and trading styles.
Benefits of the CCI Threshold Strategy
Flexibility: The CCI Threshold Strategy can be applied across different asset classes, making it versatile for various market conditions.
Objective Signals: The use of quantitative thresholds for entry and exit reduces emotional bias in trading decisions (Tversky & Kahneman, 1974).
Enhanced Risk Management: By allowing traders to set stop loss and take profit levels, the strategy aids in preserving capital and managing risk effectively.
Limitations
Market Noise: The CCI can produce false signals, especially in highly volatile markets, leading to potential losses (Bollinger, 2001).
Lagging Indicator: As a lagging indicator, the CCI may not always capture rapid market movements, resulting in missed opportunities (Pring, 2002).
Conclusion
The CCI Threshold Strategy offers a systematic approach to trading based on well-established momentum principles. By focusing on overbought and oversold conditions, traders can make informed decisions while managing risk effectively. As with any trading strategy, it is crucial to backtest the approach and adapt it to individual trading styles and market conditions.
References
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Lambert, D. (1980). Commodity Channel Index. Technical Analysis of Stocks & Commodities, 2, 3-5.
Pring, M. J. (2002). Technical Analysis Explained. New York: McGraw-Hill.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
US Presidents with Market Returns by Party (1910s-Present)Colored background for presidents by party affiliation with table displaying market returns for each US president and sum of total returns by party.
Weekly Range & Trend (Signed)Weekly Trend & Range is basically calculated every week.
It helps to get a broad idea whether coming week market can be directional , volatile or range bound action. So this helps me to get a hint which style of approach should be given more important on positional basis like directional or non-directional.
I mostly track in NSE:BANKNIFTY , NSE:NIFTY , BSE:SENSEX
For example:
Average range difference of past 4 weeks is bigger in compare to current week range difference means good chance for directional opportunities.
Average range difference of past 4 weeks is lesser in compare to current week range difference means good chance for non-directional opportunities.
Directional or Non-directional hint is been shown in terms of probability . So based on this i plan my week and trades.
Implied Fair Value Gap (IFVG) ICT [TradingFinder] Hidden FVG OTE🔵 Introduction
The Implied Fair Value Gap (IFVG) is distinctive due to its unique three-candlestick formation, which differentiates it from conventional Fair Value Gaps.
Implied fair value represents an estimated worth of an asset—often a business or its goodwill—based on the price likely to be received in a structured transaction between market participants at a specific point in time.
In the ever-evolving world of technical analysis, pinpointing price reversal points and market anomalies can significantly enhance trading strategies and decision-making for traders and investors. Among the advanced concepts gaining traction in this field is the Implied Fair Value Gap (IFVG), introduced by the renowned analyst Inner Circle Trader (ICT).
This tool has proven to be an effective method for identifying hidden supply and demand zones in financial markets, offering a unique edge to traders looking for high-probability setups.
Unlike traditional gaps that are visible on price charts, IFVG is a hidden gap that doesn’t appear explicitly on the chart and thus requires specialized technical analysis tools for accurate identification.
This hidden gap can signal potential price reversals and offers traders insight into high-liquidity areas where price is likely to react. This article will guide you through using the ICT Implied Fair Value Gap Indicator effectively, covering its settings, usage strategies, and key features to help you make informed decisions in the market.
🟣 Bullish Implied FVG
🟣 Bearish Implied FVG
🔵 How to Use
The IFVG indicator is designed to assist traders in recognizing hidden support and resistance zones by identifying Bullish and Bearish IFVG patterns. With this tool, traders can make better-informed decisions about suitable entry and exit points for their trades based on these patterns.
🟣 Bullish Implied Fair Value Gap
This pattern occurs in an uptrend when a large bullish candlestick forms, with the wicks of the previous and following candles overlapping the body of the central candlestick.
This overlap creates a demand zone or a hidden support level, which can act as an ideal entry point for buy trades. Often, when the price returns to this area, it is likely to resume its upward trend, presenting a profitable buying opportunity.
🟣 Bearish Implied Fair Value Gap
This pattern is similar but forms in downtrends. Here, a large bearish candlestick appears on the chart, with the wicks of adjacent candles overlapping its body. This overlap defines a supply zone or a hidden resistance level and serves as a signal for potential sell trades.
When the price returns to this zone, it often continues its downward trend, providing an optimal point for entering sell trades.
The IFVG indicator also includes various filters that traders can use to refine their analysis based on market conditions. These filters, including Very Aggressive, Aggressive, Defensive, and Very Defensive, allow users to customize the IFVG zones' width, offering flexibility according to the trader’s risk tolerance and trading style.
🟣 Example Trading Scenarios
Suppose you’re in a strong uptrend and the IFVG indicator identifies a Bullish IFVG zone. In this scenario, you could consider entering a buy trade when the price retraces to this zone, expecting the uptrend to resume. Conversely, in a downtrend, a Bearish IFVG zone can signal a favorable entry point for short trades when the price revisits this area.
🔵 Settings
Implied Block Validity Period: This parameter specifies the validity period of each identified block, taking into account the number of bars that have passed since its formation. Proper adjustment of this period helps traders focus only on relevant zones, increasing the accuracy of the analysis.
Mitigation Level OB : This option defines the mitigation level for supply and demand blocks (Order Blocks), with settings including Proximal, 50% OB, and Distal.
Depending on the selected level, the indicator will focus on closer, mid-range, or farther points for block identification, allowing traders to adjust for the level of precision required.
Implied Filter : Activating this filter allows traders to apply conditions based on the width of the IFVG zones. With options like Very Aggressive and Very Defensive, traders can control the width of IFVG zones to suit their risk management strategy—whether they prefer high-risk setups or low-risk setups.
Display and Color Settings : This section enables users to customize the appearance of the IFVG zones on their charts. Traders can set different colors for Bullish and Bearish zones, allowing for easier distinction and improved visualization.
Alert Settings : One of the standout features of the IFVG indicator is the alert system. By setting up alerts, users can be notified whenever the price approaches a demand or supply zone.
Alerts can be customized to trigger Once Per Bar (one alert per bar) or Per Bar Close (alert at the close of each bar), ensuring that traders stay updated on critical price movements without needing to monitor the chart continuously.
🔵 Conclusion
The ICT Implied Fair Value Gap (IFVG) indicator is a powerful and sophisticated tool in technical analysis, allowing professional traders to identify hidden supply and demand zones and use them as entry and exit points for buy and sell trades.
This indicator’s automatic detection of IFVG zones helps traders uncover hidden trading opportunities that can enhance their analysis.
While the IFVG indicator offers numerous advantages, it is important to use it in conjunction with other technical analysis tools and sound risk management practices.
IFVG alone does not guarantee profitability in trading; it works best when combined with other indicators such as volume analysis and trend-following indicators for a comprehensive trading strategy.
VWAP Stdev Bands Strategy (Long Only)The VWAP Stdev Bands Strategy (Long Only) is designed to identify potential long entry points in trending markets by utilizing the Volume Weighted Average Price (VWAP) and standard deviation bands. This strategy focuses on capturing upward price movements, leveraging statistical measures to determine optimal buy conditions.
Key Features:
VWAP Calculation: The strategy calculates the VWAP, which represents the average price a security has traded at throughout the day, weighted by volume. This is an essential indicator for determining the overall market trend.
Standard Deviation Bands: Two bands are created above and below the VWAP, calculated using specified standard deviations. These bands act as dynamic support and resistance levels, providing insight into price volatility and potential reversal points.
Trading Logic:
Long Entry Condition: A long position is triggered when the price crosses below the lower standard deviation band and then closes above it, signaling a potential price reversal to the upside.
Profit Target: The strategy allows users to set a predefined profit target, closing the long position once the specified target is reached.
Time Gap Between Orders: A customizable time gap can be specified to prevent multiple orders from being placed in quick succession, allowing for a more controlled trading approach.
Visualization: The VWAP and standard deviation bands are plotted on the chart with distinct colors, enabling traders to visually assess market conditions. The strategy also provides optional plotting of the previous day's VWAP for added context.
Use Cases:
Ideal for traders looking to engage in long-only positions within trending markets.
Suitable for intraday trading strategies or longer-term approaches based on market volatility.
Customization Options:
Users can adjust the standard deviation values, profit target, and time gap to tailor the strategy to their specific trading style and market conditions.
Note: As with any trading strategy, it is important to conduct thorough backtesting and analysis before live trading. Market conditions can change, and past performance does not guarantee future results.
Ido strategy RSI Oversold with MACD Buy Signal Indicator
This indicator combines the Relative Strength Index (RSI) and the Moving Average Convergence Divergence (MACD) to help identify potential buy signals based on oversold conditions and trend reversals. This script is designed for traders looking to identify entry points when an asset is likely undervalued (oversold) and showing bullish momentum.
How It Works
RSI Oversold Detection: The RSI measures the speed and change of price movements. This indicator flags when the RSI falls below 30, signaling that the asset may be oversold. The user can customize the RSI lookback period and the timeframe within which oversold conditions are considered relevant.
MACD Crossover: The MACD line crossing above the Signal line often indicates a shift to bullish momentum. In this script, a buy signal is generated when a MACD bullish crossover occurs after an RSI oversold condition has been met within a user-defined lookback window.
Buy Signal: A green triangle appears below the price chart each time both conditions are met—when the RSI has recently been in oversold territory and the MACD line crosses above the Signal line. This signal suggests that the asset may be positioned for a potential upward trend, providing a visual cue for entry points.
Customizable Settings
RSI Settings: Adjust the RSI source and period length.
MACD Settings: Customize the fast, slow, and signal lengths of the MACD to suit different market conditions.
Lookback Period: Define how many bars back to check for an RSI oversold condition before confirming a MACD crossover.
Visual Elements
Oversold Background Color: The background on the price chart is shaded red whenever the RSI is below 30.
Buy Signal: A green triangle is displayed on the chart to indicate a potential entry point when both conditions are met.
Alerts
This indicator includes optional alerts, allowing traders to receive notifications whenever the conditions for a buy signal are met, making it easier to monitor multiple assets and stay informed of trading opportunities.
This indicator is ideal for traders using a combination of momentum and trend reversal strategies, especially in volatile markets where oversold conditions often precede a trend change.
Cumulative Volume Delta Custom AlertDescription
This script calculates and visualizes the Cumulative Volume Delta (CVD) on multiple timeframes, enabling traders to monitor volume-based price action dynamics. The CVD is calculated based on up and down volume approximations and displayed as a candle plot, with color-coded alerts when significant changes occur.
Key Features:
Multi-Timeframe Analysis: The script uses a customizable anchor period and a lower timeframe for scanning, allowing it to capture more granular volume movements.
Volume-Based Trend Detection: Plots CVD candles with color indicators (teal for increasing volume delta, red for decreasing), helping traders to visually track volume trends.
Dynamic Alerts for Volume Shifts:
Triggers an alert when there is a significant (over 25%) change in CVD between consecutive periods.
The alert marker color adapts based on the current CVD value:
Blue when the current CVD is positive.
Yellow when the current CVD is negative.
Markers are placed above bars for volume increases and below for volume decreases, simplifying visual analysis.
Customizable Background Highlight: Adds a background highlight to emphasize significant CVD changes.
Use Cases:
Momentum Detection: Traders can use alerts on large volume delta changes to identify potential trend reversals or continuation points.
Volume-Driven Analysis: CVD helps distinguish buy and sell pressure across different timeframes, ideal for volume-based strategies.
How to Use
Add the script to your TradingView chart.
Configure the anchor and lower timeframes in the input settings.
Set up alerts to receive notifications when a 25% change in CVD occurs, with color-coded markers for easy identification.
Silen's EMA AreasAre you tired of reading candles? 🧨 Do you want to bring more meaning to your chart? 🧹
Then this is the script for you!
This script does:
- Add several meaningfully pre-configured EMA lines to your chart - up to EMA 300
- Colors the areas between EMA lines in 3d colors - green and red
- The Smaller the EMA, the firmer the color
- Highlights the EMA 300 in a golden color
What is the meaning of this?
Let me introduce a new word to you: EMA FOLDING .
Yes, you heard right. With this indicator you can see in 3D how EMA lines are folding above and below each other, indicating severe mood swings in the chart.
This helps you keep track of what your instrument is actually doing while it enables you to cancel out the noise and messyness of ordinary candles which can be quite random and hard to read.
Once an EMA is fully positive or negatively folded (all ema lines are green and above each other from largest EMA to smallest EMA and vice versa for negatively folded) you can be sure that you are in a Trend or certain mood (for higher timeframes, from 15mins on).
I don't ever want to read any chart without having this indicator on. Whenever I present charts to anybody I use this indicator - and the feedback is insanely positive. People tend to read and understand charts much better with this indicator than just staring at candles.
Why is this indicator different to other EMA indicators and should thereby not be deleted by the TradingView Team due to redundance with other EMA indicators?
- This is not a simple indicator for EMAs
- Rather, this is an indicator to better and easier read the whole chart
- You can detect mood swings very easily which is very hard to do with a normal EMA indicator
- I haven't found any EMA indicator on TradingView that does this job so i sincerely believe it is extremely unique
- I sincerely believe it can help people get a much better understanding of charts without actualy getting into details of EMA's or even needing to know what an EMA is.
This indicator isn't intended for trading purposes, rather it is intended to give you a better and easier understanding of the chart. Of course - you can also use it for your trading but like I said, that is not the primary intended purpose.
This indicator comes pre-configured with quite optimal values (in my opinion) but of course can be fully customized. 🧮
Test it for yourself!
Dual Momentum StrategyThis Pine Script™ strategy implements the "Dual Momentum" approach developed by Gary Antonacci, as presented in his book Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk (McGraw Hill Professional, 2014). Dual momentum investing combines relative momentum and absolute momentum to maximize returns while minimizing risk. Relative momentum involves selecting the asset with the highest recent performance between two options (a risky asset and a safe asset), while absolute momentum considers whether the chosen asset has a positive return over a specified lookback period.
In this strategy:
Risky Asset (SPY): Represents a stock index fund, typically more volatile but with higher potential returns.
Safe Asset (TLT): Represents a bond index fund, which generally has lower volatility and acts as a hedge during market downturns.
Monthly Momentum Calculation: The momentum for each asset is calculated based on its price change over the last 12 months. Only assets with a positive momentum (absolute momentum) are considered for investment.
Decision Rules:
Invest in the risky asset if its momentum is positive and greater than that of the safe asset.
If the risky asset’s momentum is negative or lower than the safe asset's, the strategy shifts the allocation to the safe asset.
Scientific Reference
Antonacci's work on dual momentum investing has shown the strategy's ability to outperform traditional buy-and-hold methods while reducing downside risk. This approach has been reviewed and discussed in both academic and investment publications, highlighting its strong risk-adjusted returns (Antonacci, 2014).
Reference: Antonacci, G. (2014). Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk. McGraw Hill Professional.
XRP Comparative RSI Indicator - Final VersionXRP Comparative RSI Indicator - Final Version
The XRP Comparative RSI Indicator offers a dynamic analysis of XRP’s market positioning through relative strength index (RSI) comparisons across various cryptocurrencies and major market indicators. This indicator allows traders and analysts to gauge XRP’s momentum and potential turning points within different market conditions.
Key Features:
• Normalized RSIs: Each RSI value is normalized between 0.00 and 1.00, allowing seamless comparison across multiple assets.
• Grouped Analysis: Three RSI groups provide specific insights:
• Group 1 (XRP-Specific): Measures XRPUSD, XRP Dominance (XRP.D), and XRP/BTC, focusing on XRP’s performance across different trading pairs.
• Group 2 (Market Influence - Bitcoin): Measures BTCUSD, BTC Dominance (BTC.D), and XRP/BTC, capturing the influence of Bitcoin on XRP.
• Group 3 (Liquidity Impact): Measures USDT Dominance (USDT.D), BTCUSD, and ETHUSD, evaluating the liquidity impact from key assets and stablecoins.
• Individual Asset RSIs: Track the normalized RSI for each specific pair or asset, including XRPUSD, BTCUSD, ETHUSD, XRP/BTC, BTC Dominance, ETH Dominance, and the S&P 500.
• Clear Color Coding: Each asset’s RSI is plotted with a unique color scheme, consistent with the first indicator, for easy recognition.
This indicator is ideal for identifying relative strengths, potential entry and exit signals, and understanding how XRP’s momentum aligns or diverges from broader market trends.
Previous Day High/Low ±0.5%The simple script was written for the educational purposes, to check if the simple system can help to hedge your strategic portfolio. Mainly works with Indexes (tested on IRUS). You can optimize strategy by changing the % in the pine code. Working mainly on D timeframe.
Current script gives you the lines on the graph, you should check if the current day close price is above the high line - buy, if below - close your buy, or reverce your position to sell, if you go in short.
XRP Comparative Price Action Indicator - Final VersionXRP Comparative Price Action Indicator - Final Version
The XRP Comparative Price Action Indicator provides a comprehensive visual analysis of XRP’s price movements relative to key cryptocurrencies and market indices. This indicator normalises price data across various assets, allowing traders and investors to assess XRP’s performance against its peers and major market influences at a glance.
Key Features:
• Normalised Price Data: Prices are scaled between 0.00 and 1.00,
enabling straightforward comparisons between different assets.
• Key Comparisons: Includes normalised prices for:
• XRP/USD (Bitstamp)
• XRP Dominance (CryptoCap)
• XRP/BTC (Bitstamp)
• BTC/USD (Bitstamp)
• BTC Dominance (CryptoCap)
• USDT Dominance (CryptoCap)
• S&P 500 (SPY)
• DXY (Dollar Index)
• ETH/USD (Bitstamp)
• ETH Dominance (CryptoCap)
• XRP/ETH (Binance)
• Visual Clarity: Each asset is plotted with distinct colors for easy identification,
with thicker lines enhancing visibility on the chart.
• Reference Lines: Optional horizontal lines indicate the minimum (0) and maximum (1) normalised values, providing clear reference points for analysis.
This indicator is ideal for traders looking to understand XRP’s relative performance, gauge market sentiment, and make informed trading decisions based on comparative price action.
Gradient color Candlesthis is a simple candle colouring script that sets the colour of the candles to a gradient and the length of the gradient can be set by a user defined number of bars
Trade 1 + StatergyThe Relative Strength Index (RSI) is a momentum oscillator used in technical analysis that measures the speed and change of price movements of a security within a range of 0 to 100. It is most commonly set to a 14-period timeframe and helps traders identify overbought or oversold conditions, suggesting potential reversal points in the market. Divergence occurs when the price trend and the RSI trend move in opposite directions. A bullish divergence signals potential upward movement when prices are making new lows while the RSI makes higher lows. Conversely, a bearish divergence suggests a possible downward trend when prices are making new highs but the RSI is making lower highs. These signals are crucial for traders looking to capture shifts in momentum and adjust their trading strategies accordingly.
use full to
5 min
10 min
15 min decition
Session Breaks [Market Mindset]Session Break Indicator
This powerful tool marks session breaks on your chart based on your chosen timeframe, helping you quickly spot key points in market sessions.
Customize it to fit your trading style with the following settings:
Resolution: Select the timeframe you want session start and end lines for.
Wait: Turn this on to delay new line creation until the bar closes, keeping your chart clean in real-time.
Styling: Adjust line width and color for optimal clarity.
Perfect for traders wanting a clear view of session transitions and opportunities!
SMA- Ashish SinghSMA
This script implements a Simple Moving Average (SMA) crossover strategy using three SMAs: 200-day, 50-day, and 20-day, with buy and sell signals triggered based on specific conditions involving these moving averages. The indicator is overlaid on the price chart, providing visual cues for potential buy and sell opportunities based on moving average crossovers.
Key Features:
Moving Averages:
The 200-day, 50-day, and 20-day SMAs are calculated and plotted on the price chart. These are key levels that traders use to assess trends.
The 200-day SMA represents the long-term trend, the 50-day SMA is used for medium-term trends, and the 20-day SMA is for short-term analysis.
Buy Signal:
A buy signal is triggered when the price is below all three moving averages (200 SMA, 50 SMA, 20 SMA) and the SMAs are in a specific downward trend (200 SMA > 50 SMA > 20 SMA). This is an indication of a potential upward reversal.
The buy signal is marked with a green triangle below the price bar.
Sell Signal:
A sell signal is triggered when the price is above all three moving averages and the SMAs are in a specific upward trend (200 SMA < 50 SMA < 20 SMA). This signals a potential downward reversal.
The sell signal is marked with a red triangle above the price bar.
Trade Information:
After a buy signal, the buy price, bar index, and timestamp are recorded. When a sell signal occurs, the percentage gain or loss is calculated along with the number of days between the buy and sell signals.
The script automatically displays a label on the chart showing the gain or loss percentage along with the number of days the trade lasted. Green labels represent gains, and red labels represent losses.
User-friendly Visuals:
The buy and sell signals are plotted as small triangles directly on the chart for easy identification.
Detailed trade information is provided with well-formatted labels to highlight the profit or loss after each trade.
How It Works:
This strategy helps traders to identify trend reversals by leveraging long-term and short-term moving averages.
A single buy or sell signal is triggered based on price movement relative to the SMAs and their order.
The tool is designed to help traders quickly spot buying and selling opportunities with clear visual indicators and gain/loss metrics.
This indicator is ideal for traders looking to implement a systematic SMA-based strategy with well-defined buy/sell points and automatic performance tracking for each trade.
Disclaimer: The information provided here is for educational and informational purposes only. It is not intended as financial advice or as a recommendation to buy or sell any stocks. Please conduct your own research or consult a financial advisor before making any investment decisions. ProfitLens does not guarantee the accuracy, completeness, or reliability of any information presented.
S&P 100 Option Expiration Week StrategyThe Option Expiration Week Strategy aims to capitalize on increased volatility and trading volume that often occur during the week leading up to the expiration of options on stocks in the S&P 100 index. This period, known as the option expiration week, culminates on the third Friday of each month when stock options typically expire in the U.S. During this week, investors in this strategy take a long position in S&P 100 stocks or an equivalent ETF from the Monday preceding the third Friday, holding until Friday. The strategy capitalizes on potential upward price pressures caused by increased option-related trading activity, rebalancing, and hedging practices.
The phenomenon leveraged by this strategy is well-documented in finance literature. Studies demonstrate that options expiration dates have a significant impact on stock returns, trading volume, and volatility. This effect is driven by various market dynamics, including portfolio rebalancing, delta hedging by option market makers, and the unwinding of positions by institutional investors (Stoll & Whaley, 1987; Ni, Pearson, & Poteshman, 2005). These market activities intensify near option expiration, causing price adjustments that may create short-term profitable opportunities for those aware of these patterns (Roll, Schwartz, & Subrahmanyam, 2009).
The paper by Johnson and So (2013), Returns and Option Activity over the Option-Expiration Week for S&P 100 Stocks, provides empirical evidence supporting this strategy. The study analyzes the impact of option expiration on S&P 100 stocks, showing that these stocks tend to exhibit abnormal returns and increased volume during the expiration week. The authors attribute these patterns to intensified option trading activity, where demand for hedging and arbitrage around options expiration causes temporary price adjustments.
Scientific Explanation
Research has found that option expiration weeks are marked by predictable increases in stock returns and volatility, largely due to the role of options market makers and institutional investors. Option market makers often use delta hedging to manage exposure, which requires frequent buying or selling of the underlying stock to maintain a hedged position. As expiration approaches, their activity can amplify price fluctuations. Additionally, institutional investors often roll over or unwind positions during expiration weeks, creating further demand for underlying stocks (Stoll & Whaley, 1987). This increased demand around expiration week typically leads to temporary stock price increases, offering profitable opportunities for short-term strategies.
Key Research and Bibliography
Johnson, T. C., & So, E. C. (2013). Returns and Option Activity over the Option-Expiration Week for S&P 100 Stocks. Journal of Banking and Finance, 37(11), 4226-4240.
This study specifically examines the S&P 100 stocks and demonstrates that option expiration weeks are associated with abnormal returns and trading volume due to increased activity in the options market.
Stoll, H. R., & Whaley, R. E. (1987). Program Trading and Expiration-Day Effects. Financial Analysts Journal, 43(2), 16-28.
Stoll and Whaley analyze how program trading and portfolio insurance strategies around expiration days impact stock prices, leading to temporary volatility and increased trading volume.
Ni, S. X., Pearson, N. D., & Poteshman, A. M. (2005). Stock Price Clustering on Option Expiration Dates. Journal of Financial Economics, 78(1), 49-87.
This paper investigates how option expiration dates affect stock price clustering and volume, driven by delta hedging and other option-related trading activities.
Roll, R., Schwartz, E., & Subrahmanyam, A. (2009). Options Trading Activity and Firm Valuation. Journal of Financial Markets, 12(3), 519-534.
The authors explore how options trading activity influences firm valuation, finding that higher options volume around expiration dates can lead to temporary price movements in underlying stocks.
Cao, C., & Wei, J. (2010). Option Market Liquidity and Stock Return Volatility. Journal of Financial and Quantitative Analysis, 45(2), 481-507.
This study examines the relationship between options market liquidity and stock return volatility, finding that increased liquidity needs during expiration weeks can heighten volatility, impacting stock returns.
Summary
The Option Expiration Week Strategy utilizes well-researched financial market phenomena related to option expiration. By positioning long in S&P 100 stocks or ETFs during this period, traders can potentially capture abnormal returns driven by option market dynamics. The literature suggests that options-related activities—such as delta hedging, position rollovers, and portfolio adjustments—intensify demand for underlying assets, creating short-term profit opportunities around these key dates.
Payday Anomaly StrategyThe "Payday Effect" refers to a predictable anomaly in financial markets where stock returns exhibit significant fluctuations around specific pay periods. Typically, these are associated with the beginning, middle, or end of the month when many investors receive wages and salaries. This influx of funds, often directed automatically into retirement accounts or investment portfolios (such as 401(k) plans in the United States), temporarily increases the demand for equities. This phenomenon has been linked to a cycle where stock prices rise disproportionately on and around payday periods due to increased buy-side liquidity.
Academic research on the payday effect suggests that this pattern is tied to systematic cash flows into financial markets, primarily driven by employee retirement and savings plans. The regularity of these cash infusions creates a calendar-based pattern that can be exploited in trading strategies. Studies show that returns on days around typical payroll dates tend to be above average, and this pattern remains observable across various time periods and regions.
The rationale behind the payday effect is rooted in the behavioral tendencies of investors, specifically the automatic reinvestment mechanisms used in retirement funds, which align with monthly or semi-monthly salary payments. This regular injection of funds can cause market microstructure effects where stock prices temporarily increase, only to stabilize or reverse after the funds have been invested. Consequently, the payday effect provides traders with a potentially profitable opportunity by predicting these inflows.
Scientific Bibliography on the Payday Effect
Ma, A., & Pratt, W. R. (2017). Payday Anomaly: The Market Impact of Semi-Monthly Pay Periods. Social Science Research Network (SSRN).
This study provides a comprehensive analysis of the payday effect, exploring how returns tend to peak around payroll periods due to semi-monthly cash flows. The paper discusses how systematic inflows impact returns, leading to predictable stock performance patterns on specific days of the month.
Lakonishok, J., & Smidt, S. (1988). Are Seasonal Anomalies Real? A Ninety-Year Perspective. The Review of Financial Studies, 1(4), 403-425.
This foundational study explores calendar anomalies, including the payday effect. By examining data over nearly a century, the authors establish a framework for understanding seasonal and monthly patterns in stock returns, which provides historical support for the payday effect.
Owen, S., & Rabinovitch, R. (1983). On the Predictability of Common Stock Returns: A Step Beyond the Random Walk Hypothesis. Journal of Business Finance & Accounting, 10(3), 379-396.
This paper investigates predictability in stock returns beyond random fluctuations. It considers payday effects among various calendar anomalies, arguing that certain dates yield predictable returns due to regular cash inflows.
Loughran, T., & Schultz, P. (2005). Liquidity: Urban versus Rural Firms. Journal of Financial Economics, 78(2), 341-374.
While primarily focused on liquidity, this study provides insight into how cash flows, such as those from semi-monthly paychecks, influence liquidity levels and consequently impact stock prices around predictable pay dates.
Ariel, R. A. (1990). High Stock Returns Before Holidays: Existence and Evidence on Possible Causes. The Journal of Finance, 45(5), 1611-1626.
Ariel’s work highlights stock return patterns tied to certain dates, including paydays. Although the study focuses on pre-holiday returns, it suggests broader implications of predictable investment timing, reinforcing the calendar-based effects seen with payday anomalies.
Summary
Research on the payday effect highlights a repeating pattern in stock market returns driven by scheduled payroll investments. This cyclical increase in stock demand aligns with behavioral finance insights and market microstructure theories, offering a valuable basis for trading strategies focused on the beginning, middle, and end of each month.
Pine Execution MapPine Script Execution Map
Overview:
This is an educational script for Pine Script developers. The script includes data structure, functions/methods, and process to capture and print Pine Script execution map of functions called while pine script execution.
Map of execution is produced for last/latest candle execution.
The script also has example code to call execution map methods and generate Pine Execution map.
Use cases:
Pine script developers can get view of how the functions are called
This can also be used while debugging the code and know which functions are called vs what developer expect code to do
One can use this while using any of the open source published script and understand how public script is organized and how functions of the script are called.
Code components:
User defined type
type EMAP
string group
string sub_group
int level
array emap = array.new()
method called internally by other methods to generate level of function being executed
method id(string tag) =>
if(str.startswith(tag, "MAIN"))
exe_level.set(0, 0)
else if(str.startswith(tag, "END"))
exe_level.set(0, exe_level.get(0) - 1)
else
exe_level.set(0, exe_level.get(0) + 1)
exe_level.get(0)
Method called from main/global scope to record execution of main scope code. There should be only one call to this method at the start of global scope.
method main(string tag) =>
this = EMAP.new()
this.group := "MAIN"
this.sub_group := tag
this.level := "MAIN".id()
emap.push(this)
Method called from main/global scope to record end of execution of main scope code. There should be only one call to this method at the end of global scope.
method end_main(string tag) =>
this = EMAP.new()
this.group := "END_MAIN"
this.sub_group := tag
this.level := 0
emap.push(this)
Method called from start of each function to record execution of function code
method call(string tag) =>
this = EMAP.new()
this.group := "SUB"
this.sub_group := tag
this.level := "SUB".id()
emap.push(this)
Method called from end of each function to record end of execution of function code
method end_call(string tag) =>
this = EMAP.new()
this.group := "END_SUB"
this.sub_group := tag
this.level := "END_SUB".id()
emap.push(this)
Pine code which generates execution map and show it as a label tooltip.
if(barstate.islast)
for rec in emap
if(not str.startswith(rec.group, "END"))
lvl_tab = str.repeat("", rec.level+1, "\t")
txt = str.format("=> {0} {1}> {2}", lvl_tab, rec.level, rec.sub_group)
debug.log(txt)
debug.lastr()
Snapshot 1:
This is the output of the script and can be viewed by hovering mouse pointer over the blue color diamond shaped label
Snapshot 2:
How to read the Pine execution map
Customizable BTC Seasonality StrategyThis strategy leverages intraday seasonality effects in Bitcoin, specifically targeting hours of statistically significant returns during periods when traditional financial markets are closed. Padysak and Vojtko (2022) demonstrate that Bitcoin exhibits higher-than-average returns from 21:00 UTC to 23:00 UTC, a period in which all major global exchanges, such as the New York Stock Exchange (NYSE), Tokyo Stock Exchange, and London Stock Exchange, are closed. The absence of competing trading activity from traditional markets during these hours appears to contribute to these statistically significant returns.
The strategy proceeds as follows:
Entry Time: A long position in Bitcoin is opened at a user-specified time, which defaults to 21:00 UTC, aligning with the beginning of the identified high-return window.
Holding Period: The position is held for two hours, capturing the positive returns typically observed during this period.
Exit Time: The position is closed at a user-defined time, defaulting to 23:00 UTC, allowing the strategy to exit as the favorable period concludes.
This simple seasonality strategy aims to achieve a 33% annualized return with a notably reduced volatility of 20.93% and maximum drawdown of -22.45%. The results suggest that investing only during these high-return hours is more stable and less risky than a passive holding strategy (Padysak & Vojtko, 2022).
References
Padysak, M., & Vojtko, R. (2022). Seasonality, Trend-following, and Mean reversion in Bitcoin.
Immediate Rebalance ICT [TradingFinder] No Imbalances - MTF Gaps🔵 Introduction
The concept of "Immediate Rebalance" in technical analysis is a powerful and advanced strategy within the ICT (Inner Circle Trader) framework, widely used to identify key market levels.
Unlike the "Fair Value Gap," which leaves a price gap requiring a retracement for a fill, an Immediate Rebalance fills the gap immediately, representing an instant balance that strengthens the prevailing market trend. This structure allows traders to quickly spot critical price zones, capitalizing on strong trend continuations without the need for price retracement.
The "Immediate Rebalance ICT" indicator leverages this concept, providing traders with automated identification of critical supply and demand zones, order blocks, liquidity voids, and key buy-side and sell-side liquidity levels.
Through features like crucial liquidity points and immediate rebalancing areas, this tool enables traders to perform precise real-time market analysis and seize profitable opportunities.
🔵 How to Use
The Immediate Rebalance indicator assists traders in identifying reliable trading signals by detecting and analyzing Immediate Rebalance zones. By focusing on supply and demand areas, the indicator pinpoints optimal entry and exit positions.
Here’s how to use the indicator in both bearish (Supply Immediate Rebalance) and bullish (Demand Immediate Rebalance) structures :
🟣 Bullish Structure (Demand Immediate Rebalance)
In a bullish scenario, the indicator detects a Demand Immediate Rebalance formed by two consecutive bullish candles with overlapping wicks. This structure signifies an immediate demand zone, where price instantly balances within the zone, reducing the likelihood of a revisit and indicating potential upside momentum.
Zone Identification : Look for two consecutive bullish candles with overlapping wicks, forming a demand zone. This structure, due to its rapid balance, usually does not require a revisit and supports further upward movement.
Entry and Exit Levels : If price revisits this zone, percentage markers, particularly 50% and 75%, act as supportive levels, creating ideal entry points for long positions.
Example : In the second image, an example of a Demand Immediate Rebalance is shown, where overlapping bullish candle shadows indicate immediate balance, supporting the continuation of the bullish trend.
🟣 Bearish Structure (Supply Immediate Rebalance)
In a bearish setup, the indicator identifies a Supply Immediate Rebalance when two consecutive bearish candles with overlapping wicks appear. This formation signals an immediate supply zone, suggesting a high probability of trend continuation to the downside, with minimal expectation for price to retrace back to this area.
Zone Identificatio n: Look for two consecutive bearish candles with overlapping shadows. This structure forms a supply area where price is expected to continue its downtrend without revisiting the zone.
Entry and Exit Level s: Should price revisit this zone, percentage-based levels (e.g., 50% and 75%) serve as potential resistance points, optimizing entry for short positions, especially if the downtrend is expected to persist.
Example : The attached chart illustrates a Supply Immediate Rebalance, where overlapping candle shadows define this area, reassuring traders of a continued downward trend with a low likelihood of price returning to this zone.
🔵 Settings
ImmR Filter : This filter allows users to adjust the detection of Immediate Rebalance zones in four modes, from "Very Aggressive" to "Very Defensive," based on zone width. The chosen mode controls the sensitivity of Immediate Rebalance detection, allowing users to fine-tune the indicator to their trading style.
Multi Time Frame : Enabling this option allows users to set the indicator to a specific timeframe (1 minute, 5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, daily, weekly, or monthly), broadening the perspective for identifying Immediate Rebalance zones across multiple timeframes.
🔵 Conclusion
The Immediate Rebalance indicator, based on rapid balancing zones within supply and demand areas, serves as a powerful tool for market analysis and improving trade decision-making.
By accurately identifying zones where price achieves instant balance without gaps, the indicator highlights areas likely to support strong trend continuations, exempt from common retracements.
The indicator’s use of percentage levels enables traders to pinpoint optimal entry and exit points more effectively, with levels like 50% and 75% acting as support within demand zones and resistance within supply zones. This empowers traders to ride strong trends without the worry of abrupt reversals.
Overall, the Immediate Rebalance is a reliable tool for both professional and beginner traders seeking precise methods to recognize supply and demand zones, capitalizing on consistent trends.
By choosing appropriate settings and focusing on the zones highlighted by this indicator, traders can enter trades with greater confidence and improve their risk management.
Patrick [TFO]This Patrick indicator was made for the 1 year anniversary of my Spongebob indicator, which was an experiment in using the polyline features of Pine Script to draw complex subjects. This indicator was made with the same methodology, with some helper functions to make things a bit easier on myself. It's sole purpose is to display a picture of Patrick Star on your chart, particularly the "I have $3" meme.
The initial Spongebob indicator included more than 1300 lines of code, as there were several more shapes to account for compared to Patrick, however it was done rather inefficiently. I essentially used an anchor point for each "layer" or shape (eye, nose, mouth, etc.), and drew from that point. This resulted in a ton of trial and error as I had to be very careful about the anchor points for each and every layer, and then draw around that point. In this indicator, however, I gave myself a frame to work with by specifying fixed bounds that you'll see in the code: LEFT, RIGHT, TOP, and BOTTOM.
var y_size = 4
atr = ta.atr(50)
LEFT = bar_index + 10
RIGHT = LEFT + 200
TOP = open + atr * y_size
BOTTOM = open - atr * y_size
You may notice that the top and bottom scale with the atr, or Average True Range to account for varying price fluctuations on different assets.
With these limits established, I could write some simple functions to translate my coordinates, using a range of 0-100 to describe how far the X coordinates should be from left to right, where left is 0 and right is 100; and likewise how far the Y coordinates should be from bottom to top, where bottom is 0 and top is 100.
X(float P) =>
result = LEFT + math.floor((RIGHT - LEFT)*P/100)
Y(float P) =>
result = BOTTOM + (TOP - BOTTOM)*P/100
With these functions, I could then start drawing points much simpler, with respect to the overall frame of the picture. If I wanted a point in the dead center of the frame, I would choose X(50), Y(50) for example.
At this point, the process just became tediously drawing each layer of my reference picture, including but not limited to Patrick's body, arm, mouth, eyes, eyebrows, etc. I've attached the reference picture here (left), without the text enabled.
As tedious as this was to create, it was done much more efficiently than Spongebob, and the ideas used here will make it much easier to draw more complex subjects in the future.
