In the dynamic landscape of stock market trading, identifying predictable patterns that precede significant price movements is paramount for informed decision-making. One such phenomenon, volatility compression, presents a compelling area of study for traders and investors alike. This research delves into the intricacies of volatility compression, a market condition characterized by a notable contraction in an asset’s short-term price fluctuations relative to its longer-term norm. This period of relative calm often sets the stage for substantial volatility expansion and directional breakouts, offering potential profit opportunities.

This paper aims to provide a comprehensive understanding of volatility compression, exploring its theoretical underpinnings and the technical methodologies employed for its identification. We will examine various indicators, including Bollinger Bands, Average True Range ratios, and Keltner Channels, to pinpoint periods of constricted price action. Furthermore, this research will delve into the crucial aspects of developing a robust trading strategy based on volatility compression, encompassing precise entry and exit rules, the integration of confirming technical indicators, and a strong emphasis on risk management. By analyzing the limitations and potential pitfalls associated with this strategy, including the challenge of false breakouts, this study seeks to equip readers with a nuanced perspective on leveraging volatility compression for effective trading.

Capitalizing on Volatility Compression: A Stock Market Trading Strategy

1. Understanding Volatility Compression

1.1 Defining Volatility and Volatility Compression:

Volatility, in the context of stock market trading, serves as a statistical barometer indicating the degree to which the price of a financial instrument fluctuates over a specific period.¹ It is often quantified by measures such as standard deviation or variance of returns.¹ High volatility is characterized by significant and often rapid price swings, suggesting a greater degree of unpredictability and potential risk, but also opportunity. Conversely, low volatility implies a period of relative price stability, with smaller and less frequent movements. However, volatility itself is not directly observable and must be calculated using historical price data.² Various methods exist for this calculation, including the standard deviation of returns, which measures the average deviation of prices from their mean over a given timeframe, the Average True Range (ATR), which quantifies the average daily price range, and implied volatility, which is derived from options prices and reflects the market’s expectation of future price fluctuations.¹ The choice of volatility measurement can influence the identification of compression periods.

Volatility compression is a market condition that arises when the short-term volatility of an asset contracts or diminishes in relation to its longer-term volatility.¹ This phenomenon suggests a period of consolidation where price movements become increasingly narrow, often preceding a significant breakout or expansion in price.¹ This contraction in volatility can be identified through various technical analysis techniques.

1.2 Theoretical Basis: Why Volatility Compression Leads to Expansion:

Periods characterized by low volatility often reflect a temporary equilibrium in the forces of supply and demand, resulting in a constricted trading range for the asset.⁶ This balance, however, is frequently transient. During these phases of compression, larger market participants may be strategically accumulating or distributing shares without causing significant price fluctuations, thereby setting the stage for a substantial price movement once sufficient buying or selling pressure is exerted.⁶ This suggests that a decrease in selling activity, for instance, as sellers become less inclined to offer their shares at lower prices, can lead to a buildup of underlying demand.⁸ Conversely, a lack of sustained buying interest might precede a downward move. The identification of volatility compression, therefore, necessitates discerning the potential direction of the impending expansion.

The concept of a “coiled spring” is frequently employed to illustrate this market behavior.⁶ Just as a tightly wound spring stores potential energy, a period of constricted price action and low volatility can build up latent energy that is subsequently released in the form of a sharp directional move.⁶ This move can occur in either direction, highlighting the importance of identifying not only the compression but also the likely direction of the eventual breakout.

1.3 Methods for Identifying Volatility Compression:

Several technical analysis tools and techniques can be employed to identify periods of volatility compression in the stock market.

1.3.1 Bollinger Bands Squeeze:

Bollinger Bands, a popular volatility indicator, consist of a simple moving average (SMA) flanked by two bands plotted at a certain number of standard deviations (typically two) above and below the SMA. These bands dynamically adjust to market volatility; they widen during periods of high volatility and contract when volatility decreases. A “Squeeze,” also known as volatility compression, is identified when these bands narrow to their tightest point over a defined lookback period, suggesting a significant decrease in volatility. Investopedia indicates that a Bollinger Squeeze is specifically triggered when volatility reaches a six-month low and is visually confirmed when the Bollinger Bands on a price chart narrow significantly, indicating a period of low volatility. This narrowing of the bands to a six-month minimum distance apart suggests a potential for an explosive breakout in either direction. While the six-month low serves as a specific timeframe for identifying compression, it is important to note that the optimal lookback period for defining a Squeeze might vary depending on the specific asset being analyzed and the trader’s preferred trading timeframe.

1.3.2 ATR Ratio:

Another method for identifying volatility compression involves comparing the short-term Average True Range (ATR) of an asset to its longer-term ATR. The ATR measures the average range between the high and low prices of an asset over a specified period, providing a gauge of its volatility. By calculating the ratio of a shorter-period ATR (e.g., 5-day ATR) to a longer-period ATR (e.g., 60-day ATR), traders can identify instances where short-term volatility is low relative to the longer-term trend.¹ Adam Grimes notes that a ratio below a certain threshold, such as the 5-day ATR falling below the 60-day ATR, suggests that short-term volatility has contracted compared to longer-term volatility, often preceding a directional move.¹ This ATR ratio offers a dynamic and relative measure of volatility compression, as it automatically adjusts to the inherent or baseline volatility level of the specific market being analyzed.¹ This adaptability can be advantageous compared to fixed thresholds, as it accounts for the varying volatility characteristics across different assets.

1.3.3 Keltner Channels:

Keltner Channels are another volatility-based indicator that can help identify periods of compression. These channels are typically constructed using an Exponential Moving Average (EMA) as the centerline, with upper and lower bands set at a distance of a multiple of the ATR above and below the EMA. Similar to Bollinger Bands, Keltner Channels widen during periods of high volatility and narrow during periods of low volatility. Volatility compression can be observed when the price of an asset consolidates within a narrow range defined by the upper and lower boundaries of the Keltner Channels. The Volatility Breakout (VBO) strategy, for example, identifies a state of low volatility compression when Bollinger Bands are contained entirely within the boundaries of the Keltner Channels.¹⁰ A potential breakout signal is then generated when the price closes definitively outside of both the Bollinger Bands and the Keltner Channels.¹⁰ This combined approach, utilizing both Bollinger Bands and Keltner Channels, offers a more stringent definition of volatility compression, as it requires confirmation of low volatility from two distinct but related indicators.¹⁰ This increased confluence may potentially filter out some of the false signals that might arise from relying on a single volatility indicator alone.

2. Identifying Potential Breakout Candidates

2.1 Screening Criteria for Stocks Exhibiting Volatility Compression:

To effectively implement a trading strategy based on volatility compression, the initial step involves identifying stocks that are currently exhibiting this phenomenon. This can be achieved through systematic screening processes. One approach is to scan the market for stocks where Bollinger Bands are currently in a Squeeze, indicating a period of historically low volatility. Another criterion involves identifying stocks with a low ratio of short-term to long-term ATR, suggesting that recent price volatility has contracted relative to its longer-term average.¹ Furthermore, traders might look for stocks where the price action shows Bollinger Bands being contained within Keltner Channels, signifying a particularly tight period of consolidation.¹⁰

The timeframe used for this screening process should be adaptable to the trader’s specific goals and trading style. For instance, identifying volatility compression on a daily chart might present suitable opportunities for swing trading strategies, where positions are held for several days or weeks. Conversely, observing compression patterns on hourly or even shorter timeframes, such as 15-minute or 5-minute charts, could be more relevant for day traders seeking to capitalize on intraday price movements. Additionally, considering the use of range bar charts can provide a unique perspective on volatility. Range bar charts plot bars based on price movement rather than time, and during periods of low volatility, fewer range bars will be printed, directly visualizing the compression. Investopedia explains that range bar charts show fewer bars during periods of low volatility, directly reflecting this contraction in price movement. This alternative charting method focuses solely on price action, filtering out time-based information, which can make periods of volatility compression more visually apparent.

2.2 Incorporating Trend Analysis and Market Context:

Beyond identifying volatility compression, it is crucial to consider the prevailing market trend and the broader market context to enhance the probability of a successful trade. Volatility Contraction Patterns (VCPs), as described by TraderLion, are often observed as continuation patterns within an established uptrend. These patterns are characterized by successive price pullbacks that become smaller over time, accompanied by a decrease in trading volume, indicating a drying up of selling pressure and a potential buildup of demand. Therefore, looking for volatility compression patterns that form after a stock has already established an uptrend can increase the likelihood of a bullish breakout. Conversely, it is generally prudent to exercise caution when considering compression patterns that form within strong downtrends, as these may be indicative of bearish continuation rather than a reversal, unless there is strong confirming evidence to the contrary.

Furthermore, an analysis of the overall market conditions is essential. Understanding whether the broader market is currently in a low volatility or high volatility regime can provide valuable context for individual stock analysis. Tools like the CBOE Volatility Index (VIX), often referred to as the “fear index,” can serve as an indicator of overall market volatility expectations. Investopedia notes that a rising VIX can signal increased fear of a market downturn. A low VIX reading might suggest a market environment where volatility is generally subdued, potentially increasing the probability of a significant volatility expansion following a period of compression in an individual stock.

2.3 The Role of Volume in Identifying High-Probability Setups:

Trading volume plays a significant role in validating volatility compression breakout setups. In the context of Volatility Contraction Patterns (VCPs), a consistent decrease in trading volume during the compression phase is often interpreted as a sign that sellers are becoming less active and the supply of the stock at lower prices is diminishing. This decrease in volume during the consolidation phase suggests that the subsequent breakout, if accompanied by a surge in volume, is more likely to be a genuine signal of increased demand or supply. TraderLion highlights that a strong VCP breakout is frequently characterized by a significant spike in volume on the day of the breakout, often in the range of 30-40% above the average. This increase in volume indicates strong conviction behind the price movement, with both institutional and retail traders participating, thereby increasing the probability of a sustained upward or downward trend. Conversely, a breakout from a volatility compression pattern that occurs on low volume might be indicative of a lack of strong conviction and could have a higher likelihood of being a false breakout or a short-lived move. Therefore, monitoring volume in conjunction with price action is crucial for identifying high-probability volatility compression breakout trades.

3. Developing the Trading Strategy

3.1 Entry Rules:

The entry rules for a volatility compression trading strategy must be clearly defined to ensure a systematic approach. Several potential entry triggers can be considered based on the methods used to identify compression.

3.1.1 Bollinger Bands Squeeze Breakout:

A common entry rule involves initiating a long position when the price closes above the upper Bollinger Band following a period of Squeeze, signaling the start of a potential upward move. Conversely, a short position can be entered when the price closes below the lower Bollinger Band after a Squeeze, suggesting a downward breakout.

3.1.2 ATR Ratio Breakout:

If using the ATR ratio, a threshold needs to be defined (e.g., a 5-day ATR falling below 0.8 times the 60-day ATR). Once this condition is met, a long entry can be triggered when the price subsequently breaks above a recent high (e.g., the high of the consolidation period). A short entry would occur when the price breaks below a recent low after the ATR ratio indicates compression.¹

3.1.3 VBO Strategy Entry:

For traders employing the Volatility Breakout (VBO) strategy, a long entry is typically initiated when the price closes above both the upper Bollinger Band and the upper Keltner Channel, after the Bollinger Bands have been contained within the Keltner Channels. A short entry occurs when the price closes below both the lower Bollinger Band and the lower Keltner Channel under the same prior condition.¹⁰

3.1.4 Volatility Contraction Pattern (VCP) Breakout:

When trading based on the Volatility Contraction Pattern, a long entry is generally placed when the price breaks above the pivot point, which is the high of the last price contraction within the VCP, and this breakout is accompanied by a noticeable increase in trading volume. This strategy is typically applied to stocks that are already in an established uptrend.

It is important to note that the entry rules should be as specific as possible, clearly outlining the conditions that must be met to trigger a trade. This includes specifying the type of breakout (e.g., a confirmed close above a level, an intraday break) and any required confirmation, such as a surge in volume.

3.2 Exit Rules:

Establishing clear exit rules is just as critical as defining entry points for a successful trading strategy. Exit rules typically involve setting profit targets and stop-loss levels.

3.2.1 Profit Targets:

Several methods can be used to determine appropriate profit targets following a volatility compression breakout. One approach involves measuring the trading range that prevailed during the compression period and projecting this range upwards (for long trades) or downwards (for short trades) from the point of the breakout. For example, if a stock traded within a $5 range during compression and then breaks out to the upside at $50, a profit target could be set at $55. Another common technique is to use multiples of the Average True Range (ATR) to set profit targets. For instance, a trader might set a profit target at a distance of two times the ATR from their entry price. In the context of VCPs, TraderLion suggests aiming for potential gains of 15% or more, while maintaining a favorable risk-to-reward ratio of 3:1 or better. Some traders also employ the strategy of using multiple profit target levels, allowing them to lock in a portion of the profits as the trade moves favorably while leaving a remaining portion to potentially capture further gains. Investopedia suggests that when trading price patterns, the range of the recent channel or pattern can be used as a price target once the stock breaks out. WH SelfInvest describes trading systems that utilize profit targets set as a multiple of the initial risk or the size of the breakout range. The choice of profit target method can depend on the specific characteristics of the volatility compression pattern, the prevailing market conditions, and the trader’s individual risk tolerance and profit objectives.

3.2.2 Stop-Loss Levels:

Stop-loss orders are essential for managing risk and limiting potential losses in any trading strategy. For volatility compression breakouts, stop-loss orders are typically placed at a level that would indicate the breakout has failed. For long trades, a stop-loss might be placed below the low of the breakout bar, while for short trades, it could be placed above the high of the breakout bar.¹⁰ In the case of VCPs, TraderLion recommends placing the stop-loss order just below the low of the last price contraction within the pattern. Investopedia advises using the previous resistance level as a new support level for long breakouts and the previous support level as a new resistance level for short breakouts as a reference point for setting stop-loss orders. Many traders also find it beneficial to use a trailing stop-loss, which automatically adjusts as the trade moves in a profitable direction, helping to protect profits while still allowing the trade room to run. The precise placement of the stop-loss should be logical and aligned with the specific volatility compression pattern being traded.

3.3 Timeframe Considerations:

Volatility compression is a phenomenon that can be observed across various trading timeframes, from short-term intraday charts to longer-term daily, weekly, or even monthly charts.⁶ Day traders, who typically hold positions for a single trading day, might focus on identifying compression patterns that develop on shorter timeframes such as 5-minute or 15-minute charts. Conversely, swing traders, who aim to profit from price movements over several days or weeks, might look for volatility compression forming on daily or weekly charts. The duration for which a trade is held will naturally vary depending on the timeframe of the identified compression and the strength and momentum of the subsequent breakout. It is important to recognize that the optimal timeframe for trading volatility compression breakouts will depend on the individual trader’s style, risk tolerance, and trading objectives. Shorter timeframes might present more frequent trading opportunities but could also be associated with a higher incidence of false signals or “noise.”

4. Utilizing Technical Indicators for Confirmation

4.1 Integrating Volatility Indicators:

To increase the reliability of a volatility compression trading strategy, it is often beneficial to use additional technical indicators to confirm the anticipated breakout and the subsequent expansion of volatility.

4.1.1 Bollinger Bands:

After identifying a Bollinger Bands Squeeze, the widening of the bands following a price breakout can serve as a confirmation of increasing volatility and the potential commencement of a sustained trend in the direction of the breakout.

4.1.2 Average True Range (ATR):

Following a breakout from a volatility compression zone, an increase in the ATR value can provide confirmation that the price movement is indeed expanding and that volatility is increasing as expected.

4.1.3 VIX:

Monitoring the VIX, the market’s fear gauge, can also offer insights. A low VIX reading preceding a volatility compression pattern in an individual stock might suggest a higher probability of a significant price breakout and subsequent volatility expansion in that specific stock.

4.1.4 Keltner Channels:

In strategies that utilize both Bollinger Bands and Keltner Channels to identify compression, a confirmed break of the price outside the Keltner Channels after the Bollinger Bands were inside can provide further validation of a significant volatility expansion and a potentially strong directional move.

Employing multiple volatility indicators can lead to a more robust confirmation of the transition from a low volatility compression phase to a high volatility expansion phase. However, it is important to select indicators that complement each other and to avoid using an excessive number of indicators, which could lead to conflicting signals or analysis paralysis.

Table 1: Volatility Indicators for Confirmation

4.2 Combining Momentum Indicators:

In addition to volatility indicators, incorporating momentum indicators can help to gauge the strength and potential sustainability of a breakout from a volatility compression pattern.

4.2.1 Relative Strength Index (RSI):

The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Looking for the RSI to move in the direction of the breakout can provide confirmation of the momentum behind the move. For example, in the case of a bullish breakout, an RSI reading above 50 might be considered a desirable confirmation of upward momentum.

4.2.2 Moving Averages:

Price breaking above key moving averages, such as the 50-day or 200-day moving average, following a period of volatility compression can signal a potential shift in trend and the start of a more sustained directional move. The crossing of shorter-term moving averages above longer-term moving averages can also provide bullish confirmation.

Momentum indicators can be valuable in filtering out potential false breakouts by confirming that the price movement has sufficient strength and is likely to continue in the anticipated direction.

Table 2: Momentum Indicators for Confirmation

5. Risk Management Framework

5.1 Determining Appropriate Position Sizing:

Proper position sizing is a cornerstone of effective risk management in any trading strategy, including one based on volatility compression. It involves determining the appropriate number of shares or contracts to trade based on the trader’s capital, risk tolerance, and the specific characteristics of the trade setup. A common guideline is to risk only a small percentage of total trading capital on any single trade, such as 1% or 2%. The position size should also be adjusted based on the volatility of the stock being traded and the distance between the entry price and the stop-loss level. Higher volatility generally warrants smaller position sizes to limit potential losses. The fundamental principle is to ensure that any single losing trade does not have a significant impact on the overall trading capital.

5.2 Strategies for Managing Risk During Periods of High Volatility:

While the goal of a volatility compression strategy is to profit from the subsequent expansion of volatility, it is crucial to have strategies in place to manage the inherent risks associated with volatile market conditions. One approach is to consider widening stop-loss levels slightly to account for potentially larger price swings that can occur during high volatility periods. However, it is important to avoid widening stop-losses excessively, as this could lead to larger-than-anticipated losses. Another risk management tactic involves potentially reducing position sizes during periods of heightened market volatility, such as around major economic news announcements or company earnings reports. This helps to mitigate the impact of potentially sharp and unexpected price movements.

5.3 The Importance of Stop-Loss Orders:

The use of stop-loss orders is an absolutely essential component of risk management when trading volatility compression breakouts. A stop-loss order is an instruction to automatically close a trade if the price reaches a predetermined level, thereby limiting the potential loss on the trade. In the context of volatility breakouts, stop-loss orders are typically placed at a level that would invalidate the breakout thesis. For instance, after a bullish breakout, a stop-loss might be placed just below the previous resistance level, which should now act as support. It is a fundamental principle of prudent trading to always have a stop-loss order in place before initiating a trade.

6. Backtesting and Performance Evaluation

6.1 Guidance on How to Backtest the Strategy:

Before deploying any trading strategy with real capital, it is crucial to evaluate its historical effectiveness through a process called backtesting. To backtest a volatility compression strategy, traders need to obtain historical price data for the stocks and timeframes they intend to trade. Then, the clearly defined entry and exit rules of the strategy should be applied to this historical data in a systematic and unbiased manner. All simulated trades, including the entry price, exit price, and the resulting profit or loss, should be meticulously recorded. It is also beneficial to note any relevant observations about the market conditions or the behavior of the strategy during different periods. Utilizing trading simulation software or platforms can significantly streamline the backtesting process by automating the application of the trading rules to historical data.

6.2 Key Metrics for Evaluating the Strategy’s Effectiveness:

After conducting a backtest, several key metrics can be used to evaluate the performance and effectiveness of the volatility compression trading strategy. The win rate, which is the percentage of trades that resulted in a profit, provides an indication of the strategy’s accuracy. The profit factor, calculated as the ratio of total gross profit to total gross loss, indicates the overall profitability of the strategy. An average profit factor greater than 1 suggests that the strategy generates more profit than loss. Analyzing the average profit per trade and the average loss per trade can provide insights into the typical outcome of winning and losing trades. Finally, the maximum drawdown, which represents the largest peak-to-trough decline in account equity during the backtesting period, is a critical measure of the risk associated with the strategy. These metrics collectively provide a quantitative assessment of the strategy’s historical performance and its risk characteristics.

7. Limitations and Potential Pitfalls

7.1 Addressing the Possibility of False Breakouts and Whipsaws:

It is important to acknowledge that volatility compression does not invariably lead to a successful breakout, and breakouts can and do fail. Market conditions can change rapidly, and what appears to be a high-probability setup can sometimes result in a false breakout, where the price initially moves out of the compression zone but then reverses direction. These rapid price reversals, often referred to as whipsaws, can trigger stop-loss orders and lead to losses. Employing confirmation indicators, such as observing a significant increase in volume accompanying the breakout or waiting for momentum indicators to align with the direction of the breakout, can help to reduce the likelihood of being caught in false breakouts.

7.2 The Impact of Market Conditions and News Events on the Strategy:

The effectiveness of a volatility compression trading strategy can be significantly influenced by overall market conditions and unexpected news events. Major economic data releases, company earnings reports, and geopolitical events can introduce sudden and significant volatility into the market, potentially invalidating established compression patterns or leading to sharp, unexpected price movements. Traders utilizing this strategy should therefore remain vigilant about upcoming news releases and events that could impact the stocks they are trading or the broader market. Being aware of such potential catalysts for volatility can help traders to manage their positions more effectively and avoid being caught off guard by sudden market shifts.

7.3 Psychological Considerations in Trading Volatility Breakouts:

The anticipation of a breakout following a period of volatility compression can sometimes lead to traders initiating positions prematurely, before the actual breakout has been confirmed according to their defined rules. This can result in being stopped out if the price does not move as expected. Furthermore, the fear of missing out (FOMO) can sometimes cause traders to chase breakouts that have already occurred and are potentially overextended, increasing the risk of entering at an unfavorable price. Maintaining discipline and adhering strictly to the pre-defined entry and exit rules of the trading strategy is crucial to avoid emotional decision-making, which can often lead to suboptimal trading outcomes.

Conclusion

Capitalizing on volatility compression offers a potentially profitable stock market trading strategy by identifying periods of low volatility that often precede significant price movements. By employing techniques such as Bollinger Bands Squeezes, ATR ratios, and the Volatility Breakout strategy, traders can identify potential breakout candidates. Integrating trend analysis, market context, and volume confirmation further enhances the probability of successful trades. The strategy necessitates clearly defined entry and exit rules, including profit targets and stop-loss levels, tailored to the chosen timeframe. Utilizing additional technical indicators, such as other volatility and momentum indicators, can provide valuable confirmation signals. However, effective risk management, through appropriate position sizing and the consistent use of stop-loss orders, is paramount. Backtesting the strategy across various market conditions and timeframes is essential to evaluate its historical performance and identify potential limitations, such as false breakouts and the impact of market-moving news. Ultimately, a disciplined and systematic approach, coupled with an awareness of the psychological aspects of trading, is crucial for successfully implementing a volatility compression trading strategy.

Works cited

1. Volatility: Meaning in Finance and How It Works With Stocks – Investopedia, accessed May 4, 2025, https://www.investopedia.com/terms/v/volatility.asp
2. The Anatomy of Trading Breakouts – Investopedia, accessed May 4, 2025, https://www.investopedia.com/articles/trading/08/trading-breakouts.asp
3. Volatility | Trading Lesson | Traders’ Academy | IBKR Campus, accessed May 4, 2025, https://www.interactivebrokers.com/campus/trading-lessons/volatility/
4. Volatility Trading Strategies: How to Trade Volatility – Admiral Markets, accessed May 4, 2025, https://admiralmarkets.com/education/articles/general-trading/volatility-trading-strategies
5. Volatility Compression Breakout — Indicator by LeafAlgo – TradingView, accessed May 4, 2025, https://www.tradingview.com/script/Lc8WH9UF-Volatility-Compression-Breakout/
6. Volatility Contraction Pattern (VCP): How to Day Trade It – Tradingsim, accessed May 4, 2025, https://www.tradingsim.com/blog/volatility-contraction-pattern
7. David Pieper breakout trading strategy based on volatility. – WH SelfInvest, accessed May 4, 2025, https://www.whselfinvest.com/en-nl/trading-platform/free-trading-strategies/tradingsystem/83-david-pieper-histo-breakout-strategy
8. Mastering The Volatility Contraction Pattern – TraderLion, accessed May 4, 2025, https://traderlion.com/technical-analysis/volatility-contraction-pattern/
9. Volatility Momentum Breakout Strategy par cryptechcapital – TradingView, accessed May 4, 2025, https://fr.tradingview.com/script/dJe0bGvQ-Volatility-Momentum-Breakout-Strategy/
10. Trading Volatility Compression – • The Blog of Adam H Grimes, accessed May 4, 2025, https://adamhgrimes.com/volatility-compression-2/
11. “Breakout strategies are not profitable” : r/Daytrading – Reddit, accessed May 4, 2025, https://www.reddit.com/r/Daytrading/comments/1eue5y9/breakout_strategies_are_not_profitable/

According to Google Gemini, volatility compression, a state in the S&P 500 characterized by a low ratio of short-term to longer-term volatility, often manifests as a period of constricted price movement.1 This report analyzes the correlation between such periods and the subsequent occurrence of significant price movements. The findings suggest that volatility compression does increase the likelihood of a sharp move in the S&P 500; however, it does not inherently predict the direction of this move. While volatility compression can serve as an early signal for potential trading opportunities, its reliability as a directional indicator is limited and requires confirmation from other analytical tools. Various trading strategies, including breakout trading and options strategies, are employed to capitalize on the volatility expansion that typically follows compression. Nevertheless, these strategies are subject to inherent limitations and risks, including the possibility of false signals.

Volatility Compression in the S&P 500 as a Signal for Sharp Market Moves

Introduction

Volatility, in the context of the S&P 500, represents a statistical measure of the dispersion of its returns, often quantified by metrics such as standard deviation or variance. Higher volatility is typically associated with larger price swings in either direction within the securities markets. Understanding volatility is paramount, particularly in the realm of options pricing, where it serves as a crucial determinant of contract value. Volatility compression, conversely, describes a market condition where the ratio of short-term volatility relative to longer-term volatility is notably low. This often materializes as a phase where the S&P 500 trades within a narrow and defined price range, indicating a marked decrease in the index’s price volatility. This report aims to rigorously analyze the correlation between these periods of volatility compression in the S&P 500 and the subsequent emergence of sharp price movements, whether upward or downward, and to evaluate the efficacy of volatility compression as an early signal for such market events.

Understanding Volatility Compression in the S&P 500

Volatility compression in the S&P 500 signifies a period of diminished price fluctuations, often acting as a precursor to a substantial price movement. This phenomenon can be understood as a temporary state of equilibrium where the forces of buying and selling are relatively balanced, resulting in a market characterized by indecision. When the S&P 500’s price range tightens, it indicates a decrease in volatility, suggesting that the factors that typically cause price changes are currently subdued, leading to this phase of compression. However, this equilibrium is inherently transient; new catalysts will eventually arise, disrupting the balance and initiating a significant price movement.

Several technical analysis tools are utilized to identify and measure volatility compression in the S&P 500. Bollinger Bands, which are plotted two standard deviations away from a simple moving average, narrow when volatility decreases. A significant constriction of these bands, known as a Bollinger Band Squeeze, is often interpreted as a strong signal that a period of low volatility is nearing its end and that a substantial volatility expansion and subsequent price breakout are likely to occur. The tightening of the bands around the price suggests that the current stability is unlikely to persist, and the price will eventually move out of this confined range, potentially leading to a sharp move. Similarly, Keltner Channels, which are typically set using the Average True Range (ATR) above and below a moving average, also converge when market volatility diminishes. The TTM Squeeze indicator, a more sophisticated tool, leverages the interplay between Bollinger Bands and Keltner Channels to pinpoint periods of volatility compression. A “squeeze” is identified when the Bollinger Bands are entirely contained within the Keltner Channels.

The Average True Range (ATR) itself is a direct measure of market volatility, quantifying the average range between high and low prices over a specified period. A declining ATR value directly indicates a reduction in the S&P 500’s price volatility, thus signifying volatility compression. A sustained period of low ATR readings can highlight a market that is in a compressed state, potentially building towards a significant price movement. The TTM Squeeze indicator further aids in this identification by visually representing periods of low volatility with specific markers. For instance, red dots on the indicator often signify that the S&P 500 is in a “squeeze,” meaning volatility is low and a potential breakout is imminent. The end of the squeeze, often indicated by a change in the indicator’s color or pattern, suggests that volatility is expanding, and a price breakout is likely. While the momentum histogram component of the TTM Squeeze can offer hints about the potential direction of the breakout, this aspect is not always a reliable predictor.

The Cboe Volatility Index (VIX) serves as a crucial benchmark for assessing the overall expected volatility of the S&P 500 market over the next 30 days. It is derived from the prices of S&P 500 index options. A generally inverse correlation is observed between the VIX and the S&P 500 index, where an increase in the VIX often coincides with a decline in the S&P 500, and vice versa. A sustained period of low VIX readings might suggest that the market is experiencing volatility compression, potentially indicating a phase of calm before a subsequent increase in volatility and a sharp market move. A low VIX implies that market participants are not anticipating significant price swings in the near term. However, this period of low expected volatility can sometimes precede a sudden surge in realized volatility, leading to a substantial price movement in the S&P 500.

Historical Analysis of Volatility Compression and Sharp Moves

Historically, the S&P 500 has experienced several periods of low volatility. Notable examples include the extended phase of subdued volatility observed between February 2016 and January 2018, as well as the relatively calm market conditions that prevailed for a significant portion of 2023. These prolonged periods of low volatility were often attributed to a confluence of factors, such as a decrease in the correlation of equity returns, a prevailing low interest rate environment, and generally stable macroeconomic conditions. Understanding the underlying drivers of these compression phases is essential for contextualizing the subsequent market behavior.

Analysis of the market’s response following these periods of volatility compression reveals a common expectation among traders and analysts: a phase of low volatility is frequently followed by a phase of heightened volatility, characterized by significant price fluctuations and potential breakouts from established trading ranges. It is crucial to note that these breakouts can manifest in either direction, resulting in sharp upward rallies or substantial downward corrections. The market volatility spike in February 2018, which occurred after the extended period of low volatility in the preceding years, serves as a prominent historical illustration of how volatility compression can precede a sharp market correction. This event highlighted the potential for increased risk-taking and complacency during prolonged low-volatility environments. The extended period of low volatility leading up to February 2018 might have fostered an environment of increased leverage and reduced risk aversion among market participants. When concerns regarding inflation and the trajectory of interest rates began to surface, it triggered a rapid unwinding of leveraged positions, leading to a sudden and significant increase in volatility and a substantial downturn in the S&P 500.

Considering specific historical examples further illuminates this relationship. Significant one-day gains and losses in the S&P 500 have frequently occurred following periods of relative calm or in reaction to major economic or political announcements. Examining historical charts and volatility data surrounding major market events, such as the bursting of the dot-com bubble in 2000-2002 or the global financial crisis of 2008-2009, could reveal patterns where periods of low volatility preceded the onset of these major market corrections or the subsequent sharp recovery rallies. Studying these past market crashes and recoveries can help identify instances where volatility compression acted as a precursor to these significant market events. This historical context is invaluable for understanding the potential relationship between periods of low volatility and subsequent substantial price movements.

Correlation and Predictive Power

Analyzing the statistical correlation between identified periods of volatility compression in the S&P 500 and the subsequent occurrence of sharp price movements reveals a general market expectation: low volatility often precedes high volatility, suggesting a positive correlation between the end of a compression phase and the beginning of a significant price change. However, it is crucial to emphasize that volatility compression, in and of itself, does not inherently determine the direction of the ensuing sharp move, whether it will be upwards or downwards. The primary correlation observed is between the period of low volatility and the increased likelihood of a substantial price change, rather than a prediction of the specific direction this change will take. Volatility compression indicates that the market is in a state of consolidation, often described as being “coiled” and ready to move. The compression phase is characterized by a decrease in the standard deviation of returns. The subsequent sharp move signifies an increase in this standard deviation. The correlation lies in this transition from a period of low volatility to one of high volatility, which often manifests as a sharp price change.

Academic research and expert analysis offer varying perspectives on the predictive capabilities of volatility compression for the S&P 500’s direction. Some studies suggest that advanced machine learning models can be effectively applied to analyze volatility indices and predict the future direction of the stock market with a degree of success. Additionally, the VIX index, while primarily designed as a measure of expected volatility, has been shown to contain some predictive information regarding the subsequent magnitude of changes in the S&P 500, even if it does not consistently indicate the direction of those changes. Furthermore, some experts in the field have noted that low levels of implied volatility, particularly when observed during market highs, can sometimes serve as a cautionary signal of an impending significant market correction. While these sophisticated analytical techniques attempt to extract directional signals from volatility data, it is important to acknowledge that there is no universally reliable method to predict with absolute certainty whether a breakout from a volatility compression phase will be upwards or downwards. Predicting market direction remains a complex endeavor. While the occurrence of volatility compression suggests an imminent increase in price movement, the ultimate direction of this movement is influenced by a multitude of factors, including prevailing fundamental news, shifting investor sentiment, and critical technical price levels. Volatility compression can be a valuable component of a more comprehensive predictive model but is rarely sufficient as a standalone tool for accurate directional forecasting.

Different perspectives exist regarding the reliability of volatility compression as an early signal for a sharp move in the S&P 500. Many traders and analysts incorporate the observation of volatility compression into their trading strategies as a signal to be prepared for potential trading opportunities that may arise from a subsequent breakout. However, it is generally cautioned that volatility compression should not be treated as a definitive and isolated predictor of market direction. Instead, it is most effective when used in conjunction with other confirming technical and fundamental analysis techniques to build a more robust trading thesis. Therefore, volatility compression is perhaps best considered as a preparatory signal. It indicates an increased probability of a significant price movement occurring in the near future, thereby prompting traders to actively look for additional confirming signals that can help establish a directional bias for their trading decisions. Recognizing volatility compression allows traders to anticipate a potential increase in market activity. This anticipation enables them to formulate their trading plans, identify key price levels that will be crucial for confirming breakouts, and proactively manage their risk exposure. However, the actual initiation of a trade should ideally be triggered by a clear directional signal that confirms the breakout from the volatility compression phase.

Trading Strategies Based on Volatility Compression

Traders often employ various strategies to capitalize on the potential for significant price movements that typically follow periods of volatility compression in the S&P 500. Breakout trading strategies are common, where traders actively seek to identify the moment when the price of the S&P 500 decisively breaks out of the defined range established during the volatility compression phase. They then initiate long positions if the breakout is to the upside and short positions if the breakout is to the downside. A critical element of these strategies is the observation of a significant increase in trading volume accompanying the price breakout, which is often seen as a confirmation of the move’s strength and potential for continuation.

Options trading strategies also play a significant role in profiting from anticipated volatility expansion. For instance, buying straddles or strangles allows traders to benefit from a large price movement in either direction, as these strategies involve purchasing both call and put options with the same expiration date but different strike prices (strangles) or the same strike price (straddles). Some specialized options strategies are specifically designed to profit from non-directional increases in volatility, such as Don Fishback’s Odds Compression methodology, which seeks opportunities when a stock’s price has converged into a very narrow range, anticipating a breakout in either direction.

The Volatility Contraction Pattern (VCP) is a specific chart pattern that many traders watch for as a signal of potential upward breakouts following a period of volatility compression. This pattern is characterized by a series of successive price pullbacks, each smaller than the last, accompanied by decreasing trading volume. This price action is interpreted as a sign that selling pressure is diminishing while buying demand is potentially building, often leading to a strong upward price movement. Key characteristics of a VCP include evidence of strong underlying demand prior to the compression, recent overbought conditions that introduce supply pressure, and ultimately, diminishing supply indicated by decreasing volatility and a noticeable drop in trading volume, sometimes referred to as “volume dry-up”.

Trading strategies based on the TTM Squeeze indicator involve identifying periods of low volatility, indicated by the “squeeze” condition, and then looking for the “firing” of the squeeze. This firing is often accompanied by a directional signal from the indicator’s momentum histogram, which traders use to determine whether to initiate long or short positions. To increase the likelihood of success, traders often align these TTM Squeeze signals with the prevailing trend observed on higher timeframe charts.

The fundamental principle underlying all these strategies is the understanding that extended periods of low volatility are inherently unstable and will eventually give way to periods of increased volatility and significant price movement as the market’s equilibrium is disrupted. The practical application of these strategies typically involves identifying a phase of volatility compression using the aforementioned tools, establishing specific entry points based on confirmed breakouts or options triggers, and diligently managing risk through the use of stop-loss orders to limit potential losses. Backtesting analysis, where traders evaluate the historical performance of these strategies on past market data, can provide valuable insights into their potential profitability and risk characteristics across different market conditions. While backtesting results are not guarantees of future performance, they can help traders assess the viability and potential of volatility compression-based trading strategies.

Factors Influencing Volatility Compression and Subsequent Moves

Several key macroeconomic factors can contribute to periods of volatility compression in the S&P 500. A sustained low interest rate environment, for instance, can reduce the cost of borrowing and potentially dampen market volatility. Similarly, a period of overall stable macroeconomic performance, characterized by consistent economic growth and low inflation, can also lead to lower levels of market volatility. Conversely, macroeconomic uncertainties, such as those related to the future path of interest rates, expectations regarding inflation, and the overall outlook for economic growth, can trigger an increase in market volatility and potentially lead to sharp price movements in the S&P 500.

Market sentiment plays a significant role in influencing both volatility compression and the subsequent sharp moves. Periods of high investor confidence and a sense of complacency might coincide with low market volatility, as investors are less inclined to react strongly to minor market fluctuations. Conversely, heightened levels of fear and uncertainty among investors typically lead to increased market volatility and larger price swings as participants become more reactive to news and potential risks.

Significant news events and geopolitical developments can also have a profound impact on market volatility. Breaking news, unexpected policy announcements (such as changes in tariffs or trade agreements), or escalating geopolitical tensions can quickly disrupt periods of low volatility and trigger substantial price movements in the S&P 500. These events introduce uncertainty and can cause investors to reassess their positions, leading to increased trading activity and volatility.

Other market-specific factors can also affect volatility compression in the S&P 500. The increasing popularity and trading volume of short-term options, particularly zero-days-to-expiry (0DTE) options, and the growing issuance of yield-enhancing structured products are factors that some observers believe can contribute to the compression of overall market volatility. Additionally, a lower correlation of equity returns among the individual stocks that constitute the S&P 500 can result in subdued overall index volatility, even if some individual stocks are experiencing significant price fluctuations. The complex interplay of these macroeconomic conditions, shifts in market psychology, impactful news events, and evolving market structures creates the dynamic environment that drives both periods of volatility compression and the subsequent sharp price movements observed in the S&P 500.

Limitations and Risks of Using Volatility Compression as a Signal

Relying solely on volatility compression as a trading indicator carries the inherent risk of encountering false signals. Periods of low volatility can sometimes persist for extended durations without a significant breakout ever materializing. Conversely, breakouts can occur but subsequently fail to maintain momentum, leading to whipsaw trading conditions where traders are stopped out of positions prematurely.

It is therefore critically important to utilize volatility compression in conjunction with other complementary technical analysis tools and a thorough understanding of the fundamental market context to enhance the probability of successful trades. Confirmation of a potential breakout should be sought through various indicators, such as a significant increase in trading volume accompanying the price movement, the price decisively breaking through established support or resistance levels, or corroborating signals from momentum indicators that suggest the move has strength and conviction.

There are specific market conditions under which volatility compression might prove to be a less reliable signal for predicting sharp moves in the S&P 500. During periods characterized by extreme market manipulation, unforeseen “black swan” events that defy typical market logic, or in highly illiquid market environments where normal volatility patterns are disrupted, the predictive power of volatility compression can be significantly diminished. Furthermore, it is essential to remember the fundamental limitation that volatility compression, when analyzed in isolation, does not provide a reliable indication of the direction of the anticipated sharp price movement, whether it will be upwards or downwards. An over-reliance on volatility compression as a singular trading signal, without considering the broader market context and diligently employing appropriate risk management strategies, can ultimately lead to suboptimal trading decisions and potential financial losses.

Conclusion

In summary, the analysis indicates that periods of volatility compression in the S&P 500 are frequently followed by an expansion of volatility and an increased probability of sharp price movements. While the observation of volatility compression can indeed serve as a valuable early signal, alerting traders to the potential for a significant market move, it is crucial to recognize its limitations. Notably, volatility compression does not reliably predict the direction of the subsequent price change. Therefore, it is recommended that traders and investors integrate the analysis of volatility compression into their overall market assessment framework, utilizing it in conjunction with a comprehensive suite of other technical and fundamental analysis techniques. Furthermore, the consistent application of sound risk management principles is paramount when trading based on volatility compression or any other market signal.

Works cited

www.interactivebrokers.com, accessed May 4, 2025

https://www.interactivebrokers.com/campus/trading-lessons/volatility/#:~:text=When%20the%20ratio%20of%20short,to%20be%20in%20volatility%20compression. Volatility | Trading Lesson | Traders’ Academy | IBKR Campus, accessed May 4, 2025

https://www.interactivebrokers.com/campus/trading-lessons/volatility/ Volatility: Meaning in Finance and How It Works With Stocks, accessed May 4, 2025

https://www.investopedia.com/terms/v/volatility.asp Trading Compression: Wedges, Triangles, Pennants & Flags – Stopsaving.com, accessed May 4, 2025

https://www.stopsaving.com/technical-analysis-course/compression-patterns/ Why is Volatility Important in Trading? – Bookmap, accessed May 4, 2025

https://bookmap.com/blog/why-is-volatility-important-in-trading Top 8 Volatility Indicators That Every Trader Should Know – IG, accessed May 4, 2025

https://www.ig.com/en-ch/trading-strategies/are-these-the-8-best-volatility-indicators-traders-should-know–230427 Bollinger Band Squeeze – ChartSchool – StockCharts.com, accessed May 4, 2025

https://chartschool.stockcharts.com/table-of-contents/trading-strategies-and-models/trading-strategies/bollinger-band-squeeze TTM Squeeze | ChartSchool | StockCharts.com, accessed May 4, 2025

https://chartschool.stockcharts.com/table-of-contents/technical-indicators-and-overlays/technical-indicators/ttm-squeeze Introduction to TTM Squeeze | TrendSpider Learning Center, accessed May 4, 2025

https://trendspider.com/learning-center/introduction-to-ttm-squeeze/ Volatility Index®Methodology: Cboe 1-Day Volatility Index® – Cboe Global Markets, accessed May 4, 2025

https://cdn.cboe.com/api/global/us_indices/governance/Volatility_Index_Methodology_Cboe_1-Day_Volatility_Index.pdf Monitoring volatility in financial markets, accessed May 4, 2025

https://www.esma.europa.eu/sites/default/files/trv_2018_2-monitoring_volatility_in_financial_markets.pdf What could explain the recent drop in VIX? – Bank for International Settlements, accessed May 4, 2025

https://www.bis.org/publ/qtrpdf/r_qt2403x.htm Inside Volatility Trading: Breaking Down the VIX Index and its Correlation to the S&P 500 Index – Cboe Global Markets, accessed May 4, 2025

https://www.cboe.com/insights/posts/inside-volatility-trading-breaking-down-the-vix-index-and-its-correlation-to-the-s-p-500-index/ Volatility Trading Strategies: How to Trade Volatility – Admiral Markets, accessed May 4, 2025

https://admiralmarkets.com/education/articles/general-trading/volatility-trading-strategies Volatilitycontraction — Indicateurs et Stratégies – TradingView, accessed May 4, 2025

https://fr.tradingview.com/scripts/volatilitycontraction/ Taking the long view on tariff-driven volatility – Janus Henderson Investors, accessed May 4, 2025

https://www.janushenderson.com/en-no/institutional/article/taking-the-long-view-on-tariff-driven-volatility/ S&P 500 ® Index Historical Trends – Guggenheim Investments, accessed May 4, 2025

https://www.guggenheiminvestments.com/advisor-resources/interactive-tools/sp-500-historical-trends The Market Moves in Regimes: A Historical Look at S&P 500 Price Cycles | WisdomTree, accessed May 4, 2025

https://www.wisdomtree.com/investments/blog/2025/04/07/the-market-moves-in-regimes-a-historical-look-at-sp-500-price-cycles Here’s what recent history says happens after the S&P 500 breaches this critical level, accessed May 4, 2025

https://www.morningstar.com/news/marketwatch/20250307232/heres-what-recent-history-says-happens-after-the-sp-500-breaches-this-critical-level Dow nosedives 1600 points, S&P 500 and Nasdaq drop the most since 2020 after Trump’s tariff onslaught – NBC10 Philadelphia, accessed May 4, 2025

https://www.nbcphiladelphia.com/news/business/money-report/u-s-stocks-drop-after-hours-as-trump-imposes-sweeping-tariffs-sp-500-etf-falls-2-live-updates/4150072/?os=avdF&ref=app Timeline of U.S. Stock Market Crashes – Investopedia, accessed May 4, 2025

https://www.investopedia.com/timeline-of-stock-market-crashes-5217820 Top 10 Stock Market Drops & Recoveries – Hartford Funds, accessed May 4, 2025

https://www.hartfordfunds.com/practice-management/client-conversations/managing-volatility/top-10-stock-market-drops-recoveries.html Morning Lineup | Bespoke Investment Group, accessed May 4, 2025

https://www.bespokepremium.com/category/morning-lineup/ Taking the long view on tariff-driven volatility – Janus Henderson Investors – US Advisor, accessed May 4, 2025

https://www.janushenderson.com/en-us/advisor/article/taking-the-long-view-on-tariff-driven-volatility/ Taking the long view on tariff-driven volatility – Janus Henderson Investors – South Africa Professional Advisor, accessed May 4, 2025

https://www.janushenderson.com/en-za/advisor/article/taking-the-long-view-on-tariff-driven-volatility/ The S&P 500 pushed through its trading range – but can the bulls hold the line?, accessed May 4, 2025

https://www.morningstar.com/news/marketwatch/20250215223/the-sp-500-pushed-through-its-trading-range-but-can-the-bulls-hold-the-line US GDP Contracts for the First Time in Three Years – Action Forex, accessed May 4, 2025

https://www.actionforex.com/contributors/fundamental-analysis/595437-us-gdp-contracts-for-the-first-time-in-three-years/ Carry off, carry on – Bank for International Settlements, accessed May 4, 2025

https://www.bis.org/publ/qtrpdf/r_qt2409a.htm Calm Before the Storm: Stock’s Volatility Contracts, Ready to ‘Skyrocket’?, accessed May 4, 2025

https://in.investing.com/analysis/calm-before-the-storm-stocks-volatility-contracts-ready-to-skyrocket-200533025 A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices | Request PDF – ResearchGate, accessed May 4, 2025

https://www.researchgate.net/publication/372931369_A_comparison_of_machine_learning_methods_for_predicting_the_direction_of_the_US_stock_market_on_the_basis_of_volatility_indices (PDF) Predicting the S&P 500 stock market with machine learning models – ResearchGate, accessed May 4, 2025

https://www.researchgate.net/publication/379076543_Predicting_the_SP_500_stock_market_with_machine_learning_models A Practitioner’s Guide to Reading VIX – S&P Global, accessed May 4, 2025

https://www.spglobal.com/spdji/en/education-a-practitioners-guide-to-reading-vix.pdf Implied Volatility Compresses at Stock Market Highs | SpotGamma™, accessed May 4, 2025

https://spotgamma.com/implied-volatility-compresses-at-stock-market-highs/ How to Trade the TTM Squeeze Indicator | TrendSpider Blog, accessed May 4, 2025

https://trendspider.com/blog/how-to-trade-ttm-squeeze-indicator/ Volatility Contraction Pattern (VCP): How to Day Trade It – Tradingsim, accessed May 4, 2025

https://www.tradingsim.com/blog/volatility-contraction-pattern Mastering The Volatility Contraction Pattern – TraderLion, accessed May 4, 2025

https://traderlion.com/technical-analysis/volatility-contraction-pattern/ Don Fishback’s Odds Compression- MetaStock, accessed May 4, 2025

https://www.metastock.com/products/thirdparty/?3pc-add-osc&=1&=1 Volatility Strategies – Ardea Investment Management, accessed May 4, 2025

https://www.ardea.com.au/wp-content/uploads/How-To-Profit-From-Interest-Rate-Volatility.pdf Starting Your Backtest · Volatility User Guide – GetVolatility, accessed May 4, 2025

https://www.getvolatility.com/user-guide/starting-your-backtest Straddling outside and into earnings: Part II – BSIC | Bocconi Students Investment Club, accessed May 4, 2025

https://bsic.it/straddling-outside-and-into-earnings-part-ii-2/ TTM Squeeze Indicator: What Is It & How To Use It | LiteFinance, accessed May 4, 2025

https://www.litefinance.org/blog/for-beginners/best-technical-indicators/ttm-squeeze/ TTM Squeeze Indicator: Technical Signals for Traders – Charles Schwab, accessed May 4, 2025

https://www.schwab.com/learn/story/ttm-squeeze-indicator-technical-signals-traders Technicals and The “TTM Squeeze” – TradeMachine, accessed May 4, 2025

https://learn.trademachine.com/docs/technicals-and-the-ttm-squeeze Volatility Compression Explained! #shorts – YouTube, accessed May 4, 2025

https://m.youtube.com/shorts/XilbGWd2ERs Backtested a Volatility Strategy From an Academic Paper, Beat Market by 4x – Reddit, accessed May 4, 2025

https://www.reddit.com/r/investing/comments/uobsfs/backtested_a_volatility_strategy_from_an_academic/ Volatility – Options Backtesting, Screening, and Charting, accessed May 4, 2025

https://www.getvolatility.com/ Building and Backtesting a Volatility-based Trading Strategy with ChatGPT – R-bloggers, accessed May 4, 2025

https://www.r-bloggers.com/2023/04/building-and-backtesting-a-volatility-based-trading-strategy-with-chatgpt/ Backtesting a Short S&P 500 Strategy – Tradewell, accessed May 4, 2025

https://www.tradewell.app/post/backtesting-a-short-s-p-500-strategy Does THIS Strategy REALLY outperform the S&P500? Backtest in Python – YouTube, accessed May 4, 2025

https://www.youtube.com/watch?v=ZXCSPC3Kw18 Volatility — Indicators and Strategies – TradingView, accessed May 4, 2025

https://www.tradingview.com/scripts/volatility/?script_access=all&script_type=strategies Backtesting a Forecasting Strategy for the S&P500 in Python with pandas | QuantStart, accessed May 4, 2025

https://www.quantstart.com/articles/Backtesting-a-Forecasting-Strategy-for-the-SP500-in-python-with-pandas/ How To Predict S&P 500 Direction (Day Trading)… $TSLA, $NVDA, $FSLR – YouTube, accessed May 4, 2025

https://www.youtube.com/watch?v=w1ZhS9r2XNE The Biggest Backtesting Mistakes You Can Make – Warrior Trading, accessed May 4, 2025

https://www.warriortrading.com/backtesting-mistakes/ Volatility Trading Strategies Course | Learn to Trade Volatility – Quantra by QuantInsti, accessed May 4, 2025

https://quantra.quantinsti.com/course/volatility-trading-strategies TRADERS’ TIPS – JANUARY 2019, accessed May 4, 2025

http://traders.com/Documentation/FEEDbk_docs/2019/01/TradersTips.html 5 factors causing market volatility now – Fidelity Investments, accessed May 4, 2025

https://www.fidelity.com/learning-center/trading-investing/volatility-2025 Seven Considerations To Make When Trading Volatility – tastytrade, accessed May 4, 2025

https://www.tastytrade.com/en/research/seven-considerations-make-when-trading-volatility