Zeiierman

█ The Truth Behind Volume Bars — What Do Green and Red Actually Mean?Most traders learn early on that green volume bars mean bullish activity, and red bars mean bearish pressure. But is it really that simple? What does volume truly reflect, and are we making assumptions that can mislead us?█ What Volume Actually IsVolume represents the number of shares/contracts traded during a specific time interval. Every transaction includes both a buyer and a seller. So, volume itself doesn’t distinguish whether a trade was bullish or bearish. Instead, platforms color volume bars based on price movement:Green: If price closed higher than it opened.Red: If price closed lower than it opened.Some platforms, like TradingView, allow you to color volume based on whether the price closed higher or lower than the previous candle’s close.So YOU, as a trader, have the chance to decide whether to assign volume bars either bullish or bearish! It’s a setting parameter anyone can change. Traders around the globe might look at the same volume bar, but some interpret it as bearish, while others interpret it as bullish. What is the most correct way?█ The Assumption Behind the ColorThis coloring assumes that:A rising price means buyers were more aggressive (lifting the ask).A falling price means sellers were more aggressive (hitting the bid).This is a proxy — an approximation. It simplifies market pressure into a binary outcome: if price goes up, it's bullish volume; if it goes down, it's bearish. But the market isn't always so binary.However, the assumption is only an approximation of buying vs. selling. In reality, every single trade involves both a buyer and a seller, so volume itself isn’t inherently “buy” or “sell” – what matters is who initiated the trades. As one trading expert explains, talking about “buying volume” vs “selling volume” can be misleading: for every buyer there is a seller, so volume cannot be literally split into purchases and sales​. Instead, what traders really mean by “bullish volume” is that buyers were more aggressive (lifting offers) and drove the price up, whereas “bearish volume” means sellers were more aggressive (hitting bids) and drove the price down​. The colored volume bar is essentially a proxy for which side won the battle during that bar.█ Why This Can Mislead YouPrice might close higher, not because there were more buyers than sellers (there never are — every trade has both), but because buyers were more urgent. And sometimes price moves due to other forces, like:Short covering.Stop-loss runs.Liquidity vacuums.This means a green bar might not reflect strong demand, just urgency from the other side closing their positions.⚪ Example: Take the well-known GameStop short squeeze as an example. If you looked only at the volume bars during that rally, you’d see a wall of strong green candles and high volume, which might suggest aggressive bullish buying.However, that interpretation would be misleading.Under the surface, the surge wasn't driven by fresh bullish conviction — it was massive short covering. Traders who were short were forced to buy back shares to cover their positions, which drove prices even higher. The volume was categorized as bullish, but the true intent behind the move had nothing to do with new buying pressure.This demonstrates why relying solely on volume color or candle direction can lead to false conclusions about market sentiment.Does this simple up/down volume labeling truly reflect buying vs. selling pressure? To a degree, yes – it captures the net price outcome, which often corresponds to who was more aggressive. For example, if many buyers are willing to pay higher prices (demand), a bar will likely close up and be colored green, reflecting that buying interest. Conversely, if eager sellers are dumping shares and undercutting each other, price will drop, yielding a red bar that flags selling pressure. Traders often use rising volume on up-moves as confirmation of a bullish trend’s strength, and high volume on down-moves as a warning of distribution, which indeed aligns with traditional analysis​That said, the method has important limitations and nuances, documented both anecdotally and in research:⚪ Volume is not one-dimensional: Since every trade has both a buyer and seller, one cannot literally count “buy volume” vs “sell volume” without more information. The green/red coloring is a blunt classification based on price direction, not an actual count of buys or sells. It assumes the price change direction is an adequate proxy for the imbalance of buying vs. selling. This is often true in a broad sense, but it’s not a precise measure of order flow.⚪ Intrabar Dynamics Are Lost: A single bar’s color only tells the end result of that interval, not the story of what happened during the bar. For instance, a 4-hour candle might be red (down) overall, but it could have contained three hours of rally (buying) followed by a steep selloff in the final hour that erased the gains. The volume bar will be colored red due to the net price drop, even though significant buying occurred earlier in the bar. In other words, a large red bar can mask that there were pockets of bullish activity within – the selling just happened to win out by the close of that period. Without looking at smaller time frames or detailed data, one can’t tell from a single color how the buying/selling tug-of-war progressed within the bar.⚪ Gap Effects and Criteria Choices: The choice of using open vs. close or previous close can alter the interpretation of volume. As discussed, a day with a big gap can be labeled differently under the two methods. Neither is “right” or “wrong” – they just highlight different perspectives (intraday momentum vs. day-over-day change). Traders should be aware that colored volume bars are an approximation. A green volume bar under one method might turn red under the other method for the same bar. This doesn’t mean volume changed – it means the classification scheme changed. For example, a stock that closes below its open but still higher than yesterday will show a red volume bar by the intraday method but would be considered an “up-volume day” in OBV terms (previous close method).⚪ No Indication of Magnitude or Commitment: A single color also doesn’t convey how much buying or selling pressure there was, only which side won. Two green volume bars might both be green, but one could represent a modest uptick with tepid buying, whereas another could represent an aggressive buying spree – the color alone doesn’t distinguish this (other than one bar likely being taller if volume was higher). Traders often need to consider volume relative to average (e.g. using volume moving averages or looking for volume spikes) to judge the significance of a move, not just the color.█ SummaryThe coloring of volume bars is a visual shortcut, not an exact science. It’s a guess based on price direction — useful, but imperfect. Understanding this helps traders avoid reading too much into what a green or red volume bar actually means.-----------------DisclaimerThe content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.

█ Mastering Volatile Markets Part 3: Why Patience is Your Biggest EdgeIf you've read Part 1 about position sizing and Part 2 on liquidity, then you already know how to adapt to the mechanics of volatile markets. The next great tool in your arsenal will be patience.Your biggest opponent in wild markets is your own mind.In volatile markets, your emotions can easily get the best of you. Fear of missing out (FOMO) is one of the most dangerous emotions that drives poor decisions.█ FOMO (Fear of Missing Out) Hits Hardest in Volatile MarketsWild price swings, like 300-500 point moves in the Nasdaq or Bitcoin jumping $1000 in seconds, can make it feel like easy money is everywhere.You can quickly get the overwhelming temptation to chase moves, especially when it seems like you're missing every opportunity.This is where most traders lose.Let me state some harsh truths that I had to learn the hard way through many losses:Volatility doesn't equal opportunity.Fast moves don't mean easy trades.Most wild price moves are designed to trap liquidity and punish impatience.The true reality is that the market wants you to overreact in these conditions.It wants you to buy after a big move.It wants you to short after a flush.It thrives on you being emotional, chasing, and reacting.Because reactive traders = liquidity providers for smart money. Every single trader has made this mistake — not just once, but over and over again. Jumping into the market after a big move, hoping it will continue… but what usually happens? The market snaps back and stops you out.Can you relate? Share your story or experience with this in the comments below! █ What Experienced Traders Do Instead⚪ They Know the First Move is Often the TrapBreakout? Expect a fakeout.Breakdown? Expect a snapback.New high? Watch for stop hunts.New low? Watch for a flush.Effectively speaking, pro traders don't chase the market. We wait for stop hunts to complete, liquidity grabs to finish, price to return into their zone, and for confirmations before entering the market.⚪ They Train Patience Like a SkillProfessional traders aren't more patient because they're "special." We are patient because we’ve learned the hard way that chasing leads to pain.⚪ They Know When Not to TradeIt is bad to trade when there’s no clear structure, no clean confirmation, if the spread is too wide or when the liquidity is too thin.Instead, pro traders let the market come to them, not the other way around.⚪ They Turn FOMO into ConfidenceInstead of saying, "I'm missing the move…", I recommend you think:"If it ran without me — it wasn't my trade.""If it comes back into my setup — now it's my trade."█ So, what have we learned today?Volatility triggers FOMO. FOMO triggers bad decisions. Bad decisions trigger losses.To win long-term, you must stay calm, selective and professional. Let other traders be emotional liquidity. That's how you survive volatile markets.█ What We Covered Already:Part 1: Reduce Position SizePart 2: Liquidity Makes or Breaks Your TradesPart 3: Why Patience is Your Biggest Edge█ What's Coming Next in the Series:Part 4: Trend Is Your Best Friend-----------------DisclaimerThe content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.

█ Mastering Volatile Markets Part 2: Why Liquidity Makes or Breaks Your TradesIf you've read the first part of this four-part series, you know that reducing position size is a key strategy for surviving volatile markets. The second crucial factor that determines success or failure in wild markets is understanding liquidity.In volatile markets, liquidity is often the real reason behind those massive price spikes — whether 300-500 point moves in the NAS100, violent whipsaws in crypto or stop hunts in forex. █ Liquidity: The Silent Killer in Wild MarketsIn normal market conditions, liquidity is everywhere. You can enter and exit trades with minimal slippage, and everything feels smooth. But in volatile conditions, liquidity can disappear quickly.Here's why it happens:Market makers pull back to avoid getting caught in wild moves.Spreads widen, making execution harder.Order books thin out, meaning there aren't enough buy or sell orders to absorb aggressive price movements.Even small orders can cause significant price changes when liquidity is low.This is what causes those huge candles you often see in volatile markets. It's not just about more buyers or sellers; it's about less liquidity available to absorb those trades.There’s also a common misunderstanding at play here: High Volume = High LiquidityMany newer traders see a big volume candle and think, "Oh, high volume means it's safe to trade." But that’s an inaccurate conclusion.⚪ Volume refers to the number of transactions happening. ⚪ Liquidity refers to how much depth the market has to handle those transactions without causing price instability.In volatile markets, high volume doesn't mean there's enough liquidity.And low liquidity causes wild wicks, huge spreads, higher slippage and unstable price action.█ How to Navigate Low Liquidity in Volatile MarketsSo, how can you trade effectively in these conditions?1) Expect Crazy Moves — Levels Will Get ViolatedIn high-volatility, low-liquidity markets:Support and resistance levels won't hold as they usually do.Price will blow through key levels like they were nothing.Fakeouts become extremely common.2) Don't Rely Solely on Support & ResistanceAs a newer trader, it's vital not to blindly rely on S/R levels in these markets. Here's why:Don't expect clean bounces or perfect reactions.Fakeouts, wicks, and stop hunts are normal.Tight stops right behind these levels? You'll get stopped out a lot.Experienced traders know this, which is why we adapt the strategies to handle the market's unpredictability.3) Split Your Orders Into Smaller ChunksOne of the most effective techniques in volatile markets is order splitting.Break it into smaller chunks instead of entering your full position at one price. This would help you survive fakeouts, scale in better across larger price moves and avoid becoming liquidity for bigger players.Example: Let's say you want to go long at support (15,000 on the NAS100), instead of entering all at 15,000. Instead Enter:25% at 15,00025% at 14,95025% at 14,90025% at 14,850This way, if the market fakes out below support due to low liquidity, you get filled at better prices without panic.4) Control Your Emotions — Understand the EnvironmentThis is HUGE in volatile markets.Many retail traders panic when prices move against them quickly. But if you understand the nature of low liquidity, you can remain calm:It's normal for the price to move wildly.Levels will get swept.Fake moves are common before the market plays out the right way.█ SummaryLet’s take stock of what we learned today about liquidity in highly volatile markets:High volatility often equals low liquidity.High volume does not equal high liquidity.Expect fakeouts, wild price behavior, and wide spreads.Don't rely blindly on support/resistance levels.Split your orders into smaller chunks to manage risk.Trade smaller position sizes and stay calm.Remember, you must adapt not only your size but also your execution. Understand liquidity, or it will punish you.█ What We Covered Already:Part 1: Reduce Position SizePart 2: Liquidity Makes or Breaks Trades █ What's Coming Next in the Series:Part 3: Patience Over FOMOPart 4: Trend Is Your Best Friend-----------------DisclaimerThe content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.

█ Order Imbalance and Change Point DetectionTrading might sometimes seem like magic, but at its core, the market operates on simple principles, supply and demand, and the flow of information. Recent academic work shows that retail traders can gain an edge even without expensive data feeds by understanding some fundamental ideas, like order imbalance and change point detection.In this article, we break down key concepts such as order imbalance, sudden volume shifts, change point detection, and the CUSUM algorithm. We also explain how retail traders can apply these ideas to improve their strategies.█ What Is the Order Book and Order Imbalance?⚪ The Order BookEvery market has an order book, simply a list of all buy orders (bids) and sell orders (asks) for an asset. ⚪ Order Imbalance – A Key IndicatorOrder imbalance measures the difference between the total buying and selling orders for the order book.Definition: Order imbalance is the difference in volume between buy orders and sell orders.Why It Matters: A strong imbalance means one side (buyers or sellers) is dominating. For example, if there are significantly more buy orders than sell orders, the market may be gearing up for a price increase.⚪How It’s Detected in Research:Researchers calculate a volume-weighted average price (VWAP) across multiple price levels in the order book (typically the top 20 levels) and compare it to the mid-market price.A positive imbalance indicates aggressive buying, while a negative imbalance suggests selling pressure.█ Sudden Volume Shifts and Change Point Detection⚪Sudden Volume ShiftsWhat It Means: Sometimes, there is an abrupt and noticeable change in the number of orders placed. This sudden shift in volume can signal a big move on the horizon.Example: In a trading context, this might be seen when volume bars spike unexpectedly on a price chart, often accompanying rapid price moves or breakouts.⚪Why They Are Crucial:Sudden volume increases often coincide with significant order flow events. For instance, if a large number of buy orders hit the market at once, this could indicate a rapid shift in trader sentiment and serve as a precursor to a sustained price move.█ Change Point Detection – Spotting the ShiftDefinition: Change point detection is a statistical technique used to identify the exact moment when the properties of a data series change significantly.Purpose: In trading, it helps distinguish meaningful shifts in market behavior from random noise.How It’s Used: Researchers apply this to order imbalance data to flag moments when the market’s buying or selling pressure changes abruptly. These flagged moments (or “change points”) can then be used to forecast short-term price movements.█ Meet CUSUM: The Cumulative Sum AlgorithmCUSUM stands for Cumulative Sum. It’s a simple yet powerful algorithm that detects changes in a data series over time.⚪ How CUSUM Works:Tracking Deviations: The algorithm continuously adds up minor differences (or deviations) from an expected value (like a running average).Signal for Change: When the cumulative sum exceeds a predetermined threshold, it signals that a significant change has occurred.In Trading: CUSUM can be applied to measure the order imbalance. When the cumulative deviation is high enough, it indicates a strong change in market pressure, an early warning signal for a potential price move. For example, a rising cumulative sum based on increasing buy-side pressure might indicate that the price will likely move upward.█ How Can Retail Traders Benefit Without Full LOB Data?Full access to the order book (all price levels and orders) can be expensive and is usually reserved for institutional traders. However, retail traders can still gain valuable insights by:⚪ Using Proxies for Order Imbalance:Many trading platforms offer basic volume indicators.Look for volume spikes or unusual shifts in trading volume as a sign that order imbalance might occur.⚪ Leveraging Simplified Change Detection:Even if you don’t have complex LOB data, you can set up simple alerts on your trading platform.For instance, you might create a custom indicator that watches for rapid increases in volume or price moves, similar to a basic version of the CUSUM algorithm.⚪ Focusing on Key Price Levels:Even with limited data, monitor support and resistance levels. A sudden break (accompanied by high volume) can serve as a proxy for a change in market dynamics.⚪ Adopting a Data-Driven Mindset:Integrate these concepts into your routine analysis. When you see a significant volume shift or a sudden spike in activity, consider it a potential “change point” and adjust your strategy accordingly.█ In SummaryOrder Imbalance measures the difference between buying and selling volumes in the order book, offering insights into market direction.Sudden Volume Shifts are significant changes in trading volume that can signal a shift in market sentiment.Change Point Detection helps identify the precise moments when these shifts occur, filtering out noise and highlighting actionable signals.CUSUM is a powerful tool that continuously tracks cumulative deviations in market data, alerting traders when the market undergoes a significant change.For retail traders, these methods underscore the importance of watching price and understanding the underlying order flow. While you might not have access to full-depth order book data, using volume indicators and setting up alert systems can help you capture the essence of these insights, providing a valuable edge in your trading decisions.-----------------DisclaimerThe content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.

In today’s digital age, social media has become a cornerstone of information for nearly every aspect of our lives. From lifestyle tips to financial advice, influencers wield significant power over public sentiment. Among them are financial influencers, or "finfluencers," who share investment tips, stock picks, and market analyses. But how reliable is their advice? Can retail traders use their recommendations to improve their trading strategies?A recent research paper titled Finfluencers by the Swiss Finance Institute dives deep into these questions. The study examines the accuracy, influence, and implications of finfluencers’ advice. Its findings are both eye-opening and actionable for retail traders looking to navigate the crowded world of social media-driven investing.█ The Truth About FinfluencersThe study analyzed tweet-level data from over 29,000 finfluencers on StockTwits, classifying them into three distinct groups:Skilled Finfluencers: These individuals represent 28% of the sample and are the true gems among finfluencers. Their advice generates an average of 2.6% monthly abnormal returns, indicating that they provide genuinely valuable insights. Skilled finfluencers often tweet less frequently and tend to post data-driven and sometimes negative assessments, which align with their ability to outperform.Unskilled Finfluencers: Accounting for 16% of the sample, unskilled finfluencers have little to no impact on returns. Their advice is neither harmful nor particularly beneficial, making them neutral players in the social media finance space. Despite their lack of effectiveness, these influencers still attract some attention due to their activity levels and relatability.Antiskilled Finfluencers: Shockingly, 56% of finfluencers fall into this category, making them the majority. Antiskilled influencers consistently provide poor advice, generating an average of -2.3% monthly abnormal returns. Their recommendations often reflect overly optimistic or flawed beliefs, leading followers astray. Despite their negative track record, antiskilled finfluencers tend to have the largest followings and the most influence, driven by behavioral biases such as homophily and their frequent activity on social media.Surprisingly, the study found that unskilled and antiskilled finfluencers have more followers and exert greater influence than their skilled counterparts. This phenomenon is linked to behavioral biases such as homophily—a tendency for people to align with others who share similar opinions, even if those opinions lack merit.█ Why Antiskilled Influencers ThriveOne might wonder how antiskilled finfluencers manage to amass large followings despite their poor track records. The research highlights several reasons:Popularity Over Precision: Social media rewards engagement and relatability, often sidelining the importance of accuracy.Behavioral Biases: Retail traders are drawn to familiar or optimistic messages, even when they’re unfounded.Tweet Frequency: Antiskilled influencers tend to post more frequently, increasing their visibility and perceived authority.Interestingly, the study also found that skilled finfluencers tend to post less frequently and are more likely to share negative but accurate assessments. This trait aligns with their ability to generate better returns but limits their mass appeal.█ How Retail Traders Can BenefitThe research offers valuable lessons for retail traders looking to cut through the noise and make informed decisions:⚪ Think Critically About Popular AdviceJust because an influencer has a large following doesn’t mean their advice is sound. Popularity often correlates with engagement rather than expertise. Before acting on any recommendation, evaluate the influencer’s track record and consider the rationale behind their advice.⚪ Embrace Contrarian InvestingOne of the study’s most intriguing findings is the profitability of a contrarian approach. By systematically trading against the advice of antiskilled influencers, traders can achieve abnormal returns. This strategy, humorously dubbed “the wisdom of the antiskilled crowd,” underscores the potential of doing the opposite of what bad advice suggests.⚪ Look for Quality Over QuantitySkilled finfluencers often tweet less frequently but provide higher-quality insights. Traders should prioritize substance over volume, seeking out influencers who back their recommendations with data and sound reasoning.⚪ Understand Behavioral BiasesBeing aware of biases like homophily can help traders make more rational decisions. Instead of gravitating toward advice that feels familiar or comforting, focus on advice that is well-supported and objective.█ A Practical ExampleImagine you follow an antiskilled finfluencer who frequently posts bullish advice on various stocks. According to the research, these recommendations are likely to lead to losses. Instead of following their advice, you could develop a contrarian strategy by shorting or avoiding their suggested stocks. Backtesting this approach could reveal a consistent edge over time.Similarly, tracking skilled finfluencers who post less often but provide thoughtful analyses can complement this strategy, offering a balanced approach to decision-making.█ Final ThoughtsThe Finfluencers research sheds light on the complex dynamics of financial advice on social media. While social platforms have democratized access to information, they’ve also amplified the voices of unskilled and antiskilled influencers. For retail traders, this presents both challenges and opportunities.By approaching social media advice with a critical eye and leveraging the insights from this research, traders can navigate the pitfalls of herd mentality and capitalize on the inefficiencies created by antiskilled influencers. Ultimately, the key is to focus on evidence-based strategies and remember that the messenger’s popularity doesn’t always reflect the quality of their message.As the researchers aptly conclude: “The message is more important than the messenger.” In the ever-evolving world of retail trading, this is advice worth heeding.-----------------DisclaimerThis is an educational study for entertainment purposes only.The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs.My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!

█ Interpreting Long/Short Ratios in Futures Trading: Beyond Bullish and BearishFor beginner traders, the long/short ratio in futures markets can seem like a clear-cut indicator of market sentiment. Many assume that a high ratio of longs to shorts means the market is bullish, while more shorts than longs signals a bearish outlook. But in reality, this interpretation is oversimplified and can lead to misguided trading decisions.In this article, we'll break down the nuances of the long/short ratio in futures trading, explaining why positions on the “short side” don’t always indicate a bearish stance and how traders can better interpret these ratios for a well-rounded perspective.█ Understanding the Basics: Futures Trading Is Not Spot TradingIn the futures market, every trade requires a buyer (long position) and a seller (short position). For each person going long, there’s a counterpart going short. This zero-sum structure means that, by definition, there’s always a balance between longs and shorts. However, the reasons why traders take long or short positions vary widely—and not all of them are directional bets on price movement.█ Why Not All Shorts Are Bearish (And Not All Longs Are Bullish)Let’s dig into why a trader might take the short side without actually betting on a price drop:⚪Hedging: Some traders go short to hedge an existing position. For instance, if they already hold a large amount of Bitcoin in the spot market, they might take a short position in Bitcoin futures to protect against potential downside risk. This doesn’t mean they’re bearish on Bitcoin; they’re just managing risk.⚪Arbitrage: Some traders take short positions for arbitrage purposes. For example, they might go long in one market and short in another to profit from small price differences without having any directional view on Bitcoin’s future price. Their short position is purely for balancing and not a bet on falling prices.⚪Market Making: Market makers provide liquidity to the market by taking both long and short positions. Their goal isn’t to profit from price movements but to capture the spread between the bid and ask prices. They don’t have a directional view—they’re simply facilitating trades.⚪Closing Long Positions: When traders close long positions, they effectively create a new short transaction. For instance, if a trader decides to exit a long position by selling, they’re adding to the short side of the market. But this action doesn’t necessarily mean they expect prices to drop—it could just mean they’re taking profits or reallocating their portfolio.█ Interpreting CoinGlass Long/Short Ratio Charts: Volume vs. AccountsLet’s look at the long/short ratio charts on CoinGlass as an example. CoinGlass provides two main types of ratios:⚪ Volume-Based Ratio: This chart shows the volume of capital in long vs. short positions. For example, a high volume in longs might suggest that large players are buying into Bitcoin. However, it’s important to remember that some of these long positions could be from market makers, hedgers, or arbitrageurs, who may not expect Bitcoin to rise. The volume itself doesn’t tell us why they’re in these positions.⚪ Account-Based Ratio: This chart tracks the number of accounts on each side (long vs. short) on exchanges like Binance. A higher number of accounts on the short side doesn’t mean all those traders are bearish. Many could be taking short positions to balance other trades or hedge risks. They’re not necessarily expecting Bitcoin to decline; they’re just managing their positions.█ Example Analysis: Misinterpreting Long/Short RatiosImagine you’re looking at a CoinGlass chart that shows an increase in long volume around November 5th. A beginner might see this and think, “Everyone’s bullish on Bitcoin!” But as we discussed, some of this long volume could be non-directional. It could include positions taken by market makers providing liquidity or hedgers who are long on Bitcoin futures but have a corresponding short in another market.Similarly, if you see a spike in the number of short accounts, don’t automatically assume that everyone expects Bitcoin to fall. Some of those accounts might just be managing risk or taking advantage of arbitrage opportunities.█ Avoiding the Pitfall of Overinterpreting the Long/Short RatioThe biggest mistake traders make is interpreting the long/short ratio as a direct indicator of market sentiment. Remember, every trade has a counterparty. If there’s a high volume of longs, it simply means there’s an equal volume of shorts on the other side. The market’s overall sentiment isn’t always reflected in this ratio.Instead of relying solely on the long/short ratio, consider these other factors to form a clearer market view:Market Sentiment Indicators: Use sentiment tools, news, and social media sentiment to understand how traders are feeling beyond just positions.Volume Trends: Look at overall market volume to see if there’s conviction behind the moves.Context and Price Action: Interpret the ratio in the context of price action and recent events. If there’s a strong bullish trend, a higher long ratio might reflect confidence in the trend rather than simply volume.█ Conclusion: A Balanced Perspective for Smarter TradingUnderstanding the long/short ratio requires a more nuanced perspective. Just because the “longs” are up doesn’t mean everyone’s bullish—and just because the “shorts” are up doesn’t mean everyone’s bearish. The futures market is filled with diverse participants, each with unique motives, from hedging and arbitrage to liquidity provision.By looking at these ratios with a balanced view, traders can avoid common pitfalls and interpret the data more accurately. Trading is about context and strategy, not just numbers on a chart. So, next time you’re checking the long/short ratio, remember: there’s more to it than meets the eye.█ Final Takeaway: Focus on Context, Not Just RatiosThe long/short ratio can be a helpful tool, but it’s only one piece of the puzzle. Use it in combination with other market indicators, and always consider the motives behind trades. By doing so, you’ll make better-informed trading decisions and avoid falling into the trap of oversimplifying complex market data.-----------------DisclaimerThis is an educational study for entertainment purposes only.The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs.My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!

█ Understanding Price Clustering in the Bitcoin MarketPrice clustering is a phenomenon where certain price levels, particularly round numbers, tend to appear more frequently in financial markets. This study focuses on how price clustering occurs in the Bitcoin market, providing insights that can be valuable for traders. █ The Psychology Behind Price ClusteringOne of the primary reasons behind price clustering in the Bitcoin market is the psychological impact of round numbers. Market participants often perceive prices ending in 0 or 00 as significant, which leads to a concentration of buy and sell orders around these levels. This behavior is not unique to Bitcoin; it has been observed across various financial markets, from stocks to foreign exchange.For instance, when Bitcoin prices approach a round number like $30,000 or $50,000, traders might expect strong resistance or support at these levels. This expectation can lead to increased trading activity, causing prices to cluster around these key levels. The psychological importance of these numbers can also cause traders to place stop-loss or take-profit orders around them, further reinforcing the clustering effect.█ Key Findings from the Study⚪ Clustering Around Round Numbers: The study highlights that Bitcoin prices tend to cluster around round numbers, such as $10,000, $20,000, or $50,000. This is primarily driven by psychological barriers, where traders view these round numbers as significant price levels, leading to an increased concentration of trading activity.⚪ Impact of Time Frames: The extent of price clustering varies significantly with the time frame. In shorter time frames (like 1-minute or 15-minute intervals), price clustering is less pronounced due to the randomness of price movements. However, as the time frame lengthens (hourly or daily), the clustering effect becomes more apparent, suggesting that traders may be more likely to anchor their strategies around these round numbers over longer periods.⚪ Differences in Open, High, and Low Prices: The study also finds differences in clustering patterns between open, high, and low prices. High prices tend to cluster around the digits 8, 9, and 0, while low prices cluster around 1, 2, and 0. Open prices generally show less clustering, suggesting they are less influenced by immediate market psychology. This pattern suggests that traders should pay particular attention to high and low prices during trading sessions, as these are more likely to show clustering around key levels.High Price: This is the highest price that Bitcoin reaches during a specific time period (for example, during a day or an hour). The study found that high prices cluster more around certain numbers, especially numbers ending in 0 or 9. So, high prices often end in numbers like $10, $100, $1,000, or $9,999 because traders tend to react to these round numbers.Low Price: This is the lowest price Bitcoin hits during a certain time period. Similar to high prices, low prices also cluster, but more around numbers ending in 0 and 1. So, low prices might end in numbers like $10, $1,001, or $5,001.Why is there a difference?High prices tend to cluster at numbers ending in 0 or 9 because those feel like natural stopping points for traders.Low prices tend to cluster at numbers ending in 0 or 1 for similar reasons.⚪ Price Level Influence: The study highlights that clustering behavior changes with the overall price level of Bitcoin. At lower price levels (e.g., below $10,000), there is more clustering around multiples of 5, such as $25, $50, or $75. As the price increases, the significance of these smaller increments diminishes, and clustering around larger round numbers becomes more dominant.█ Practical Insights for Retail TradersUnderstanding price clustering is crucial for traders because it sheds light on how market participants behave, particularly around psychologically significant price levels. These insights can help traders anticipate where the market might encounter resistance or support, allowing them to make more informed decisions.⚪ Identify Key Psychological Levels: Retail traders can benefit from identifying and monitoring round number levels in Bitcoin prices, such as $10,000, $30,000, or $50,000. These levels are likely to act as psychological barriers, leading to increased trading activity. Understanding these levels can help traders anticipate potential support or resistance areas where price reversals may occur.⚪ Adjust Trading Strategies Based on Time Frame: The study suggests that the effectiveness of using price clustering in trading strategies depends on the time frame. For short-term traders, clustering may be less reliable, but for those operating on longer time frames, clustering around round numbers could provide actionable signals for entry or exit points.⚪ Focus on High and Low Prices: Retail traders should pay particular attention to clustering in high and low prices during a trading session. These prices are more likely to exhibit clustering, indicating areas where traders might place stop-loss orders or where price reversals could occur. By aligning their trades with these clusters, traders could improve their risk management. If you’re setting stop-loss orders, for instance, placing them just beyond a cluster point could help you avoid being stopped out prematurely by normal market noise. Similarly, identifying clusters at high prices could offer better opportunities for taking profits.⚪ Consider the Overall Price Level: The level at which Bitcoin is trading also affects clustering. For example, when Bitcoin is at a lower price, traders might find opportunities by focusing on price levels ending in 5 or 0. However, as Bitcoin’s price increases, clustering becomes more concentrated around larger round numbers. Adjusting trading strategies to consider the current price level can enhance decision-making. Price Clustering at Low Levels (<$10 USD):There is significant clustering at prices ending in 0, but also notable clustering at prices ending in 5, which acts as a psychological barrier at these lower levels. Prices ending with 50 are also frequently observed as significant psychological barriers. Clustering is weaker overall at these levels compared to higher price ranges, but still noticeable at certain intervals.Price Clustering at Mid-Levels ($100–$1,000 USD):Clustering becomes more focused on round numbers like 00, 50, and 25. As prices increase, clustering around smaller numbers like 5 or 10 reduces. Larger psychological barriers, such as 100 and 500, emerge as significant points of clustering.Price Clustering at Higher Levels (≥ $10,000 USD):At these price levels, clustering becomes even more prominent around major round numbers like 10,000, 20,000, etc. The last two digits 00 become much more frequent, and there is almost no clustering at digits like 5 or 1. Clustering becomes very strong at larger round figures, with a strong psychological barrier hypothesis at play.Summary of Clustering at Different Levels:Low Prices (<$10): Clustering at 5, 10, 50, and 100.Mid Prices ($100–$1,000): Strong clustering at 00, 50, and 25.High Prices (≥$10,000): Dominant clustering around 00 and multiples of 1,000 (e.g., 10,000, 20,000).█ ConclusionPrice clustering is more than just an academic concept; it’s a practical tool that can significantly enhance your trading strategy. By understanding how prices tend to cluster around psychological levels, adapting your approach based on time frames, and recognizing the impact of Bitcoin’s price level, you can make more informed trading decisions. By integrating these insights into your trading plan, you’re not only aligning your strategy with the behavior of the broader market but also positioning yourself to capitalize on key price movements. Whether you’re a seasoned trader or just starting out, the knowledge of price clustering can help you navigate the volatile Bitcoin market with greater confidence and precision.█ ReferenceXin, L., Shenghong, L., & Chong, X. (2020). Price clustering in Bitcoin market—An extension. Finance Research Letters, 32, 101072. -----------------DisclaimerThis is an educational study for entertainment purposes only.The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs.My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!

█ Diving Into Dark PoolsIn recent years, dark pools have become a significant part of the financial markets, offering an alternative trading venue for institutional traders. But what exactly are dark pools, and how do they impact market quality and price efficiency? This article delves into the comprehensive study titled "Diving Into Dark Pools" by Sabrina Buti, Barbara Rindi, and Ingrid Werner, which sheds light on the complexities of dark pool trading in the US stock market.█ What Are Dark Pools?Dark pools are private financial forums or exchanges for trading securities. Unlike public stock exchanges, dark pools do not display the order book to the public until after the trade is executed, providing anonymity to those placing trades. This lack of pre-trade transparency can help prevent large orders from impacting the market price, which is particularly beneficial for institutional investors looking to trade large volumes without revealing their intentions.█ How Do Dark Pools Work?In dark pools, the details of trades are not revealed to other market participants until the trade is completed. This lack of transparency helps prevent significant price movements that could occur if the order were known beforehand. Dark pools typically execute trades at the midpoint of the best bid and ask price in the public markets, ensuring fair pricing for both parties involved.█ Why Are Dark Pools Used?Dark pools are primarily used by institutional investors who need to execute large trades without revealing their trading intentions. Displaying such large orders on public exchanges could lead to unfavorable price movements due to market speculation and front-running by other traders.█ Benefits of Dark PoolsReduced Market Impact: Large orders can be executed without affecting the stock's market price.Anonymity: Traders can buy or sell significant amounts without revealing their identity or strategy.Lower Transaction Costs: By avoiding the public markets, traders can often reduce the costs associated with large trades.Improved Execution: Dark pools can offer better execution prices due to the lack of market impact and reduced volatility.█ Why Do Large Actors Hide Their Orders Using Dark Pools?Large institutional investors use dark pools to hide their orders to:Avoid Market Manipulation: Prevent others from driving the price up or down based on the knowledge of a large pending trade.Maintain Strategic Advantage: Keep trading strategies and intentions confidential to avoid imitation or counter-strategies by competitors.Achieve Better Prices: Execute trades at more favorable prices by not alerting the market to their actions.█ Actionable Insights for TradersUnderstand Market Dynamics: Knowing how and why dark pools are used can provide insights into market liquidity and price movements.Monitor Market Quality: Be aware that increased dark pool activity can improve overall market quality by reducing volatility and spreads.Assess Price Efficiency: Recognize that while dark pools can enhance market quality, they might also lead to short-term inefficiencies like price overreaction.█ Key Findings from the StudyThe study analyzed unique data on dark pool activity across a large cross-section of US stocks in 2009. Here are some of the critical insights:Concentration in Liquid Stocks: Dark pool activity is predominantly concentrated in liquid stocks. Specifically, Nasdaq stocks show higher dark pool activity compared to NYSE stocks when controlling for liquidity factors.Market Quality Improvement: Increased dark pool activity correlates with improvements in various market quality measures, including narrower spreads, greater depth, and reduced short-term volatility. This suggests that dark pools can enhance market stability and efficiency for certain stocks.Complex Relationship with Price Efficiency: The relationship between dark pool activity and price efficiency is multifaceted. While increased activity generally leads to lower short-term volatility, it can also be associated with more short-term overreactions in price for specific stock groups, particularly small and medium-cap stocks.Impact on Market Dynamics: On days with high share volume, high depth, low intraday volatility, and low order imbalances, dark pool activity tends to be higher. This indicates that traders are more likely to use dark pools when market conditions are favorable for large trades.█ ConclusionDark pools play a crucial role in modern financial markets by allowing large trades to be executed without revealing the trader’s intentions, thus minimizing market impact and reducing costs. For retail traders, understanding the mechanics and implications of dark pools can lead to better-informed trading decisions and a deeper comprehension of market behavior. The study concludes that while dark pools generally contribute to improved market quality by reducing volatility and enhancing liquidity, their effect on price efficiency is nuanced. For small and medium stocks, dark pools can lead to short-term price overreactions, while large stocks remain largely unaffected. The findings underscore the importance of understanding the different impacts on various stock categories to make informed trading decisions.For institutional traders and market participants, understanding the role and impact of dark pools is crucial for navigating the modern financial landscape. By offering an alternative venue for executing large trades discreetly, dark pools play a pivotal role in today's trading ecosystem.█ ReferenceButi, S., Rindi, B., & Werner, I. (2011). Diving into Dark Pools. Charles A. Dice Center for Research in Financial Economics, Fisher College of Business Working Paper Series, 2010-10.-----------------DisclaimerThis is an educational study for entertainment purposes only.The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs.My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!

█ The disposition effect in team investment decisions: Experimental evidenceThe disposition effect is a well-documented phenomenon in behavioral finance. Investors tend to sell winning investments too early and hold onto losing investments for too long. This behavior is primarily driven by emotional responses such as regret and joy. To delve deeper into this bias, a recent study compared the disposition effects in team investment decisions versus individual decisions. Here are the key takeaways, implications for traders, and how we can learn from these findings to improve investment strategies.Summary: Disposition Effect Overview: The disposition effect describes the tendency of investors to sell assets that have increased in value (winners) while holding onto assets that have decreased in value (losers). This behavior is influenced by emotional responses and is explained by theories like prospect theory and mental accounting.Team vs. Individual Investors: The study revealed that team investors exhibit stronger disposition effects compared to individual investors. Teams are more reluctant to realize losses and more prone to selling winners prematurely. This suggests that group dynamics can exacerbate these biases.Emotional Influence: Emotional responses, especially regret, play a crucial role in amplifying the disposition effect in team settings. Teams reported higher levels of regret and rejoice, indicating that group dynamics, such as groupthink and group polarization, heighten these emotions.█ Key FindingsThe results of this study provide compelling evidence about the impact of team dynamics on investment decisions, specifically regarding the disposition effect.⚪ Increased Disposition Effect in Teams: One of the standout findings is that teams exhibited a significantly higher disposition effect than individual investors. Quantitatively, teams were found to sell winning stocks at a rate of 22%, compared to just 17% for individuals. Moreover, they held onto losing stocks with greater tenacity, only selling 13% of such positions compared to 17% for individual traders.⚪ Reluctance to Realize Capital Losses: Teams' reluctance to realize capital losses suggests a heightened aversion to admitting mistakes or confronting poor outcomes when decisions are made collaboratively. This behavioral pattern could be attributed to a psychological mechanism called' loss aversion.'⚪ Premature Sale of Winning Investments: Similarly, teams' tendency to sell winning investments prematurely can be linked to a desire to secure quick wins to validate group decisions. This behavior aligns with the concept of 'resulting,' where the outcome of a decision disproportionately influences one's perception of the decision's quality.The study suggests that psychological phenomena like group thinking and emotional amplification play significant roles in shaping team investment behaviors. These phenomena lead teams to minimize conflict and reach a consensus without critically evaluating alternative viewpoints.█ How Traders Can Benefit from This KnowledgeSelf-awareness and Training: Traders should be trained to recognize the disposition effect in their decision-making processes. By being aware of their tendencies to hold onto losers and sell winners prematurely, they can critically evaluate their decisions and strive for more rational outcomes.Implementation of Structured Decision-Making: Structured decision-making protocols can help traders, especially in team settings, mitigate the influence of emotions. Techniques such as pre-defined selling rules, automatic stop-loss orders, and regular portfolio reviews can reduce emotional biases.Use of Technology: Trading algorithms that follow strict rules for buying and selling can help traders avoid the disposition effect. Additionally, tools that prominently display purchase prices or highlight long-term performance trends can assist traders in making more rational decisions.Nudging Techniques: Implementing nudges such as automatic reminders about initial investment goals or highlighting long-term gains can counteract the immediate emotional responses driving the disposition effect. These nudges can encourage traders to make more balanced decisions.Group Dynamics Management: Teams should be aware of groupthink and group polarization and actively work to counteract these effects through diverse perspectives and critical evaluations. Regular debriefing sessions and third-party evaluations can help teams make more balanced decisions.Adopting these measures could help trading teams counteract the negative aspects of the disposition effect and enhance overall performance by fostering a more disciplined investment approach.█ ConclusionsThe disposition effect is a significant behavioral bias that can adversely affect investment performance. The study demonstrates that this effect is more pronounced in team settings due to amplified emotional responses. By understanding and addressing the emotional drivers behind the disposition effect, traders can develop strategies to mitigate its impact and improve their investment decisions. Structured decision-making, the use of technology, nudging techniques, and proper management of group dynamics are practical ways to combat the disposition effect in both individual and team settings. Embracing these strategies can lead to more rational and profitable investment practices.█ Reference Rau, H. A. (2015). The disposition effect in team investment decisions: Experimental evidence. Journal of Banking & Finance, 61, 272-282. doi:10.1016/j.jbankfin.2015.09.015-----------------DisclaimerThis is an educational study for entertainment purposes only.The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs.My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!

█ Adapting to the New Norm: How Traders Can Thrive in Evolving MarketsThe world of trading is perpetually dynamic, with strategies that once dominated the market becoming less effective as both investors and technology evolve. A recent comprehensive study titled "How exactly do markets adapt? Evidence from the moving average rule in three developed markets" offers a profound look into how moving average (MA) strategies, once quite successful, have seen diminished efficacy in markets such as the DJIA, FT30, and TOPIX. This shift not only underscores the markets' adaptive nature but also serves as a clarion call for traders around the globe to rethink their strategies. Here’s how traders can adapt and thrive in this new trading landscape.█ The Shifting Sands of Market PredictabilityHistorically, moving averages provided traders with reliable signals that helped predict market movements effectively. However, the study reveals that these strategies have lost some of their predictive powers over time. This decline is attributed to the market's anticipatory actions—traders are reacting to signals even before they are officially generated. This highlights a critical need for traders to stay ahead by being more proactive rather than reactive in their strategies.█ Embracing the Adaptive Market Hypothesis (AMH)The Adaptive Market Hypothesis suggests that market efficiency is not a fixed state but rather a condition that evolves. This hypothesis aligns well with the observed trends in MA strategy effectiveness. Traders who adapt to the market's current rhythm and flow, understanding that what worked yesterday might not work tomorrow, are more likely to succeed. This calls for an agile approach to trading, where strategies are regularly reviewed and revised in response to shifting market dynamics.█ Leveraging Anticipation for ProfitabilityOne intriguing aspect of the study is the potential profitability of trading based on anticipated signals. Traders who can effectively forecast and act on these signals might find lucrative opportunities, even in a market where traditional indicators are faltering. This forward-looking approach requires robust analytical tools and a keen intuition for market sentiment, urging traders to develop a nuanced understanding of market triggers and trends.█ Strategies for the Modern TraderTo navigate this evolved market landscape, traders should consider several strategic shifts:⚪Continuous Learning: Stay abreast of market trends and shifts in trading paradigms. Traders should continually update their understanding of market behaviors and adapt their strategies accordingly. Relying on outdated models or historical data without considering market evolution may lead to suboptimal trading decisions.⚪Diversification of Techniques: Blend traditional methods like technical analysis with modern approaches such as machine learning and data analytics to create a well-rounded strategy.⚪Dynamic Adaptation: Be prepared to pivot strategies quickly in response to new information or shifts in market conditions. This might involve faster response times to emerging trends or the adoption of automated trading systems that can execute trades based on predetermined criteria.⚪Monitoring Market Conditions: Traders should be vigilant about changes in market conditions that could alter the effectiveness of established trading rules. This includes keeping an eye on broader economic indicators, market sentiment, and technological advancements in trading.⚪Risk Management: With increased market unpredictability, robust risk management strategies become even more critical. Diversifying investments and employing stop-loss orders can help mitigate potential losses.█ ConclusionThe evolution of market efficiency suggests a future where adaptability and foresight are more valuable than ever. For traders, the key to success lies in understanding and anticipating market changes, rather than relying solely on historical data. As we move forward, the ability to adapt will define the new era of trading success.In this ever-changing market landscape, staying informed, adaptable, and proactive are not just advantages but necessities for the modern trader.-----------------DisclaimerThis is an educational study for entertainment purposes only.The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs.My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!