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Pepe NOSTRos
4b74667f89358cd582ad82b16a2d24d5bfcb89ac4b1347ee80e5674a13ba78b2
Time is near. Little by little then all at once. We ask for nothing, we do not recruit We simply share the lore when we return We are Raid Traders because we know the time is near So until the end, we raid.

Even the freedom to take your things if they see youass undesirable? I think you may want to abridge what they see as their eights in that circumstance fren. Rights are relative and subjective.

the books set me off on a lifetime of distaste for Jesuits. I also dont eat duck because of that book. nasty Portugese Jesuits bro. Just nasty.

Nonsense. Makes no sense at all but holy shid bro! do that again!

nostr:note12j9upxdg8vpt2s2q9j6el3q6kle323tn9x8ptksq527u05n2069qk5m47w

careful . . . thats how you get hippies. You dont want hippies do you? kek

Nice leg unit count. does it kick too or just dance. Are you a "dancing man" Count?

Navigating the Tides: A Guide to Trend Identification & Price Swing Amplitude in Trading

Sometimes its easier to deal with complex data by reducing the dimensionality. Trading based on trend and swing amplitude is in a sense just that. You decide whether up or down and what the likely range of motion is around trend line and trade accordingly. Easier said than done though so here is a super high level guide to swing trading that may be a good starting point. Its only one tool in the shed and only works when conditions permit, but it is a solid starting point for understanding what the charts are saying.

To understand the concept of trading based on trend identification and determining the price swing amplitude to establish a statistical range for trend pricing, you can follow these steps:

1. **Identifying the Trend**: The first step in this strategy is to identify whether the market is in an uptrend, downtrend, or ranging. This can be done by analyzing historical price data and looking at various technical indicators such as moving averages, support and resistance levels, and trendlines [1][2].

2. **Determining Price Swing Amplitude**: Once the trend is established, the next step is to determine the amplitude of the price swings. This involves analyzing how much the price moves in a given time frame. The range between the highs and lows during the trend can provide insight into the normal fluctuations of the market for that asset [5].

3. **Setting the Statistical Range**: Based on the historical price swing amplitude, you can set a statistical range that defines the upper and lower bounds of what is considered 'normal' price movement within the trend. This range can be based on statistical measures such as standard deviation to account for variations and provide a buffer [10].

4. **Entry and Exit Strategies**: With the statistical range in place, you can then develop strategies for entering and exiting trades. Typically, you would look to sell or short-sell when the price approaches the upper end of the statistical range, as this is where the asset may be overbought and potentially due for a correction [8]. Conversely, you might consider buying or covering shorts when the price hits the lower end of the range, as this could indicate that the asset is oversold and may soon reverse upward [6][12].

5. **Continuous Monitoring and Adaptation**: It's important to continuously monitor the market for changes in volatility, volume, and price action, as these can all affect the statistical range. The trend and the range are not static; they can change over time due to new information or shifts in market sentiment [3].

6. **Risk Management**: A key component of this strategy is risk management. By setting clear rules for entry and exit points, you can manage your exposure to the market and protect your capital. It's also essential to consider the overall market conditions and not rely solely on the statistical range [4][13].

7. **Backtesting**: Before applying this strategy with real capital, it's advisable to backtest your approach using historical data to see how it would have performed in different market conditions. This can help you refine your strategies and understand potential risks [14].

In summary, trading based on trend identification and price swing amplitude involves understanding the normal range of price movements within a trend, setting statistical parameters around this range, and making buy or sell decisions when the price moves outside these bounds. It's a disciplined approach that requires continuous analysis and adaptation to market conditions.

Citations:

[1] https://www.investopedia.com/ask/answers/difference-between-fundamental-and-technical-analysis/

[2] https://www.investopedia.com/articles/active-trading/041814/four-most-commonlyused-indicators-trend-trading.asp

[3] https://www.equiti.com/sc-en/education/market-analysis/trend-analysis-101/

[4] https://marketmasters.app/identifying-market-trends-strategies-for-profitable-trading/

[5] https://www.equitypandit.com/how-to-do-a-trend-analysis-in-stock-market-a-complete-guide/

[6] https://medium.com/coinmonks/how-to-identify-the-trend-a-simple-guide-1ea852aab199

[7] https://www.investopedia.com/terms/t/technicalanalysis.asp

[8] https://elitetradersuniversity.com/technical-analysis-101-charts-indicators-and-patterns/

[9] https://stockstotrade.com/trend-trading-strategy/

[10] https://tradingliteracy.com/how-to-read-price-action/

[11] https://howtotrade.com/trading-strategies/trend-trading/

[12] https://blueberrymarkets.com/learn/advanced/price-action-trading-strategy/

[13] https://www.forex.academy/technical-analysis-key-strategies-for-identifying-forex-market-trends/

[14] https://www.quora.com/How-can-I-learn-technical-analysis-for-short-term-trading

[15] https://www.forex.com/en/news-and-analysis/a-guide-to-market-trends/

The real estate tokenizer coin scams will be heating up around now i guess.

Replying to Avatar Pepe NOSTRos

Regression, Entropy and the Market Whales

Regression towards the mean is a statistical phenomenon in which extreme values tend to be followed by more moderate values, and vice versa. In financial markets, this principle can affect both low entropy energy sources (such as market whales) and high entropy waste (transaction noise).

1. Low Entropy Energy Sources: When market "whales" make large trades or hold significant positions in a particular security, they can cause the price to move significantly away from its historical average. However, due to regression towards the mean, it is likely that subsequent prices will revert back towards their long-term average as other traders adjust their expectations and trading strategies. This process may result in a temporary decrease in the value of low entropy energy (information) provided by whales, as their unique insights become less valuable when the market reverts to its historical average.

2. High Entropy Waste: Transaction noise generated by high-frequency traders or retail investors can also be affected by regression towards the mean. During periods of extreme price movements (caused, for example, by a major news event), transaction noise may temporarily increase as traders make rapid and uncoordinated adjustments to their positions. However, over time, these extreme price movements are likely to revert back towards the historical average due to regression towards the mean, reducing the level of transaction noise in the market.

In summary, both low entropy energy sources (market whales) and high entropy waste (transaction noise) can be affected by the principle of regression towards the mean in financial markets. This phenomenon may lead to temporary changes in the value of information provided by whales or the level of transaction noise in the market as prices revert back towards their long-term average trend.

In other words. Most of the time the most likely shid happens.

Regression, Entropy and the Market Whales

Regression towards the mean is a statistical phenomenon in which extreme values tend to be followed by more moderate values, and vice versa. In financial markets, this principle can affect both low entropy energy sources (such as market whales) and high entropy waste (transaction noise).

1. Low Entropy Energy Sources: When market "whales" make large trades or hold significant positions in a particular security, they can cause the price to move significantly away from its historical average. However, due to regression towards the mean, it is likely that subsequent prices will revert back towards their long-term average as other traders adjust their expectations and trading strategies. This process may result in a temporary decrease in the value of low entropy energy (information) provided by whales, as their unique insights become less valuable when the market reverts to its historical average.

2. High Entropy Waste: Transaction noise generated by high-frequency traders or retail investors can also be affected by regression towards the mean. During periods of extreme price movements (caused, for example, by a major news event), transaction noise may temporarily increase as traders make rapid and uncoordinated adjustments to their positions. However, over time, these extreme price movements are likely to revert back towards the historical average due to regression towards the mean, reducing the level of transaction noise in the market.

In summary, both low entropy energy sources (market whales) and high entropy waste (transaction noise) can be affected by the principle of regression towards the mean in financial markets. This phenomenon may lead to temporary changes in the value of information provided by whales or the level of transaction noise in the market as prices revert back towards their long-term average trend.

not yet. am still accumulating. dxy is gonna tumble for a decade soon so just dont rush it pl pls pls.

My lil corner of nostr is not very big but I like it and dig the ppl.

https://m.primal.net/HuYB.webp

Steady lads. Big whales in the water lurking. Theres gonna be high volume liquidity flow when they move.