Crypto / BOME
BO
BOOK OF MEME
$0.0₃402
+0.00%
Past 3months
Trading vol10.12M
Market cap27.66M
Fully Diluted Valuation27.66M
Total Supply68.87B
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MasterAnanda
BOOK OF MEME (BOME) can start moving right away
In a way, it is already moving... BOMEUSDT is on its third green day but still at bottom prices. It is early for this pair and Cryptocurrency —meme coin— project. I don't know why nor how but this one made it into my list, we trade it often. Lately things are good. There aren't that many wins because the market isn't moving, but there aren't that many loses either. If you look at this chart, you can tell why. There are no new lows. With a lack of a bearish trend, there is nothing to lose other than time; and, time is never lost. Yes, we are waiting and we wait, but the waiting time is what will support a massive bullish wave. We could be seeing slow and steady growth for months and it would be the same. Say two months growing slowly or two months at bottom prices. If the complete bullish phase lasts five months before a major correction, the first two months would still be a sort of consolidation. Ok. The wait is over. Forget the past. Enjoy the present, focus on this moment now and prepare for the future, what comes next. The build-up process is always like this. Three days green, slow, then comes a sudden jump. I see it now on the ETHUSDT and BTC charts. BOMEUSDT recovered above the October 2025 low and this opens the bullish zone. Five months now fully over and no bearish continuation. The lack of bearish action is the strongest signal of all. The prolonged period of sideways at bottom prices reveals an accumulation phase. The next move is a major rise. The only question that remains: How far up can it go? I saw some projects growing 200-300% in the past few days. This can work as an example. Those moving first, haven't been shy, so we can expect strong growth on those that are yet to move. Thank you for reading. Namaste.
7:33 PM · Apr 1, 2026
0
1
mansour65horzadeh
import pandas as pd import numpy as np import matplotlib.pyplot
import pandas as pd import numpy as np import matplotlib.pyplot as plt import yfinance as yf from datetime import datetime # دریافت داده‌های تاریخی (مثال: بیت‌کوین) symbol = "BTC-USD" start_date = "2023-01-01" end_date = datetime.now().strftime("%Y-%m-%d") data = yf.download(symbol, start=start_date, end=end_date) df = data [ ].copy() # ۱. محاسبه میانگین متحرک (MA) def calculate_ma(df, window=20): df = df .rolling(window=window).mean() return df df = calculate_ma(df, window=20) df = calculate_ma(df, window=50) # ۲. محاسبه RSI def calculate_rsi(df, window=14): delta = df .diff() gain = (delta.where(delta > 0, 0)).rolling(window=window).mean() loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean() rs = gain / loss df = 100 - (100 / (1 + rs)) return df df = calculate_rsi(df, window=14) # ۳. محاسبه MACD def calculate_macd(df, fast=12, slow=26, signal=9): df = df .ewm(span=fast, adjust=False).mean() df = df .ewm(span=slow, adjust=False).mean() df = df - df df = df .ewm(span=signal, adjust=False).mean() df = df - df return df df = calculate_macd(df) # ۴. رسم نمودارها fig, axes = plt.subplots(4, 1, figsize=(14, 10), gridspec_kw={'height_ratios': }) # نمودار قیمت و MA axes .plot(df.index, df , label='Close Price', color='black', linewidth=1) axes .plot(df.index, df , label='MA 20', color='blue', linewidth=1) axes .plot(df.index, df , label='MA 50', color='red', linewidth=1) axes .set_title(f'{symbol} - Price & Moving Averages') axes .legend() axes .grid(True) # نمودار RSI axes .plot(df.index, df , label='RSI (14)', color='purple', linewidth=1) axes .axhline(y=70, color='red', linestyle='--', linewidth=0.7) axes .axhline(y=30, color='green', linestyle='--', linewidth=0.7) axes .fill_between(df.index, 30, 70, alpha=0.1, color='gray') axes .set_title('RSI Indicator') axes .legend() axes .grid(True) # نمودار MACD و Signal Line axes .plot(df.index, df , label='MACD', color='blue', linewidth=1) axes .plot(df.index, df , label='Signal Line', color='red', linewidth=1) axes .set_title('MACD Indicator') axes .legend() axes .grid(True) # نمودار هیستوگرام MACD axes .bar(df.index, df , label='MACD Histogram', color='gray') axes .axhline(y=0, color='black', linewidth=0.5) axes .set_title('MACD Histogram') axes .legend() axes .grid(True) plt.tight_layout() plt.show() # ۵. نمایش جدول داده‌های اخیر print(df [ ].tail(10))
9:15 PM · Dec 12, 2025
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