Rajesh Kumar Nait / 个人资料
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在我的当前角色中,我专注于作为日间交易员每日交易$SOL,并在我的销售页面上提供尖端程序出售。这些程序包括本机Websocket加密货币交易所连接实用程序,并通过Websocket和API从所有热门交易所加载图表。它们在VPS上无缝运行,无需外部DLL。
如果您对加密货币图表或交易工具感兴趣,请随时通过DM与我联系。在我的MQL5销售页面上查看我的加密产品和交易所集成。我提供每天12小时的IST时区支持,每周7天。
在有限的时间内,所有产品都以30%的折扣出售。不要错过!
This is counterintuitive, but there are solid market microstructure reasons why this happens:
🔍 1. Liquidity Vacuum / Stop-Hunt Trigger
When a market rapidly moves up on low volume, it often means:
Liquidity was thin on the sell side.
A few aggressive buyers cleared the sell wall, triggering:
Stop-losses from shorts (adding buy pressure).
Limit orders above recent lows (creating a vacuum effect).
Result: Price jumps quickly, but volume is still low because not many contracts needed to be traded to move price.
🧠 Think of it like this:
"Price moves the fastest when nobody is willing to sell anymore — not when everyone's buying."
🔍 2. Passive Sellers Withdrew Orders
Another reason: Market makers pulled liquidity because the prior candles looked weak, and they didn’t want to get caught in a reversal.
With fewer passive limit sell orders in the book, even small buy orders push price up more.
This shows up as big candles but low volume.
🔍 3. False Sense of Demand – It’s Not Strength (Yet)
Sometimes big candles on low volume are fake breakouts or traps:
It looks strong, but it’s mostly short covering or bot-driven.
If buyers don’t step in after that candle, it may reverse again — so you want to see confirmation with volume after the big move.
Pionex API EA 连接器(MT5) – 无缝集成MT5 概述 Pionex API EA 连接器 允许 MetaTrader 5(MT5) 无缝集成 Pionex API ,让交易者直接在 MT5 上执行交易、管理订单、获取账户余额并跟踪交易历史。 主要功能 🔹 账户和余额管理 Get_Balance(); – 获取 Pionex 账户的当前余额。 🔹 订单执行和管理 orderLimit(string symbol, string side, double size, double price); – 按指定价格下 限价单 。 orderMarket(string symbol, string side, double size, double amount); – 以指定数量执行 市价单 。 Cancel_Order(string symbol, string orderId); – 取消特定订单(通过 ID )。 Cancel_All_Order(string symbol); – 取消该交易对的所有 未完成订单 。 🔹 订单跟踪和历史
Pionex Live MT5 Data and History -- Add the API address to Tools > Expert Advisor api.pionex.com ws.pionex.com Steps : Create Symbols Select CreateSymbols = true Restart MT5 Terminal (Most important) Select Symbols to marketwatch for which you want to load history and live data 1. Add utility to any chart and Select Mode = LiveUpdate to get trade data on chart 2. Add utility to any chart and Select Mode = History to fill history to desired date and time Use MaxDate to add any date you wish to
1. Learn to adapt as per situation
2. Never Be Determined
1. News and Fundamental analysis impact market but it also go against technical analysis or price action
2. Using an indicator can make you successful
3. Fibonacci calculations does not work
4. You do not need custom analysis assistant build on mt5 or other program before you do analysis
5. You can trade and be successful from smartphone or tablet or promotion of portability in trading.
1 year ago i was enjoying this song, my favorite
1. Running Trading & Charting Software
Most trading platforms (e.g., TradingView, NinjaTrader, MetaTrader, ThinkorSwim) rely more on CPU, but they also use GPUs for rendering charts and handling multiple monitors. GTX 970 can:
Smoothly run multiple charts and indicators.
Handle multiple monitors (good for multi-timeframe analysis).
Speed up heatmaps and visualizations of market data.
2. Accelerating Data Analysis & Backtesting
If I am using Python for market research, I can use NVIDIA’s CUDA for faster computations.
Backtesting libraries: I may Use Backtrader or Zipline with GPU acceleration for strategy testing.
Data analysis: Use cuDF (GPU-accelerated pandas) to handle large market datasets faster.
Machine learning: If you're training AI models for price prediction, NVIDIA’s TensorFlow with CUDA can offload computations to your GPU.
3. Running AI/ML Models for Market Prediction
Even though the GTX 970 is older, it supports TensorFlow/PyTorch (CUDA 11.x max) for basic ML models.
I can train simple neural networks for pattern recognition in stock price movements.
Use libraries like TA-Lib (technical analysis indicators) along with GPU-accelerated data processing.
4. GPU-Accelerated Quantitative Research
Monte Carlo simulations: Speed up simulations for option pricing or risk analysis.
Reinforcement Learning (RL): Experiment with Deep Q-Learning (DQN) for algo trading.
Order Book Analysis: Use GPU-accelerated tools for processing high-frequency trading (HFT) data.
5. Cryptocurrency & Alternative Markets
If I trade crypto, GPU acceleration helps in on-chain analysis, sentiment analysis, or even mining
Some platforms like Cryptohopper or 3Commas allow GPU-based automation for backtesting trading bots.
Limitations of GTX 970 for Trading
✅ Good for visualization, backtesting, and basic AI research.
❌ Not great for heavy deep learning or handling massive datasets.
❌ Limited VRAM (4GB) makes it unsuitable for high-end models.

