Rajesh Kumar Nait / Perfil
- Informações
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4 anos
experiência
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34
produtos
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41
versão demo
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0
trabalhos
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No meu papel atual, foco em negociar $SOL diariamente como um trader diurno e ofereço programas de ponta para venda na minha página de vendedor. Esses programas incluem utilitários de conexão nativos com exchanges de criptomoedas através de Websocket e carregamento de gráficos de todas as exchanges populares via Websocket e API. Eles funcionam perfeitamente em VPS, sem a necessidade de DLLs externas.
Se você estiver interessado em ferramentas de análise ou negociação de criptomoedas, sinta-se à vontade para entrar em contato comigo por mensagem direta. Confira meus produtos criptográficos e integrações de exchange na minha página de vendedor MQL5. Ofereço suporte por 12 horas por dia no fuso horário IST, 7 dias por semana.
Por tempo limitado, todos os produtos estão disponíveis com 30% de desconto. Não perca!
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 Connector para MT5 – Integração Perfeita com MT5 Visão Geral O Pionex API EA Connector para MT5 permite a integração perfeita entre MetaTrader 5 (MT5) e a API da Pionex . Com esta ferramenta poderosa, os traders podem executar e gerenciar operações, obter informações de saldo e acompanhar o histórico de ordens diretamente no MT5 . Principais Funcionalidades 🔹 Gerenciamento de Conta e Saldo Get_Balance(); – Obtém o saldo atual da conta na Pionex . 🔹 Execução e Gerenciamento de
Pionex Live MT5 Data and History -- Adicione o endereço da API em Ferramentas > Expert Advisor api.pionex.com ws.pionex.com Passos: Criar Símbolos Selecione CreateSymbols = true Reinicie o terminal MT5 ( muito importante! ) Selecione os símbolos no Market Watch para carregar histórico e dados ao vivo Modos disponíveis: LiveUpdate – Adicione a utilidade ao gráfico para receber dados de negociação History – Adicione a utilidade para preencher o histórico até a data e hora desejadas
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.

