OpenHFT @OpenHFT_
Quant startup looking to democratize computational finance models among retail investors for everyday use. Try our app at https://t.co/vmZPvwelYI openhft5.wordpress.com Joined December 2024-
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A shoutout to @OVVOLabs for their interesting work on nonlinear, nonparametric statistical methods (NNS) for improved risk management. Their research in this field is very novel and has interesting applications in the field of computational finance.
Stop emotional trading! 🚫 Follow data-backed recommendations from quant strategies available on MarketLens. Make informed decisions, not impulsive ones. 📱 Try MarketLens at openhft.streamlit.app #IndianStockMarket #EquityTrading #MarketAnalytics #PreTradeAnalysis
Make data your advantage💪 MarketLens provides easy-to-understand data on daily returns & volatility, empowering you to spot trends and opportunities #TradingInsights #DataAnalysis #EquityResearch #InvestSmart #IndianStockMarket #EquityTrading #MarketAnalytics #PreTradeAnalysis
If you believe AGI is indeed achievable, then you would strongly agree to the school of thought which says there will be one model to rule all financial tasks. Researchers from this line of thought have introduced Kronos 🗺️ Paper Link - arxiv.org/pdf/2508.02739
Our HFT Desk in action with our internal Reinforcement Learning based trading tool - AlgoHFT 💰
Dive deeper into market movements! 📊MarketLens offers detailed analysis on daily returns & spreads for key Indian indices & stocks. Understand the nuances before you trade. openhft.streamlit.app #IndianStockMarket #EquityTrading #MarketAnalytics #FintechIndia #TradingTools
If you are looking to take reinforcement learning one step further and involve LLMs like DeepSeek along with on-the-fly sentiment analysis then this paper is for you arxiv.org/pdf/2502.07393
If you are looking to take reinforcement learning one step further and involve LLMs like DeepSeek along with on-the-fly sentiment analysis then this paper is for you arxiv.org/pdf/2502.07393
A starting place to read about academic findings in deploying RL & other deep learning models for trading this NeurIPS paper - arxiv.org/pdf/1811.07522 An extremely worthwhile read for anyone looking to start out with Reinforcement Learning for trading!
A starting place to read about academic findings in deploying RL & other deep learning models for trading this NeurIPS paper - arxiv.org/pdf/1811.07522 An extremely worthwhile read for anyone looking to start out with Reinforcement Learning for trading!
Some of the good tutorials which currently walk through this entire process are as below: 1. Data setup - github.com/AI4Finance-Fou… 2. Train Agent - github.com/AI4Finance-Fou… 3. Deploy Agent - github.com/AI4Finance-Fou…
Some of the good tutorials which currently walk through this entire process are as below: 1. Data setup - github.com/AI4Finance-Fou… 2. Train Agent - github.com/AI4Finance-Fou… 3. Deploy Agent - github.com/AI4Finance-Fou…
Once you have a basic understanding on how to setup your dimension space and state vectors, you will need a good tutorial on Data Engineering to set up stock vectors and then to use these libraries to train an RL model/agent. These can then be used to take trading decisions
Once you have a basic understanding on how to setup your dimension space and state vectors, you will need a good tutorial on Data Engineering to set up stock vectors and then to use these libraries to train an RL model/agent. These can then be used to take trading decisions
Next as an RL engineer you need to figure out how to set up a OpenAI gym like feedback environment to simulate different states for trading. Existing python packages which can help are the following: 1. ElegantRL (github.com/AI4Finance-Fou…) 2. FinRL-Meta (github.com/AI4Finance-Fou…)
Next as an RL engineer you need to figure out how to set up a OpenAI gym like feedback environment to simulate different states for trading. Existing python packages which can help are the following: 1. ElegantRL (github.com/AI4Finance-Fou…) 2. FinRL-Meta (github.com/AI4Finance-Fou…) https://t.co/P7A0MzaxiQ
[A thread on Deep Learning for Trading] To start out with Reinforcement learning in HFT, you need to research about the following algo's: 1. Deep Q Learning (DQN) 2. Advantage Actor Critic (A2C) 3. Deep Deterministic Policy Gradient (DDPG) 4. Proximal Policy Optimization (PPO)
Without having these features in your dataset, you will absolutely do yourself a disservice and your deep learning model will fail to have good F1 scores. Feel free to comment if we have missed any imp feature which others are using for indian markets
Without having these features in your dataset, you will absolutely do yourself a disservice and your deep learning model will fail to have good F1 scores. Feel free to comment if we have missed any imp feature which others are using for indian markets
For quantitative researchers looking to build a dataset for their deep learning models in trading, the following features are absolutely essential at a scrip level 1. Current Market Price (at tick level) 2. Aggregated Bid Qty 3. Aggregated Ask Qty 4. USD/INR 6. Crude Price
A very interesting read on using Open Interest in options chain as a feature in your quant model!
A very interesting read on using Open Interest in options chain as a feature in your quant model!
Wall Street speed. Open-source transparency. Retail access. ⚡ Meet Market Lens the first open-source, low-latency pre-trade analytics platform 👉 Try it now → openhft.streamlit.app #Trading #HFT #OpenSource #algotrading #quantdeveloper #quant #computationalfinance #ml
Our trading desk has been exploring Reinforcement learning for trading in Indian markets. Tensor Trade is a very good package to check out if this space interests you !
Our trading desk has been exploring Reinforcement learning for trading in Indian markets. Tensor Trade is a very good package to check out if this space interests you !
At OpenHFT we are building our quant models for the open source trader community who can use them without any coding knowledge. 🚀Introducing MarketLens The tool which gives retail traders an edge! 🖥️App Link - openhft.streamlit.app 📕User Guide - openhft5.wordpress.com/strategies/
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