# Quant的所有文章

在 HTX 新闻中心浏览与「Quant」相关的最新资讯与深度分析。潘盖市场趋势、项目动态、技术进展及监管政策，提供权威的加密行业洞察。

Someone Turned Buffett and Munger into Agents, Then Open-Sourced It...

The open-source project "AI Hedge Fund" has gained significant traction on GitHub, creating AI agents modeled after 12 legendary investors, including Warren Buffett and Charlie Munger, to analyze stocks and develop trading strategies. It features a team of 6 analyst agents that synthesize insights and make final decisions. The system includes a backtesting module to evaluate strategies with historical data before real investment. Built by developer Virat Singh, the project supports 13 major AI models and can run locally. It uses a React front-end with a visual workflow editor and a Python/FastAPI backend orchestrated with LangGraph. The agent team covers diverse philosophies, from value investing (Graham) to growth (Cathie Wood) and risk management (Taleb). While not proven in live markets, it offers a platform for learning agent frameworks and diverse investment perspectives through simulated expert debate. The project highlights a growing trend of "distilling" financial wisdom into AI, but users are cautioned about its unverified returns and investment risks.

marsbit前天 11:16

Someone Turned Buffett and Munger into Agents, Then Open-Sourced It...

marsbit前天 11:16

Bitcoin Bears Press On, Can the $60,000 Defense Line Hold? | Invited Analysis

Bitcoin faces continued bearish pressure, testing the critical $60,000 support level. The market remains in a downtrend, with BTC breaking below a short-term rising trendline and consolidating near the lower boundary of its upward channel. A break below $60,000 could confirm a C-3 wave decline. Meanwhile, HYPE shows independent strength, holding above the $36–38 support zone after a pullback, with potential for further upside if support holds. Trading strategies emphasize short-term opportunistic positions (30% capital) using scalping models, while maintaining a core bearish stance on BTC with a held short position from $89,000 (currently +24.76%). Key resistance levels for BTC are $69,500–72,000 and $74,500–76,000; supports are $65,000–66,000, $60,000–62,500, and $57,400. Risk management includes strict stop-losses and dynamic trailing stops. All analysis is for informational purposes only; not investment advice.

marsbit03/30 06:18

Bitcoin Bears Press On, Can the $60,000 Defense Line Hold? | Invited Analysis

marsbit03/30 06:18

Earning $80,000 in One Day: How Top Players Turn Polymarket into Their Personal ATM?

In just under a day, a top trader on Polymarket, using the handle Bidou28old, netted $80,000 by exploiting the platform’s newly launched ultra-short-term prediction markets (5-minute and 15-minute intervals). The user is believed to be a quantitative trader or arbitrageur leveraging low-latency data feeds to capitalize on pricing delays. With only 48 total predictions, the trader maintained a remarkably high risk-reward ratio, often buying outcomes with only a 3-8% probability (e.g., betting on a Bitcoin rebound within minutes during a sharp decline). Even with 7 losses exceeding $10,000, the strategy remained profitable due to high payoff multiples—sometimes as high as 33x. The trader employed strict position management, placing large bets ($7,000–$19,000) on high-probability opportunities and securing returns between $4,800–$6,400 per successful trade. In one notable 30-minute span, the user executed three consecutive winning trades, earning over $18,000, demonstrating a high-frequency, data-driven approach. Activity was concentrated during U.S. evening hours (7:30–11:00 PM ET), suggesting either a North American night trader or a professional Asian quant operating during daytime hours. The trader focused predominantly on Bitcoin and Ethereum due to their high liquidity and volatility. This case highlights how sophisticated players use quantitative strategies and real-time market data to systematically profit from short-term market movements on prediction platforms.

比推02/13 12:51

Earning $80,000 in One Day: How Top Players Turn Polymarket into Their Personal ATM?

比推02/13 12:51

Making a Profit of $100,000 from 'Mosquito Meat' with 170 High-Frequency Trades per Day?

A quantitative trading bot, planktonXD, generated over $106,000 in profit on Polymarket within a year by executing more than 61,000 predictions—averaging 170 trades per day. Instead of betting on high-risk "black swan" events, it employed a high-frequency market-making and arbitrage strategy, focusing on small, consistent gains with minimal drawdowns. The bot capitalized on mispriced odds in low-liquidity markets—such as regional esports matches and crypto price predictions—by placing tiny bets on highly improbable outcomes that were statistically undervalued. For example, it achieved returns as high as 23,750% on a VALORANT match and 9,285% on a SOL price prediction by buying nearly worthless shares that surged during market panics or emotional mispricings. Key takeaways include the power of compounding small gains, the necessity of automated tools and API access, and the importance of probability management over high-risk bets. The strategy highlights that success in prediction markets lies not in forecasting outcomes, but in exploiting liquidity gaps and probabilistic edges.

比推02/11 12:36

Making a Profit of $100,000 from 'Mosquito Meat' with 170 High-Frequency Trades per Day?

比推02/11 12:36

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