IntroductionIn the crypto asset market, information asymmetry and uneven liquidity distribution are key factors leading to sharp price fluctuations. Traditional price-volume factor models can explain daily market volatility to some extent, but they often lack the capacity to handle extreme market conditions triggered by external shocks, news-driven events, or abnormal capital flows. Unlike price-volume factors that rely on public market data, the core id...

IntroductionIn the crypto asset market, information asymmetry and uneven liquidity distribution are key factors leading to sharp price fluctuations. Traditional price-volume factor models can explain daily market volatility to some extent, but they often lack the capacity to handle extreme market conditions triggered by external shocks, news-driven events, or abnormal capital flows. Unlike price-volume factors that rely on public market data, the core id...

The time series forecasting method based on news event driving and Large Language Models (LLMs)—"From News to Forecast: Iterative Event Reasoning in LLM-Based Time Series Forecasting"—jointly proposed by Professor Zhao Junhua's team from the Chinese University of Hong Kong (Shenzhen) and Professor Qiu Jing's team from the University of Sydney, was recently accepted by NeurIPS, a top-tier AI conference. This paper introduces a new paradigm for time series forecasting: predicting time series da...

The time series forecasting method based on news event driving and Large Language Models (LLMs)—"From News to Forecast: Iterative Event Reasoning in LLM-Based Time Series Forecasting"—jointly proposed by Professor Zhao Junhua's team from the Chinese University of Hong Kong (Shenzhen) and Professor Qiu Jing's team from the University of Sydney, was recently accepted by NeurIPS, a top-tier AI conference. This paper introduces a new paradigm for time series forecasting: predicting time series da...

he cryptocurrency market is highly volatile, and emotions play a crucial role in driving price fluctuations. Investor sentiment, often influenced by fear, greed, and hype, can trigger rapid buying or selling, leading to dramatic price swings. For instance, "FOMO" (fear of missing out) may drive prices up during bull runs, while panic selling during market downturns exacerbates crashes. Social media, news, and influential figures like Elon Musk further amplify emotional reaction...

he cryptocurrency market is highly volatile, and emotions play a crucial role in driving price fluctuations. Investor sentiment, often influenced by fear, greed, and hype, can trigger rapid buying or selling, leading to dramatic price swings. For instance, "FOMO" (fear of missing out) may drive prices up during bull runs, while panic selling during market downturns exacerbates crashes. Social media, news, and influential figures like Elon Musk further amplify emotional reaction...

The Institutional Crypto Data GapInstitutional participation in digital asset markets is accelerating globally. However, the data infrastructure supporting institutional decision-making in crypto remains fundamentally incomplete. Traditional financial data systems — including price feeds, macro indicators, and corporate fundamentals — were designed for markets where valuation anchors are stable and information flows are regulated. Digital asset markets operate under a different paradigm: Open...

The Institutional Crypto Data GapInstitutional participation in digital asset markets is accelerating globally. However, the data infrastructure supporting institutional decision-making in crypto remains fundamentally incomplete. Traditional financial data systems — including price feeds, macro indicators, and corporate fundamentals — were designed for markets where valuation anchors are stable and information flows are regulated. Digital asset markets operate under a different paradigm: Open...

Introduction to ESGPT Methodology"Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events," co-authored by Matthew B. A. McDermott, Bret Nestor, Peniel Argaw, and Isaac Kohane, introduces a methodology using EventGPT (ESGPT) to process continuous-time complex event sequence data. ESGPT is specifically designed for continuous-time, multimodal event sequences with internal dependencies. In the origina...

Introduction to ESGPT Methodology"Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events," co-authored by Matthew B. A. McDermott, Bret Nestor, Peniel Argaw, and Isaac Kohane, introduces a methodology using EventGPT (ESGPT) to process continuous-time complex event sequence data. ESGPT is specifically designed for continuous-time, multimodal event sequences with internal dependencies. In the origina...

I. Client InformationOrganization Name: MatrixportResearcher/Contact: LiLukaBacktest Time Range: 2025-06-09 to 2025-07-09Strategy Name: Long-Short Hedging Strategy for Currency Rotation Based on Return Sequence PredictionStrategy Type: Cross-sectional StrategyII. Indicator DescriptionIndicator Name: CO-A-01-05Indicator Interpretation: The number of times a single cryptocurrency is mentioned across global social platforms, including associated keywords such as names, tickers, and nicknames.Dat...

I. Client InformationOrganization Name: MatrixportResearcher/Contact: LiLukaBacktest Time Range: 2025-06-09 to 2025-07-09Strategy Name: Long-Short Hedging Strategy for Currency Rotation Based on Return Sequence PredictionStrategy Type: Cross-sectional StrategyII. Indicator DescriptionIndicator Name: CO-A-01-05Indicator Interpretation: The number of times a single cryptocurrency is mentioned across global social platforms, including associated keywords such as names, tickers, and nicknames.Dat...

I. Data PreprocessingThe total community speech volume (community_volume) associated with a specific cryptocurrency represents market attention and the degree of information flow for that asset during a given period. Quantifying its extreme fluctuations and structural changes can assist in identifying market anomalies, sentiment evolution, and potential trading signals.(A) Sample ScopeTime Interval: 2025-01-01 to 2025-07-26Data Frequency: 1HCoin Screening Criteria:Remove coins where the sum o...

I. Data PreprocessingThe total community speech volume (community_volume) associated with a specific cryptocurrency represents market attention and the degree of information flow for that asset during a given period. Quantifying its extreme fluctuations and structural changes can assist in identifying market anomalies, sentiment evolution, and potential trading signals.(A) Sample ScopeTime Interval: 2025-01-01 to 2025-07-26Data Frequency: 1HCoin Screening Criteria:Remove coins where the sum o...