Investment Analysis Assistant
Description
This is a highly structured, multi-dimensional, cross-asset analysis framework that emphasizes 'meta-thinking.' Its core features include layered decomposition and narrative integration, distinguishing between 'direction variables' that determine medium-to-long-term trends and 'rhythm variables' that affect fluctuations. It deeply incorporates Robert Shiller's 'narrative economics' to analyze the spread of market sentiment and stories. The framework requires analysts not only to provide conclusions but also to reveal the judgment logic, verification criteria, and potential misjudgments behind them. The ultimate goal is not to make decisions for you but to help you gradually internalize this transferable analysis method through each analysis, ultimately forming your own independent and systematic investment analysis capability.
Related Skills
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Stock Report Analyzer
Financial reports are a listed company's "physical exam report", but most investors feel lost when faced with pages of dense numbers: • 📝 Can't read the three financial statements — What do the balance sheet, income statement, and cash flow statement tell you? Which numbers matter most? • 🤔 Don't know what to look at — With dozens of pages, which key metrics should you focus on? • 📊 Lack an analysis framework — Even when you find the data, how do you judge good from bad and cross-check it? • 🏭 Industry standards differ — What counts as "good" varies completely by industry; manufacturing and internet companies can't be measured with the same yardstick. • ⏰ Time cost is too high — Manually looking up data, comparing peers, and calculating growth rates can take hours for one report. This skill was built to solve exactly these problems. It automates a professional financial analyst's framework, so you just need to enter a stock code to get a structured, logical, and beginner-friendly financial report interpretation. The tool's core value lies in its rigorous analysis framework, covering multiple dimensions from assessing growth quality to analyzing business models. It not only compares core metrics like revenue, gross margin, net margin, and cash flow, but also runs a quick Q&A on the seven key financial questions investors care about most. It clearly shows whether profits are turning into real cash, and whether receivables and inventory carry potential risks. By benchmarking against industry leaders, it helps you identify a company's true position in its industry chain. When generating the report, it also evaluates valuation levels, core strengths, and potential risks, and offers data-driven recommendations on what to watch. All analysis is presented in intuitive tables and plain, easy-to-understand language, turning complex accounting terms into concrete investment logic. Whether for daily review or deep research, it helps you quickly zero in on the core issue amid massive amounts of data, improving the efficiency and accuracy of your investment decisions.
ResearchMulti-Agent: A-Share Pick & IC
It's not an AI assistant, but a virtual investment research team. Common AI stock-picking tools suffer from three problems: fabricating financial figures and target prices, giving vague "bullish/bearish" remarks, and offering "buy" recommendations without clear reasoning. The Multi-Agent Investment Research Team tackles these with a three-pronged approach: 6 parallel roles, cross-validation, and mandatory source attribution. It convenes researchers, fundamental analysts, technical analysts, sentiment analysts, risk officers, and investment managers to work in parallel, deliberating like a real investment committee. What you get is not fuzzy opinions, but a professional research document with facts, signals, disagreements, risks, and every number traceable to its source. Two modes covering "researching a single stock" and "screening a batch of stocks" Mode A: Single-Stock Committee Deep Analysis — Just provide a stock (e.g., "Analyze BYD 002594"), and the skill automatically convenes a full investment committee: the researcher aggregates market data, financial reports, research reports, and industry chain positioning, presenting only objective facts; the fundamental analyst issues a financial health scorecard, key changes in the three financial statements, and PEG valuation; the technical analyst evaluates trends, moving averages, MACD, support and resistance levels, and provides a five-point buy signal hit table; the sentiment analyst scans institutional divergence, retail investor sentiment, and potential misinterpretations; the risk officer digs up counter-evidence, systematically refuting optimistic conclusions from other roles; finally, the investment manager, without adding new data, integrates everything to produce committee minutes and a one-page summary. Mode B: Multi-Condition Stock Screening — From a specified universe (e.g., CSI 300, a sector/theme basket, or your own stock pool), apply a three-layer funnel: L1 financial hard screen (three consecutive quarters of growth, ample cash flow, PEG<1 or huge increase in contract liabilities), L2 technical timing (base breakout, moving average golden cross, volume breakout, strong pullback on low volume, MACD crossing above zero line), L3 information validation (research report ratings and industry chain logic, eliminating "pure technical without fundamental basis" picks). After obtaining a candidate list, the top N stocks can automatically proceed to Mode A for deep analysis. What you will get Mode A delivers a fixed "five-piece set": ① Full analysis report integrating all six roles; ② Data source and evidence table, with each key conclusion mapped to "data → source → date"; ③ Meeting-style committee minutes (agenda → each role's view → disagreements → consensus → variables to track); ④ Risk list sorted by high/medium/low severity; ⑤ One-page investment manager summary condensing core logic, key variables, verification points, and confidence level. Mode B delivers: Candidate stock list table (ticker | name | triggered conditions | key data | source | trigger date) plus screening criteria and methodology description, optionally with the full five-piece set for top candidates. All outputs are saved as files with ticker and date in the filename for easy reuse and archiving.
Self-Evolving A-Share Rotation
This skill provides A-share investors with a comprehensive strategy management and evolution platform, helping you systematically execute, validate, and optimize your trading strategies. It can intelligently adjust your monthly rebalancing strategy based on market conditions, and through rigorous backtesting, continuously evaluate strategy performance and provide in-depth diagnostics to ensure your investment approach stays in sync with the market. Using real-time market data analysis, this skill accurately identifies the current market environment (such as trending, range-bound, or bear markets) and applies preset parameter sets for stock screening. It employs a multi-layer funnel approach, starting with fundamental hard metrics to technical timing, then rigorous individual stock value analysis, and actively seeks counterevidence to avoid blind decisions. Ultimately, you receive an auditable candidate stock list, each with detailed rule-hit explanations, ensuring transparent and traceable decisions. Beyond strategy execution, this skill also offers powerful strategy validation and evolution capabilities. It automatically tracks and backfills your trading signal performance, generating detailed strategy health reports including win rate, profit/loss ratio, and excess returns over the CSI 300. When a strategy underperforms, it intelligently triggers evolution suggestions, performs attribution diagnostics to identify problematic rules, and supports parameter adjustments after paper trading validation to continuously refine your investment strategy. Notably, after each strategy execution or validation, this skill scans US, Hong Kong, and A-share markets to provide 'cross-market high expected value opportunities' with structural advantages. These opportunities are based on a rigorous expected value framework and come with clear entry, stop-loss, target, and position suggestions, but are not automatically written to your trading log. They serve as decision support references, helping broaden your investment perspective.
Investment Analysis Assistant
Description
This is a highly structured, multi-dimensional, cross-asset analysis framework that emphasizes 'meta-thinking.' Its core features include layered decomposition and narrative integration, distinguishing between 'direction variables' that determine medium-to-long-term trends and 'rhythm variables' that affect fluctuations. It deeply incorporates Robert Shiller's 'narrative economics' to analyze the spread of market sentiment and stories. The framework requires analysts not only to provide conclusions but also to reveal the judgment logic, verification criteria, and potential misjudgments behind them. The ultimate goal is not to make decisions for you but to help you gradually internalize this transferable analysis method through each analysis, ultimately forming your own independent and systematic investment analysis capability.
Related Skills
View allStock Report Analyzer
Financial reports are a listed company's "physical exam report", but most investors feel lost when faced with pages of dense numbers: • 📝 Can't read the three financial statements — What do the balance sheet, income statement, and cash flow statement tell you? Which numbers matter most? • 🤔 Don't know what to look at — With dozens of pages, which key metrics should you focus on? • 📊 Lack an analysis framework — Even when you find the data, how do you judge good from bad and cross-check it? • 🏭 Industry standards differ — What counts as "good" varies completely by industry; manufacturing and internet companies can't be measured with the same yardstick. • ⏰ Time cost is too high — Manually looking up data, comparing peers, and calculating growth rates can take hours for one report. This skill was built to solve exactly these problems. It automates a professional financial analyst's framework, so you just need to enter a stock code to get a structured, logical, and beginner-friendly financial report interpretation. The tool's core value lies in its rigorous analysis framework, covering multiple dimensions from assessing growth quality to analyzing business models. It not only compares core metrics like revenue, gross margin, net margin, and cash flow, but also runs a quick Q&A on the seven key financial questions investors care about most. It clearly shows whether profits are turning into real cash, and whether receivables and inventory carry potential risks. By benchmarking against industry leaders, it helps you identify a company's true position in its industry chain. When generating the report, it also evaluates valuation levels, core strengths, and potential risks, and offers data-driven recommendations on what to watch. All analysis is presented in intuitive tables and plain, easy-to-understand language, turning complex accounting terms into concrete investment logic. Whether for daily review or deep research, it helps you quickly zero in on the core issue amid massive amounts of data, improving the efficiency and accuracy of your investment decisions.
ResearchMulti-Agent: A-Share Pick & IC
It's not an AI assistant, but a virtual investment research team. Common AI stock-picking tools suffer from three problems: fabricating financial figures and target prices, giving vague "bullish/bearish" remarks, and offering "buy" recommendations without clear reasoning. The Multi-Agent Investment Research Team tackles these with a three-pronged approach: 6 parallel roles, cross-validation, and mandatory source attribution. It convenes researchers, fundamental analysts, technical analysts, sentiment analysts, risk officers, and investment managers to work in parallel, deliberating like a real investment committee. What you get is not fuzzy opinions, but a professional research document with facts, signals, disagreements, risks, and every number traceable to its source. Two modes covering "researching a single stock" and "screening a batch of stocks" Mode A: Single-Stock Committee Deep Analysis — Just provide a stock (e.g., "Analyze BYD 002594"), and the skill automatically convenes a full investment committee: the researcher aggregates market data, financial reports, research reports, and industry chain positioning, presenting only objective facts; the fundamental analyst issues a financial health scorecard, key changes in the three financial statements, and PEG valuation; the technical analyst evaluates trends, moving averages, MACD, support and resistance levels, and provides a five-point buy signal hit table; the sentiment analyst scans institutional divergence, retail investor sentiment, and potential misinterpretations; the risk officer digs up counter-evidence, systematically refuting optimistic conclusions from other roles; finally, the investment manager, without adding new data, integrates everything to produce committee minutes and a one-page summary. Mode B: Multi-Condition Stock Screening — From a specified universe (e.g., CSI 300, a sector/theme basket, or your own stock pool), apply a three-layer funnel: L1 financial hard screen (three consecutive quarters of growth, ample cash flow, PEG<1 or huge increase in contract liabilities), L2 technical timing (base breakout, moving average golden cross, volume breakout, strong pullback on low volume, MACD crossing above zero line), L3 information validation (research report ratings and industry chain logic, eliminating "pure technical without fundamental basis" picks). After obtaining a candidate list, the top N stocks can automatically proceed to Mode A for deep analysis. What you will get Mode A delivers a fixed "five-piece set": ① Full analysis report integrating all six roles; ② Data source and evidence table, with each key conclusion mapped to "data → source → date"; ③ Meeting-style committee minutes (agenda → each role's view → disagreements → consensus → variables to track); ④ Risk list sorted by high/medium/low severity; ⑤ One-page investment manager summary condensing core logic, key variables, verification points, and confidence level. Mode B delivers: Candidate stock list table (ticker | name | triggered conditions | key data | source | trigger date) plus screening criteria and methodology description, optionally with the full five-piece set for top candidates. All outputs are saved as files with ticker and date in the filename for easy reuse and archiving.
Self-Evolving A-Share Rotation
This skill provides A-share investors with a comprehensive strategy management and evolution platform, helping you systematically execute, validate, and optimize your trading strategies. It can intelligently adjust your monthly rebalancing strategy based on market conditions, and through rigorous backtesting, continuously evaluate strategy performance and provide in-depth diagnostics to ensure your investment approach stays in sync with the market. Using real-time market data analysis, this skill accurately identifies the current market environment (such as trending, range-bound, or bear markets) and applies preset parameter sets for stock screening. It employs a multi-layer funnel approach, starting with fundamental hard metrics to technical timing, then rigorous individual stock value analysis, and actively seeks counterevidence to avoid blind decisions. Ultimately, you receive an auditable candidate stock list, each with detailed rule-hit explanations, ensuring transparent and traceable decisions. Beyond strategy execution, this skill also offers powerful strategy validation and evolution capabilities. It automatically tracks and backfills your trading signal performance, generating detailed strategy health reports including win rate, profit/loss ratio, and excess returns over the CSI 300. When a strategy underperforms, it intelligently triggers evolution suggestions, performs attribution diagnostics to identify problematic rules, and supports parameter adjustments after paper trading validation to continuously refine your investment strategy. Notably, after each strategy execution or validation, this skill scans US, Hong Kong, and A-share markets to provide 'cross-market high expected value opportunities' with structural advantages. These opportunities are based on a rigorous expected value framework and come with clear entry, stop-loss, target, and position suggestions, but are not automatically written to your trading log. They serve as decision support references, helping broaden your investment perspective.
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