Planning, sales, accounting, legal, and project management (3.9K skills)
Evaluate companies using projected cash flows, dividends, business segments, and comparisons with peers. Select suitable valuation methods, examine how assumptions change estimated value, and check for problems that can make a seemingly cheap stock misleading.
Analyze scheduled token releases, their recipients, and trading volume to estimate potential selling pressure. Review project treasury holdings, operating runway, and token supply growth to assess funding sustainability and the effect of dilution on staking yields.
Analyze the volatility implied by option prices across strike prices and expiration dates. Compare calendar spreads and other volatility strategies, then assess portfolio risk using Greeks, measures of how option values respond to market changes.
Research private companies through six perspectives, including business, finances, competition, and technology. Cross-check evidence, separate facts from inferences, and produce a valuation range, possible exit routes, and a map of missing information.
Turn news, company announcements, and policy events into scored trading inputs. Store assessments in a standard CSV file, reduce their influence over time, and combine them with signals from price indicators to support event-based strategy testing.
Analyze income statements, balance sheets, and cash flow statements together to assess earnings quality. Break down return on equity into its drivers, compare profits with operating cash flow, and organize warning signs that warrant closer accounting review.
Evaluate dividend stocks by checking earnings, cash flow, debt, and dividend history. Assess whether payouts can last, identify high yields driven by falling prices, and consider total returns alongside dividend income.
Recognize classic candlestick patterns using pandas, a Python library for tabular data. Combine bullish and bearish pattern scores into long, short, or stand-aside signals, with adjustable thresholds for candle bodies and shadows.
Retrieve minute-level price data for stocks and cryptocurrencies, calculate average prices and volume patterns, and test intraday trading strategies. Configure the candle interval and trading costs to examine results using historical market data.
Analyze price swings to detect Elliott Wave structures: five waves following a trend and three waves correcting it. Check wave rules and Fibonacci ratios, then generate signals for completed advances or pullbacks using a pandas implementation.
Design research plans to protect existing investments using futures, ETFs, options, or other assets. Compare hedge sizes, estimated costs, and potential gains or losses under different market scenarios, with guidance on monitoring and adjustments.
Generate trading signals using Ichimoku Kinko Hyo, a five-line chart framework. Combine conversion-line and base-line crossovers with price position and cloud direction to classify conditions as long, short, or stand aside using pandas.
Break down major industrial trends into materials, components, and equipment to find listed suppliers at supply bottlenecks. Compare scarcity, financial performance, and valuation, then organize candidates into a ranked research board with supporting evidence and risks.
Analyze bond prices, yields, and issuers’ ability to repay debt. The skill covers interest rate exposure, default risk models, yield spreads, Chinese local government financing platform bonds, and securities backed by pools of loans.
Analyze cross-border stock flows between mainland China and Hong Kong through Stock Connect. Compare overseas buying of mainland shares, mainland buying of Hong Kong shares, sector allocations, and price gaps between dual-listed shares.
Model trading costs and execution assumptions in backtests, including slippage, the gap between expected and simulated fill prices. Compare price impact, fees, execution delays, and order splitting to assess how assumptions affect strategy results.
Analyze US public company filings to summarize financial health, management commentary, changing risks, insider trades, and institutional holdings. Combine these findings into a structured research report with scores and investment implications.
Analyze crude oil, gold, and copper using supply and demand, inventories, futures prices, and seasonal patterns. Combine these factors with macroeconomic conditions to produce research reports showing market direction, confidence, and specific risks.
Screen Chinese A-shares, Hong Kong stocks, and US stocks using valuation ratios, profitability, and financial statement data. Set criteria to identify value or growth candidates, with market-specific guidance on using the results in historical strategy tests.
Assess a company’s management through public statements, delivered commitments, crisis decisions, and use of company funds. Produce evidence-based scores for integrity, strategy, capital allocation, and governance, alongside a verdict on long-term trust.
Apply 12 structured investing frameworks to evidence already collected. Each framework orders the questions to ask, defines reasons to reject a case, and identifies its limitations, helping explain why different approaches reach different conclusions.
Assess whether a Chinese A-share company may receive ST or *ST risk warnings next financial year. Review financial forecasts, dividends, audit opinions, and regulatory penalties, then report risk severity separately from confidence in the prediction.
Analyze candlestick data using Chan theory, a method based on price structure. Detect turning points, movement segments, and overlapping price zones, then generate buy and sell signals and compare patterns across timeframes.
Detect five-point price patterns using Fibonacci ratios and generate buy, sell, or stand-aside signals. The skill identifies Gartley, Bat, Butterfly, and Crab patterns and locates potential reversal zones, where a price trend may change direction.