「investment」の検索結果

スタンレー・ドラッケンミラーの投資哲学と戦略に基づいた投資アドバイスを提供。30年間無敗、年率30%近いリターンを達成した伝説的投資家の思考法を活用し、マクロ経済分析、リスク管理、ポジション構築、市場サイクルの読み方などについて実践的な指導を行う。投資判断、市場分析、リスク管理、ポートフォリオ構築などの相談時に使用。

Track and analyze cross-border capital flows between mainland China and Hong Kong via Stock Connect (沪港通/深港通). Monitor northbound (北向资金) and southbound (南向资金) flows, identify trending stocks, and analyze institutional positioning. Use when user asks about 北向资金, 南向资金, 外资动向, Stock Connect flows, or cross-border investment trends.

日本語の概要は準備中です。原文の説明を表示しています。

Use when preparing executive reports, evaluating investments, or calculating ROI/break-even/payback period. 30-minute analysis (87.5% time saving). Includes scenario analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze China macroeconomic data, PBOC monetary policy, fiscal policy, and their impact on A-share and HK stock markets. Track GDP, CPI, PPI, PMI, social financing, and interpret policy signals. Use when user asks about 中国宏观经济, 央行政策, economic data impact on markets, or needs to understand policy implications for investment.

日本語の概要は準備中です。原文の説明を表示しています。

Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.

日本語の概要は準備中です。原文の説明を表示しています。

Populates investment banking pitch deck templates with data from source files. Use when: user provides a PowerPoint template to fill in, user has source data (Excel/CSV) to populate into slides, user mentions populating or filling a pitch deck template, or user needs to transfer data into existing slide layouts. Not for creating presentations from scratch.

日本語の概要は準備中です。原文の説明を表示しています。

Generate professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise single-company financial summary. This skill supports four audience types: equity research, investment banking/M&A, corporate development, and sales/business development. If the user doesn't specify an audience, ask. Works for both public and private companies.

日本語の概要は準備中です。原文の説明を表示しています。

Creates professional investment banking strip profiles (company profiles) for pitch books, deal materials, and client presentations. Generates 1-4 information-dense slides with quadrant layouts, charts, and tables.

日本語の概要は準備中です。原文の説明を表示しています。

Dividend Discount Model, DDM valuation, multi-stage dividend model, Gordon Growth Model, dividend growth valuation, mature company valuation, income stock valuation, dividend yield analysis

日本語の概要は準備中です。原文の説明を表示しています。

position sizing, Kelly criterion, risk budgeting, volatility targeting, portfolio allocation, bet sizing, capital allocation, drawdown management, position management, risk parity sizing

日本語の概要は準備中です。原文の説明を表示しています。

long short equity strategy, pair trade construction, market neutral portfolio, net exposure management, factor neutrality, equity long short, hedge fund strategy, alpha generation, stock picking portfolio construction, long short position management

日本語の概要は準備中です。原文の説明を表示しています。

Long short portfolio construction, market neutral positioning, factor-balanced book, gross and net exposure management, pair selection, beta hedging, portfolio construction methodology

日本語の概要は準備中です。原文の説明を表示しています。

Technical execution timing, entry exit signals, price action analysis, volume profile, market structure, support resistance levels, trend identification, Wyckoff method, auction market theory, trade management timing, position entry exit optimization

日本語の概要は準備中です。原文の説明を表示しています。

Options price action strategy, volatility-aware entries, options structure selection by market regime, delta and gamma positioning, options overlay on directional views, expiry selection

日本語の概要は準備中です。原文の説明を表示しています。

portfolio hedging, tail risk hedging, options overlay, correlation regime, downside protection, portfolio insurance, risk mitigation strategy, hedge construction, black swan hedging, volatility hedging

日本語の概要は準備中です。原文の説明を表示しています。

Options trade execution, directional strategies long call covered call collar, spread strategies bull call bear put ratio ladder, volatility strategies straddle strangle strap strip, liquidity cost and implied volatility filters, integration with gold.technical_setups for options setup matching

日本語の概要は準備中です。原文の説明を表示しています。

Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step sequence, wedges, double tops and bottoms, triangles, head and shoulders, climaxes, measured moves, support and resistance

日本語の概要は準備中です。原文の説明を表示しています。

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.

日本語の概要は準備中です。原文の説明を表示しています。

Append-only gap closure and the cadence engine for research theses. Evaluates artifact CURRENT state (never git history, never task checkboxes) against current pins and wrong_if falsifiers, then appends a Convergence section to tasks.md re-proposing the gaps. A clean run leaves tasks.md byte-identical. Deterministic gaps (stale, invalidated) are uncapped; judgment-class gaps are capped per spec 046 Q40.

日本語の概要は準備中です。原文の説明を表示しています。

Adversarial verification of research theses — cross-run/cross-thesis contradiction via the entity index, pre-mortem (Klarman/Kahneman: assume the loss already happened, reverse the path), inversion (Munger: invert, always invert), and wrong_if falsifiability review. ≈50-finding cap sorted by severity; content-derived finding IDs; incremental scoping with three backstops; lifecycle hooks at pillar-complete / thesis-complete / pre-reduction.

日本語の概要は準備中です。原文の説明を表示しています。

Residual Income valuation, EVA Economic Value Added, excess return valuation, book value plus economic profit, financial institution valuation, bank valuation, insurance company valuation

日本語の概要は準備中です。原文の説明を表示しています。

The research-domain clarification skill — find underspecified items in a thesis spec.md (prose wrong_if, universe rows without rationale, missing budget/expiry/pins, ambiguous pillars), ask the human structured questions WITH options (max 5 per round), encode the answers back into spec.md's Clarifications section, and re-evaluate checklists/thesis-quality.md after every write (Q32 bidirectional maintenance).

日本語の概要は準備中です。原文の説明を表示しています。

Decompose the plan into research tasks — one task per ticker × skill × mode, grouped by pillar, [P]-marked by the different-files-and-no-incomplete-deps rule, with source-refs. mode: all expands to N tasks at generation, never exists as one task (Q79).

日本語の概要は準備中です。原文の説明を表示しています。