'trading' 검색 결과

Build Python integrations with crypto exchanges using CCXT. Get guidance on fetching prices and order books, placing orders, checking balances, and receiving live updates, with examples for authentication, error handling, and synchronous or asynchronous code.

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• Fetch exchange data for analysis
• Implement order placement in a trading bot
• Monitor live prices and order books

Use an authenticated command-line tool to work with Binance spot trading, futures, and asset conversion. The skill provides command references for these tasks, alongside wallet operations and other Binance services.

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• Work with Binance spot and futures trading
• Convert crypto assets through Binance Convert
• Find commands for wallet and account operations

Use natural language to compare Binance P2P offers, prices, and payment methods. Review personal orders and dispute progress, submit evidence for existing appeals, and manage advertisements when the account has the required merchant permissions.

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• Compare P2P offers by payment method
• Review personal order history and details
• Track appeals and submit supporting evidence

Assess stock, index, or currency options by comparing expected price variability implied by option prices with actual historical variability. Summarize pricing, risk sensitivities, and patterns across expiry dates and exercise prices to inform strategy choices.

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• Comparing implied and historical volatility
• Examining volatility across expiries and exercise prices
• Reviewing option prices and risk sensitivities

Analyze price differences between bond futures and cash bonds, identify the cheapest bond to deliver, and compare implied financing rates with market rates. Present valuation tables and historical context to assess potential basis trades.

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• Comparing bond futures with cash bond prices
• Identifying the cheapest bond to deliver
• Comparing implied financing rates with market rates

Generate trading signals from historical volatility, a measure of past price fluctuations. Rank its current level against recent history, signal long positions at low levels, and exit or short at high levels while retaining positions between thresholds.

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• Build signals from historical volatility levels
• Adjust calculation windows and percentile thresholds
• Set annualization for cryptocurrency data

Retrieve price and trading volume data for US, Hong Kong, and Canadian stocks, ETFs, and indices through Yahoo Finance. Also gather company profiles, financial statements, dividends, and ownership data for market research and historical strategy testing.

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• Collect historical prices across several stock markets
• Review company financial statements and ownership
• Check dividend and stock split histories

Assess market sentiment using fear and greed measures, options activity, margin trading, foreign investment flows, and social media discussion. Combine indicators on a common scale to produce a dashboard and explain signs of excessive optimism or fear.

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• Create a market sentiment dashboard
• Compare Put-Call Ratio with VIX
• Review Chinese A-share margin activity and foreign investment flows

Provides guidance for retrieving China A-share prices and trading volumes through the TDX protocol. The source is currently retired from automatic routing because servers stopped responding, with explicit selection retained for possible future recovery.

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• Reviewing the retired data source and its limitations
• Checking daily and intraday data retrieval methods
• Understanding ticker formats and output columns

Retrieve cryptocurrency prices, candlesticks, order books, funding rates, and open interest from OKX’s public API. Use spot, derivatives, and index data for market research without registering an account or configuring authentication.

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• Checking cryptocurrency prices and trading volume
• Retrieving historical candlestick data
• Examining funding rates and open interest

Collect financial discussions from Twitter/X, Telegram, Discord, and Reddit, then measure sentiment and discussion volume. Use the resulting data to study market attention, distinguish author groups, and test whether social signals relate to future returns.

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• Compare bullish and bearish sentiment around a stock
• Detect unusual increases in discussion volume
• Track discussion in crypto project communities

Manage multi-step financial research with a clear objective, acceptance criteria, and linked evidence. Track findings across turns, audit whether each criterion is supported, and report unresolved gaps while keeping the workflow limited to research.

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• Compare strategies or assets against shared criteria
• Review the evidence supporting an investment thesis
• Resume a research task across multiple turns

Analyze crypto perpetual futures funding payments and spot–futures price differences to assess carry trades. Compare exchanges, identify crowded positions, and summarize potential returns alongside risks such as funding reversals and liquidation.

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• Compare funding rates across crypto exchanges
• Estimate annualized spot–futures price differences
• Assess carry trade returns and risks

Finds and retrieves paid financial datasets when free sources lack coverage or detail. Guides comparison of providers, success rates, prices, and required inputs, while keeping execution costs and remaining credits visible.

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• Finding financial data missing from free sources
• Comparing paid providers by cost and success rate
• Checking parameters before a paid data request

Analyze public blockchain records to assess crypto market conditions. Combine network activity, large-holder transfers, decentralized finance liquidity, and valuation measures into a report with indicator comparisons, a composite score, and an interpretation of market signals.

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• Compare blockchain activity with price trends
• Examine large-holder transfers and exchange flows
• Review funds held in decentralized finance and trading liquidity

Turn stock, industry, strategy, or backtest research into structured Markdown reports. Present conclusions, supporting data, ratings, risks, and recommendations using consistent tables and terminology, with PDF delivery supported through the specified rendering tool.

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• Write a detailed stock research report
• Organize an industry or market outlook
• Report results from tests on historical trading data

Explain portfolio performance by separating the effects of sector allocation, stock selection, market factors, and timing. Compare results with a benchmark, assess risk-adjusted returns, and prepare a report showing where excess returns came from.

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• Explaining returns above or below a benchmark
• Separating sector allocation and stock-selection effects
• Assessing market exposure and trading timing

Use CCXT, a library with a common interface for over 100 cryptocurrency exchanges, to retrieve historical prices and volumes, current quotes, order books, and recent trades. Public market data requires no API key.

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• Collecting historical prices and volumes for analysis
• Fetching current quotes for multiple trading pairs
• Inspecting order books and recent trades

Analyze bid–ask spreads, order books, and buying and selling imbalances to assess liquidity, or how easily an asset trades. Estimate large-order price impact and transaction costs, with additional guidance on Chinese A-share auction and block trades.

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• Estimate transaction costs for large orders
• Assess liquidity using order book depth and spreads
• Study trading imbalances and signs of liquidity stress

Compare company earnings forecasts with analyst consensus, the market’s shared estimate. Assess earnings surprises and changes in analyst expectations, then organize signals and supporting assumptions for trading research and historical testing.

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• Compare earnings forecasts with analyst consensus
• Measure earnings surprises after results
• Track upward and downward analyst revisions

Write signal generation code for backtests combining stocks, crypto, forex, and other markets. Apply market-specific indicator settings and volatility-adjusted weights, while the existing CompositeEngine handles trading calendars, shared capital, and each market's rules.

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• Building a backtest combining stocks and crypto
• Applying different indicator settings to each market
• Adjusting portfolio weights for differences in volatility

Use investor psychology to examine trading signals and risk controls, especially in China A-shares. The skill provides sentiment measures, checklists for biased decisions, and frameworks for assessing momentum, which follows trends, and reversal strategies.

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• Reviewing market optimism and fear
• Examining momentum and reversal strategies
• Checking investment decisions for cognitive biases

Diagnose failed or abnormal backtests, which test trading strategies on historical data. Inspect result files, strategy code, and configuration to identify bugs, make targeted repairs, rerun tests, and verify the updated metrics.

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• Investigating backtest execution errors
• Finding why a strategy produces no trades
• Checking delayed trades or low capital usage

Analyze crypto derivatives for research and backtesting using perpetual funding payments, futures prices across expiry dates, and options volatility. Organize market metrics, compare strategy candidates, and outline risks such as margin shortages, funding reversals, and exchange failures.

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• Researching funding-rate arbitrage
• Comparing futures prices across expiry dates
• Analyzing options volatility and price sensitivity