Natural Language Processing News Trade

Entry Logic

• Long entry is triggered when an NLP model identifies a positive news story about a company (e.g., a new product launch, a positive earnings surprise).
• Short entry is triggered by a negative news story (e.g., a product recall, a regulatory investigation).
• Confirmation requires a spike in trading volume.
• Timeframe is short-term (e.g., 1-minute to 15-minute chart).
• Location context is not the primary driver.
• Market condition is a news-driven environment.

Exit Logic

• Profit target is a fixed percentage gain or when the initial news-driven momentum fades.
• No scaling out.
• Trailing stop is used to lock in profits.
• Exit on signal failure if the price does not react to the news.
• Exit on opposite signal is not applicable.
• Exit on time expiration after a short holding period.
• Exit on momentum loss.

Stop Loss Structure

• Hard stop is placed at a level that invalidates the trade idea.
• Soft stop is not used.
• Maximum dollar loss is defined per trade.
• Maximum percent loss is a set percentage of the account.
• Structural stop is based on the initial price action.

Risk Management Framework

• Risk per trade is a fixed percentage of the account.
• Maximum daily and weekly loss limits are enforced.
• Maximum drawdown is monitored.
• Risk-reward ratio is based on historical performance.

Position Sizing Model

• Sizing is fixed fractional.
• Volatility adjustment is used to account for the increased volatility around news events.
• Conviction sizing is based on the significance of the news story.
• No scaling in.
• No scaling out.

Trade Filtering

• Filter out minor news stories.
• Avoid trading in illiquid stocks.
• Instrument selection is based on which companies are in the news.
• Time of day restrictions apply, as most news is released outside of market hours.
• Be aware of the risk of trading on news, which can be unpredictable.

Context Framework

• The news story provides the primary context.
• The reaction of the price to the news is the key confirmation signal.
• Higher timeframe context is less relevant in this short-term strategy.

Trade Management Rules

• Be prepared for fast and volatile price movements.
• Use limit orders to control entry and exit prices.
• Do not chase the price if you miss the initial move.

Time Rules

• Optimal trading window is immediately after the news is released.
• Avoid trading long after the news has been digested by the market.
• Session-specific patterns can be identified based on when news is typically released.

Setup Classification

• A+ setup: Major news story with a strong price reaction and high volume.
• A setup: Significant news story with a clear price reaction.
• B setup: Minor news story with a muted price reaction.
• C setup: No clear news or price reaction (avoid).

Market Selection Criteria

• Instruments are stocks of companies that are frequently in the news.
• High liquidity and tight spreads are essential.
• The stock should have a history of reacting to news.

Statistical Edge Metrics

• Metrics are derived from backtesting the NLP news trading model.

Failure Conditions

• The market may not react to the news as expected.
• The news may already be priced in.
• The NLP model may misinterpret the news.

Psychological Rules

• Act quickly and decisively when a news-based opportunity arises.
• Avoid getting caught up in the hype and stick to the trading plan.
• Be prepared for the high level of risk involved in news trading.

Advanced Components

• Advanced NLP techniques are used to extract information from news articles.
• Machine learning models can be trained to predict the market's reaction to news.
• The strategy can be automated to trade on news in real-time.

Location

• The strategy is most effective in markets where news plays a significant role in price discovery.
• It may be less effective in more technically-driven markets.
• The speed and accuracy of the news feed and NLP model are critical.