What are women doing in extremely scarce intraday trading? 🔥
Pre-market preparation (5:30 AM - 9:00 AM)
Check the overnight trends of European and American markets, macroeconomic data (such as non-farm employment, CPI), and central bank policy changes to assess their impact on the market for the day.
Pay attention to breaking news (geopolitical conflicts, corporate mergers, black swan events), such as the impact of the Russia-Ukraine conflict on energy prices.
Based on positions and market predictions, set key support/resistance levels, stop-loss points, and target prices.
Communicate with the quantitative team about model signals and adjust algorithm parameters.
Case study: If holding a short position in Tesla, one needs to anticipate volatility risks arising from Musk's Twitter remarks or Federal Reserve interest rate decisions.
3. Technical checks and compliance confirmation
Test the stability of the trading system to ensure one-click ordering and risk control modules are functioning properly.
Review position limits and margin ratios to avoid triggering compliance red lines (such as MiFID II regulatory requirements).
Intra-day trading (9:00 AM - 4:00 PM)
Monitor and execute in real-time while observing multiple screens: market terminals (Bloomberg/Reuters), order book depth, and self-developed dashboards (such as VWAP algorithm tracking).
Quickly respond to market anomalies: for instance, if there’s a sudden flash crash in Nasdaq 100 futures at 10:15, determine whether it's a technical failure or a fundamental change.
Female advantage: Some studies indicate that women excel at multitasking, which helps in managing high-frequency information flow.
2. Risk management
Dynamically calculate VaR (Value at Risk), Greek letters (option Delta/Gamma), to prevent the portfolio from being overly exposed to a single risk factor.
Execute stop-loss strategies: for example, automatically close 50% of positions when S&P 500 futures drop below the 200-day moving average.
Post-market review (4:00 PM - 7:00 PM)
Dissect the sources of daily profit and loss: is it due to beta market fluctuations or alpha stock selection ability? For instance, in gold bullish profits, 70% comes from the decline of the dollar index, while 30% comes from risk aversion sentiment.
Use Python/Pandas to backtest strategies and identify overfitting issues.
Adjust models based on changes in market structure: for example, if the basis between Bitcoin futures and spot narrows, it may reduce arbitrage positions.
Participate in quantitative meetings to discuss the effectiveness of factors (such as whether the momentum factor has lost effectiveness in 2023).
Study reports (such as Goldman Sachs' commodity outlook) and academic papers.
Learn new tools: such as mastering on-chain data analysis of DeFi protocols.
