MARKET SENTIMENT AND VOLATILITY FORECASTING - Prompt¶
Cross-Asset Volatility and Sentiment Forecasting: A Multi-Modal Analysis¶
Datasets¶
Below are multiple micro datasets provided in markdown format. They include structured tables, time-series data, and unstructured text meant to help you assess market sentiment, volatility drivers, and macroeconomic conditions. Note that some datasets (marked with DS) are included as potential distractions.
Dataset 1: Volatility Indices Data (Visual: Line Graph)
| Date | VIX (S&P 500) | MOVE (10Y Treasuries) | Implied Volatility - Brent (%) | Implied Volatility - Gold (%) |
|---|---|---|---|---|
| 2023-09-01 | 18.2 | 9.5 | 22.0 | 12.5 |
| 2023-09-08 | 19.0 | 10.0 | 22.5 | 12.8 |
| 2023-09-15 | 20.1 | 10.2 | 23.0 | 13.0 |
| 2023-09-22 | 21.0 | 10.5 | 23.8 | 13.5 |
| 2023-09-29 | 20.5 | 10.3 | 23.2 | 13.2 |
| 2023-10-06 | 22.0 | 10.7 | 24.0 | 13.8 |
| 2023-10-13 | 22.5 | 11.0 | 24.5 | 14.0 |
Dataset 2: Market Sentiment Scores (Visual: Bar Chart)
| Date | Central Bank Sentiment (1-10) | Financial News Tone (1-10) | Reddit/Twitter Sentiment (1-10) |
|---|---|---|---|
| 2023-09-01 | 7 | 6 | 5 |
| 2023-09-08 | 6 | 5 | 4 |
| 2023-09-15 | 5 | 4 | 3 |
| 2023-09-22 | 4 | 3 | 2 |
| 2023-09-29 | 5 | 4 | 3 |
| 2023-10-06 | 6 | 5 | 4 |
| 2023-10-13 | 7 | 6 | 5 |
Dataset 3: Macroeconomic Indicators (Visual: Clustered Bar Chart)
| Date | CPI YoY (%) | PMI | NFP (in thousands) | Unemployment Rate (%) |
|---|---|---|---|---|
| 2023-09-01 | 2.1 | 55 | 150 | 4.0 |
| 2023-09-15 | 2.2 | 54 | 145 | 4.1 |
| 2023-09-29 | 2.3 | 53 | 140 | 4.2 |
| 2023-10-13 | 2.4 | 52 | 135 | 4.3 |
Dataset 4: Option Term Structure Data (Visual: Line Graph)
| Date | S&P 500 30d IV (%) | 10Y T-Note 30d IV (%) | Brent 30d IV (%) | Gold 30d IV (%) |
|---|---|---|---|---|
| 2023-09-01 | 18.0 | 10.0 | 22.0 | 12.5 |
| 2023-10-01 | 19.5 | 10.5 | 23.5 | 13.0 |
Dataset 5: News Headlines and Central Bank Statements (Unstructured Data)
- "Central Bank signals gradual tightening amid global uncertainty." (Date: 2023-10-05)
- "Financial news: Equity markets rally despite mixed earnings reports." (Date: 2023-10-06)
- "Breaking: New policy measures expected to cushion market headwinds." (Date: 2023-10-07)
- "Central Bank statement: 'We maintain cautious optimism despite rising inflation.'" (Date: 2023-10-08)
Dataset 6: ETF Flows and Institutional Positioning DS (Visual: Bar Chart)
| Date | ETF Flows (USD Millions) | Institutional Net Long (%) |
|---|---|---|
| 2023-09-01 | 500 | 55 |
| 2023-09-15 | 450 | 53 |
| 2023-09-29 | 520 | 56 |
| 2023-10-13 | 480 | 54 |
Dataset 7: Social Media Sentiment Aggregates (Visual: Scatter Plot)
| Date | Twitter Sentiment Score | Reddit Sentiment Score |
|---|---|---|
| 2023-09-01 | 5.0 | 4.8 |
| 2023-09-15 | 4.2 | 4.0 |
| 2023-09-29 | 3.5 | 3.4 |
| 2023-10-13 | 4.0 | 3.9 |
Dataset 8: Commodity Price Indexes (Visual: Line Graph)
| Date | Brent Crude Spot Price (USD/barrel) | Gold Spot Price (USD/oz) |
|---|---|---|
| 2023-09-01 | 85 | 1800 |
| 2023-09-15 | 88 | 1780 |
| 2023-09-29 | 90 | 1750 |
| 2023-10-13 | 92 | 1765 |
Dataset 9: Historical Asset Returns DS (Visual: Line Charts)
| Date Range | Asset Class | Average Daily Return (%) | Volatility (%) |
|---|---|---|---|
| 2023-07-01 to 2023-09-30 | Equities | 0.05 | 1.2 |
| 2023-07-01 to 2023-09-30 | Fixed Income | 0.02 | 0.8 |
Question¶
As a senior strategist at a global macro hedge fund, your objective is to deliver a high-conviction forecast for cross-asset volatility and market sentiment over the next 30 days. Based on the provided datasets, please:
- Classify the current market sentiment regime (e.g., risk-on, risk-off, or transitional) by integrating the sentiment scores from central bank communications, financial news tone, and social media data.
- Forecast the 30-day forward implied and realized volatility for the following asset classes:
- Equities (S&P 500 via VIX dynamics)
- Fixed Income (10Y Treasury via MOVE index)
- Commodities (Brent Crude and Gold)
- Identify and quantify the key drivers (e.g., macroeconomic indicators, option term structures, central bank statements) influencing the forecast and highlight any potential volatility clusters or contagion risks across asset classes.
- Recommend tactical hedging strategies (e.g., VIX calls, long gamma positions, or correlation dispersion trades) based on your forecast.
Instruction¶
Please include all intermediate calculations, working steps, and references to the appropriate datasets as evidence in your analysis. Begin your final answer with a brief executive summary that highlights the key findings and recommendations of your forecast. Be sure to illustrate your thought process and justify your conclusions using both quantitative data and qualitative insights drawn from the datasets.