Explore the assumptions behind a sector shock
What does this scenario calculate, and what evidence would support a real market forecast?
This is an authored sensitivity exercise with four sector rows and fixed coefficients. It does not retrieve prices, establish that a headline caused a market decline, calculate the Cboe VIX or optimize an investment allocation. Use its controls to inspect how assumptions change arithmetic, then compare that model with identified financial data.
The headline and source attribution have not been matched to a dated report. Sector beta and sentiment values are fixtures without an observation window or estimation dataset. Output percentages have no confidence intervals, backtest or causal evidence. The index and defensive-shift numbers are illustrative formula outputs, not market measurements or recommendations.
Try a worked example
At 12 months and −0.65 sentiment, the default weights 35/25/20/20 produce −4.25% composite impact. The derived index is round(14.5 + 4.25 × 1.6235294, 1) = 21.4. The derived shift is round(4.25 × 3.5294117, 1) = 15.0%. The fixed allocation preset changes weights to 25/20/20/35; it produces −2.99%, 19.4 and +10.6% at those same inputs. The preset moves utilities by 15 percentage points even though the derived shift then reads 10.6%; it does not execute the displayed shift or solve an optimization problem.
Trace the weighted calculation
Each sector return is its stored beta times its stored sentiment times 100 times 0.06884067 times months/12 times global sentiment/−0.65, rounded to two decimals. The composite adds weight/100 times those rounded returns. The timeline presets change months, leaving weights and global sentiment in place.
The weights can sum below or above 100%; the model flags the total but neither normalizes it nor supplies cash, borrowing or financing costs. A zero total produces zero composite impact, the index baseline 14.5 and zero shift. Positive global sentiment reverses every row's sign. The absolute-impact formulas then increase the index and shift even when the composite is positive.
Distinguish the real VIX methodology
Cboe describes VIX as a measure of 30-day expected market volatility derived from SPX option prices. This page reads no option chain and instead maps absolute composite impact to a fixed baseline. Its legacy projected_volatility_index field is a toy index, even when its stored string includes VIX. Cboe: volatility index methodology overview
A convincing forecast would identify the target quantity, input data and dates, estimation method, calibration sample and evaluation outside that sample. Matching one chosen default output does not demonstrate predictive accuracy. A 1–36-month linear multiplier also does not establish a 30-day implied-volatility model.
Treat allocation changes as assumptions
Investor.gov describes allocation, diversification and rebalancing in relation to investment goals and risk tolerance. This tool supplies four fixed sector coefficients and one fixed allocation preset; it has no covariance matrix, objective function, constraints, taxes or transaction costs. It cannot establish an optimal portfolio for a person. Investor.gov: allocation and diversification
The bars visualize stored sector returns; the allocation chart shows chosen weights. Neither is a historical price series. JSON captures inputs, results and sector rows; CSV summarizes the rows and outputs. Exports are scenario notes, not a Bloomberg report or trading instruction. Reset restores the original assumptions, and no import or saved portfolio is provided.
Sources and further reading