SPDR S&P 500 ETF

6m ahead

Predictive Factors

The engine identifies what we call the causally predictive factors: a small set of assets judged to be the most important driving forces behind your selected item's forecast.

Microsoft

Nvidia Corporation

China / U.S. Foreign Exchange Rate USDCNY

SPDR S&P Midcap 400 ETF Trust

Intel

as of Thu 2023-12-14 UTC

Our Probabilistic Prediction

Based on the predictive features above, we run many models repeatedly, each predicting a set of possible outcomes for the date in 6m and aggregate them.

Goodness of Probabilistic Prediction

Test of hypothesis that a sample of the realised probability level is uniformly distributed between 0 and 1 (whitepaper), using significance level 0.001 for the p-value. The user is free to use another significance level e.g. 0.01, 0.05 for the test.

SPDR S&P 500 ETF

🟢 p-value: 0.014 > 0.001

Each model casts a single vote on the likely direction of change. If one actually makes trades, a trade will be opened every day with the size in number of shares/lots proportional to the majority vote and kept open for 6m. The currently open trades result in the position for the next end-of-day time point (when the market is open),

	% Up	% Down	% Undecided
SPDR S&P 500 ETF	77%	6%	17%

with respect to the following time points,

	Time	Value
SPDR S&P 500 ETF	Thu 2023-12-14 UTC	472.01

Performance of Past Trades

The overall profit and loss of the trades opened in the above manner, in contrast to the buy-and-hold strategy of one constant share, would have been as plotted below. The Sharpe ratio is calculated on returns measured as the difference between values rather than in percentage, assuming zero trading cost.

SPDR S&P 500 ETF

	Active	Buy-and-Hold
Sharpe ratio (the higher the better)	1.5	1.3
Solvency II Value-at-Risk 99.5% (the lower the better)	-	-