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Invesco Nasdaq-100 ETF

SPDR S&P 500 ETF

SPDR Dow Jones Industrial Average ETF

6m ahead

Predictive Factors

Causally predictive factors identified as the most influential for the values of the selected instruments at the time point 6m away:

iShares 7-10 Year Treasury Bond ETF

2025-01-19T16:59:55.112578 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/

Hong Kong / U.S. Foreign Exchange Rate USDHKD

2025-01-19T16:59:55.132652 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/

General Electric

2025-01-19T16:59:55.152584 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/

AT&T Inc

2025-01-19T16:59:55.172820 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/

Micron Technology, Inc. Common Stock

2025-01-19T16:59:55.193511 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/

as of

Our Probabilistic Prediction

We train models based on the identified causal predictors and run them, with each model predicting a set of possible outcomes for the time point 6m away. The sets of possible outcomes are then aggregated.

2025-01-19T16:59:56.529728 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
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.

Invesco Nasdaq-100 ETF

🟢 p-value: 0.011 > 0.001

2025-01-19T16:59:56.667738 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
2025-01-19T16:59:57.506532 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
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

2025-01-19T16:59:57.645908 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
2025-01-19T16:59:59.757782 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
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 Dow Jones Industrial Average ETF

🟢 p-value: 0.018 > 0.001

2025-01-19T16:59:59.905543 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/

Trades

Each model casts a single vote on the likely direction of change. If a trade is executed, the size, in terms of the number of shares or lots, is proportional to the majority vote, and the trade is kept open for the duration of the forecast horizon, which is 6m. This exercise is repeated every day.

The position for the next day, averaged over the sizes of currently opened trades, is as follows

% Up % Down % Un­de­cided
Invesco Nasdaq-100 ETF 65% 2% 33%
SPDR S&P 500 ETF 82% 0% 18%
SPDR Dow Jones Industrial Average ETF 95% 0% 5%

with respect to the time point respectively,

Time Value
Invesco Nasdaq-100 ETF Fri 2025-01-17 UTC 521.74
SPDR S&P 500 ETF Fri 2025-01-17 UTC 597.58
SPDR Dow Jones Industrial Average ETF Fri 2025-01-17 UTC 434.72

Performance of Past Trades

The Sharpe ratio is calculated on returns measured as the difference between values rather than in percentage, assuming zero trading cost.

Invesco Nasdaq-100 ETF
Active Buy-and-Hold
Sharpe ratio
(the higher the better)
1.53 1.53
Solvency II Value-at-Risk 99.5%
(the lower the better)
- -
2025-01-19T16:59:57.256142 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
SPDR S&P 500 ETF
Active Buy-and-Hold
Sharpe ratio
(the higher the better)
1.58 1.53
Solvency II Value-at-Risk 99.5%
(the lower the better)
- -
2025-01-19T16:59:58.331676 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/
SPDR Dow Jones Industrial Average ETF
Active Buy-and-Hold
Sharpe ratio
(the higher the better)
1.1 1.13
Solvency II Value-at-Risk 99.5%
(the lower the better)
- -
2025-01-19T17:00:00.806508 image/svg+xml Matplotlib v3.7.3, https://matplotlib.org/