kkta_data

Data analytics, Principal investments, Financial advisory. KK Trust Advisors.

[kkta_data @kkta_data]

D/ Two-factor model. Two-factor model yields the following results. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Compared to One-factor model, the trends of SP500, Nikkei and Gold are separated. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Factor loadings for ML1 (The "Equity/Market" Factor): SP500 dominates this factor with a massive loading of 0.87. Nikkei has a negative loading (-0.39), suggesting that it moves inversely to this specific factor. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Factor loadings for ML2 (The "Global Sentiment/Commodity" Factor) : Nikkei225 (0.78) and Gold (0.59) load strongly here. Brent has a moderate negative loading (-0.49), suggesting it moves against the grain of whatever Nikkei and Gold are capturing. #statistics,#factoranalysis

[kkta_data @kkta_data]

Communality(h2) and uniqueness(u2). SP500 is essentially a perfect fit. Nearly 100% of the SP's variance is explained by these two factors. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Nikkei is also a very strong fit. 69% of its movement is captured. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Brent & Gold have low to moderate 0.28 and 0.35 each, meaning more than 60% of their behavior is unique (or unexplained) by this model. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

3w T-Bills is a fail. Only 1.9% of its ariance is explained. In practical terms, this variable is just noise in this specific model and doesn't belong with the others. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

In summary, Two-factor model effectively captures the variance of the S&P 500 and Nikkei, both of which show an inverse relationship with Brent. Gold follows a distinct trajectory, remaining largely decoupled from equity movements. #statistics,#factoranalysis, #sp500, #nikkei225

[kkta_data @kkta_data]

While the 3w T-Bill is a clear outlier with negligible explanatory power. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Note: Factor ML2 is dominant (27%) and ML1 is next (19%) of the total variance. These two factors capture 47%. While this is a solid start for a two-factor model, it suggests that over half of the data's fluctuations are still driven by unique or unexplained components.

[kkta_data @kkta_data]

The model identifies two largely independent forces. ML2 is the more influential driver, but because the Cumulative Var is 0.47, the model is moderately effective—it explains just under half of the total movement. Thanks for attention. EoD.

[kkta_data @kkta_data]

C/ One-factor model. One-factor model yields the following results. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Factor loadings for ML1 are strongly positive for Gold, the S&P 500, and the Nikkei 225, but negative for Brent Crude, reflecting a co-movement between equities and gold that runs counter to oil dynamics during this period. #statistics,#factoranalysis, #sp500, #nikkei225, #brent

[kkta_data @kkta_data]

Communalities (h2) are high across Gold, Brent, and both equity indices, while the 13-week T-Bill exhibits negligible communality. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Consequently, uniqueness (u2) is concentrated almost entirely in the 13 T-Bill. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

In summary, One-factor model captures a regime where Brent Crude moves inversely to SP500, Gold and Nikkei 225. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

Note: The model's SS loadings stand at 1.23, accounting for 25% of the total variance. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

For a dataset of five variables, a total explained variance of 25% is relatively low, suggesting a single-factor model may not fully capture the market's underlying dynamics. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold

[kkta_data @kkta_data]

B/ To determine the optimal number of factors, we conducted a parallel analysis. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold