Top Tweets for #factoranalysis
D/ Two-factor model. Two-factor model yields the following results. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
Compared to One-factor model, the trends of SP500, Nikkei and Gold are separated. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
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
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
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
Nikkei is also a very strong fit. 69% of its movement is captured. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
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
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
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
While the 3w T-Bill is a clear outlier with negligible explanatory power. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
C/ One-factor model. One-factor model yields the following results. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
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
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
Consequently, uniqueness (u2) is concentrated almost entirely in the 13 T-Bill. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
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
Note: The model's SS loadings stand at 1.23, accounting for 25% of the total variance. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
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
B/ To determine the optimal number of factors, we conducted a parallel analysis. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
The actual data yielded higher values than the simulated data for up to three factors. Based on these results, we begin our factor analysis with a one-factor model. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
A/ We conducted a factor analysis from February to mid-May 2026, a period of high volatility and dramatic shifts in financial markets. #statistics,#factoranalysis, #sp500, #nikkei225, #brent, #gold
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