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The datasets from which these PYPL forecasts are drawn originate from FactSet. They represent the aggregated estimates made available to academics or practitioners via the Institutional Brokers’ Estimate System (IBES). Although this seems like a fair way of predicting future profits given that they have some level expertise in investment banking, studies show there's still an optimism bias present among these professionals.

Regression-based models suffer from the use of past earnings in a linear or exponential framework. This can lead to bias because these models assume that future performance will mirror historical trends exactly, whereas business cycle dynamics and seasonality may introduce randomness over time periods.

While there is a clear consensus that a factor-based approach to investment is rewarded over time, it goes without saying that the implementation of factor investing strategies, especially in the world of long-only money-management, is rarely subject to the same consensus. Index providers who offer funds that generally contain a small number of stocks in relation to the size and risk level they are designed for, often do so by selecting certain conditions or factors within each company.

For example, some commercial indexes aim at proportionality between price movements and dividends paid out over time while others look exclusively on liquidity considerations alone; yet still more restrict their selection criteria based around corporate governance issues like transparency reports rating various aspects such as soundness levels among others relevant metrics available about any given firm when deciding whether it should be included into an investor’s portfolio.

United States Oil ETF Seasonality

Components
Historical price and seasonality data
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Seasonality

This multi-factor forecast for Paypal Holdings (PYPL) is based on a weighted average of five factor-dervied forecasts.
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USO Seasonality Chart

Left-hand side y-axis coordinates measure return in percentage.

USO Seasonal Returns

USO Seasonal Probabilities

USO Seasonal Returns Previous 17 Years

Month Mean
January -1.55027
February 2.44798
March -1.55172
April 1.55189
May 0.86292
June 2.89435
July -1.55464
August -1.64601
September -1.34434
October -2.32481
November -3.19643
December -0.54692
Month Mean Median Win Freq
January -1.55027 -1.55027 31.25000
February 2.44798 2.59591 68.75000
March -1.55172 3.91566 62.50000
April 1.55189 2.62032 64.71000
May 0.86292 -1.04444 41.18000
June 2.89435 3.17265 64.71000
July -1.55464 0.09703 52.94000
August -1.64601 -2.96994 35.29000
September -1.34434 -2.49561 47.06000
October -2.32481 -2.32481 43.75000
November -3.19643 -0.11707 50.00000
December -0.54692 2.55496 62.50000
All Seasonality Visualizations

About United States Oil ETF

USO is an exchange-traded security that seeks to track the daily percentage changes in its share price to reflect the daily percentage changes in the spot price of light, sweet crude oil. The goal of the security is to provide shareholders with an investment that closely correlates to movements in the underlying commodity. USO is priced and traded as a security on the NYSE.
Best month to buy USO
United States Oil ETF has tended to perform the best during the month of June, during which shares have historically returned an average of 2.9.
Worst month to buy USO
United States Oil ETF has tended to perform the worst during the month of November, during which shares have historically returned an average of -3.2.
About Market Seasonality
Seasonality can be defined as the predictable changes that occur over a one-year period in an economy, market or business, based on the seasons of the calendar year.

Traders often attempt to take advantage of seasonal patterns by holding long and short positions in assets simultaneously in the same or a related markets, such as equity sectors, index futures or commodities.

Investors in individual equities may take seasonality into account when when analyzing the impact that seasonal changes may have on the fortunes of particular companies. For example, for many businesses, sales can vary depending on the season. In such cases, the share prices of business that experience higher profits during specific seasons may simultaneously register significant gains while later giving them back during off-peak periods.Seasonality can be defined as the predictable changes that occur over a one-year period in an economy, market or business, based on the seasons of the calendar year.
All Seasonality Visualizations

Seasonality

This chart shows the seasonal tendencies  of the share price of Apple Inc USO over the last 40 years.
Components
Historical price and seasonality data
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PYPL forecast 2025 logo
USO
Guest Commentary
Robson Chow is a hedge fund manager
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