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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.

AAPL Stock Seasonality

Components
Historical price and seasonality data
PYPL forecast 2025 logoPYPL forecast 2025 logo

Seasonality

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

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

See seasonal chart with year by year performance

AAPL Seasonal Returns

AAPL Seasonal Probabilities

AAPL Seasonal Returns Previous 43 Years

Month Mean Median Win Freq
January 3.96153 3.96153 66.67000
February 1.73547 1.73547 57.14000
March 2.82054 1.32106 52.38000
April 3.97041 2.93295 64.29000
May 1.95596 1.95596 54.76000
June -2.64875 -2.64875 42.86000
July 3.23987 3.23987 61.90000
August 5.61259 6.04207 64.29000
September -4.47373 -1.42413 38.10000
October 6.52190 6.32371 73.17000
November 2.83827 3.10787 56.10000
December 2.10825 3.66000 61.90000
All Seasonality Visualizations

AAPL Seasonal Returns Previous 43 Years

Month Mean
January 3.96153
February 1.73547
March 2.82054
April 3.97041
May 1.95596
June -2.64875
July 3.23987
August 5.61259
September -4.47373
October 6.52190
November 2.83827
December 2.10825

About Apple Inc

About Apple Inc

Apple, Inc. engages in the design, manufacture, and sale of smartphones, personal computers, tablets, wearables and accessories, and other variety of related services. It operates through the following geographical segments: Americas, Europe, Greater China, Japan, and Rest of Asia Pacific. The Americas segment includes North and South America. The Europe segment consists of European countries, as well as India, the Middle East, and Africa. The Greater China segment comprises of China, Hong Kong, and Taiwan. The Rest of Asia Pacific segment includes Australia and Asian countries. Its products and services include iPhone, Mac, iPad, AirPods, Apple TV, Apple Watch, Beats products, Apple Care, iCloud, digital content stores, streaming, and licensing services.

When is the best month to buy AAPL?

Apple Inc has performed the best during the month of October, during which shares have returned an average of 6.52% over the last 43 years.

When is the worst month to buy AAPL?

Apple Inc has performed the worst during the month of September, during which shares have returned an average of -4.47% over the last 43 years.
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.

Academic research supports the notion that seasonal pricing patterns occur with regularity in futures contracts of commodities with fixed maturities, most notably in the natural gas and crude oil markets.

For example, Ewald, Haugom, Stordal, Lien and Wu find evidence for seasonality in futures products that appears distinct from the seasonal patterns in spot price for the respective commodities.

Traders often attempt to take advantage of seasonal patterns through spread trades that hold long and short positions in assets of differing maturities simultaneously or across related assets in financial products such as equity sector ETFs, 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.
All Seasonality Visualizations

Seasonality

This chart shows the seasonal tendencies  of the share price of Apple Inc AAPL over the last 43 years.
Components
Historical price and seasonality data
PYPL forecast 2025 logoPYPL forecast 2025 logo
PYPL forecast 2025 logo
AAPL
Guest Commentary
Robson Chow is a hedge fund manager
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