For Traders
Click the green button to start
performing no-code quant
analysis on this security
Backtest XLK
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.

XLK Components Realized Volatility Streamgraph

Historical price and realized volatility data
PYPL forecast 2025 logoPYPL forecast 2025 logo


This multi-factor forecast for Paypal Holdings (PYPL) is based on a weighted average of five factor-dervied forecasts.
Backtest PYPL
PYPL forecast 2025 logo
XLK Components Realized Volatility Streamgraph

Left-hand side y-axis orders liquidity rank of individuals chart components.
Right-hand side y-axis coordinates measure the price of XLK.

Components Realized Volatility

Component Last Value
AAPL 38.77976
ACN 46.42313
ADBE 56.85513
ADI 58.80251
ADP 40.43938
AMAT 72.16706
AMD 94.43710
AVGO 55.69893
CRM 59.85852
CSCO 33.05378
FIS 52.75120
IBM 35.14209
INTC 42.43882
INTU 57.61953
LRCX 78.59868
MA 51.63879
MSFT 45.58899
MU 70.01754
NOW 75.04366
NVDA 90.66829
ORCL 34.11936
PYPL 79.26366
QCOM 72.25404
TXN 51.92491
V 41.64376
All Realized Volatility Visualizations
Component 1 Month Ago 1 Week Ago Last Value
AAPL 38.77976 38.63915 30.15665
ACN 46.42313 45.73907 38.27502
ADBE 56.85513 53.30568 43.12488
ADI 58.80251 52.87430 34.41449
ADP 40.43938 40.35793 25.41425
AMAT 72.16706 81.04700 69.69853
AMD 94.43710 84.25646 68.55535
AVGO 55.69893 55.14872 40.82248
CRM 59.85852 58.78609 44.13940
CSCO 33.05378 31.59577 24.34058
FIS 52.75120 47.86960 39.78401
IBM 35.14209 35.48488 28.10434
INTC 42.43882 41.80179 32.49699
INTU 57.61953 56.36512 44.04553
LRCX 78.59868 80.70474 61.16246
MA 51.63879 51.16286 38.24134
MSFT 45.58899 48.63842 36.11950
MU 70.01754 63.63834 47.97591
NOW 75.04366 84.14026 67.55908
NVDA 90.66829 84.33221 66.47064
ORCL 34.11936 32.46968 34.94012
PYPL 79.26366 79.64412 47.70435
QCOM 72.25404 70.64576 47.45050
TXN 51.92491 49.38162 30.44168
V 41.64376 41.93227 28.68851

About Realized Volatility

Realized volatility (as derived from the square root of variance) is a measurement of the standard deviation of returns of an asset over a given time period, typically annualized.

How Realized Volatility is Measured

Realized volatility can be measured many ways. The classical way of calculating realized volatility is by taking the log returns of close to close prices.

Per Euan Sinclair, “there is no uncertainty due to measurement. But there is uncertainty over whether the measure is truly representative of the underlying reality.”

The streamgraph visualization above displays realized volatility over the previous 21 days by applying the Yang-Zhang method of calculating realized volatility. This measurement utilizes more data points than the typical close-to-close estimator, which results in a measurement that is considered more accurate.

We measure realized volatility for each component of a particular index or ETFs in order to help understand volatility dynamics, and anomalies underneath the surface.

How to Read the Streamgraph

The streamgraph is a data visualization that enables the representation of many timeseries in an efficient manner. The Tradewell realized volatility streamgraph shows the change in realized volatility through time across multiple datasets, displaced around a central axis (the 0-line).

The streamgraph highlights three main attributes of realized volatility:

1. The overall level of realized volatility at the index or etf level relative to history.
If you notice the streamgraph expanding and then contracting, that behavior is representative of individual component volatility expanding and contracting. The widest part of the streamgraph represents the period with the most volatility across components, while the narrowest part of the streamgraph represents the period with the least volatility across components.

2. Anomalies in individual components realized through time.
When companies have large moves, ie volatility increases significantly due to earnings, unexpected events or otherwise, the streamgraph will immediately highlight those anomalies visually — the width of an individual securities contribution to the streamgraph will widen considerably and the individual component ticker will be displayed on the streamgraph on the Date where realized volatility was highest for Technology Select Sector SPDR Fund. As volatility clusters, it is common to see the width persist after an anomalous move in a particular security.

3. The level of realized volatility of individual components relative to other components that comprise Technology Select Sector SPDR Fund.

About the Streamgraph Coordinates

The X-axis displays trading days by date, and the Y-axis contains the component realized volatility. The absolute distance between each line on the chart is the 21-day realized volatility for Technology Select Sector SPDR Fund.

Technology Select Sector SPDR Fund

XLK is an exchange traded fund whose portfolio is comprised of US technology sector stocks. This investment seeks to provide the same performance as stocks in the Technology Select Sector Index. The fund typically invests at least 95% of its assets in the securities that comprise this index.
All Realized Volatility Visualizations

Realized Volatility

This chart shows the component realized volatility of XLKover the past year of trading.
Historical price and realized volatility data
PYPL forecast 2025 logoPYPL forecast 2025 logo
PYPL forecast 2025 logo
Guest Commentary
Robson Chow is a hedge fund manager
Tradewell is not responsible for the content, data, or information on third-party websites or provided by third-party data providers. We publish links to various external sources and data from various data providers as a convenience, but we cannot verify any claims made by those sites and cannot guarantee that they are safe interpretations of information provided within these pages. If you choose to visit a linked site or consume data, you do so at your own risk and you will be subject to such sites' terms of use and privacy policies, over which Tradewell has no control. Tradewell shall not be liable for any damages incurred by visiting the linked sites or by making decisions or interpreting the data published on webpages or in the Tradewell app.

The information contained on this website is current as of the date indicated, and may be superseded by subsequent market events or for other reasons. The views and opinions expressed on this website are those of the authors alone - they do not necessarily reflect those held by Tradwell, its affiliates nor employees alike. Investors should be aware that the information expressed in articles is not intended to relate specifically to any product offered by Tradewell. It's being provided for informational purposes only and cannot serve as investment advice or guidance on your individual financial situation.

Any hypothetical performance shown is based on the retrospective application of a model developed with hindsight. While these results are presented for illustrative purposes only, it's important to note that there may be limitations built into any projection.

Certain articles may have been written prior to the author being an employee or contractor of Tradewell. The views expressed on the website are those of the authors and not necessarily those of Tradewell. Published material is intended for informational purposes only and should not be construed as legal or tax advice, nor is it intended to replace the advice of a qualified attorney or tax advisor.