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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.

XLB Components Realized Volatility Streamgraph

Components
Historical price and realized volatility 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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XLB 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 XLB.

Components Realized Volatility

All Realized Volatility Visualizations
Component 1 Month Ago 1 Week Ago Last Value
ALB 63.09021 65.02968 49.54961
AMCR 32.02724 31.24515 22.80537
APD 33.81968 29.69639 23.37298
AVY 45.58843 45.26293 31.83517
BLL 39.49873 38.36204 30.36643
CE 46.04513 44.41664 27.59140
CF 80.61386 72.76359 53.17381
CTVA 40.99379 41.31479 29.47857
DD 40.69037 39.91113 28.79888
DOW 39.97389 39.54250 26.57666
ECL 39.60727 39.33447 26.04496
EMN 37.60454 39.35628 28.89481
FCX 66.08792 60.77361 45.13681
FMC 40.11690 35.51003 29.64925
IFF 46.51182 40.78300 32.61500
IP 37.24533 37.67402 29.91392
LIN 37.27108 32.87368 23.20044
LYB 43.73518 42.91723 30.95221
MLM 47.12945 41.99081 30.85953
MOS 70.96533 64.79108 45.08717
NEM 46.31205 38.67339 28.14489
NUE 65.82603 63.65922 54.52132
PPG 33.74089 32.74960 27.53110
SHW 40.01042 39.81987 31.78265
VMC 39.95501 40.90460 31.69808

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 Materials 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 Materials 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 Materials Select Sector SPDR Fund.

Materials Select Sector SPDR Fund

XLB is an exchange traded fund whose portfolio is comprised of US materials sector stocks. This investment seeks to provide the same performance as stocks in the Materials Select Sector Index. The index contains securities from the following industries: chemicals, metals and mining, paper and forest products, containers and packaging, construction materials.
All Realized Volatility Visualizations

Realized Volatility

This chart shows the component realized volatility of XLBover the past year of trading.
Components
Historical price and realized volatility data
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Robson Chow is a hedge fund manager
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