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Nasdaq-100 Components Realized Volatility Streamgraph

Emerging Markets Realized Volatility Streamgraph

International Developed Markets Realized Volatility Streamgraph

US Equity Sectors Realized Volatility Streamgraph

XLU Components Realized Volatility Streamgraph

XLP Components Realized Volatility Streamgraph

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.

XLI Components Realized Volatility Streamgraph

Components

Historical price and realized volatility data

Seasonality

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

Backtest PYPL

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

Components Realized Volatility

Component	Last Value
BA	58.52730
CARR	44.83642
CAT	38.89910
CSX	37.07067
DE	41.88990
EMR	35.25931
ETN	40.44186
FDX	32.29798
GD	30.02797
GE	44.96301
HON	37.49433
INFO	39.84368
ITW	37.29769
JCI	42.11219
LHX	38.60038
LMT	30.28290
MMM	35.95577
NOC	40.02086
NSC	36.64797
PH	53.14573
ROP	36.60775
RTX	39.76168
UNP	32.24636
UPS	42.94538
WM	28.76727

All Realized Volatility Visualizations

Component	1 Month Ago	1 Week Ago	Last Value
BA	58.52730	57.20713	43.00801
CARR	44.83642	42.47251	34.90990
CAT	38.89910	39.64391	33.32550
CSX	37.07067	36.38901	26.06008
DE	41.88990	41.28325	36.17855
EMR	35.25931	33.02115	25.54655
ETN	40.44186	38.87132	26.86316
FDX	32.29798	28.34447	25.86737
GD	30.02797	28.86015	21.05279
GE	44.96301	42.00127	29.01445
HON	37.49433	35.39457	23.60873
INFO	39.84368	39.02264	27.37327
ITW	37.29769	36.30069	20.32582
JCI	42.11219	42.20688	29.94290
LHX	38.60038	35.03572	30.48709
LMT	30.28290	27.23464	22.86408
MMM	35.95577	34.38066	20.47314
NOC	40.02086	34.31539	24.02009
NSC	36.64797	38.11019	29.81445
PH	53.14573	52.40607	28.73840
ROP	36.60775	38.41401	31.92695
RTX	39.76168	38.80982	24.28336
UNP	32.24636	31.74807	24.42639
UPS	42.94538	40.98302	25.27855
WM	28.76727	28.43329	22.96117

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 Industrial 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 Industrial 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 Industrial Select Sector SPDR Fund.

Industrial Select Sector SPDR Fund

XLI is an exchange traded fund whose portfolio is comprised of US industrial sector stocks. This investment seeks to provide the same performance as stocks in the Industrial Select Sector Index. This index includes stocks from the following industries: aerospace and defense; industrial conglomerates; marine; transportation infrastructure, machinery, road and rail, air freight and logistics.

All Realized Volatility Visualizations

Realized Volatility

This chart shows the component realized volatility of XLIover the past year of trading.

Components

Historical price and realized volatility data

AAPL

Guest Commentary

Robson Chow is a hedge fund manager

Thank you for reading... and hope you are enjoying the holidays. The full post can be found here https://t.co/uLKVnqB5ZS
— QuartersPower (@HalfersPower) December 30, 2021

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