Cannabis ETFs: Performance, Risk, and Market Impact Analysis

Journal of Asset Management
https://doi.org/10.1057/s41260-025-00400-8
ORIGINAL ARTICLE
Rolling in the green? A closer look at cannabis ETFs’ market munchies
Frank J. Fabozzi1
· Davinder K. Malhotra2
Revised: 16 December 2024 / Accepted: 16 February 2025
© The Author(s) 2025
Abstract
The investment landscape often grapples with the ethical dilemmas posed by “sin stocks,” shedding light on the complex
interactions between investor sentiment, societal standards, and market behavior. Although sin stocks have been the subject
of some analysis, the exploration into cannabis exchange-traded funds (ETFs) remains sparse. This research compares the
performance of cannabis ETFs against both U.S. and international equities, delving into their correlation, returns, and risk
across a variety of market scenarios, including the effects of the COVID-19 pandemic. The findings suggest that cannabis
ETFs generally lag traditional equities, highlighting potential risks. While they performed better during the COVID-19
lockdown, the findings point to inadequate security selection and a lack of effective market timing strategies. Even though
equally weighted portfolios that included cannabis ETFs and broader market indices provided a slight risk reduction when
compared to investing in cannabis ETFs alone, they consistently underperformed the conventional equity indices in terms
of risk-adjusted returns across all analyzed periods. The diversification benefit was most pronounced during the volatile
COVID-19 closure period, but it was less effective in the post-vaccination market environment. Cannabis ETFs may promise
higher returns, but their significant downside risk requires careful assessment to determine if the potential rewards justify
the risk. This research stresses the importance of adopting careful investment strategies in this developing sector.
Keywords Sin stocks · Cannabis exchange-traded funds · Alpha · Market timing · COVID-19
Introduction
In the realm of investing, certain industries prompt debates
and moral considerations. Referred to as “sin stocks,” businesses engaged in alcohol, tobacco, gambling, and weapons
often provoke controversy due to ethical concerns among
investors. The performance of sin stocks has yielded conflicting findings in numerous studies. While some research suggests that sin stocks tend to generate higher-than-expected
profits (Weisskopf 2020; Salaber 2007; Fabozzi et al. 2008;
Rezaeian & Racine, 2024; Hong & Kacperczyk 2009; Han
et al. 2022), others indicate lackluster performance (Lobe &
Walkshäusl 2016; Richey 2017; Sagbakken & Zhang, 2022).
This paradox underscores the intricate interplay between
investor sentiment, social norms, and market dynamics.
This paradoxical nature underscores the importance of
understanding the dynamics driving investor behavior and
market trends. The decision to invest in sin stocks involves
considerations beyond financial performance, including ethical considerations and societal norms. As such, investors
must weigh the potential financial gains against the ethical
implications when making investment decisions in these
industries.1
Investors’ reluctance to be associated with morally questionable companies has prompted the creation of exclusion lists, deliberately omitting sin stocks from investment
1
* Davinder K. Malhotra
[email protected]
Frank J. Fabozzi
[email protected]
1
Carey Business School, Johns Hopkins University,
Baltimore, USA
2
Thomas Jefferson University, Philadelphia, USA
Cannabis stocks (and linked ETFs) are associated with “sin stocks”.
However, this association is not straightforward because cannabis
can be legally used either for recreational purposes or for medical
reasons. The existence of therapeutic purposes for using cannabis
might influence investors’ perception, making them consider cannabis
stocks apart/different from sin stocks. Indeed, alcohol, tobacco, gambling, and weapons cannot be used for therapeutic purposes, and they
are arguably bad for health. Perceptions are likely not to be so clear
regarding cannabis. The legal use of cannabis simply offers new business perspectives that are attractive and promising, without raising a
lot of ethical and moral considerations.
Vol.:(0123456789)
F. J. Fabozzi, D. K. Malhotra
portfolios. An intriguing trend has emerged with the rise of
exchange-traded funds (ETFs) targeting sin stocks. While
ETFs covering a broad spectrum of sin stocks have yet to
materialize, specific funds focus on subcategories within this
contentious sector.
In recent years, the burgeoning cannabis industry has captured the interest of investors seeking exposure to a rapidly
evolving market. With regulatory landscapes and societal
attitudes toward cannabis undergoing transformation, specialized investment vehicles, notably cannabis ETFs, have
emerged as dynamic approaches to capitalize on the sector’s
growth potential. This research paper explores the performance dynamics of cannabis ETFs, aiming to analyze the
factors influencing their success or challenges. Through an
examination of absolute- and risk-adjusted performance,
we offer insights into the investment opportunities and risks
associated with this unique segment of the financial markets. As the cannabis industry navigates uncharted territory,
understanding the performance patterns of associated ETFs
becomes crucial for investors making informed decisions in
this evolving investment landscape.
This study is significant for two reasons. First, medical
marijuana has gained legal status in 40 states along with
Washington D.C., and as of January 2024, 24 states, the
District of Columbia, and Guam have also legalized recreational cannabis use for individuals aged 21 and above.
The legalization trend reflects a shifting landscape in public
policy regarding cannabis.2 Second, according to Statista,
the US cannabis market is poised for substantial growth in
the foreseeable future. Projections indicate that the revenue
from this market is anticipated to reach US$39.85 billion
in 2024, with a projected compound annual growth rate of
13.93% from 2024 to 2028. By the end of 2028, the market
volume is estimated to hit US$67.15 billion. This growth
trajectory suggests a significant economic impact, with cannabis expected to contribute $115.2 billion to the economy
in 2024 alone.3
Given the enormity of the projected growth in the cannabis industry and its substantial contribution to the US
economy, there’s a critical need to evaluate the risk–return
characteristics of funds investing in this sector. The cannabis
industry is notably marked by inherent volatility, stemming
from evolving regulations, shifting legal landscapes, and the
dynamic nature of consumer preferences. Understanding the
risk profiles associated with cannabis ETFs is crucial for
investors to gauge their exposure to market fluctuations and
assess potential impacts on portfolio performance.
Although some studies have examined the performance of
“sin” stocks, to our knowledge, no study has been conducted
2
3
https://​flowh​ub.​com/​canna​bis-​indus​try-​stati​stics.
https://​www.​stati​sta.​com/​outlo​ok/​hmo/​canna​bis/​united-​states.
to investigate the performance of ETFs investing in cannabis
companies, despite the apparent interest from investors in
cannabis-related investments. While studies have extensively
examined the performance of ETFs across different asset
classes such as commodities, digital assets, and energy, the
specific dynamics surrounding cannabis ETFs remain relatively unexplored.
Given the heightened interest among investors in cannabis
companies, this research paper investigates the performance
dynamics of cannabis ETFs, focusing on factors influencing their success or challenges. Through an examination of
monthly returns, this study aims to provide insights into the
unique investment opportunities and risks associated with
this evolving sector of the financial markets.
Furthermore, the risks posed by marijuana businesses
and ETFs are different because of new US regulations. In
contrast to sin stocks of alcohol, tobacco, and gambling,
marijuana is still federally illegal even as more states legalize it. Changes to the regulatory landscape, such as federal
legalization or bank reforms, could fuel market growth, institutional investment, and M&A. Insurance reimbursement for
cannabis therapies could also add to the boom. This uncertain policy environment must be factored into the valuation
equations of an investor and bring speculative risks with it.
The primary research question of this study is to assess
how incorporating cannabis ETFs into a well-diversified
portfolio impacts its risk-adjusted performance, providing
a deeper understanding of the investment opportunities and
risks associated with cannabis stocks. The objective is to
examine how cannabis ETFs can improve the risk–return
trade-off within a diversified portfolio, rather than simply
comparing the performance of a concentrated portfolio of
cannabis ETFs with that of well-diversified U.S. and global
equities. This study investigates the potential for improving
the risk-adjusted performance of a well-diversified portfolio
by including cannabis ETFs, offering a more nuanced analysis that aligns with broader investment considerations and
underscores the potential role of cannabis ETFs in portfolio
management.
This study aims to address three fundamental questions
regarding cannabis ETFs. First, it investigates whether cannabis ETFs generate a higher risk-adjusted rate of return
than other investment alternatives, such as U.S. and global
equities, as well as their performance when included alongside these equities, and whether they can achieve positive
alpha. Second, it evaluates whether cannabis ETF managers
demonstrate superior asset selection and market timing abilities. Finally, the study analyzes the performance of cannabis
ETFs during a period of unprecedented market uncertainty
and volatility caused by the COVID-19 outbreak.
The paper is divided into six sections. A review of studies
concerning the performance of ETFs is provided in Section “Previous studies”, along with the identification of the
Rolling in the green? A closer look at cannabis ETFs’ market munchies
research gap in evaluating the performance of ETFs specifically investing in cannabis companies. Section “Data”
details the various models utilized for performance evaluation. Section “Methodology” describes the dataset followed
by our empirical findings in Section “Empirical analysis”.
Section “Summary and conclusions” summarizes our
findings.
Previous studies
Several studies have explored the performance of “sin”
stocks, but none have specifically explored the performance
of institutional investors who invest in them. Salaber (2007),
who conducted research spanning 18 European countries
from 1975 to 2006, found that sin stocks in tobacco, alcohol,
and gaming sectors performed better in high-litigation-risk
environments. He also noted that Protestants tend to exhibit
a greater aversion to sin stocks compared to Catholics.
Fabozzi et al. (2008) investigated how social values
impact economic values, focusing on sin-seeking activities such as alcohol consumption, adult services, gaming,
tobacco, weapons, and biotech alterations. They found that
sin stocks, comprising this subset of companies, consistently outperformed common benchmarks, yielding an annual
return of 19% over the study period.
Rezaeian and Racine (2024) contested the notion that sin
stocks (alcohol, tobacco, and gambling securities) are inherently riskier than non-sin stocks. Analyzing North American data from 1980 to 2017, they matched sin stocks with
similar non-sin firms using propensity score methodology.
Their findings indicated that, apart from gambling stocks’
idiosyncratic risk, sin stocks generally do not exhibit significantly greater risk than their non-sin counterparts. They
emphasized the category-sensitive nature of Corporate
Social Responsibility’s risk mitigation potential.
Hong and Kacperczyk (2009) explored the investment
behavior surrounding sin stocks. Their study revealed that
norm-constrained institutions, such as pension plans, tend
to hold fewer of these stocks compared to mutual funds or
hedge funds. Despite receiving less analyst coverage, sin
stocks exhibited higher expected returns, possibly due to
being neglected by norm-constrained investors and facing
greater litigation risks heightened by social norms. Their
findings underscored the significant impact of social norms
on stock prices and returns, highlighting the need to consider
social preferences in investment decisions.
Comparing sin stock returns to faith-based returns, Perez
and Soydemir (2010) find that the betas of sin stock move
opposite to faith-based betas. Sin stocks exhibited positive
and significant Jensen’s alpha, while faith-based stocks
showed negative and significant Jensen’s alpha, suggesting sin stocks outperform faith-based stocks relative to the
market. The rolling regression technique revealed differing
movements in sin and faith-based betas, with sin beta averaging half of the market average. Additionally, the sin portfolio’s Sharpe ratio was statistically higher than that of the
faith-based portfolio, supporting its outperformance.
Kim and Venakatachalam (2011) highlighted recent
empirical evidence suggesting that stock market participants overlook sin stocks due to social norms, regulatory
scrutiny, and/or litigation risk. They further contended that
despite their superior returns and financial reporting quality,
investors continued to disregard sin stocks, possibly due to
societal norms and non-financial considerations in portfolio
management.
Lobe and Walkshäusl (2016) explored whether portfolios
consisting of sin stocks outperformed those comprised of
socially responsible stocks globally, regionally, and domestically. Contrary to prior research, they found no evidence of
sin stocks either outperforming or underperforming. Investigating the return performance of a portfolio consisting
of US “vice stocks,” Richey (2017) found that the CAPM,
Fama–French three-factor, and Carhart four-factor models
showed a positive and significant alpha for the vice portfolio. However, the significance diminished when explanatory variables from the Fama–French five-factor model were
included. Blitz and Fabozzi’s (2017) examination of sin
stocks’ performance globally until 2016 revealed a positive
CAPM alpha in U.S., European, and global datasets. However, this alpha vanished when accounting for size, value,
momentum, and Fama and French (2015) quality factors. In
Japan, sin stocks displayed notable exposures to profitability and investment factors but lacked significant one-factor
alpha. Their findings suggest that sin stocks’ performance
adheres to existing asset pricing models, challenging the
notion of a sin premium.
Perez and Gutierrez (2018) found that non-fundamental
factors, such as investor sentiment, influence returns for sin
portfolios, with this impact varying over time. Moreover,
this influence is less pronounced for sin stocks compared to
the S&P 500 and similar portfolios. In a study by Chew and
Li (2021), moral stock preference was experimentally investigated in terms of sin stock aversion (SSA) and virtue stock
affinity (VSA). The research revealed the presence of both
SSA and VSA, with SSA being more pronounced. Additionally, SSA/VSA correlated positively with social preference
and belief bias. The study suggested an asymmetry between
SSA and VSA, indicating a disproportionate avoidance of
sin stocks compared to favoring virtue stocks, suggesting
moral loss aversion. Sagbakken and Zhang (2022) explored
sin stocks in the European market from 2006 to 2020. Their
findings indicated the absence of a consistent sin premium
for either new or traditional sin stocks when compared to the
market or peer stocks. Han et al. (2022) observed that sin
stocks consistently outperformed the market over the decade
F. J. Fabozzi, D. K. Malhotra
from 2009 to 2018. This pattern corresponds to the increasing prevalence of socially responsible investing, prompting
more norm-constrained investors to eschew sin stocks. Further examinations reveal that sin stocks excel in low-liquidity
and high-uncertainty conditions, demonstrating resilience
during economic downturns. The results corroborate the
shunned stock hypothesis, emphasizing the enduring significance of sin stocks in the marketplace.
In recent years, some studies have examined the performance of cannabis stocks. Weisskopf (2020) reported that a
portfolio comprising cannabis stocks demonstrates both high
volatilities and returns. However, the author also reported
low correlations and beta coefficients when compared to
broader stock markets, other industries typically associated
with sin activities, and cryptocurrencies. This suggests that
investing in the cannabis industry could offer unique diversification benefits and potential opportunities for investors
seeking to enhance their portfolios.
Despite the abundance of studies scrutinizing the overall
performance of sin stocks, none have focused on the specifics of institutional investors’ involvement in cannabis
companies. As attitudes toward cannabis evolve, there is a
clear absence of research focusing on institutional investors,
such as ETFs, that target cannabis businesses. Given the
swift expansion and evolving regulatory framework of the
cannabis industry, comprehending the performance dynamics of cannabis ETFs assumes paramount importance. This
study endeavors to address this gap by scrutinizing the riskadjusted performance of cannabis ETFs.
Data
Data for this study are sourced from Morningstar Direct. We
obtained monthly returns for cannabis ETFs from January
2016 to April 2023. We started with only one fund in 2016
with total assets under management of only $2.23 million.
By April 2023, it was 10 cannabis ETFs with total assets
under management equal to $820 million, an increase of
almost 35,000% within seven years. The average annual
turnover ratio for these ETFs was 45.90% in 2022. All ETFs
included in our study are actively managed funds with a minimum turnover ratio of 12% and a maximum turnover ratio
of 74%. The average annual expense ratio of cannabis ETFs
was 0.79% in 2016, declining to 0.64% in 2022.4 Table 1
summarizes the characteristics of the data used in this study.
In the period from January 2016 to April 2023, cannabis ETFs demonstrated a mean return of −1.17%, coupled
with a relatively high standard deviation of 13.04%. This
resulted in a negative average return per unit of risk, indicating that the returns did not adequately compensate for
the associated volatility. In comparison, both the S&P 500
Index and the FTSE All World Ex. U.S. Index displayed
more favorable average returns per unit of risk, suggesting
a potentially more balanced risk–return profile for investors
in these broader market indices.
In contrast, an equally weighted portfolio of S&P 500,
the FTSE All World ex U.S. Index, and cannabis ETFs
achieved a positive mean return of 0.20%, with a lower
standard deviation of 6.78%. While the risk-adjusted return
remained modest at 0.03, this diversified portfolio significantly enhanced overall performance and stability compared
to holding cannabis ETFs alone. In comparison to cannabis
ETFs alone, the equally weighted portfolios of cannabis
ETFs with the S&P 500 or the FTSE All World ex U.S.
Index exhibited reduced volatility but negative mean returns
(−0.19% and −0.10%, respectively). Nonetheless, these
portfolios’ somewhat negative risk-adjusted returns (−0.02
and −0.01, respectively) suggest that the risk–return tradeoff was not much improved.
During the period January 2020 to January 2021, cannabis ETFs exhibited a notable improvement, achieving a mean
return of 4.10%. However, the higher standard deviation of
19.31% indicated increased volatility, resulting in a positive
but modest average return per unit of risk. In contrast, the
S&P 500 Index, despite a marginal mean return, demonstrated a lower standard deviation, contributing to a comparable average return per unit of risk. This period underscores
the heightened volatility and potential return opportunities
associated with cannabis ETFs.
4
The fund sizes, turnover percentages, expense ratios, and stated
investment goals of marijuana ETFs give cannabis ETFs contrasting characteristics. AdvisorShares Pure US Cannabis ETF (MSOS),
an average fund size of $685.6 million, is growth-oriented by investing in cannabis-related companies in the US, as shown by its 48%
turnover ratio and 0.72% expense ratio. On the contrary, specialty
and unaligned strategies are the area of specialty funds such as AdvisorShares Pure Cannabis ETF (YOLO), Amplify Seymour Cannabis
ETF (CNBS), and AXS Cannabis ETF (THCX), suggesting a broad
sector approach. They have a turnover ratio of 27%-71.1%, which is
an indication of active trading. Cambria Cannabis ETF (TOKE) has
the lowest expense ratio of 0.42% with a 23% turnover ratio and has a
low expense ratio specialization strategy.
Rolling in the green? A closer look at cannabis ETFs’ market munchies
Table 1 Summary of monthly returns and risk metrics for cannabis ETFs, S&P 500, FTSE All World Ex. U.S. Index, and three equally weighted
portfolios
Cannabis ETFs S&P 500 Index FTSE All
World Ex. U.S.
Index
January 2016 to April 2023
Mean
−1.17
Standard deviation
13.04
Average return per
−0.09
unit of risk
January 2020 to January 2021
Mean
4.10
Standard deviation
19.31
Average return per
0.21
unit of risk
February 2021 to April 2023
Mean
−6.23
Standard deviation
11.90
Average return per
−0.52
unit of risk
Equally weighted
portfolio of Cannabis ETFs, S&P 500
Index, and FTSE All
World Ex. U.S. Index
Equally weighted
portfolio of Cannabis
ETFs and S&P 500
Index
Equally weighted
portfolio of Cannabis
ETFs and FTSE All
World Ex. U.S. Index
0.80
6.09
0.13
0.98
4.93
0.20
0.20
6.78
0.03
−0.19
8.56
−0.02
−0.10
7.92
−0.01
−0.04
9.38
0.00
0.90
7.20
0.12
1.65
11.06
0.15
2.03
13.42
0.15
2.50
12.46
0.20
0.70
6.39
0.11
1.84
5.92
0.31
−1.23
6.73
−0.18
−2.76
8.66
−0.32
−2.20
7.36
−0.30
This table provides a summary of the average monthly returns, standard deviation of monthly returns, and average monthly return per unit of risk
for cannabis ETFs, Standard & Poor 500 index, FTSE All World Ex. U.S. Index, and three equally weighted portfolios: one consisting of ETFs,
the S&P 500 Index, and the FTSE All World ex U.S. Index; another of ETFs and the S&P 500 Index; and a third of ETFs and the FTSE All
World ex U.S. Index. The analysis covers monthly returns from January 2016 to April 2023, as well as sub-periods including January 2020 to
January 2021 (COVID-related lockdowns pre-vaccinations), and February 2021 to April 2023 (Post-COVID Vaccinations).
The equally weighted portfolio of cannabis ETFs, the
S&P 500, and the FTSE All World ex U.S. Index yielded
a mean return of 1.65%, which, although lower than that
of cannabis ETFs alone, came with significantly reduced
volatility (11.06%). Consequently, the risk-adjusted return
was 0.15, slightly lower but still indicative of a balanced
approach. This portfolio provided greater stability while
still obtaining a portion of the potential benefits of cannabis
ETFs.
The FTSE All World ex U.S. Index and the cannabis
ETFs portfolio, which were equally weighted, obtained the
highest mean return (2.50%) and lesser volatility (12.46%) in
comparison to the cannabis ETFs themselves. It is an appealing alternative to holding cannabis ETFs in isolation during
this period, as it generated a risk-adjusted return of 0.20.
Turning attention to the period from February 2021 to
April 2023, cannabis ETFs experienced a significant decline
with a negative mean return of −6.23%. The standard deviation remained relatively high at 11.90%, resulting in a negative average return per unit of risk. In contrast, the S&P 500
Index and the FTSE All World Ex. U.S. Index showcased
more favorable average returns per unit of risk, suggesting
a more stabilized performance in comparison to cannabis
ETFs during this timeframe.
The negative average returns per unit of risk for cannabis ETFs in both the overall period and the more recent
timeframe underscore the inherent risk associated with
these investments. The notable increase in mean return
during the period from January 2020 to January 2021
indicates that while cannabis ETFs can present opportunities for positive returns, investors must be prepared for
heightened volatility. The comparison with broader market
indices, such as the S&P 500 and FTSE All World Ex.
U.S. Index, highlights the importance of diversification.
Investors may need to weigh the potential returns from
cannabis ETFs against the stability offered by more diversified portfolios.
Equally weighted portfolios with cannabis ETFs exhibited subpar performance. A diversified portfolio integrating cannabis ETFs with the S&P 500 and the FTSE All
World ex U.S. Index yielded an average monthly return
of −1.23%, resulting in a return per unit of risk of −0.18.
Portfolios that combined cannabis ETFs exclusively with
the S&P 500 or the FTSE All World ex U.S. Index produced inferior results, exhibiting average monthly returns
of −2.76% and −2.20%, along with risk-adjusted returns
of −0.32 and −0.30, respectively.
In general, the data indicate that cannabis ETFs
have performed below average in both absolute and
F. J. Fabozzi, D. K. Malhotra
risk-adjusted terms during this time frame. Their position
in diversified portfolios was not impervious to losses,
which resulted from industry issues and general market
trends.
Methodology
We assessed the risk-adjusted performance of cannabis ETFs
by comparing their performance against several benchmarks
and utilizing various risk–return metrics. The benchmarks
considered were the Standard & Poor 500 Index (a proxy
for U.S. equities) and FTSE All World ex U.S (a proxy
for global equities). To examine how cannabis ETFs can
enhance the risk–return trade-off within a diversified portfolio, rather than comparing the performance of a concentrated
portfolio of cannabis ETFs with that of well-diversified U.S.
and global equities, we constructed three equally weighted
portfolios: one consisting of ETFs, the S&P 500 Index, and
the FTSE All World ex U.S. Index; another of ETFs and
the S&P 500 Index; and a third of ETFs and the FTSE All
World ex U.S. Index. The evaluation of risk-adjusted performance employed the Sharpe ratio (Sharpe 1966), Sortino ratio (Sortino & Van der Meer 1991), and Omega ratio
(Keating & Shadwick 2002) based on monthly returns from
January 2016 to April 2023. These ratios are commonly used
to assess the risk-adjusted performance of investment portfolios or funds.
In the analysis of cannabis ETFs, the Carhart (1997) fourfactor model served as a framework to assess performance:
the Fama and French (1993) three-factor (which includes
market risk, size, and value factors), plus a momentum factor. Alpha, a critical metric in the analysis, provides insights
into the skill or ability of the portfolio manager in generating returns beyond what can be explained by market movements and identified factors. It quantifies the excess return
of an ETF compared to its expected return based on its risk
exposure, aiding in assessing whether active management or
other unique strategies contributed to superior performance.
The Sharpe ratio measures how well an investment compensates an investor for the risk they assume. Calculating
the ratio of an investment’s excess return to its standard
deviation, a higher Sharpe ratio indicates greater returns
relative to the level of risk taken. The Sortino ratio is a modified version of the Sharpe ratio that distinguishes between
favorable and unfavorable volatility in a portfolio.5 Finally,
the Omega ratio assesses the performance of financial assets
based on their risk and return characteristics. Calculating
a ratio of weighted gains to weighted losses, it classifies
expected returns into two categories: those surpassing the
projected average and those falling below it.6 Unlike the
Sharpe ratio, the Omega ratio considers the entire return distribution, offering a comprehensive assessment of risk and
return characteristics. This unique feature makes the Omega
ratio a valuable measure of asset efficiency that provides
information beyond what the Sharpe ratio alone can offer.
Careful consideration of benchmark selection is essential
when comparing Sharpe ratios, as the choice of a market
portfolio proxy directly impacts the standard deviation of the
market portfolio’s return, affecting the Sharpe ratio for both
the benchmark and the portfolio under evaluation.
Carhart’s four‑factor model
The utilization of factor models in investment analysis provides a structured analytical framework for comprehensively
understanding investment returns. These models systematically break down returns into components associated with
various underlying risk factors, including market trends, economic conditions, sector-specific attributes, and other relevant determinants. By quantifying the relationship between
investment returns and these risk factors, factor models
offer valuable insights into the foundational determinants
of investment performance.
A central concept in factor modeling is alpha, a quantitative measure that assesses investment performance beyond
the predictive capability of established risk factors. Alpha
represents the portion of performance that remains unexplained after accounting for exposure to systematic market
or factor-related risks, encapsulating the value attributed to
the skill or approach of the investment manager.
In contrast to traditional models like the CAPM and the
Fama–French three-factor model, the Carhart (1997) fourfactor model introduces four distinct factors: market risk,
size, value, and momentum. This model, well-established
for evaluating traditional financial assets like stocks, poses
challenges when applied to cannabis ETFs, given the unique
characteristics of the cannabis industry.
The Carhart four-factor model incorporates a momentum factor which is particularly relevant in the context of
5
Unlike the Sharpe ratio, the Sortino ratio calculates downside
deviation, providing a refined assessment of risk by considering only
adverse volatility. A higher Sortino ratio indicates superior performance in relation to downside deviation.
6
Unlike the Sharpe ratio, the Omega ratio considers the entire return
distribution, offering a comprehensive assessment of risk and return
characteristics. This unique feature makes the Omega ratio a valuable
measure of asset efficiency that provides information beyond what
Footnote 6 (continued)
the Sharpe ratio alone can offer. Careful consideration of benchmark
selection is essential when comparing Sharpe ratios, as the choice of
a market portfolio proxy directly impacts the standard deviation of
the market portfolio’s return, affecting the Sharpe ratio for both the
benchmark and the portfolio under evaluation.
Rolling in the green? A closer look at cannabis ETFs’ market munchies
cannabis, known for its price volatility. In the Carhart model,
four factors contribute to the explanation of stock returns:
• Market Risk (denoted by MKT): This factor denotes the
excess return of the market portfolio over the risk-free
rate, reflecting the systematic risk associated with investing in the overall market within the Carhart framework.
• Size (denoted by SMB for Small Minus Big): SMB quantifies the historical excess returns of small-cap stocks
compared to large-cap stocks. Over the long term, smallcap stocks historically outperform large-cap stocks, capturing the size effect apparent in stock returns.
• Value (denoted by HML for High Minus Low): HML
signifies the historical excess returns of value stocks
relative to growth stocks. Value stocks typically possess
lower price-to-book ratios compared to growth stocks,
highlighting the tendency of value stocks to outperform
growth stocks over time.
• Momentum (MOM): MOM represents the historical
excess returns of stocks exhibiting positive price momentum against those displaying negative price momentum.
Strong recent performers tend to sustain their positive
performance in the short term, encapsulating the momentum effect observed in stock returns.
The inclusion of the momentum factor in the Carhart
model distinguishes it from the Fama–French three-factor
model, providing a more inclusive framework for explaining
the variability in stock returns. The model posits that, apart
from market risk, factors such as company size, valuation
(value versus growth), and price momentum wield significant influence in determining stock returns.
The four-factor model employed in this study is
(
)
Ri,t − Rf ,t = 𝛼i + 𝛽i,MKT Rm,t − Rf ,t + 𝛽i, SMB× SMBt
(1)
+ 𝛽i,HML × HMLt + 𝛽i,MOM × MOM + 𝜀i,t
where Ri,t is the percentage return of fund i in month t, Rf ,t is
the US T-bill rate for month t, Rm,t is the return on the CRSP
value-weighted index for month t, SMBt is the realization on
the capitalization factor for month t, and HMLt is the realization on the value factor for month t. βi,MKT, βi,SMB, βiSMB,
βi,HML and βi, MOM are the coefficients of the factors (market,
size, value, and momentum, respectively) for stock i, αi is
the intercept or alpha term representing the excess return
not explained by the factors, and ϵi represents the error term.
A positive alpha (α) signifies superior performance considering the level of risk undertaken by the portfolio manager. This success could stem from timing skills, security
selection ability, or better-than-expected performance of
the fund’s owned securities. Conversely, a negative alpha
indicates subpar performance relative to the risk assumed.
Such underperformance may be attributed to poor security
selection or unexpected changes in the prices of the fund’s
holdings.
SMB will exhibit a positive slope denoted as βSMB for
small-company stocks, while large-company stocks will display a negative slope. A positive estimate for βHML indicates
a sensitivity to the value component, whereas a negative
estimate indicates sensitivity to the growth factor. A positive
intercept (α) suggests superior performance compared to the
three-factor model, while a negative intercept (α) indicates
inferior performance.
The momentum factor, βMOM, seeks to capture the tendency where assets that have demonstrated strong recent
performance continue to perform well, while those with
poor recent performance continue to underperform. Typically, this factor relies on the past 6 to 12 months of returns
to assess momentum.
Robustness check
To enhance the reliability of our findings, our analysis
extends to encompass conditional alphas, and market timing and selectivity measures for cannabis ETFs. These additional assessments are undertaken to reinforce the robustness
of our conclusions, thereby ensuring their resilience across
various methodological frameworks and scenarios.
Conditional factor models: Many studies evaluate the
performance of managed funds using metrics that can be
biased due to the inherent volatility of risks and risk premia
over time. However, Ferson and Schadt (1996) introduced
a conditional performance measure that considers common
variation. Their research revealed that incorporating lags of
public information factors, such as interest rates and dividend yields (known to impact stock returns), yields superior
results compared to standard methods. These lagged public
information factors possess valuable information and predictive power for future market movements, enabling more
informed evaluations of ETF performance.
To estimate the conditional measure of performance, Ferson and Schadt (1996) expanded the classic Jensen alpha
model by incorporating a vector of lagged public information variables. This modification enables the estimation of α,
the conditional measure of performance. Instead of relying
on unconditional betas, they transformed the fundamental
models by utilizing time-varying conditional anticipated
returns and betas. These tools are readily available and have
demonstrated effectiveness in predicting stock returns.
This approach employs specific instruments, including
the three-month Treasury bill rate (TR3M), the term structure slope (SLOPE) representing the difference between the
30-year Treasury bond yield and the three-month Treasury bill yield, the corporate bond market quality spread
(QS) represented by the difference between the yield on
Moody’s BAA rated corporate bonds and Moody’s AAA
F. J. Fabozzi, D. K. Malhotra
rated corporate bonds, and the dividend yield on the S&P
500. All these instruments lag by one month to capture the
necessary temporal dynamics.
The following equation presents the resulting conditional
models, where Zj,t-1 represents the demeaned value of the
unconditional elements:
Conditional Carhart four-factor model
(
)
{
(
)}
Ri,t − Rf ,t = 𝛼i + 𝛽i Rm,t − Rf ,t + 𝛿 zt−1 × Rm,t − Rf ,t
+ 𝛽s × SMBt + 𝛽v × HMLt + 𝛽M × MOM + 𝜖i,t
(2)
By incorporating these lagged public information variables and employing time-varying conditional measures, Ferson and Schadt (1996) provide a more robust and accurate
approach to evaluating the performance of managed funds.
Market timing and selectivity: A fund manager’s ability
to choose assets that will generate the projected returns in
the future is known as selectivity. Conversely, market timing refers to the capability of investment managers to adjust
portfolio holdings in response to changes in the asset portfolio or overall market price movements. Studies by Treynor and Mazuy (1966), Kon and Jen (1978), Henriksson
and Merton (1981), and Lee and Rahman (1990) examined
mutual fund market timing and selectivity. These studies
have indicated that mutual fund managers generally underperform in terms of market timing and selectivity.
Treynor and Mazuy (1966) incorporated a quadratic term
into the CAPM to assess market timing and selectivity. They
used another CAPM-based model with a quadratic element
to evaluate managers’ ability to predict market fluctuations.
The four studies cited above revealed that mutual fund managers achieve only moderate success in terms of market timing and selectivity. In this study, we employed two models to
examine market selectivity and timing. The following foundational model introduced by Treynor and Mazuy (1966)
augments the CAPM or market model with a quadratic component to capture market timing and selectivity:
)2
)
(
(
Ri,t − Rf ,t = 𝛼s + 𝛽1 Rm,t − Rf ,t + 𝛽2 × Rm,t − Rf ,t + 𝜀i,t
(3)
The coefficient β2 provides insight into the manager’s
ability to accurately predict market performance by examining the relationship between the portfolio return and the
market return in a non-linear manner. A positive and statistically significant β2 indicates superior market timing skills,
suggesting that the manager can effectively anticipate market
movements. Conversely, a negative and statistically significant β2 suggests poor market timing abilities. A negative
value for β2 indicates that the fund manager lacks market
timing abilities. On the other hand, α represents selectivity,
which refers to the manager’s skill in selecting individual
securities that outperform the market.
Conditional market timing and selectivity
To further analyze the security selection and market timing
abilities of the fund managers of cannabis ETFs, we assess their
performance by constructing conditional market timing and
selectivity models. These models aim to identify the fund managers’ market timing and selectivity skills based on publicly
available information. Building upon the approach proposed
by Ferson and Schadt (1996), the following equation represents
the conditional market timing and selectivity of these funds:
(
)
{
(
)}
Ri,t − Rf ,t = 𝛼i + 𝛽i Rm,t − Rf ,t + 𝛿 zt−1 × Rm,t − Rf ,t
(
)2
+ 𝛽2 × Rm,t − Rf ,t + 𝜀i,t
(4)
Analysis of the downside risk of monthly returns
Value at Risk (VaR) and Expected Shortfall (ES) are two risk
measures commonly used in finance to assess potential losses
in an investment portfolio under adverse market conditions.
Both measures provide insights into the potential downside
risks associated with a cannabis ETF, thus aiding in the evaluation of an ETF’s robustness.
VaR is a statistical measure used to estimate the maximum
potential loss that an investment portfolio may incur over a
specified time horizon at a certain confidence level. For ETFs,
VaR can be employed to understand the potential downside
risk associated with the fund’s investments. A lower VaR indicates that the fund is less exposed to extreme losses, while a
higher VaR suggests higher potential losses during adverse
market conditions. By comparing the VaR of different ETFs,
investors can evaluate which funds demonstrate stronger risk
management and performance stability. This analysis helps
identify ETFs better equipped to handle market volatility and
potential losses, enabling more informed investment decisions.
ES, also known as conditional VAR (CVaR), extends
beyond VaR by providing information about the expected magnitude of losses that exceed the VaR threshold. ES measures
the average loss that can be expected when losses exceed the
VaR threshold. Like VaR, ES helps investors understand the
potential downside risk of an ETF. An ETF with a lower ES
implies that the losses incurred beyond the VaR threshold are
less severe on average, indicating better risk management and
more robust performance.
Empirical analysis
To initiate our empirical examination of cannabis ETFs’
performance in comparison to U.S. and global equities, we
performed a series of analytical procedures encompassing
Rolling in the green? A closer look at cannabis ETFs’ market munchies
correlation analysis, risk-adjusted performance evaluation,
and alpha computations.
Correlation analysis
We begin our empirical analysis by examining the correlation between the monthly returns of cannabis ETFs, S&P
500 Index, and FTSE All World Ex. U.S. Index. Table 2,
which summarizes the results of correlation analysis, shows
that based on monthly returns from January 2016 to April
2023, the correlation between monthly returns of cannabis
ETFs and U.S. and global equities albeit positive at 0.54
and 0.44, respectively, is relatively on the lower side. The
relatively lower correlations suggest that the movements of
cannabis ETFs are not highly synchronized with U.S. and
global equities during this extended time period.
During COVID-19-induced lockdowns and prior to
the start of vaccinations, the correlation between monthly
returns of ETFs, S&P 500 Index, and FTSE All World Ex.
U.S. Index increased to 0.71 and 0.70, respectively. This
suggests a heightened alignment in their performance during
a period of market volatility and uncertainty.
The correlation between monthly returns of ETFs and
U.S. equities remained high even after vaccinations started
at 0.77. On the other hand, the correlation between monthly
returns of ETFs and global equities declined significantly
to 0.28. This suggests a divergence in performance between
cannabis-related investments and the broader global equity
market post-vaccination.
The increased correlation during market turbulence may
indicate that cannabis ETFs are more influenced by broader
market sentiment and economic conditions. The divergence
in correlation with global equities post-vaccination may
Table 2 Correlation among
monthly returns of cannabis
ETFs, S&P 500, and FTSE All
World Ex. U.S. Index
January 2016 to April 2023
Cannabis ETFs
S&P 500 Index
FTSE All World Ex. U.S. Index
January 2020 to January 2021
Cannabis ETFs
S&P 500 Index
FTSE All World Ex. U.S. Index
February 2021 to April 2023
Cannabis ETFs
S&P 500 Index
FTSE All World Ex. U.S. Index
suggest that factors influencing cannabis-related investments
differ from those impacting the global equity market. The
decline in correlation with global equities could present an
opportunity for diversification, as cannabis ETFs may not
move in lockstep with the broader global market.
Risk‑adjusted returns
Table 3 summarizes the risk-adjusted performance of cannabis ETFs relative to U.S. and global equities as proxied
by S&P 500 Index and FTSE All World Ex. U.S. Index,
respectively.
In the analysis spanning from January 2016 to April
2023, as shown in Table 3, it is evident that cannabis ETFs
exhibited subpar performance relative to both the S&P 500
Index and the FTSE All World Ex. U.S. Index across key
performance metrics, including the Sharpe ratio, Sortino
ratio, and Omega ratio. Specifically, the computed Sharpe
ratio, Sortino ratio, and Omega ratio for cannabis ETFs
were −0.10, −0.14, and 0.76, respectively. In contrast, the
S&P 500 Index demonstrated more favorable metrics, with
values of 0.12, 0.17, and 1.35 for the Sharpe ratio, Sortino
ratio, and Omega ratio, respectively. Similarly, the FTSE All
World Ex. U.S. Index outperformed cannabis ETFs, yielding
ratios of 0.18, 0.27, and 1.65 for the Sharpe, Sortino, and
Omega ratios, respectively.
The negative values for the Sharpe and Sortino ratios for
cannabis ETFs indicate that the returns associated with these
investments were tied to higher levels of risk or downside
volatility relative to the risk-free rate or a specified target
level, respectively. Additionally, the Omega ratio below 1
for cannabis ETFs implies that the likelihood of positive
Cannabis ETFs
S&P 500 Index
FTSE All World
Ex. U.S. Index
1.00
0.54
0.44
1.00
0.65
1.00
1.00
0.71
0.70
1.00
0.98
1.00
1.00
0.77
0.28
1.00
0.44
1.00
This table shows the correlation among monthly returns of cannabis ETFs, S&P 500 Index, and FTSE All
World Ex. U.S. index. The analysis encompasses monthly returns from January 2016 to April 2023, as well
as sub-periods including January 2020 to January 2021 (COVID-related lockdowns pre-vaccinations), and
February 2021 to April 2023 (Post-COVID Vaccinations)
F. J. Fabozzi, D. K. Malhotra
Table 3 Risk-adjusted performance analysis of cannabis ETFs, S&P 500, FTSE All World Ex. U.S. Index, and three equally weighted portfolios
Sharpe ratio Sortino ratio Omega ratio
January 2016 to April 2023
Cannabis ETFs
S&P 500 Index
FTSE All World Ex. U.S. Index
Equally weighted portfolio of Cannabis ETFs, S&P 500 Index, and FTSE All World Ex. U.S. Index
Equally weighted portfolio of Cannabis ETFs and S&P 500 Index
Equally weighted portfolio of Cannabis ETFs and FTSE All World Ex. U.S. Index
COVID−19 induced lockdowns to first vaccination (January 2020 to January 2021)
Cannabis ETFs
S&P 500 Index
FTSE All World Ex. U.S. Index
Equally weighted portfolio of Cannabis ETFs, S&P 500 Index, and FTSE All World Ex. U.S. Index
Equally weighted portfolio of Cannabis ETFs and S&P 500 Index
Equally weighted portfolio of Cannabis ETFs and FTSE All World Ex. U.S. Index
February 2021 to April 2023 (post-COVID−19 vaccination rollout period)
Cannabis ETFs
S&P 500 Index
FTSE All World Ex. U.S. Index
Equally weighted portfolio of Cannabis ETFs, S&P 500 Index, and FTSE All World Ex. U.S. Index
Equally weighted portfolio of Cannabis ETFs and S&P 500 Index
Equally weighted portfolio of Cannabis ETFs and FTSE All World Ex. U.S. Index
−0.10
0.12
0.18
0.02
−0.03
−0.02
−0.14
0.17
0.27
0.02
−0.05
−0.04
0.76
1.35
1.65
1.05
0.91
0.93
0.21
−0.01
0.12
0.15
0.15
0.20
0.47
−0.01
0.18
0.25
0.27
0.38
1.80
0.98
1.36
1.50
1.51
1.75
−0.53
0.09
0.29
−0.20
−0.33
−0.31
−0.52
0.14
0.48
−0.23
−0.37
−0.34
0.24
1.25
2.44
0.57
0.39
0.41
This table offers an overview of the risk-adjusted performance, featuring Sharpe, Sortino, and Omega ratios for cannabis ETFs, Standard &
Poor’s 500 index, FTSE All World Ex. U.S. index, and three equally weighted portfolios: one consisting of ETFs, the S&P 500 Index, and the
FTSE All World ex U.S. Index; another of ETFs and the S&P 500 Index; and a third of ETFs and the FTSE All World ex U.S. Index. The analysis spans monthly returns from January 2016 to April 2023, alongside sub-periods including January 2020 to January 2021 (COVID-related
lockdowns pre-vaccinations), and February 2021 to April 2023 (Post-COVID Vaccinations)
returns was comparatively lower in proportion to the likelihood of negative returns, further highlighting the suboptimal
risk–return profile of these investments during the specified
time period.
Conversely, the positive values of the Sharpe and Sortino
ratios for the S&P 500 Index and FTSE All World Ex. U.S.
Index suggest that these indices achieved a more favorable
balance between returns and risk, with the S&P 500 Index
exhibiting slightly higher risk-adjusted performance compared to the FTSE All World Ex. U.S. Index. Moreover, the
Omega ratios exceeding 1 for both indices signify a higher
probability of positive returns relative to negative returns,
emphasizing their more robust risk–return profiles.
Sharpe, Sortino, and Omega ratios underscore the relative underperformance of cannabis ETFs compared to the
S&P 500 Index and FTSE All World Ex. U.S. Index. Investors should consider these findings when assessing their
investment strategies’ risk-adjusted returns and effectiveness, especially considering the metrics observed during the
specified timeframe. During the period from January 2020 to
January 2021, which encompasses the COVID-19 induced
lockdowns and preceding the commencement of vaccinations, an analysis of monthly returns reveals that cannabis
ETFs exhibited superior performance compared to both U.S.
and global equities across key risk-adjusted performance
metrics, namely the Sharpe ratio, Sortino ratio, and Omega
ratio. Specifically, cannabis ETFs outperformed U.S. and
global equities significantly, as evidenced by substantially
higher Sharpe, Sortino, and Omega ratios. The calculated
ratios for cannabis ETFs during this period were 0.21, 0.47,
and 1.80 for the Sharpe, Sortino, and Omega ratios, respectively. In contrast, the S&P 500 Index generated comparatively lower and, in the case of Sharpe and Sortino ratios,
negative values with −0.01, −0.01, and 0.98 for the Sharpe,
Sortino, and Omega ratios, respectively. Similarly, the FTSE
All World Ex. U.S. Index exhibited lower ratios with values
of 0.12, 0.18, and 1.36 for the Sharpe, Sortino, and Omega
ratios, respectively.
The positive values of the Sharpe and Sortino ratios for
cannabis ETFs during this specific period suggest that the
returns associated with these investments were not only
positive but were achieved with lower levels of risk and
downside volatility. Additionally, the Omega ratio exceeding 1 implies a higher likelihood of positive returns relative to negative returns, emphasizing the robust risk–return
profile of cannabis ETFs during this timeframe. Amid the
Rolling in the green? A closer look at cannabis ETFs’ market munchies
COVID-19 pandemic, the cannabis industry showcased
remarkable resilience. In numerous jurisdictions, cannabis
was categorized as an essential business, enabling companies to sustain their operations despite widespread lockdown
measures. Moreover, there was a notable surge in demand for
cannabis products throughout the pandemic period. Many
individuals turned to cannabis as a means of alleviating anxiety and stress brought about by the global health crisis. This
increased demand further, underscoring the significance of
the cannabis industry’s role during times of societal challenge and uncertainty.7
Conversely, the S&P 500 Index and FTSE All World Ex
have negative or lower ratios. U.S. Index during the same
period indicates suboptimal risk-adjusted performance compared to cannabis ETFs. The negative Sharpe and Sortino
ratios for the S&P 500 Index underscore that the returns
associated with this index were associated with higher levels
of risk and downside volatility relative to the risk-free rate
or a specified target level.
The examination of monthly returns from January 2020
to January 2021 reveals a notable outperformance of cannabis ETF compared to U.S. and global equities, emphasizing
the resilience and effectiveness of these investments during a period marked by COVID-19 induced uncertainties.
Investors may find these findings valuable when assessing
the relative performance and risk characteristics of different
asset classes during challenging market conditions.
In the post-vaccination period, following the analysis of
monthly returns, the risk-adjusted performance of cannabis ETFs experienced a significant downturn, as indicated
by notably negative values for the Sharpe, Sortino, and
Omega ratios. Specifically, during this period, the calculated ratios for cannabis ETFs were −0.53, −0.52, and 0.24
for the Sharpe, Sortino, and Omega ratios, respectively.
In contrast, the S&P 500 Index delivered relatively more
favorable ratios, with values of 0.09, 0.14, and 1.25 for the
Sharpe, Sortino, and Omega ratios, respectively. Similarly,
the FTSE All World Ex. U.S. Index exhibited superior ratios
with values of 0.29, 0.48, and 2.44 for the Sharpe, Sortino,
and Omega ratios, respectively.
The negative values of the Sharpe and Sortino ratios cannabis ETFs during this post-vaccination period suggest that
the returns associated with these investments were not only
negative but were achieved with higher levels of risk and
downside volatility. Additionally, the Omega ratio below
1 implies a lower likelihood of positive returns relative to
7
Average store revenue was up 52% to 130% in March 2020 compared with January 2020 at more than 1,300 stores using cannabis
e-commerce platform Jane Technologies. Jane also reports the number of new users ordering online increased 142% over the last month.
(https://​www.​cnbc.​com/​2020/​03/​25/​legal-​canna​bis-​indus​try-​sees-​
record-​sales-​in-​coron​avirus-​crisis.​html).
negative returns, highlighting the diminished risk–return
profile of cannabis ETFs during this specific timeframe.
Conversely, the positive and higher ratios for the S&P 500
Index and FTSE All World Ex. U.S. Index during the same
period indicates more favorable risk-adjusted performance
than cannabis ETFs. The positive Sharpe and Sortino ratios
for these indices suggest that the returns associated with
these investments were positive and achieved with lower
levels of risk and downside volatility.
The notably high Omega ratio for the FTSE All World
Ex. U.S. Index, exceeding 2, implies a significantly higher
likelihood of positive returns relative to negative returns,
emphasizing the robust risk–return profile of this global
equity index during the post-vaccination period.
The assessment of risk-adjusted performance during the
post-vaccination period reveals a marked deterioration in
the performance of cannabis ETFs, contrasting with more
favorable outcomes for the S&P 500 Index and the FTSE
All World Ex. U.S. Index. The financial performance of
cannabis companies faced challenges due to several factors.
These included high operating costs, regulatory compliance
expenses, and restricted access to traditional banking and
financing solutions. These hurdles collectively placed strains
on the profitability and stability of cannabis businesses,
impeding their ability to operate efficiently and compete
effectively within the industry.
Pot stocks have encountered significant challenges
recently, notably due to the removal of legislation, such as
the SAFE Banking Act, aimed at expanding banks’ collaboration with legal cannabis companies. The failure of this
legislation, despite multiple attempts in the previous year,
has caused a severe setback to the industry. The absence
of the SAFE Banking Act means that banks are primarily
prohibited from engaging with marijuana-related companies
due to the substance’s federal illegality. Consequently, many
cannabis firms are forced to operate primarily in cash or
devise alternative methods to navigate the banking system’s
restrictions. Moreover, cannabis companies encounter the
same challenging market dynamics as other stocks, including a potentially weakening economic outlook and a rising
interest-rate environment. These factors collectively contribute to pot stocks’ difficulties in the current landscape.8
Carhart’s Four-Factor Model: Table 4 summarizes
the regression results of Carhart’s four-factor model. The
adjusted ­R2, indicative of the model’s explanatory power,
displays variations throughout the studied durations. From
January 2016 to April 2023, the model explained 43% of
the variance in cannabis ETF returns, signifying a moderate explanatory capability. In the subsequent period from
8
https://​fortu​ne.​com/​2023/​04/​20/​canna​bis-​stocks-​pot-​marij​uana-​
indus​try/
F. J. Fabozzi, D. K. Malhotra
January 2020 to January 2021, the adjusted ­R2 maintained
a robust 41%, underscoring the model’s resilience. Notably,
from February 2021 to April 2023, there is a marked surge in
the adjusted ­R2 to 67%, denoting an augmented explanatory
power during this specific period.
The alpha, denoting abnormal returns beyond market factors, consistently indicates underperformance of cannabis
ETFs. Throughout the period from January 2016 to April
2023, the alpha is −2.65%, indicating an average underperformance when adjusted for market risk, size, value, and
momentum factors. Similarly, in the timeframe from January
2020 to January 2021, the alpha remains at −1.77%, signifying persistent underperformance. Notably, from February
2021 to April 2023, the alpha witnessed a significant decline
to −6.67%, marking a more pronounced underperformance
during this latter period. Also, the alphas are statistically
significant for the periods January 2016 to April 2023 and
February 2021 to April 2023, which implies persistent
Table 4 Carhart four-factor model analysis of monthly returns of cannabis funds
Adjusted R2
Alpha
Mkt-RF
SMB
HML
MOM
January 2016 to January 2020 to
April 2023
January 2021
February 2021
to April 2023
0.43
−2.65*
1.50***
1.21***
−0.12
0.08
0.67
−6.67***
1.74***
1.58***
0.51*
0.09
0.41
−1.77
1.19
2.54
−0.32
0.41
***
Statistically significant at the 1% significance level, **statistically
significant at the 5% significance level, * statistically significant at the
10% significance level.
This table displays the outcomes of the Carhart four-factor model,
examining monthly returns from January 2016 to April 2023. Furthermore, it furnishes insights for sub-periods spanning January 2020
to January 2021 (COVID-related lockdowns pre-vaccinations), and
February 2021 to April 2023 (Post-COVID Vaccinations)
Table 5 Comparative analysis
of monthly net alphas using the
four-factor model for cannabis
ETFs, S&P 500, and FTSE All
World Ex. U.S. Index
January 2016 to April 2023
COVID-19 induced lockdowns to
first vaccination (January 2020 to
January 2021)
February 2021 to April 2023 (PostCOVID-19 vaccination rollout
period)
***
underperformance of cannabis ETFs relative to the overall
market.
The Market Risk Factor (Mkt-RF), reflecting the sensitivity of cannabis ETF returns to market movements, displays
variations. Across all periods, there is a positive relationship
between market returns and cannabis ETF returns, which
means that these ETFs are exposed to systematic risk factors.
From January 2016 to April 2023, the coefficient is 1.50,
indicating a significant positive relationship. In the subsequent period from January 2020 to January 2021, the coefficient decreases to 1.19, suggesting a somewhat weakened
positive relationship. However, from February 2021 to April
2023, the coefficient rises to 1.74, indicating a strengthened
positive relationship during this specific period. The coefficient for the market risk factor is statistically significant for
January 2016 to April 2023, as well as for February 2021
to April 2023.
We also find that, on average, cannabis ETF returns tend
to increase when companies are smaller (SMB), have higher
value (HML), and show positive momentum (MOM).
The coefficient for the SMB factor is positive and statistically significant, suggesting that, according to Carhart’s
model, the size factor contributes meaningfully to explaining the expected excess returns of the asset or portfolio in
question. Smaller firms performed better than larger firms
in generating excess returns. Between January 2020 and
January 2021, the impact of higher value (HML) was negative, meaning it did not help much during that period. On
the other hand, smaller size (SMB) and positive momentum
(MOM) still had a good effect.
Moving forward to February 2021 to April 2023, the positive effects of smaller size (SMB) and positive momentum
(MOM) continued. Interestingly, the impact of higher value
(HML) changed—it became positive, meaning it started to
help during this later period.
We also compared the alphas for cannabis ETFs to those
for the S&P 500 Index and FTSE All World Ex. U.S. Index
Cannabis ETFs
S&P 500 Index
FTSE All
World Ex. U.S.
Index
−2.65***
−1.77
−0.23
−0.79
0.27
−0.78
−6.67***
−0.25
0.84
Statistically significant at the 1% significance level
This table compares monthly net alphas for cannabis ETFs, S&P 500 Index, and FTSE All World Ex. U.S.
index based on the four-factor model. The analysis covers monthly returns from January 2016 to April
2023, with additional insights offered for sub-periods including January 2020 to January 2021 (COVIDrelated lockdowns pre-vaccinations), and February 2021 to April 2023 (Post-COVID Vaccinations)
Rolling in the green? A closer look at cannabis ETFs’ market munchies
Table 6 Monthly net alphas for cannabis ETFs using conditional
four-factor model
January 2016 to April 2023
COVID-19 induced lockdowns
to first vaccination (January
2020 to January 2021)
February 2021 to April 2023
(Post-COVID-19 vaccination
rollout period)
***
Table 7 Results of Treynor–Mazuy and conditional Treynor–Mazuy
models for alpha (α) and beta (β) values
Multi-factor model
Adjusted
R-square
Treynor–Mazuy
Model
Conditional Treynor–Mazuy Model
−1.08
−9.74
0.44
0.33
αs
αs
−6.64***
0.63
Statistically significant at the 1%-significance level.
This table displays the monthly net alphas for cannabis ETFs using
the conditional four-factor model. The data include monthly returns
from January 2016 to April 2023, providing insights into distinct
sub-periods: January 2020 to January 2021 (pre-vaccination COVIDrelated lockdowns) and February 2021 to April 2023 (post-COVID
vaccinations)
for the period January 2016 to April 2023 (full sample),
COVID-19 (January 2020 to January 2021), and PostCOVID-19 (February 2021 to April 2023). Table 5 summarizes the results for the Carhart four-factor model. Over the
period from January 2016 to April 2023, the performance of
cannabis ETFs, as measured by Carhart’s four-factor model,
exhibited a noteworthy alpha of −2.65, indicating a statistically significant underperformance compared to the S&P
500 Index, which showed an alpha of −0.23, and the FTSE
All World Ex. U.S. Index, which demonstrated a positive
alpha of 0.27.
During the phase encompassing the onset of COVID19-induced lockdowns in January 2020 to the first vaccination in January 2021, cannabis ETF recorded an alpha of
−1.77. In contrast, the S&P 500 Index and the FTSE All
World Ex. U.S. Index displayed comparatively lower alphas
of −0.79 and −0.78, respectively. This period suggests a
general decline in performance across the analyzed indices,
with cannabis ETFs experiencing a relatively more pronounced negative impact.
In the subsequent period from February 2021 to April
2023, which marks the post-COVID-19 vaccination rollout
phase, cannabis ETFs displayed a substantial alpha of −6.67,
signifying a considerable underperformance. In contrast, the
S&P 500 Index showed a marginal alpha of −0.25, while
the FTSE All World Ex. U.S. Index exhibited a contrasting
positive alpha of 0.84. This period underscores a heightened
divergence in performance, with cannabis ETFs facing significant challenges compared to the broader market indices,
particularly during the post-vaccination period.
Table 6 summarizes the results of applying the conditional Carhart’s four-factor model to monthly returns of
cannabis ETFs. Across the period from January 2016 to
April 2023, the analysis shows an alpha of −1.08, indicating
January 2016 to April
2023
January 2020 to January
2021
February 2021 to April
2023
*
β2
β2
−3.24
0.01
−2.88
−0.001
(−2.46**)
(0.46) (−2.03**) (−0.03)
0.31
0.01
−0.63
0.14
(0.05)
(0.15) (−0.10)
0.55
−5.60
−0.04
−4.81
−0.04
(−2.47**) (−0.78) (−2.13**) (−0.76)
*Significant at the 5%.
This table provides the results of the Treynor–Mazuy model and conditional Treynor–Mazuy model, displaying alpha (α) and beta (β) values across distinct time intervals. The data span from January 2016
to April 2023, with delineations for January 2020 to January 2021
and February 2021 to April 2023. Alpha and beta values are supplemented by t-statistics, denoting their statistical significance. Beta values reflect the asset’s market sensitivity
underperformance relative to the market with an adjusted
R-squared of 0.44. During the COVID-19 lockdowns (January 2020 to January 2021), a significant alpha of −9.74 indicates substantial underperformance. The adjusted R-squared
for this period is 0.33. In the post-vaccination phase (February 2021 to April 2023), the model shows a statistically
significant alpha of −6.64, suggesting continued underperformance. The adjusted R-squared increases notably to 0.63,
indicating stronger explanatory power post-vaccination.
We also investigated the market timing and security selection abilities of cannabis ETF fund managers employing the
Treynor and Mazuy (1966) model. The outcomes of this
examination are shown in the second and third columns of
Table 6, offering insights into the managers’ capacity to time
the market and make effective security selections strategically. For the January 2016 to April 2023 period, the α value
of −3.24% is statistically significant at the 5% level. This
negative α suggests underperformance, indicating that the
fund managers, on average, exhibited selectivity that led to
lower returns than the benchmark. The β2 value is 0.01 and
is not statistically significant, suggesting that, on average,
market timing did not play a significant role in the fund managers’ performance during this period.
During the January 2020 to January 2021 period, the α
value is 0.31 and is not statistically significant at the 5%
level. This α suggests that, during this period, the selectivity of fund managers did not lead to statistically significant outperformance or underperformance relative to the
benchmark. The β2 value is 0.01, which is not statistically
significant, indicates that market timing also did not contribute significantly to performance during this specific
period.
F. J. Fabozzi, D. K. Malhotra
For the February 2021 to April 2023 period, the α value
is −5.60, which is statistically significant at the 5% level,
indicating that, on average, fund managers exhibited selectivity that led to a statistically significant underperformance
during this period. The −0.04 value for β2 is not statistically
significant and, therefore, suggests that market timing, on
average, did not play a significant role in fund managers’
performance during this later period.
Results of the conditional market timing and selectivity
model are summarized in the last two columns of Table 7.
These results mirror those presented in the second and third
columns in the table. Negative alphas are observed across all
sample periods, with statistically significant negative alphas
recorded from January 2016 to April 2023 and from February 2021 to April 2023. This suggests inadequate security
selection by portfolio managers. Additionally, β2 is negative,
though it lacks statistical significance.
Table 8 summarizes the results of the two downside risk
measures, VaR and ES, of the monthly returns of cannabis
ETFs, the S&P 500 Index, and the FTSE All World Ex. U.S.
Index, and three equally weighted portfolios: one consisting
of ETFs, the S&P 500 Index, and the FTSE All World ex
U.S. Index; another of ETFs and the S&P 500 Index; and a
third of ETFs and the FTSE All World ex U.S. Index.
For cannabis ETFs, the VaR is −21%, indicating a 95%
probability that the maximum loss will not exceed 21% over
the specified time horizon. In contrast, the S&P 500 Index
has a VaR of −9.92%, suggesting a 95% probability that
losses will not surpass 9.92%. Similarly, the FTSE All World
Ex U.S. Index has a VaR of −7.65%, meaning there is a 95%
probability that the maximum loss will not exceed 7.65%.
This comparison reveals that cannabis ETFs have the
highest VaR, indicating greater exposure to potential losses
under adverse market conditions than the S&P 500 Index
and the FTSE All World Ex U.S. Index.
The ES for cannabis ETFs is −25.32%, signifying that
the average loss, when losses exceed the VaR threshold, is
25.32%. The S&P 500 Index has an ES of −13.07%, meaning
the average loss beyond the VaR threshold is 13.07%. The
FTSE All World Ex U.S. Index shows an ES of −11.12%,
indicating an average loss of 11.12% when losses exceed the
VaR threshold.
These results indicate that cannabis ETFs also have the
highest ES, suggesting that when losses exceed the VaR
threshold, they are more severe than those in the S&P 500
Index and the FTSE All World Ex U.S. Index.
The data suggest that cannabis ETFs are riskier compared to the S&P 500 Index and the FTSE All World Ex
U.S. Index, as evidenced by their higher VaR and ES values.
Specifically, the higher VaR for cannabis ETFs indicates a
greater potential for extreme losses within the specified confidence level. Additionally, the higher ES for cannabis ETFs
implies that the severity of losses beyond the VaR threshold
is greater.
Upon analyzing the equally weighted portfolios that combine cannabis ETFs with broader market indices, it is evident that the risk is significantly reduced compared to the
risk associated with cannabis ETFs alone. The VaR for the
portfolio consisting of cannabis ETFs, the S&P 500 Index,
and the FTSE All World ex. U.S. Index is −11.90 with an
ES −14.38%, indicating a substantial enhancement in risk
mitigation through diversification across these three asset
classes.
Similarly, the VaR of the equally weighted portfolio of
cannabis ETFs and the S&P 500 Index is −15.80%, with an
ES of −17.98%. While the risk associated with these portfolios remains higher than that of the broader indices alone,
they still offer a significant reduction in risk compared to
investing solely in cannabis ETFs. Investors should consider
these higher downside risks when evaluating cannabis ETFs,
despite their potential for high returns or other attractive
characteristics. On the other hand, the S&P 500 Index and
the FTSE All World ex U.S. Index appear to be less risky in
terms of potential and average extreme losses.
Table 8 Results of value at risk (VaR) and expected shortfall (ES)
Cannabis ETFs (%) S&P 500 Index (%) FTSE All World
Ex U.S. Index
(%)
VaR at 95% confi- −21
dence interval
Expected shortfall −25.32
Equally weighted
portfolio of Cannabis ETFs, S&P 500
Index, and FTSE
All World Ex. U.S.
Index (%)
Equally weighted
portfolio of Cannabis ETFs and S&P
500 Index (%)
Equally weighted
portfolio of Cannabis ETFs and FTSE
All World Ex. U.S.
Index (%)
−9.92
−7.65
−11.90
−15.80
−13.47
−13.07
−11.12
−14.38
−17.98
−16.18
This table provides VaR and ES for cannabis ETFs, S&P 500 Index, FTSE All World Ex U.S. Index, and three equally weighted portfolios: one
consisting of ETFs, the S&P 500 Index, and the FTSE All World ex U.S. Index; another of ETFs and the S&P 500 Index; and a third of ETFs
and the FTSE All World ex U.S. Index. The analysis is based on monthly returns from January 2016 to April 2023. Value at Risk is computed at
the 95% confidence level
Rolling in the green? A closer look at cannabis ETFs’ market munchies
Summary and conclusions
Investors, drawn to the growing cannabis industry, are
directing their focus toward cannabis ETFs. Despite the
allure of the cannabis industry, our study indicates that these
ETFs consistently lagged behind both U.S. and global equity
counterparts. This suggests that the cannabis sector may
involve higher inherent risks than traditional equity investments. The relatively low positive correlation between the
average monthly returns of cannabis ETFs and both US and
global stocks indicate that investing in the cannabis sector
may offer some diversification benefits. However, investors
should not rely solely on cannabis ETFs for diversification
as they underperformed traditional equities over the sample
period.
Our study’s risk-adjusted performance analyses indicate
that cannabis ETFs generally underperformed compared to
U.S. and global equities. The findings highlight the volatility experienced by cannabis ETFs during the COVID-19
pandemic and suggest suboptimal security selection by ETF
fund managers, with no clear evidence of effective market
timing abilities. While portfolios that included both cannabis
ETFs and broader market indices offered modest risk reduction compared to investing solely in cannabis ETFs, they
consistently produced lower risk-adjusted returns than traditional stock indices across all time periods examined. Diversification benefits were particularly evident during the volatile COVID-19 lockdown period but proved less significant
in the post-vaccination market environment. This research
underscores the challenges of achieving risk-adjusted solid
returns from cannabis ETFs, particularly when combined
with more stable investments.
The research also found that the equally weighted portfolios offer a compromise between the high risk of cannabis
ETFs and the lower risk of traditional equity indices. These
portfolios mitigate the excessive downside risk associated
with cannabis ETFs by combining them with broader market
indices, as evidenced by the reduced VaR and ES figures.
However, they do not achieve the low-risk levels of the S&P
500 or FTSE All World Ex. U.S. indices suggest that diversification is beneficial but does not entirely eliminate the
inherent risks of investing in cannabis ETFs.
Further research is needed to understand the long-term
prospects of cannabis ETFs fully and to assess the effects
of changing regulations on their performance as the sector
continues to evolve. While cannabis ETFs provide access to
a rapidly expanding industry, they carry considerable risks
due to regulatory uncertainty and market volatility. Before
incorporating these ETFs into their investment portfolios,
investors should carefully evaluate their risk tolerance. To
manage these risks effectively, adopting diversified investment strategies is crucial.
The observed underperformance of cannabis ETF compared to traditional equities highlights the importance of
adopting cautious investment strategies in this emerging sector. This research underscores the need for additional studies
to evaluate the long-term potential of cannabis ETFs and to
understand the implications of evolving regulations on their
performance. Investors must maintain continuous scrutiny
as they navigate the green frontier of this maturing industry.
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Publisher's Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Frank J. Fabozzi is a Professor of Practice at John Hopkins’ Carey
Business School. Frank is the editor of The Journal of Portfolio Management, co-editor of The Journal of Financial Data Science, and an
editor of Annals of Operations Research. From 1988 to 2023, he served
on the board of directors of BlackRock fixed income complex. He is
the CFA Institute’s 2007 recipient of the C. Stewart Sheppard Award
and 2015 recipient of the James R. Vertin Award. He was inducted into
the Fixed Income Analysts Society Hall of Fame in November 2002.
Frank earned a BA (magna cum laude) and MA in economics in 1970
from The City College of New York where he was elected to Phi Beta
Kappa and a PhD in economics in 1972 from the City University of
New York. He has earned the designations of CFA and CPA.
D. K. Malhotra is a Professor of Finance at Thomas Jefferson University. He has published numerous articles in finance journals, winning
several awards – CBOT Best Paper Award at the Southwest Finance
Association Meeting, Best Paper Award at the Southeast Decision Sciences meetings (1998 and 2013), Research Award at IABPAD Conference (2010 and 2013), and McGraw-Hill/Irwin Distinguished Paper
Award in International Business Studies at the Federation of Business
Discipline Conference (2013). The Securities and Exchange Commission has cited his research on mutual fund expenses, Investment
Company Institute, Securities Industry Association, The Wall Street
Journal, and New York Times. His research has also been cited in Congressional testimonies on mutual fund expenses. Dr. Malhotra earned
a doctorate and masters in finance from the University of Alabama and
a master’s in commerce from the University of Delhi.