Factor Cyclicality: Understanding the Shifts
Factor investing thrives on the concept that factors tend to outperform the broader market during different economic phases. These phases, in turn, can be influenced by broader macroeconomic conditions such as interest rates, inflation, GDP growth, and geopolitical events. Factor cyclicality refers to the tendency of different factors to perform better or worse depending on these changing economic conditions.
For instance, momentum tends to thrive during expansions, while low volatility and quality outperform in downturns. Understanding factor cyclicality is crucial for optimising portfolios by aligning factors with the prevailing economic environment.
Factor Cyclicality in the Indian Context
Academic studies and real-world evidence support the idea that factor cyclicality is an important consideration. Research by academics such as Fama and French (1993) on the three-factor model, has highlighted that factor performance varies over time, influenced by broader economic and market cycles. Their findings emphasize the role of multifactor strategies in diversifying across multiple factors to improve risk-adjusted returns and reduce exposure to any single factor’s inherent volatility.
The application of factor investing in emerging markets like India comes with its own unique set of challenges, largely due to the differences in market microstructure, data availability, and liquidity compared to developed markets. Nonetheless, Indian market research has revealed the behaviour of different factors through varying economic cycles.
Dynamic Adjustments for Optimal Returns
Bijoy and Kedia (2023) underscore the importance of adapting factor strategies to prevailing market conditions. Their study found that factors like trading volume, dividend yield, and long-term volatility significantly impact abnormal returns. Dynamic adjustments to factor exposures, rather than static strategies, can lead to better performance by leveraging current market opportunities.
Understanding Market Cyclicality
A working paper from the Madras School of Economics highlights the critical role of understanding market cyclicality. The research emphasises that market participants’ behaviour shifts across economic cycles, influencing factor performance. Recognizing these shifts helps investors anticipate changes and refine their strategies to stay ahead of market dynamics.
These findings highlight the cyclical nature of factor performance, underscoring the importance of managing factor exposure based on the prevailing economic environment to enhance risk-adjusted returns in the Indian market. The unique nature of the Indian stock market, as shown in these studies, calls for tailored factor strategies.
The table below shows the historical calendar year performance of various factors:
Factor |
2006* |
2007 |
2008 |
2009 |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
2018 |
2019 |
2020 |
2021 |
2022 |
2023 |
2024* |
NJ Quality+ |
3.04 |
50.12 |
-52.39 |
114.47 |
33.43 |
-15.82 |
33.14 |
6.34 |
60.27 |
11.42 |
7.46 |
42.24 |
-2.32 |
2.92 |
24.85 |
49.62 |
4.51 |
56.67 |
28.18 |
NJ Enhanced Value |
9.12 |
58.94 |
-60.87 |
122.88 |
25.36 |
-28.80 |
38.01 |
1.50 |
66.04 |
10.84 |
3.18 |
48.49 |
-13.97 |
-0.06 |
23.46 |
48.03 |
3.17 |
35.28 |
19.14 |
NJ Traditional Value |
2.07 |
76.79 |
-64.28 |
160.38 |
30.81 |
-32.51 |
35.37 |
-10.74 |
72.35 |
5.87 |
16.88 |
48.22 |
-19.97 |
-13.33 |
14.80 |
53.67 |
10.70 |
56.57 |
27.20 |
NJ Momentum+ |
12.98 |
89.56 |
-58.68 |
96.74 |
28.92 |
-17.03 |
43.71 |
3.00 |
81.74 |
15.22 |
0.22 |
69.43 |
-7.92 |
9.16 |
37.75 |
55.99 |
6.75 |
47.78 |
32.17 |
NJ Low Volatility+ |
7.13 |
37.75 |
-46.47 |
98.97 |
34.53 |
-10.72 |
31.86 |
5.83 |
60.72 |
10.65 |
10.53 |
36.43 |
0.27 |
2.17 |
17.84 |
31.65 |
3.60 |
38.59 |
21.47 |
Nifty 500 TRI |
10.55 |
64.58 |
-56.78 |
85.67 |
15.27 |
-26.40 |
33.48 |
3.89 |
39.12 |
0.04 |
4.68 |
37.65 |
-1.55 |
8.64 |
17.70 |
30.95 |
4.25 |
26.91 |
16.00 |
*Does not represent a complete calendar year. | Past performance may or may not sustain in future.
Factor Cyclicality During Major Economic Events
The analysis of factor performance during significant economic crises, such as the Global Financial Crisis (GFC) and the COVID-19 pandemic, reveals distinct patterns across different investment factors and regions. By comparing performance across three periods i.e. pre-crisis, during the crisis, and post-crisis, we can understand the cyclicality of factors and their resilience.
India
Global Financial Crisis
COMPARATIVE ANALYSIS OF FACTOR PERFORMANCE DURING GLOBAL FINANCIAL CRISIS GFC |
Portfolio Returns |
Pre GFC Bull-Period (30/09/2006 to 31/12/2007) |
GFC Correction (01/01/2008 to 31/03/2009) |
Post GFC Recovery (01/04/2009 to 31/12/2010) |
NJ Quality+ |
54.67% |
-53.87% |
197.47% |
NJ Momentum+ |
114.17% |
-59.77% |
163.90% |
NJ Low Volatility+ |
47.57% |
-46.29% |
170.94% |
NJ Enhanced Value |
73.43% |
-63.16% |
196.78% |
NJ Traditional Value |
80.45% |
-65.45% |
250.88% |
NJ Multi Factor+ |
68.63% |
-51.66% |
168.66% |
Nifty 500 - TRI |
82.15% |
-56.67% |
116.72% |
Source: Internal research, CMIE, NJ’s Smart Beta Platform (in-house proprietary model of NJAMC). Calculations are for the specific periods mentioned in the respective column. NJ Quality+, NJ Momentum+, NJ Low Volatility+, NJ Traditional Value, NJ Enhanced Value and NJ Multi Factor+ are in-house proprietary methodologies developed by NJ Asset Management Private Limited. The methodologies will keep evolving with new insights based on the ongoing research and will be updated accordingly from time to time. Past performance may or may not be sustained in the future and is not an indication of future return. The above is only for illustration purposes and should not be construed as indicative return of offering of NJ Asset Management Private Limited.
Covid-19 Pandemic
COMPARATIVE ANALYSIS OF FACTOR PERFORMANCE DURING COVID-19 PANDEMIC |
Portfolio Returns |
Pre Pandemic Period (01/01/2019 to 31/12/2019) |
During Pandemic Period (01/01/2020 to 23/03/2020) |
Post Pandemic Period (24/03/2020 to 31/12/2021) |
NJ Quality+ |
2.92% |
-33.47% |
179.90% |
NJ Momentum+ |
9.16% |
-30.75% |
208.87% |
NJ Low Volatility+ |
2.17% |
-30.00% |
120.19% |
NJ Enhanced Value |
-0.06% |
-39.28% |
202.92% |
NJ Traditional Value |
-13.33% |
-43.50% |
217.70% |
NJ Multi Factor+ |
-1.74% |
-32.74% |
166.51% |
Nifty 500 - TRI |
8.64% |
-36.67% |
139.79% |
Source: Internal research, CMIE, NJ’s Smart Beta Platform (in-house proprietary model of NJAMC). Calculations are for the specific periods mentioned in the respective column. NJ Quality+, NJ Momentum+, NJ Low Volatility+, NJ Traditional Value, NJ Enhanced Value and NJ Multi Factor+ are in-house proprietary methodologies developed by NJ Asset Management Private Limited. The methodologies will keep evolving with new insights based on the ongoing research and will be updated accordingly from time to time. All the indices have been scaled to Rs.1,000 as of 30th September 2006. Past performance may or may not be sustained in the future and is not an indication of future return. The above is only for illustration purposes and should not be construed as indicative return of offering of NJ Asset Management Private Limited.
USA
Global Financial Crisis
COMPARATIVE ANALYSIS OF FACTOR PERFORMANCE DURING GLOBAL FINANCIAL CRISIS (GFC) |
Portfolio Returns |
Pre GFC Bull-Period (30/09/2006 to 31/12/2007) |
GFC Correction (01/01/2008 to 31/03/2009) |
Post GFC Recovery (01/04/2009 to 31/12/2010) |
S&P 500 Quality TRI |
24.43% |
-37.50% |
55.82% |
S&P 500 Enhanced Value TRI |
5.72% |
-58.62% |
95.23% |
S&P 500 Momentum TRI |
16.47% |
-37.98% |
45.92% |
S&P 500 Low Volatility TRI |
6.85% |
-28.50% |
47.71% |
S&P 500 QVM Multi-factor TRI |
26.96% |
-39.99% |
44.99% |
S&P 500 TRI |
12.56% |
-43.94% |
60.83% |
Source: Internal research, Bloomberg. Calculations are for the specific periods mentioned in the respective column. Past performance may or may not be sustained in the future and is not an indication of future return. The above is only for illustration purposes and should not be construed as indicative return of offering of NJ Asset Management Private Limited.
Covid-19 Pandemic
COMPARATIVE ANALYSIS OF FACTOR PERFORMANCE DURING COVID-19 PANDEMIC |
Portfolio Returns |
Pre Pandemic Period (01/01/2019 to 31/12/2019) |
During Pandemic Period (01/01/2020 to 23/03/2020) |
Post Pandemic Period (24/03/2020 to 31/12/2021) |
S&P 500 Quality TRI |
33.91% |
-28.88% |
92.72% |
S&P 500 Enhanced Value TRI |
29.22% |
-47.88% |
107.62% |
S&P 500 Momentum TRI |
26.25% |
-26.15% |
93.80% |
S&P 500 Low Volatility TRI |
28.26% |
-31.90% |
64.99% |
S&P 500 QVM Multi-factor TRI |
26.18% |
-32.31% |
84.68% |
S&P 500 TRI |
31.49% |
-30.43% |
100.22% |
Source: Internal research, Bloomberg. Calculations are for the specific periods mentioned in the respective column. Past performance may or may not be sustained in the future and is not an indication of future return. The above is only for illustration purposes and should not be construed as indicative return of offering of NJ Asset Management Private Limited.
Europe
Covid-19 Pandemic
COMPARATIVE ANALYSIS OF FACTOR PERFORMANCE DURING COVID-19 PANDEMIC |
Portfolio Returns |
Pre Pandemic Period (01/01/2019 to 31/12/2019) |
During Pandemic Period (01/01/2020 to 23/03/2020) |
Post Pandemic Period (24/03/2020 to 31/12/2021) |
S&P Europe 350 Quality TRI |
35.34% |
-31.37% |
73.92% |
S&P Europe 350 Enhanced Value TRI |
20.46% |
-48.05% |
96.54% |
S&P Europe 350 Momentum TRI |
31.88% |
-24.84% |
67.49% |
S&P Europe 350 Low Volatility TRI |
26.84% |
-27.69% |
52.99% |
S&P Europe 350 QVM Multi-factor TRI |
31.49% |
-30.43% |
100.22% |
S&P Europe 350 TRI |
27.24% |
-32.16% |
66.48% |
Source: Internal research, Bloomberg. Calculations are for the specific periods mentioned in the respective column. Past performance may or may not be sustained in the future and is not an indication of future return. The above is only for illustration purposes and should not be construed as indicative return of offering of NJ Asset Management Private Limited.
The comparison of factor performance during the COVID-19 pandemic and the Global Financial Crisis reiterates the importance of factor cyclicality in building a robust portfolio. While single-factor strategies can perform exceptionally well during certain market phases, their reliance on a singular factor exposes investors to concentrated risks.
On the other hand, multifactor strategies provide diversification across factors, allowing investors to capture different risk premiums and achieve more stable returns over time. By understanding factor cyclicality and adjusting factor exposures based on macroeconomic conditions, investors can enhance their portfolios and reduce the impact of economic fluctuations.