Investigating the Impact of the Announcement of Loan Moratorium on Stock Prices: Evidence from Indian Public Sector Banks

Abstract

The present article applies event study methodology in an attempt to investigate the impact of the announcement of 3-month moratorium by Reserve Bank of India on Indian public sector bank equity returns. For the present study, the estimation period is considered to be 120 trading days while the event window is considered to be 21 trading days. To compute the expected returns, the study uses a single-index model or the market model proposed by Fama [Fama, E., 1976. Foundations of finance. Basic Books]. The findings of the study suggest that the market responded to the news relating to the liquidity infusion by the Reserve Bank of India, falling global indices, development of potential coronavirus vaccine, and the announcement of 3 weeks period lockdown. The study further concluded that the market anticipated that the government may announce loan moratorium since industry bodies like The Associated Chambers of Commerce and Industry of India and The Federation of Indian Chambers of Commerce and Industry have recommended loan moratorium in order to safeguard the business enterprises especially the micro-, small- and medium-enterprise sector. Thus, the adjustment in the bank stock prices occurred before the announcement of the 3-month loan moratorium and as a consequence the average annual return on day ED-0 is found to be insignificant.

Keywords

Loan moratorium event study methodology single-index model coronavirus pandemic

Introduction

The coronavirus outbreak that was first reported in China has not only disrupted the healthcare system of many countries but also affected their economies. India, so far, has suffered heavily due to the outbreak. The nationwide lockdown for 21 days resulted in closing down of all major economic activities as a result of which the small businesses were severely affected and micro-, small- and mediumenterprises (MSMEs) came forward as a drowning unit. In order to maintain stability and liquidity in the debt, money and foreign exchange market and to provide relief to small businesses the Reserve Bank of India had to infuse liquidity and announce a 3-month loan moratorium. Although the announcement of loan moratorium came as a relief for debtors but it is a burden for banks. During the moratorium period, the banks will not get the interest payments and after the moratorium period ends, there is no surety that the probability of defaults will be lessening and the asset quality of banks will be maintained. Further, with no interest earnings and lack of demand for loans, the banks will lose their credit creation capacity. In the context of the present study, the announcement of the loan moratorium may have impacted the stocks returns of the banking sector amid all other news related to COVID-19. On the basis of the study of Mansur et al. (1991) and Philippatos and Viswanathan (1994), the present study hypothesize that information related to deteriorating asset quality of banks may be priced negatively in the market. In other words, the market will negatively price the securities of banks and other financial institutions as a result of the announcement of a 3-month loan moratorium.

On March 27 the announcement for 3-month loan moratorium was made while on May 22, further extension of loan moratorium was announced. Thus, as we prepare the article two announcements have been made so far regarding the loan moratorium. However, the present study will focus on the first announcement of a 3-month loan moratorium made on March 27 and investigate the impact of the announcement on the stock prices of Indian public sector banks using the event study methodology.

The efficient market hypothesis suggests the ways for calculating the expected returns. This paves the way for the birth of event studies. The event studies were invented to know the magnitude of impact created by a particular economic event on the stock prices over a short period of time by comparing the actual return to the theoretical return computed on the basis of efficient-market hypothesis. Central to an event study is the measurement of an abnormal stock return. The first evidence of event study was found in Dolley (1933) and it was related to stock price adjustment with the information of stock splits (Mackinlay, 1997). The studies by Ball and Brown (1968) and Fama et al. (1969) used the methodologies which we use today for conducting event studies and so, the studies are considered as pioneering for the present event analysis methodology. Ball and Brown (1968) suggested that if on releasing any information the actual income change is less than the conditional expected return, define it as a bad news and also if the association is found between the two, the information will always produce results less than what is conditionally expected and vice versa. The main concern of Fama et al. (1969) was to capture the abnormal behavior, if any, of stock returns in case of stock splits. The study considered 622 securities listed in the New York stock exchange and used the market model. Stock splits were found to be the reason for adjustments in stock prices but only to the extent that they were associated with the anticipated future dividend changes. Anand and Singh (2008) investigated five mergers in Indian banking sector during 1999 to 2005 using event study. The market model and two-factor model were used for arriving at the calculations of cumulative average returns and the study found that both the acquirer and target banks were able to reap benefits of significant and positive stock returns in all the concerned mergers except one. Overall, the study concluded that mergers were beneficial for both the acquirer bank and target bank and also for the combined unit which resulted after merger. Mishra (2005) investigated the reaction of stock prices when announcements related to bonus issues are made. Using event study methodology, the study found that the significant positive returns were observed on eighth or ninth day prior to the announcement date and on the event day the returns were negative. The study argued that due to the information leakage, the information might have been adjusted prior to the event date.

The remainder of the article has four sections: “Literature Review” section highlights the findings of some of the important articles available on announcement of loan moratorium and its impact on stock prices. The section “Data and Methodology” discusses the sample size, source of the data and the methodology applied. The section “Results and Discussion” presents the empirical findings and provides interpretation of the results. The section “Conclusion” provides the concluding remarks.

Literature Review

The studies related to debt moratorium were also done by using event study methodology and extensively cover the impact of announcement of Latin American debt moratoria. Mansur et al. (1991) examined the equity returns of large US and European commercial banks listed in the London stock exchange in order to know the effects of announcement of interest payment moratorium in Brazil. The moratorium was announced on February 27, 1987. Daily returns of 60 pre-event trading days and 30 post-event trading days were considered for analysis and the study used the market model for calculating the excess returns. The significance of excess returns and cumulative excess returns were tested and the study concluded that the London market reacted quickly to the announcement which supports the information effect hypothesis. In addition, the study examined if the equity returns deteriorated according to the banks’ level of exposure to loans and found that the market equally penalized all the banks even if they were having different levels of loan exposure. Thus, the results supported the nondiscriminating exposure hypothesis. Bruner and Simms (1987) anticipated the deterioration of asset quality due to the announcement for the cease of principal payment of its external debt by Mexico and consequently fall in security returns of large US banks as these banks had loan assets in Mexico. The study selected 48 banks among the 200 largest banks listed on the New York stock exchange and considered the security prices of the banks from 100 trading days prior to the event day to 57 trading days after the event day. As the security returns were found to be affected due to the event, the study concluded that the announcement impounded information on asset quality of banks. Slovin and Jayanti (1993) examined the stock returns of banks affected by announcement of the Mexican and Bolivian debt moratorium and analyzed if the returns behave differently in presence of bank capital regulation. The study considered 39 banks listed in either New York stock exchange or American stock exchange and employed a market model for calculating excess returns. The study found that all the banks that had the debt exposure reported significant negative returns on both the event days, that is, the Mexican as well as the Bolivian debt moratorium announcement date. Further, by disaggregating the 39 banks into capital sufficient and capital deficient banks, the study found that the bank with sufficient capital had less negative returns than the banks with deficient capital. It suggests that the investors were aware of the information regarding the asset deterioration and consequently the securities were priced in the market. Mansur et al. (1990) examined the stock returns of 21 major US commercial banks affected by the Argentinean debt rescheduling announcement and investigated if the market penalized the banks differently according to the debt exposure level of the banks. Daily returns of 90 pre-event trading days and 60-post-event trading days were considered for analysis. The study found that stocks of all the banks had negative returns with the announcement and the market penalized the banks which were less exposed to debt more than the banks which were more exposed to debt. It indicates that though the information of debt exposure was public, the market did not consider it in pricing the securities. Jayanti and Booth (1993) examined the stock returns of six Canadian banks affected by the announcement of Latin American debt restructuring which includes the four moratoria announced by Mexico, Bolivia, Argentina and Brazil. Daily stock returns of 253 trading days prior to the event and 3 trading days post to the event were considered and the market model was used for analysis. Also for addressing the heteroscedasticity in the market model, the GARCH model was used. The study concluded that overall, the stocks of the concerned banks were not affected by the announcements made by Mexico, Argentina, and Bolivia but heavily affected by that of Brazil. It argued that Canadian banks had well equipped capital reserves when the first three events happened but at the time of the fourth event, the stocks were penalized due to the impending risk based capital requirements which increased the probability of risk for these banks.

The announcement of loan moratorium is a significant event which will have both positive and negative effects on the Indian economy. The present paper is an attempt to study the impact of the event on the stock prices of Indian public sector banks. In Indian context, the present study is first of its kind and adds to the literature of the application of event study methodology and impact of announcement of loan moratorium on security’s price.

Data and Methodology

The present study is based on all the public sector commercial banks listed in Bombay Stock Exchange (BSE). There are 11 public sector commercial banks listed in BSE. In the study, the event study methodology is applied for which daily returns for 130 trading days prior the event date (ED) and 10 trading days thereafter are computed (see Figure 1). In the article, the day of announcement of 3-month loan moratorium is considered as the event and thus, March 27, 2020 is taken as the event date. The estimation period is from September 26, 2019 to March 12, 2020 (120 trading days) and the event window is from March 12, 2020 to April 16, 2020 (21 trading days), that is, 10 days before the event and 10 days post-event. All the data relating to stock prices and market indices are sourced from Yahoo! Finance.

Figure 1.

Source: The authors.

The stock returns and the market returns are calculated using the following formula:

R_{i, t} = \ln (P_{i, t} / P_{i, t - 1})

where Ri,t is the stock return of security i day t, P_i,t is the stock price of security i for day t and Pi,t−1 is the stock price of security i for day t − 1.

\begin{matrix} R_{i, t} = \ln (P_{i, t} / P_{i, t - 1}) \\ R_{m, t} = \ln (P_{m, t} / P_{m, t - 1}) \end{matrix}

where Rm,t is the market return of index m for day t, P_m,t is the stock market index m for day t and P_m,t−₁ is the stock market index m for day t − 1.

The study used the single-index model also known as the market model proposed by Fama (1976) for the purpose of computing the expected returns. Under the single-index model the expected returns can be computed using the following equation:

E (R_{i, t}) = α_{i} + β_{i} R_{m, t} + ε_{i, t}

where E (R^i,t) is the expected return of security i for day t, α_i and β_i are the market model parameters that will be computed over the estimation period, R_m,t is the market return of index m for day t.

After computing the expected returns using the single-index model, abnormal returns (ARs) will be determined using the following equation:

A R_{i, t} = R_{i, t} - E (R_{i, t})

where AR^i,t is the excess return or abnormal return of security i for day t, R_i,t is the stock return of security i day t and E (R_i,t) is the expected return of security i day t.

To test whether the ARs are statistically different from zero the following t-test is applied:

T A R_{i, t} = A R_{i, t} / S . E_{i}

where TAR_i,t is the t-statistic of security i for day t, AR_i,t is the excess return or abnormal return of security i for day t and S. E_i is the standard error of security i and is computed over days ED-130 to ED-11.

The daily ARs are then aggregated into average abnormal returns (AARs) by using the following formula:

A A R_{t} = 1 / N \sum_{i = 1}^{N} A R_{i, t}

where AARt is the average abnormal return for day t, AR_i,t is the excess return or abnormal return of security i for day t and N is the number of public sector banks in the sample.

To test whether the AARs are statistically different from zero the following t-test is applied:

T A A R_{t} = A A R_{t} / S D

where TAAR_t is the t-statistic of corresponding average abnormal return for day t, AAR_t is the average abnormal return for day t, SD is the standard deviation of AARs and is calculated over days ED-130 to ED-11.

The AARs are cumulated over time in order to compute the cumulative average abnormal returns (CAARs). For the present study, CAAR has been computed for five-time windows [−10,10], [−5,5], [−3,3], [−2,2], and [−1,1]. The following formula is used to compute CAAR for different time windows:

C A A R_{T 1} {_{,}}_{T_{2}} = \sum_{t = T 1}^{T 2} A A R_{t}

where CAAR_{T1, T2} is the cumulative average abnormal return for days T₁, T₂ and AAR_t is the average abnormal return for day t.

To test whether the CAARs are statistically different from zero the following t-test is applied:

T C A A R = C A A R_{T 1, T 2} / S D \times {(T)}^{1 / 2}

where TCAAR is the t-statistic of CAAR_{T1, T2,} SD is the standard deviation of AARs and is calculated over days ED-130 to ED-11 and T = (T₁ – T₂ + 1).

Results and Discussion

The ARs along with their corresponding t-statistic computed for the event window is summarized in Tables 1 and 2. The AR shows the impact of news and information on individual security during the event window. From Tables 1 and 2, it can be observed that the public-sector banks had both significant positive and negative ARs during the event window. State Bank of India, Punjab National Bank, and Bank of Baroda had significant positive returns on days ED-10 and ED-9 while the Central Bank of India had significant positive returns on day ED-10 only. Other banks like Bank of Maharashtra, Bank of India, and United Bank of India had significant positive ARs on ED-9. It is important to note that significant negative ARs can be seen on day ED-2 for all the banks excluding Indian Bank, Indian Overseas Bank, Bank of Baroda, and Central Bank of India. In addition, significant ARs can also be observed on day ED-1 for Punjab National Bank, Bank of Baroda, Bank of India, Canara Bank, State Bank of India, and United Bank of India. In the post-event window, Bank of India had significant negative ARs on days ED+1 and ED+2 while Punjab National Bank and Canara Bank had significant negative returns only on day ED+2. Further, no public sector banks had significant negative ARs on the event date, that is, on the day of announcement of 3 months loan moratorium.

Table 1.

Abnormal Returns and t-Statistic for Public Sector Banks

Day	PNB		BOM		BOB		BOI		CB		CBI
Day	AR	t-stat	AR	t-stat	AR	t-stat	AR	t-stat	AR	t-stat	AR	t-stat
ED-10	0.05	2.95*	0.01	0.52	0.09	4.78*	0.03	1.64	0.03	1.57	−0.08	−3.11*
ED-9	0.07	4.03*	0.05	1.98*	0.09	4.67*	0.10	5.71*	0.07	3.97*	0.15	5.84
ED-8	0.03	1.57	0.01	0.40	0.07	3.86*	0.05	3.28*	0.04	2.58*	0.04	1.46
ED-7	0.12	6.73*	0.03	1.07	0.07	3.59*	0.11	6.69*	0.07	4.13*	0.05	1.77
ED-6	0.07	3.71	−0.01	−0.28	−0.02	−0.80	0.03	1.80	0.09	5.40*	−0.03	−0.97
ED-5	−0.05	−2.88*	−0.04	−1.42	−0.05	−2.43*	−0.10	−5.79*	−0.12	−7.53*	−0.03	−1.06
ED-4	0.14	7.75	0.08	3.05*	0.04	2.34	0.14	8.53*	0.02	1.40	0.07	2.79
ED-3	−0.01	−0.32	−0.04	−1.74	−0.01	−0.29	−0.04	−2.41*	0.02	1.39	−0.03	−1.05
ED-2	−0.14	−7.85*	−0.05	−2.10*	−0.03	−1.68	−0.09	−5.57*	−0.07	−3.97*	−0.04	−1.60
ED-1	−0.09	−5.03*	−0.03	−1.13	−0.10	−5.37*	−0.04	−2.11*	−0.03	−2.05*	0.00	−0.06
ED-0	0.01	0.61	0.03	1.28	−0.02	−0.99	0.02	1.25	0.04	2.66*	0.03	1.19
ED+1	0.04	2.39	0.05	1.95	0.02	1.24	0.04	2.23*	0.03	1.97	0.02	0.77
ED+2	−0.07	−3.79*	−0.02	−0.82	−0.03	−1.56	−0.06	−3.60*	−0.02	−1.22*	−0.03	−1.16
ED+3	0.00	−0.10	0.03	1.03	0.01	0.67	0.07	4.05*	0.07	4.04*	0.04	1.56
ED+4	0.01	0.37	0.01	0.31	−0.02	−0.94	0.04	2.51*	−0.03	−1.87	0.01	0.52
ED+5	−0.10	−5.96*	−0.04	−1.48	−0.13	−6.68*	−0.12	−6.91*	−0.11	−6.45*	−0.07	−2.55
ED+6	0.02	1.22	0.00	0.19	0.01	0.51	0.01	0.83	0.01	0.62	0.02	0.63
ED+7	−0.03	−1.42	−0.02	−0.61	0.00	−0.20	−0.03	−1.93	−0.02	−0.99	0.00	−0.01
ED+8	0.02	1.13	0.00	0.00	0.00	0.05	0.02	0.99	−0.01	−0.88	0.00	0.01
ED+9	0.00	0.17	0.01	0.29	−0.01	−0.46	0.02	1.12	−0.01	−0.74	0.00	0.09
ED+10	−0.014	−0.77	0.00	−0.02	0.00	0.12	−0.01	−0.73	−0.02	−1.10	0.00	0.18

Source: The authors.

Notes: AR, abnormal return; BOB, Bank of Baroda; BOI, Bank of India; BOM, Bank of Maharashtra; CB, Canara Bank; CBI, Central Bank of India; ED, event date; PNB, Punjab National Bank.

*Significant at 5 percent level.

Table 2.

Abnormal Returns and t-Statistic for Public Sector Banks (Contd.)

Day	SBI		IB		IOB		UBI		UCO
Day	AR	t-stat	AR	t-stat	AR	t-stat	AR	t-stat	AR	t-stat
ED-10	0.07	3.02*	0.00	0.02	−0.04	−1.50	0.01	0.37	−0.01	−0.19
ED-9	0.05	2.06*	0.04	1.30	0.03	1.28	0.08	3.46*	0.03	0.70
ED-8	0.00	0.14	0.01	0.23	0.01	0.43	0.05	2.18*	0.02	0.50
ED-7	0.09	3.85*	0.02	0.79	0.02	0.71	0.09	3.97*	−0.01	−0.31
ED-6	−0.02	−0.84	0.06	2.00*	−0.01	−0.23	0.02	0.92	0.00	0.09
ED-5	−0.06	−2.50*	−0.01	−0.24	−0.02	−0.91	−0.07	−3.18*	−0.06	−1.67
ED-4	0.08	3.27*	0.03	1.24	0.04	1.33	0.10	4.37*	0.06	1.56
ED-3	−0.03	−1.31	−0.07	−2.33*	0.02	0.59	0.03	1.34	−0.04	−1.01
ED-2	−0.07	−2.95*	−0.04	−1.45	−0.02	−0.86	−0.11	−4.52*	−0.10	−2.59*
ED-1	−0.06	−2.54*	−0.01	−0.52	0.01	0.52	−0.02	−1.04	0.00	0.11
ED-0	0.02	1.05	0.01	0.43	0.01	0.25	0.05	1.98*	0.04	0.99
ED+1	0.03	1.15	−0.01	−0.38	−0.01	−0.35	0.04	1.56	0.01	0.37
ED+2	0.00	−0.08	−0.02	−0.76	−0.02	−0.69	−0.04	−1.74	−0.02	−0.47
ED+3	0.01	0.50	0.07	2.33*	0.01	0.54	0.06	2.74*	0.04	1.03
ED+4	−0.02	−0.99	0.05	1.70	0.02	0.75	0.03	1.33	0.01	0.28
ED+5	−0.07	−3.14*	−0.06	−1.96	−0.06	−2.19*	−0.11	−4.87*	−0.06	−1.50
ED+6	−0.01	−0.38	0.01	0.33	0.00	0.17	0.01	0.22	0.00	−0.08
ED+7	−0.04	−1.62	0.00	−0.08	−0.01	−0.55	−0.07	−2.76*	−0.01	−0.30
ED+8	0.00	0.09	−0.01	−0.48	0.01	0.39	0.01	0.40	0.00	−0.07
ED+9	0.01	0.43	0.01	0.24	0.00	0.15	0.03	1.10	0.03	0.78
ED+10	0.02	1.03	0.00	−0.02	−0.01	−0.36	0.00	0.09	0.05	1.41

Source: The authors.

Notes: AR, abnormal return; ED, event date; IB, Indian Bank; IOB, Indian Overseas Bank; SBI, State Bank of India; UBI, United Bank of India; UCO, United Commercial Bank.

*Significant at 5 percent level.

The AARs for the event window are presented in Table 3. From the table, it can be observed that days ED-9 (AAR = 6.8%, t-stat = 3.232) and ED-7 (AAR = 5.9%, t-stat = 2.812) had significant positive AARs. The significant positive AARs represents the price adjustment which occurred from the news of ₹4.05 lakh crore liquidity infusion by Reserve Bank of India to ensure the stability and liquidity of the debt, money and foreign exchange markets. The price adjustment (AAR = −5.5%, t-stat = −2.622) which occurred on day ED-5 represent the market’s reaction to the falling global indices amid the COVID-19 pandemic. Such news affects the banking stocks more as compared to stocks relating to other industries. Banks are the pillars of credit creation and economic recession/depression can severely cripple the credit creation process. Stock market crash at a global scale is an indicator of the possible global economic recession. The price adjustment that occurred on day ED-4 represented the market’s positive reaction to the news of potential coronavirus vaccine and the global economic recovery. In addition the success of 14-h Janata Curfew had also contributed to the positive reaction of the market towards banking stocks. On March 24, 2020, the Government of India announced the 21 days lockdown and the news triggered a further price adjustment on day ED-2 (AAR = −6.9%, t-stat = −3.276).

Table 3.

Average Abnormal Returns and t-Statistic for Public Sector Banks

Day	AAR	t-stat	Day	AAR	t-stat
ED-10	0.015	0.694	ED+1	0.024	1.132
ED-9	0.068	3.232*	ED+2	−0.030	−1.414
ED-8	0.031	1.459	ED+3	0.037	1.757
ED-7	0.059	2.812*	ED+4	0.010	0.465
ED-6	0.018	0.833	ED+5	−0.083	−3.948*
ED-5	−0.055	−2.622*	ED+6	0.008	0.361
ED-4	0.073	3.466*	ED+7	−0.020	−0.966
ED-3	−0.017	−0.804	ED+8	0.003	0.125
ED-2	−0.069	−3.276*	ED+9	0.008	0.372
ED-1	−0.034	−1.596	ED+10	0.003	0.136
ED-0	0.022	1.067

Source: The authors.

Notes: AAR, average abnormal return; ED, event date.

*Significant at 5 percent level.

It is needless to say that the announcement of 3-month loan moratorium and the announcement of 21-day complete lockdown overlapped with each other. Further, the market anticipated that the government may announce loan moratorium since industry bodies like The Associated Chambers of Commerce and Industry of India and The Federation of Indian Chambers of Commerce and Industry have recommended loan moratorium in order to safeguard the business enterprises especially the MSME sector. Thus, the adjustment in the bank stock prices occurred before the announcement of the 3-month loan moratorium and as a consequence the average annual return on day ED-0 is found to be insignificant. However, the study found significant negative AAR on day ED+5 which represents the market mood of avoiding the banking, NBFCs and financial sector stocks.

Figure 2.

Source: The authors.

The CAAR along with their corresponding t-statistics are summarized in Table 4. From the table, it can clearly be seen that CAAR is negative and significant at the time window of [−5,5] and [−2,2] while it is statistically insignificant at the time window of [−10,10], [−3,3], and [−1,1].

Table 4.

Cumulative Average Abnormal Returns

Time Window	[−10,10]	[−5,5]	[−3,3]	[−2,2]	[−1,1]
CAAR	0.069	−0.121	−0.066	−0.086	0.013
t-stat	1.001	−2.430*	−1.654	−2.552*	0.485

Source: The authors.

Note: CAAR, cumulative average abnormal return.

*Significant at 5 percent level.

Conclusion

The primary objective of the study is to investigate the impact of the announcement of 3-month moratorium on the stock prices of Indian public sector banks. For this purpose, event study methodology is applied and the expected returns, excess returns, cumulative abnormal returns, AARs, and CAARs are computed by taking the daily stock and market returns. The study considered an estimation period of 120 trading days while the event window is from March 12, 2020 to April 16, 2020, a total of 21 trading days. The findings of the study suggest that all the public sector banks had both positive and negative ARs in the event window. Further, the significant abnormal average returns suggests that the market responded to the news relating to the liquidity infusion by the Reserve Bank of India, falling global indices, potential coronavirus vaccine, and lockdown. Nevertheless, the price adjustments around the event date indicate the negative impact of the announcement of loan moratorium on the stock prices of public sector banks. However, as it is mentioned earlier in the article that the announcement of 3-month loan moratorium and the announcement of 21-day lockdown overlapped with each other and thus, the adjustments in the security prices occurred before the announcement date. To put it another way, it can be said that the lack of statistical significance of the AAR on the event date indicates that the market possessed the information relating to the deteriorating quality of assets well before the announcement of the 3-month loan moratorium and thus, the market made prior adjustments.

The present study can be extended by investigating the reaction of the share price of the Indian private sector banks to the announcement of the 3-month loan moratorium. Further, it will be interesting to see how the Indian stock market reacted after the announcement of the extension of loan moratorium.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Appendix

Major News

Date	New Information
March 13, 2020	News of infusing ₹4.05 lakh crore liquidity by the Reserve Bank of India to ensure the liquidity and stability of debt, money and foreign exchange markets.
March 18, 2020	News of falling stock market indices globally. Dow closed below 20,000 points, a fall of 1,338 points. In addition, S&P 500 fell 5.2 percent while Nasdaq Composite fell 4.7 percent.
March 20, 2020	World Health Organization officials noted that the development of COVID-19 vaccine has made remarkable progress and entered into human trials and hope of global economic recovery.
March 24, 2020	Prime Minister Narendra Modi addresses the nation and announced a 3-week period lockdown.
March 27, 2020	Reserve Bank of India defers all loan repayments taken from any financial institution by 3 months.

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