Relationship between Monthly Common Stock Prices and Monthly Inflation in India

Purpose: The purpose of the study is to scrutinise whether monthly inflation rate and monthly common stock prices are interlinked and if they are linked, then what is the kind of affiliation among the variables. Methodology: The paper has used the vector autoregression model (VAR) to determine whether there exists a relationship between monthly common stock prices and monthly inflation rates or not. Findings: The paper's findings can be summarised as no cointegration exists between monthly inflation rates and monthly stock prices, meaning there is no relationship (neither long nor short) between inflation and common stock prices. The other insight that can be concluded from the research is that there also doesn’t exist any cause-and-effect relationship between the inflation rate & monthly common stocks.


INTRODUCTION
Inflation refers to an increase in the mean general price level for all products and services over a specific duration or the rate at which a currency's value depreciates.The fall in the country's purchasing power can also be termed inflation.A numerical estimate of the magnitude with which purchasing power is lost is frequently depicted in the rise of the mean price index of a basket of chosen goods and services in an economy.As a result, monetary policymakers' primary priority is keeping inflation at a steady level because the country's economic progress is reflected by the inflation rate in a given country.As a result, its price stability also determines a country's performance in the global market.
This research aims to comprehend whether there exists any relationship between monthly inflation rates and monthly common stock prices and to do so, we must first grasp what stock prices are.Let's have a look at what Stock is.The stock exchange is a public market where the stakeholders buy and sell new and old securities over the counter and via the stock exchange.As stocks represent fragmented ownership of a corporation, the stock exchange may be a site where these stocks can be executed by the capitalists.As the stock market channelises the funds of enterprises, a well-functioning exchange is important for a country's economic growth.According to general economic theory, when the inflation rate rises, an economy performs poorly.Fearing to lose their money, the financial investors sell their stocks.The increase in the supply of stock assets on the market caused by an increase in inflation causes a fall in stock prices, implying that inflation and stock prices have a negative or inverse connection.
The research also examines the effects of economic shocks that occurred during the study period and impacted the country's stock prices and inflation rate.Therefore, it would be interesting to find out what relationship is there between the monthly inflation rates and monthly common stocks.If they are interlinked, then it would be interesting to find out the nature of the relationship.

LITERATURE REVIEW
The question "How effectively can an investor hedge against inflation with a very diversified portfolio of common stocks" was asked by Bodie (1976), and the data used in the paper were annual, quarterly and monthly from 1953 to 1972.The methodology of the study was the Meanvariance model Markowitz and Tobin for portfolio and the results concluded that the real equity returns are negatively related to both the unanticipated and the anticipated inflation rate.
The paper by Fama and Schwert (1977) used the data for the period 1953 to 1971, and they used the linear regression methods to find out which financial assets were hedges against inflation (both expected and unexpected).The results concluded that the estate of the US government was a complete hedge against both unexpected and expected inflations.
The paper by Egypt Omran and Pointon (2001) scrutinised the impact of inflation rates on the conduct of Egypt's stock market.The Error Correction Mechanism (ECM) model was used in the paper for analysis, and the results showed that a negative relationship exists between inflation and market activity and liquidity.
The paper by AL-Zoubi and AL-Sharkas (2010) scrutinised the relationship between stock prices and inflation in countries such as Kuwait, Jordan, Morocco and Saudi Arabia the data used was from 2000 to 2009, and the data frequency was monthly.The model used in the study was the Unrestricted vector Autoregressive (UVAR) model.The results turned out to be consistent with the hypothesis of Fisher, which states that there exists a positive relationship The paper by Mousa, Al-Safi, Hasoneh and Abo-orabi (2012) analysed the annual data for the period of 1998 to 2007 for the country Jordan and tried to establish the relationship between inflation and common stock prices.The study concluded that not every company offers a perfect hedge against inflation, some of the companies exhibited a negative relationship, while some of the companies also exhibited a positive relationship.

Data Source
The criteria for selecting the variables for the study are based on the existing literature and evidence from the empirical studies.The National Stock Exchange index (NSE) substitutes the monthly common stock price (MCSP), and the monthly inflation rate is taken as it is for the study.The monthly data frequency for the duration of Jan 2014-March 2022 is used in this research paper, and the source of the data is RBI (Reserve Bank of India) for monthly inflation rates and the National Stock Exchange source for monthly common stock prices.
Descriptive statistics for the inflation and stock prices for complete data are represented in Table 1, and the line graphs for both variables (inflation and stock prices) are shown in Graph 1 and Graph 2, respectively.Graph 1 represents monthly inflation which shows that there is no specific trend in the case of inflation; it experienced both upward and downward trends.Figure 2 shows a graphical representation of monthly common stock prices, showing a continuous upward trend in India's stock prices from 2014 to 2022.

METHODOLOGY
The paper has used the vector autoregression model (VAR) to determine whether there exists a relationship between monthly common stock prices and monthly inflation rates or not.
To fulfil the objective of the study various steps need to be followed.
i. Testing for a unit root in the presence of structural breaks and determining the order of integrating for two variables by employing tests devised by Zivot-Andrews Test.
A series is said to be stationary when its mean, variance and covariance are constant over time.
ii.The CO-integration test identifies scenarios where two or more non-stationary time series are integrated to determine whether they have a long-run or short-run relationship.The Johansen co-integration can be applied in this respect.
iii.Granger-The granger-causality used to determine the correlation among the time series.It is used to determine the way the relation flows, whether from inflation to stock prices or vice versa.If there is co-integration, there should be Granger-causality in at least one direction.If there is causality, then it implies that a variable can predict another variable with which it is cointegrated.

Stationarity Test
The test of stationarity of the series is done by performing a unit root test.A series is said to be stationary when the data is independent of the time for which data is taken.The paper used the Zivot-Andrew test for determining whether the data is stationary or not and, at the same time whether there exist any structural breaks or not.

Null Hypothesis (NO): Non-Stationary Series Alternative Hypothesis (NA): Stationary Series
Table 5 below   It can be concluded by analysing table 5 that the data is non-stationary because the test statistic (1.3358) is exceeding the 5% critical value (0.9479), hence according to Zivot-Andrew test, the null hypothesis is not rejected and null hypothesis is that data is non-stationary.But by looking at the Figure above, there exists a structural break during the year 2020 and not during the year of demonetisation which was also the period of economic shock for the country.Hence, the data is non-stationary, with one structural break.

Co-integration Test
The cointegration test is used to determine what kind of relationship exists between the variables taken for study.The paper has applied Johansen Cointegration to determine the level between the monthly inflation rate and monthly common stock prices.The results of Johansen cointegrated are shown in table 6 below, and the analysis is below the table.From the above table, the paper can conclude that since trace statistics are at a lower level than that of a five per cent critical value, hence there is not enough evidence to reject the null hypothesis and therefore no cointegration is present between the monthly stock prices and monthly inflation.Hence, no long-run association can be concluded from the above analysis.The paper used a vector autoregression model to determine the short-term association among the chosen variables.

Vector Autoregression Model
In view to establish the relation among the multiple variables as they change over time, the vector autoregression model is used.The single variables auto-regressive models are generalised by enabling multivariate time series by the VAR model.The Granger Causality test determines the cause-and-effect relation between the monthly inflation rate and common stocks.If the p-value from the analysis is below 0.05, then the null hypothesis will not be rejected because of lack of evidence, it means that the lagged x values do not explain the variation in y and vice versa.

Figure
Figure 2: Monthly Common Stock Prices represents the outcome of the Zivot-Andrew test, and Figure 4 will show whether there were any structural breaks or not during the time of the study.Sample: 1 -99 Number of observations = 99 Ho: No structural breaks Null Hypothesis (NO): Variables are not cointegrated Alternative Hypothesis (NA): Variables are cointegrated

Table ( 7
) below shows the results of the VAR model for the data taken in the study and the table shows the results from performing the Granger Causality test on the data.