that these companies use to hedge this risk. To take an example, the steel companies in India( like Jindal Steel) are dependent upon South-Asian countries for their coal requirements. So in order to avoid any undue consequences of currency rate variation, the Indian companies take long positions( buying contracts at a later date) in case they fear depreciation of the Indian Rupee versus the currency of the country from which the raw material is sourced. Similarly, major software companies are dependent upon other countries( especially US) for their income. A depreciation of the Indian rupee boosts the revenues of these companies. Thus, hedging against their receivables becomes imperative for these companies and options are the commonly used instrument. However, depending upon the requirements of firms, they adopt an appropriate strategy.
The BSE-30 companies were taken as a starting point to analyse the hedging strategies adopted by the top firms in India. A sector wise trend was observed and the correlation between the exposure of foreign currency and the annualized returns of the stocks of BSE-30 companies was analysed. The major industries analysed were: 1) Automobile and Motor Vehicles 2) Software 3) Steel, Metals and Mining 4) Pharmaceutical 5) Power 6) Petroleum & Gas The variables used to analyse the trends in the industry are as follows: 1) Total Forex Earnings / Total Revenue 2) Raw Material Imports / Total Imports 3) FCCBs / Total Borrowings
The total earnings in foreign currency were taken as a proxy for the receivables of a company, the raw material imports were the proxy for the receivables and the FCCB represents the external debt of a company. Based upon the above parameters a number of trends were observed.
The automobile sector had limited earnings from abroad( Exhibit 13); however they borrowed heavily from the foreign markets. This could be attributed to M & A activities that most of the Indian automobile companies have done in the recent past and are exposed to the global market. Additionally, major companies like Mahindra & Mahindra and Maruti Suzuki have entered currency swap agreements to streamline their cash flows.
Software companies( Exhibit 14) in India are primarily dependent upon foreign currency. They seem to go in for options and are seen taking put options primarily as they anticipate the Indian currency to depreciate further than its current levels.
The Steel, Metals and Mining industry( Exhibit 15) is highly dependent upon the import of raw materials and they have hedge reserves for Copper, Gold, Silver and other metals in a number of currencies like USD, EUR, CHF, BRL, and YEN.
The Pharmaceuticals sector( Exhibit 16) is characterized by high payments for technology and high external debt financing because pharmaceutical companies like Cipla, Sun Pharmaceuticals find raising debt in the countries of their vendors cheaper.
4.0 EXPLANATION OF MODEL
A univariate analysis was conducted which was conjectured by a random effects panel regression. The random effects panel regression assumes that there are no individual returns on panel data. In the univariate analysis, the variable considered was the total annualized returns; the market being a forward looking market, time lags were studied to know the variation explained. Here, stock market annualized returns are regressed as forward indicators on forex related variables.
After the data collection, the data was organized and compiled, followed by smoothening. Since Rupee suffers from volatility and US Dollar is the vehicle currency; all the data points were converted into USD, by using average currency rates. As a way to remove the outliers in the model, the companies whose data was not available even for a single time period were excluded. To replace such companies, data points were drawn of companies which are present in the BSE 200; in a decreasing order of their market capitalization.
( Author remarks: Difficulties were faced during data collection. Researchers and readers are advised to leave banking sector companies, for the analysis)
The banking sector and IT sector companies behave differently as compared to other companies in the BSE 30. For IT companies, contradictory data points were found on CMIE Prowess, which led to their elimination from the analysis. Also, since the banking sector suffers from heavy regulations and has reserve requirements to meet, its data points were excluded.
Hypothesis: The forex risk of a company for the current time period( T) depends upon the annualized stock returns for the previous time period( T-1)
Total returns( period T) are a function of its lagged values, starting from period( T-1)… till( T-n) th period.
Dependent Variable: Annualized total returns.
Independent variables: FCCB / Total borrowing(%), Raw material imports / Total raw material purchases( in % terms), total forex earnings / total income(%), net revenue in forex( USD million), net forex flows( USD million), total net forex earnings( USD million)
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