A Study on Relationship Between Price of Us Dollar and Selected Commodities

Transcription

1 Volume 119 No , ISSN: (on-line version) url: A Study on Relationship Between Price of Us Dollar and Selected Commodities Dr. G. Sankararaman 1, Mr.S.Suresh 2, Ms. T. Komatheswari 3, Dr.S.T.Surulivel 4, Dr.S.Selvabaskar 5, Dr.V.VijayAnand 6 & Dr.V.Rengarajan 7 1 & 2 Professors, Department of Management Studies, Rajalakshmi Engineering College, Chennai 3 Show Room Manager, Bharati Airtel, Chennai 4 Senior Assistant Professor, School of Management, SASTRA Deemed University, Thanjavur 5 Associate Professor, School of Management, SASTRA Deemed University, Thanjavur 6 &7 Assistant Professors, School of Management, SASTRA Deemed University, Thanjavur ABSTRACT This study examines the relationship between US dollar exchange rates and commodity prices. There are many factors influencing the commodity price but this study focuses US Dollar exchange rate alone. Instead of taking more number of commodities only five commodities were selected for the analysis they are gold, crude oil, sugar, potato and cardamom. Data sets of the period from January 2006 to December 2015 used for the study. Statistical tool used to analyze the study are correlation, regression and trend analysis. There exist an inverse relationship between US dollar exchange rate and gold price. US dollar exchange rate has an impact on Crude oil price, sugar price, and potato price. But US Dollar exchange rate and cardamom price are not correlated. From the study it is observed that cardamom price is not affected by US dollar exchange rate. The results indicate that in the long run the impact of US dollar exchange rate changes on commodity prices is negative and statistically significant. Key Words: Dollar Exchange Rate, Gold Price, Crude Oil Price and Gold Price. Introduction Since many agricultural commodities are priced in US dollars in international markets, a weaker dollar may increase the demand for agricultural commodities of foreign consumers and thus the prices of agricultural commodities. Note, that the price impact of the demand shift of agricultural commodities may be particularly large since it is believed that the demand and supply of these commodities are price inelastic. Another reason of the inverse relationship between agricultural commodity prices and the US dollar exchange rate may be inflation. Investors and speculators invest in agricultural commodity futures when the US dollar depreciates because they are concerned about high inflation rates, thus driving up agricultural commodity and food prices. 203

2 The purpose of this study is to examine the long-run relationship between, US dollar exchange rates and the prices of five selected world agricultural commodities. It mainly investigates the effects of increases and decreases in US Dollar exchange rate on agricultural products. In order to analyze the relation between US exchange rates, and agricultural commodity price, data sets based on yearly observations from 2005 to June 2015is used. In particular, five data sets were used in the present study, of which the first is consisted of one energy commodity price(oil price) the second of one metal commodity price(gold Price) and third of selected three agricultural commodity prices namely sugar, cardamom, potato prices. In this study data is collected through secondary research. Correlation, Regression, Descriptive statistics and Trend analysis are the tools use for the study. Need for the study 1. The purpose of the study is to examine the long-run relationship between, US dollar exchange rates and the prices of agricultural commodities. 2. This study provides the behavioral pattern of commodity prices in accordance with increase or decrease in the value of US Dollar 3. This study will help the investor to find the better investment avenues in the commodities market. 4. This work would be helpful to the investors at the time of their investment decisions Objectives of the study: Primary objective: To determine the relationship between exchange rate of US Dollar and commodities price movements. Secondary Objectives: 1. To study the relationship between US Dollar and Crude oil price movements. 2. To analyze the relationship between US Dollar and Gold price movements 3. To study and analyze the impact of exchange rate of USD on Sugar price. 4. To study and analyze the impact of exchange rate of USD on Cardamom price. 5. To study and analyze the impact of exchange rate of USD on Potato price. Research Methodology The type of research design used in the study was Analytical research, because it helps to describe a particular situation prevailing in an environment. For causal research to establish the quantitative relationship between prices of commodities and USD exchange rate were collected from the various secondary sources like newspapers, internet, magazines, books, journals. The data used in this study consist of yearly observations of the period from 2006 to 2015 for the Indian prices of agricultural commodities, the crude oil prices and the real effective US dollar exchange rates. Following Statistical Tools were used in the study: Correlation, Regression and Trend Analysis 204

3 Hypotheses: 1. Hypothesis Assumed (H0): No relationship between USD exchange rate and Sugar price. Alternative Hypothesis (H1): Relationship exists between USD exchange rate and Sugar price. 2. Hypothesis Assumed (H0): No relationship between USD exchange rate and Potato price. Alternative Hypothesis (H1): Relationship exists between USD exchange rate and Potato price. 3. Hypothesis Assumed (H0): No relationship between USD exchange rate and Cardamom price. Alternative Hypothesis (H1): Relationship exists between USD exchange rate and Cardamom price. 4. Hypothesis Assumed (H0): No relationship between USD exchange rate and Gold price. Alternative Hypothesis (H1): Relationship exist between USD exchange rate and Gold price 5. Hypothesis Assumed (H0): No relationship between USD exchange rate and Crude oil price. Alternative Hypothesis (H1): Relationship exist between USD exchange rate and Crude oil price Review of Literature The Relationship between Oil, Exchange Rates, and Commodity Prices Ardian Harri, Lanier Nalley, and Darren Hudson; Journal of Agricultural and Applied Economics, (August 2009) To examine the price relationship through time of the primary agricultural commodities, exchange rates, and oil prices. Methodologies used are 1. ADF Unit Root Test 2. Johansen Trace Co integration Test This paper finds that commodity prices are linked to oil for corn, cotton, and soybeans, but not for wheat, and that exchange rates do play a role in the linkage of prices over time. Common factor analysis on a panel of fifty-one international commodity prices by Chen et al. (2010) uses data from January 1980 to December The study uses the PANIC (Panel Analysis of Non motionless in Idiosyncratic and Common Components) procedure developed by Bai and Ng (2004) and identifies two common factors for commodity prices. The results indicate that the first common factor is non-stationary, while the second common factor is stationary. The graphical evidence shows that the first common factor is a mirror image of the US exchange rate. Thus, the study concludes that the highly persistent movements of commodity prices are mainly attributed to the first common component, which is closely related to the US exchange rate, while the stationarity of the second common factor implies short-lived deviations from equilibrium price dynamics reflecting changes in the world demand and supply conditions in accordance with prices theories (Kellard and Wohar, 2006; Wang and Tomek, 2007). Study on dynamic relationship among gold price, oil price, exchange rate and stock market returns K. S. Sujit and B. Rajesh Kumar International Journal of Applied Business and Economic Research,(2011) This study is an attempt to test the dynamic relationship among gold price, stock returns, exchange rate and oil price. This study consist the following methodology 1.Unit root tests; 2. Granger causality test, 3.Cointegration; 4.Vector auto regression (VAR). The results show that exchange rate is highly affected by gold price &oil price. However, stock market has fewer roles in affecting the exchange rate. Relationships between the prices of crude oil and several food commodities-the study by Ghaith and Awad (2011) uses co integration analysis to investigate long-run relationships between the prices of crude oil and several food commodities (e.g. maize, wheat, sorghum, soybean, barley, linseed oil, soybean oil, and palm oil) for the period from January 1980 to 205

4 December The results indicate that there is strong evidence of long-run relationship between crude oil and food commodity prices. The dynamic relationship between oil price, US dollar exchange rate and twenty four world agricultural commodities, by Nazlioglu and Soytas (2012) examines the dynamic relationship between oil price, US dollar exchange rate and twenty four world agricultural commodities in a panel framework using classical panel co integration and causality analysis for the period from January 1980 to February The empirical results on panel co integration indicate that the impact of an increase in the oil prices is positively significant in all individual agricultural commodities except in the case of cotton and coffee. Furthermore, the impact of a decline in the value of the US dollar is positive in all individual agricultural commodity prices except in the case of coconut oil, cacao, and coffee. With regard to the panel coefficients, agricultural commodity prices are positively correlated with the oil prices with an estimated coefficient of 0.25, and are negatively correlated with the US dollar exchange rate with an estimated coefficient between and A study on impact of select factors on the price of Gold Dr. Sindhu (Mar. - Apr. 2013) (10) IOSR Journal of Business and Management (IOSR-JBM) To study the influence of factors like exchange rate of US dollar with INR, Crude oil Prices, repo rate and inflation rate on gold prices. Methodologies used are Trend Analysis Standard Deviation, Regression and Correlation. There exists an inverse relation between the US$ and gold prices. The crude oil prices have an impact on the gold prices. Gold prices and repo rates are interdependent. Gold prices and inflation rates are also dependent and positively correlated The relationship between agricultural commodity prices, crude oil prices and US dollar exchange rates: a panel VAR approach and causality analysis - Anthony N. Rezitis; International Review of Applied Economics, This study examines the relationship between crude oil prices, US dollar exchange rates and thirty selected international agricultural prices and five international fertilizer prices in a panel framework 1.panel VAR approach 2.causality analysis. The empirical results of the present study indicate that crude oil prices as well as US dollar exchange rates affect international agricultural Commodity and fertilizer prices. Relationship between Crude oil price and Rupee, Dollar Exchange Rate: An Analysis of Preliminary Evidence - Dr.A.Hidhayathulla1 & Mahammad Rafee B (Mar-Apr-2014). IOSR Journal of Economics and Finance (IOSR-JEF) To examine the effects of oil price on exchange rate of Indian rupee against US dollar using time series data from to Multiple Linear Regression Oil price and imports are rising continuously. This pushes up the demand for dollar which strengthens the dollar against rupee and Indian rupee is continuously depreciating. This erodes purchasing power of Indian currency in the international market. An Econometric Analysis between Commodities and Financial Variables: The Case of Southeast Asia Countries Norasyikin Abdullah Fahami ; SharazadHaris; Hasyeilla Abdul Mutalib (June 2014). International Journal of Business and Social Science Researchers try to find relationship between commodities (crude oil and gold) and two commodity-relevant financial variables (exchange rate and the equity index). The methodologies used are 1.Unit Root Test 2.Johansen Juselius Co integration Test 3.Granger s Causality Test. From the study it is found that there is bidirectional causality between the leading index and exchange rate.ii. Exchange rate Granger causes crude oil (unidirectional causality) iii. Gold is the least affected commodity and also commodity that play fewest roles in affecting other variables. Empirical analysis of agricultural commodity prices, crude oil prices and US dollar exchange rates using panel data econometric methods - Anthony N. Rezitis; International 206

5 Journal of Energy Economics and Policy, 2015 The purpose of the study is to examine the longrun relationship between crude oil prices, US dollar exchange rates and the prices of thirty selected international agricultural prices and five international fertilizer prices using panel econometric methods. 1. Panel unit root analysis 2. Panel error correction analysis 3. Panel co-integration analysis The results of this study indicate that when unobserved heterogeneous effects with common factors are considered, effects of oil prices and USD exchange rates on agricultural commodity prices are much weaker than in the case in which such effects are not considered. The Relationship between Gold Prices and Exchange Value of US Dollar in India Girish Karunakaran Nair; Nidhi Choudhary; Harsh Purohit;(2015),(10) ISSN(Emerging Markets journal) The main objective of the paper is to understand the impact of recession of 2008 on relationship between exchange rate of US dollar in INR and gold prices in India the methodology used are 1. Johansen Co-Integration; 2.Ganger Causality. The relationship between two variables under study has been dynamic and inconsistent in nature. The study concludes that the relationship between gold prices and USD exchange rate has been impacted by recession in India. Impact of Crude Oil Price and Exchange Rate on Performance of Indian Stock Market Saurabh Singh; Ritika Kapil(2016);13; ISSN(Asian Journal of Research in Banking and Finance) The main objective of the paper is to investigate empirically the dynamic relationship among crude oil price, exchange rate and Indian stock market and the methodology used are Correlation, Regression Granger-causality approach Augmented Dickey Fuller (ADF) test. Finally it is found that there is a significant negative correlation between nifty returns and exchange rate and significant positive correlation between nifty returns and crude oil, and a unidirectional causality running from nifty returns to exchange rates and crude oil price to nifty returns. A Study on Performance of Select Commodities Due to Demonetisation - Sankararaman, et al, (2018), International Journal of Pure and Applied Mathematics, ISSN: The study mainly focuses on Indian commodity market, and the effects of implantation of demonetization in commodity market. It takes into consideration of investor s investment pattern in select commodities. This study tries to educate the impact of change in money value that reflects in the purchasing the commodities by the investors. It tries to achieve the optimum return using derivative instruments hedging techniques.this study provide the investors for their investment portfolio in future on commodity market. There is a myth among the investors there is a rise in price of gold will always dependent to rise in price of crude oil which will be vice versa. This study will clearly states the dependency and price fluctuation in gold and crude oil and also identify their relationship of select commodity in demonetization period. Results and Discussions 207

6 Table 1 Table showing value of Crude oil and USD in INR YEAR CRUDE OIL USD Table 2 Correlation coefficient Correlations Crudeoil USD Crudeoil Pearson Correlation ** Sig. (2-tailed).007 N USD Pearson Correlation.786 ** 1 Sig. (2-tailed).007 N **. Correlation is significant at the 0.01 level (2-tailed). Correlation coefficient value of indicates strong correlation between US Dollar exchange rate and crude oil. Oil imports became a substantial source of demand for dollar in India s foreign exchange market. This strong oil demand contributes to strengthen the dollar against Indian rupee, among the other factors. 208

7 Graph: 1 USD in INR vs Crude oil Price in INR CRUDE OIL USD 0 YEAR From the above mentioned graph it is inferred that during the period of 2007 to 2010, Oil price rising continuously. This oil import pushes up the demand for dollar which strengthens the dollar against rupee and Indian rupee is continuously depreciating. This erodes purchasing power of Indian currency in the international market. Regression Hypothesis Assumed (H0): No relationship between USD exchange rate and Crude oil price. Alternative Hypothesis (H1): Relationship exists between USD exchange rate and Crude oil price. Table 3 Model Regression output: Dependent variable considered- Crude oil price Variables Entered Variables Removed Method 1 USD a. Enter a. All requested variables entered. b. Dependent Variable: Crude oil Table 4 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), USD 209

8 Table 5 ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total 1.034E7 9 a. Predictors: (Constant), USD b. Dependent Variable: Crude oil Table 6 Coefficients Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) USD a. Dependent Variable: Crudeoil Significant correlation with R= R square value shows that approximately 61% of variation in Crude oil prices accounted for with US Dollar value. Significant linear regression with p value= Regression Equation is Y= X Since P-value is <0.05 H0 is rejected, Thus there is exists relationship between USD exchange rate and Crude oil Price. The ve intercept of t value as well as ve intercept of regression equation shows the inverse relation between the US$ and Crude oil prices Graph 2 TREND: USD Vs CRUDE OIL PRICE 210

9 Trend line equation for Crude oil price is Y= 296.1x From the trend line for Crude oil we can conclude that on average price of the crude oil increases by rupees per barrel every year. Table 7 US Dollar Exchange rate in INR Vs Potato price in INR YEAR POTATO/kg in INR USD in INR Table 8 Correlation coefficient POTATO USD POTATO 1 USD Graph 3 Lowest price of potato l kg was recorded in the year 2008 = Rs Highest price of potato l kg was recorded in the year 2015 = Rs Potato prices shoot up drastically in the year 2009 and 2012 due to high inflation rate, in the same corresponding year Indian rupee against US Dollar value weakens. 211

10 Graph: 4 Trend Analysis of USD and Potato in INR Trend line equation of potato is Y=0.444x From the trend line for Potato we can conclude that on average price of the potato increases by rupees every year and USD exchange rate value is also increasing on the average of rupees every year. Regression Hypothesis Assumed (H0): No relationship between USD exchange rate and Potato Price. Alternative Hypothesis (H1): Relationship exist between USD exchange rate and Potato Price Table 9 Variables Entered/Removed Model Variables Entered Variables Removed Method 1 USD a. Enter a. All requested variables entered. b. Dependent Variable: Potato Table 10 Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate a a. Predictors: (Constant), USD 212

11 Table 11 ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), USD b. Dependent Variable: Potato Table 12 Coefficients Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) USD a. Dependent Variable: Potato Significant correlation with R= R square value shows that approximately 68% of variation in Potato prices accounted for with US Dollar value. Significant linear regression with p value= Regression Equation is Y=0.197X Since P-value is <0.05 H0 is rejected, Thus there is exists relationship between USD exchange rate and potato Price. The negative intercept of t value as well as negative intercept of regression equation shows the inverse relation between the US$ and Potato prices. US Dollar Exchange rate vs Sugar Price Table 13 USD and sugar in INR Year sugar/kg US dollar

12 Correlations Table no 14 Correlation coefficient USD Sugar USD Pearson Correlation ** Sig. (2-tailed).010 N Sugar Pearson Correlation.765 ** 1 Sig. (2-tailed).010 N **. Correlation is significant at the 0.01 level (2-tailed). From correlation coefficient value of it is inferred that USD exchange rate is highly (positive) correlated with Sugar price. In the commodity market most commodities are priced in dollars, since India is the 2nd highest exporter of sugar, sugar price is highly dependent on exchange rate. Graph 5 USD in INR vs Sugar Price in INR Lowest value of the sugar was observed in the year 2007= RS.12 Highest value of the sugar was observed in the year 2014= RS.33 The graph shows that from 2006 to 2010 sugar maintains inverse relationship with USD exchange rate because during this period Indian economy was down and global recession lies in this period. After 2010 sugar price increase steadily along with the increasing exchange rate. It is inferred that sugar price is influenced by exchange rate. 214

13 Graph: 6 Trend Analysis of USD and sugar in INR Trendline equation of USD is Y=2.3552x Trendline equation of sugar, y = x From the trendline for sugar, we can conclude that on average price of the sugar increases by rupees every year. And USD exchange rate value is also increasing on the average of rupees every year. Regression Result: Hypothesis Assumed (H0): No relationship between USD exchange rate and Sugar price. Alternative Hypothesis (H1): Relationship exists between USD exchange rate and Sugar price Table 15 Regression output: Dependent variable considered: sugar price. Variables Entered/Removed b Model Variables Entered Variables Removed Method 1 USD a Enter a. All requested variables entered. b. Dependent Variable: Sugar Table 16 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), USD 215

14 Table 17 ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), USD b. Dependent Variable: Sugar Table 18 Coefficients a Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) USD a. Dependent Variable: Sugar Significant correlation with R= Approximately 64% of variation in sugar prices accounted for with US Dollar value. Significant linear regression with p value=0.01. Regression Equation is Y=0.744X Since P-value is <0.05 H0 is rejected, Thus there is exists relationship between USD exchange rate and Sugar Price. The negative intercept of t value as well as negative intercept of regression equation shows the inverse relation between the US$ and sugar prices. US Dollar Exchange rate in INR vs Cardamom Price INR Table 19 Cardamom and USD in INR Year cardamom kg US dollar

15 Table 20 Correlations USD Cardamom USD Pearson Correlation Sig. (2-tailed).460 N Cardamom Pearson Correlation Sig. (2-tailed).460 N Correlation coefficient value depicts the weak relationship between cardamom price and US Dollar exchange rate. Since Cardamom is festive season commodity majority of the trading takes place during festive season, and cardamom price depends on demand, supply and production factors. Graph: 7 USD in INR vs Cardamom Price in INR Lowest price accounted in the year 2006: Rs.450/kg Highest price accounted in the year 2010: Rs.1417/kg. Reason for cardamom price hike in the year 2010 is growing domestic consumption, strong export demand, amid lower production in Guatemala. 217

16 Graph 8 Trend Analysis of USD exchange rate and Cardamom Price in INR Trendline equation for Cardamom price is Y= 47.56x From the trendline for Cardamom we can conclude that on average price of the cardamom increases by rupees per kg every year. And USD exchange rate value is also increasing on the average of rupees every year Regression Result: Hypothesis Assumed (H0): No relationship between USD exchange rate and Cardamom price. Alternative Hypothesis (H1): Relationship exists between USD exchange rate and cardamom price 218

17 Table 21 Variables Entered/Removed b Model Variables Entered Variables Removed Method 1 USD a. Enter a. All requested variables entered. b. Dependent Variable: Cardamom Table 22 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), USD Table 23 ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), USD b. Dependent Variable: Cardamom Coefficients a Table 24 Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) USD a. Dependent Variable: Cardamom Significant correlation with R= R square value shows that approximately 6% of variation in Cardamom prices accounted for with US Dollar value. Significant linear regression with p value= Regression Equation is Y=9.240 X = Since P-value is >0.05 H0 is accepted, Thus there is exists no relationship between USD exchange rate and cardamom Price. 219

18 US Dollar Exchange rate in INR vs Gold oil Price in INR Table 25 Gold and USD in INR Year Gold Price dollar Table 26 Correlations USD Gold USD Pearson Correlation ** Sig. (2-tailed).001 N Gold Pearson Correlation.874 ** 1 Sig. (2-tailed).001 N **. Correlation is significant at the 0.01 level (2-tailed). Correlation coefficient value significances the relationship between gold rate and crude oil. It is because when the value of US dollar devaluates in international market bankers as well as investors and traders from all over the world hedge against this adversity through investments in gold. 220

19 Graph 9 USD in INR vs Gold Price in INR Lowest gold rate was observed in the year 2006= 6255 Highest gold rate was observed in the year 2013= The graph depicts that gold price has increased many folds from the year 2008 to 2013 it is because of global recession period from and many investors invested in gold rather than US dollar. Graph20 Trend Analysis of USD exchange rate and Gold Price in INR 221

20 Trend line equation for gold price is Y= x From the trend line for gold we can conclude that on average price of the gold increases by rupees every year. And USD exchange rate value is also increasing on the average of rupees every year Regression Hypothesis Assumed (H0): No relationship between USD exchange rate and Gold price. Alternative Hypothesis (H1): Relationship exist between USD exchange rate and Gold price Table 27 Variables Entered/Removed b Model Variables Entered Variables Removed Method 1 USD a. Enter a. All requested variables entered. b. Dependent Variable: Gold Table 28 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), USD Table 29 ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression 2.689E E a Residual 8.317E E7 Total 3.521E8 9 a. Predictors: (Constant), USD b. Dependent Variable: Gold Table 30 Coefficients a Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) USD a. Dependent Variable: Gold Significant correlation with R= R square value shows that approximately 80% of variation in gold prices accounted for with US Dollar value. Significant linear regression with p value= Regression Equation is Y= X

21 Since P-value is <0.05 H0 is rejected, and H1 is accepted. Thus there is exists relationship between USD exchange rate and Crude oil Price. The negative intercept of t value as well as negative intercept of regression equation shows the inverse relation between the US dollar and gold price. CONCLUSION This study examines the long-run relationship between US dollar exchange rates and the prices of five selected agricultural commodities. In the selected five commodities, two commodities namely Gold and Crude oil share an inverse relationship with US dollar exchange rate. Similarly out of three selected agricultural commodities, two commodities sugar and potato maintains negative relationship with US dollar exchange rate whereas Cardamom shares no relation with US Dollar exchange rate. The findings of the present study support the results of previous studies, which indicate that the agricultural commodity prices are negatively correlated with the US dollar exchange rates i.e. commodity price decrease with increasing US Dollar value against Indian rupee. References 1. Abbott, P. C., C. Hurt, and W. E. Tyner. What s driving food prices in 2011? Farm Foundation Adrangi, B., Chatrath, A., Raffiee, K.,2003, Economic activity, inflation and hedging: The case of gold and silver investments, The Journal of Wealth Management 6, Anthony N. Rezitis, Empirical analysis of agricultural commodity prices, crude oil prices and US dollar exchange rates using panel data econometric methods, Journal of Energy Economics and Policy, 39, Anthony N. Rezitis, The relationship between agricultural commodity prices, crude oil prices and US dollar exchange rates: a panel VAR approach and causality analysis, International Review of Applied Economics 5. Ardian Harri, Lanier Nalley, and Darren Hudson; The Relationship between Oil, Exchange Rates, and Commodity Prices, Journal of Agricultural and Applied Economics, (10) (August 2009) 6. R.Rameshkumar Study On The Optimization Of Solar Assisted Vapour Absorption Refrigeration System, International Journal Of Innovations In Scientific And Engineering Research(Ijiser), Vol 2 Issue 7 Jul 2015 Pp Girish Karunakaran,Nair;Nidhi Choudhary;Harsh Purohit, The Relationship between Gold Prices and Exchange Value of US Dollar in India. ; ISSN(Emerging Markets journal (2015),(10) 8. Hidhayathulla A & Mahammad Rafee.B; Relationship between Crude oil price and Rupee, Dollar Exchange Rate: An Analysis of Preliminary Evidence; IOSR Journal of Economics and Finance (IOSR-JEF) ;4, (Mar-Apr-2014) 9. Norasyikin Abdullah Fahami ; SharazadHaris; Hasyeilla Abdul Mutalib, An Econometric Analysis between Commodities and Financial Variables: The Case of Southeast Asia Countries International Journal of Business and Social Science; (June 2014).(8) 10. Sankararaman G, Rengarajan V, Natarajan R and Nandhini V, A Study On Performance Of Select Commodities Due To Demonetisation,, International Journal of Pure and Applied Mathematics Volume 119 No , (April 2018) 223

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