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2004 - 20094
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Subject: Rural Banking and Finance Management × End date: 2009 × Start date: 2004 ×
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    ThesisItemOpen Access
    Prediction of futures prices of rubber
    (Department of Rural Banking and Finance Management, College of Co-operation, Banking and Management, Vellanikkara, 2009) Anjaly, K N; KAU; Molly Joseph
    The present study entitled “PREDICTION OF FUTURES PRICES OF RUBBER” was conducted with the following objectives i) to examine the price movements of rubber futures through NMCE; ii) to predict the rubber futures prices and iii) to compare the forecasting performance of univariate and multivariate models. Futures trading perform two important functions - price discovery and hedging of price risk, hence an effort to predict the futures prices of rubber, a predominant crop of Kerala, is of contemporary significance to the rubber growers and traders. The study was based on secondary data. Futures prices of daily open, low, high, close and spot and volume traded of rubber were collected for a period from April 2003 to August 2008 from National Multi Commodity Exchange. The daily data were converted into monthly averages for the analysis. The price movements of rubber futures have been examined using ordinary line graph, correlation, candlestick chart, Compound Annual Growth Rate (CAGR) and ANOVA. Correlation has been found inorder to measure the relation between the domestic rubber prices and the crude oil prices. ANOVA was used to find the significance in the growth rate of rubber prices over different time periods. Prediction of futures prices of rubber has been done using the Multiple Linear Regression, Principal Component Analysis and ARIMA and the results of these models were compared to measure the forecasting performance of these models. The price movements of rubber futures using the line graph showed that both the spot and futures prices were highly related and hence prediction of one with the other is possible. Rubber is an internationally traded commodity and the hike in the rubber prices globally influence the domestic the rubber pries. Moreover the rise in the crude oil prices influenced the natural rubber prices, since the movements of domestic rubber prices and the crude oil prices showed a positive correlation. The volumes traded were also fluctuating over the years. The ban on futures trading in rubber drastically reduced the volume traded due to loss of investors’ confidence. Candlestick chart showed that the prices were fluctuating with bullish, bearish and neutral trend. Even though the rubber prices increased, the growth rate of rubber prices and volume traded over the years revealed a lower annualized gain making it clear that there was no abnormal hike in the rubber prices. Hence the rise in rubber prices cannot be attributed to futures trading. The prediction of futures prices of rubber were done by different forecasting models, viz., ARIMA, MLR and PCA. MLR got R square and adjusted R square of 92.1 per cent and 91.5 per cent both values showing the significance of the model for predicting the futures prices. Even though the value of R square is very high none of the regression coefficients were significant in the multiple linear regression model. This might be due to the multicollinearity of the independent variables viz; open, high, low and volume traded which are highly correlated. Hence the principal component analysis was done. The R square and Adjusted R square for the regression equation fitted using the Principal components as regressor are 91.7 per cent and 91.6 per cent respectively. So with P1 ie., the first component generated using open price, it was able to predict 91.7 per cent of the variation in the close price of rubber futures. The ARIMA results got R square of 99 per cent wth MAPE 1.97 per cent indicating that the forecasting inaccuracy was very low and the Normalized Bayesian Criteria (BIC) of 10.478 indicated goodness of fit of the model and the accuracy of the prediction. While comparing the results of MLR, PCA and ARIMA, it was found ARIMA performed better in prediction. Also the forecasting errors of ARIMA were negligible indicating the forecasting efficiency of the model. Hence the study concluded that the univariate model outperforms the multivariate model with better accuracy in prediction.
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    ThesisItemOpen Access
    Commodity futures - A study of online trading in rubber
    (Department of Rural Banking and Finance Management, College of Co operation and Management, Vellanikkara, 2007) Anu, S Nair; KAU; Padmini, E V K
    The present study entitled “COMMODITY FUTURES A STUDY OF ONLINE TRADING IN RUBBER” was conducted with the following objectives. 1) To examine the price movements of rubber futures through National Multi Commodity Exchange of India Ltd. (NMCE). 2) To assess the impact of futures trading on farming decisions of rubber farmers; and 3) To identify the determinants of online trading by rubber farmers. Primary and secondary data have been used for the study. Daily data of rubber futures in NMCE and the corresponding spot prices were collected from the website of NMCE. The data regarding the area production, yield, export, import, major producing countries and major consuming countries were collected from the souvenir of publications of Rubber Board, Economic Survey and website of tire review. Primary data to analyse the impact of futures trading and to identify the determinants were collected using a structured interview schedule. The sample respondents constituted 33 trading farmers from the districts of Kottayam, Palakkad and Thrissur and another group of 33 non-trading farmers from the district of Kottayam. The trend in area production, and yield were analysed using compound growth rate and percentage change over the previous year. The compound growth rate of area under rubber is found to be 8.2 per cent during the period 1950-51 to 2004-05. Although in absolute terms production has been increasing, there has been a decreasing trend since 1999-2000 till 2001-02. The compound growth rate of production comes to 16.36 per cent. The productivity of natural rubber recorded a continuous growth over the period except in 1999-2000 to 2001-02. The compound growth rate for yield works out to 7.47 per cent. A look into the global natural rubber scenario revealed that Thailand, Indonesia and Malaysia are the leading producers and they together constitute about 77 per cent of the global production. India is the fourth largest producer and consumer of natural rubber. China tops the list of consuming countries. The major exporters are Thailand, Indonesia and Malaysia and the major importers are China, USA and Japan. The analysis of the commodity derivatives market in India revealed that out of the three National Commodity Exchanges, National Multi Commodity exchange is the first exchange. All these three exchanges are multi commodity exchanges. The commodity exchanges are regulated by forward markets commission which is coming under the Ministry of Consumer Affairs, food and nutrition. To analyse the objective of examining the price movements of rubber futures through NMCE the co-integration technique is used. The results revealed that the futures prices of two months prior to delivery (F2) one month prior to delivery (F1) and delivery month (F0) are efficient in predicting the spot prices of rubber and prediction using futures price three months prior to delivery (F3) is not effective. The impact of futures trading on the farm management practices of the rubber farmers were analysed using simple percentages and averages. The study revealed that there is no change in any of the activity undertaken by the rubber farmers before and after commencement of futures trading. The non-trading farmers are enjoying the economics of large scale operations. Also the only positive change of the futures trading is their awareness about the storing facilities available at Central Warehousing Corporation eventhough they are not using that facility. The influence of private traders in marketing the product is as high as Rubber co-operative Marketing Society and Rubber Producers Society. No exploitation was faced by any of the farmers as they are educated farming community having better bargaining power. The futures trading could not make a considerable impact on the farming decisions of rubber farmers because they are not at all interested in delivery and so they are least bothered about the underlying asset. They consider futures trading as an avenue for speculation where they can bet on the price movements. For identifying the determinants of online trading by rubber farmers, Kendall’s coefficient of concordance was applied. Accessibility to trading terminal, awareness creation and computer literacy were found the most important determinants of futures trading. There are some differences in the ranks assigned by trading and non-trading members. Availability of warehousing facility, procedure formalities and speculative nature were found least important determinants. Starting of terminal outlets in remote areas, extensive campaign for awareness creation about futures trading and computer education to remove the aversion towards screen based trading will attract move number of participants to futures trading. Compulsory delivery of the underlying asset is to be enforced by the regulatory authorities to make the real farmers the beneficiaries of futures trading and thereby ensuring a remunerative price.
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    ThesisItemOpen Access
    Loan recovery management in primary co-operative agricultural and rural development banks in Kerala
    (Department of Rural Banking and Finance Management, College of Co-operation Banking and Management, Vellanikkara, 2004) Renjitha, N T; KAU; Lizy, M A
    The study entitled "Loan Recovery Management in Primary Co-operative Agricultural and Rural Development Banks in Kerala" was conducted to examine the effectiveness of the existing loan recovery management of Primary Co-operative Agricultural and Rural Development Banks in Kerala and to identify the factors influencing recovery. The study was conducted among four PCARDBs of Ernakulam and Thrissur district viz., Kanayannur CARDB (B 1), Ernakulam CARDB (B2), Cochin CARDB (B3) and Irinjalakuda CARDB (B4). The sample size included 80 respondents i.e., 20 borrowers from each bank at random, of which 15 were defaulters and five were non-defaulters or prompt repayers. Ten officials (including secretaries and BODs) from each bank were also interviewed to collect information on the effectiveness of the loan recovery system of the banks. Secondary data on selected performance indicators of the banks were also used for the study. Statistical tools like AAGR, simple averages, percentages, simple growth rate, simple correlation, efficiency index, priority index and bi-variate tables were used for the analysis. The analysis on the overdue amount of the selected PCARDBs, revealed that Cochin CARDB (B3) had the highest amount of overdues among all the banks, , during the reference period. Profits of all banks have eroded due to provisronmg for accumulated overdues. B4 has shown the best performance in terms of lower overdues and higher profitswhen compared to the other banks. An increase in the demand for nOI1- agricultural loans, particularly RHLs was found, which indicates a shift in the lending pattern. Overdues above four years were growing tremendously in all the banks. Most of the females were found to be prompt repayers. Inspite of having better education, the borrowers were creating huge overdues. This indicates the existence of wilful defaulters. The study found that the defaulters of all t11:;: banks except B4, having annual income above the subsistence level had higher am aunt of overdues, This highlights the fact that, even after having sufficient income, they were deliberately making dues as a result of the inefficient loan recovery management of the bank. The study revealed that procedural delays, lack of adequate securities to hypothecate, misutilisation of loans and inadequate income restricted the borrowers from getting timely loans. It was further observed that defective loaning policy, conspicuous consumption, and illness of family members as well as hope for 10a11 write-off policy were the other reasons behind non-repayment by borrowers. Misutilisation of loan amount was least in B4, which indicates the presence of effective supervision and monitoring mechanism in the bank. Loan amount was mainly diverted for meeting ceremonial expenses, consumption needs and educational expenses of children. The most serious problem in obtaining loam was revealed to be the procedural delay. From the inter-bank comparison on the effectiveness of the present loan recovery management system, it was found that B4 showed an outstanding performance in this regard, whereas B3 revealed to be the least efficient bank. According to the officials and employees of the banks, the reasons for poor recovery included lack of modern management techniques, lack of adequate staff training programmes, lack of infrastructural facilities and inefficiency of the legal machinery for recovering dues from borrowers. As a remedial measure to minimise overdues, coercive action against wilful defaulters and incentives for proper repayment must come into effect. For checking the rising trend of over dues in future, an effective loan appraisal as well as loan monitoring cell managed by professionals has to be established in each bank. The banks must put into effect the SARF AESI Ad, 2002 in order to bring a solution to the problem of overdues. The banks must therefore perceive that prolonged existence of this disease is not beneficial to the organisation and a strong mechanism to check this menace has to be created.
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    ThesisItemOpen Access
    Futures trading in pepper
    (College of Co-operation Banking Management, 2008) Sapna, K Rani; KAU; Molly, Joseph
    The study on “Futures trading in Pepper” has been conducted with the main objectives of analyzing price discovery mechanism of pepper futures in NMCE and examining the benefits of futures trading in pepper to farmers and traders. Both primary and secondary data were used for the study. The first objective of analyzing the price discovery mechanism of pepper futures was done using secondary data on daily futures and spot prices from May 2003 to March 2008 of NMCE. For examining the benefits of futures trading in pepper to farmers and traders, primary data were collected from sample farmers and traders by means of a structured interview schedule. Two districts of Kerala, namely, Ernakulam and Wayanad were selected to identify the farmers and traders respectively, for collecting information regarding the benefits derived from futures trading. From each of the two districts of Ernakulam and Wayanad, 30 respondents were selected to analyze the benefits of futures trading in pepper to farmers and traders. These respondents were classified as trading farmer, non - trading farmers and non- farmer traders. The data collected have been processed using MS – Excel sheets. Co-integration technique, Kendall’s Co-efficient of Concordance, Mann Whitney U Test, Student’s t – Test, Compound Annual Growth Rate and annual growth rate were used to analyse the data. An analysis of trend of futures and spot prices of pepper has revealed the efficiency of the price discovery mechanism of pepper futures. The spot and futures prices under the study period showed an increasing trend. As spot price is always below the futures price there is opportunity for hedging. Both the spot and futures prices are moving more or less in the same direction. Since the trend lines are very closely moving, it implies that the two prices are highly related and prediction of one using the other is possible. To analyse price discovery mechanism of pepper futures Co-integration technique was used. Futures prices prior to three months (F3), four months (F4) and five months (F5) prior to delivery are closer to the spot price. This also brought to light the efficiency of the co integration technique in identifying the movement of two variables in the same direction. The advantages of online trading to different group of traders in the pepper futures by means of Kendall’s co-efficient of concordance outlined increased trade volume, increasing liquidity in trading and better terminal facility as the most preferred advantages for the farmer traders of Wayanad. For the non farmer traders, easy settlement, increased number of participants and time saving are of importance, while increased liquidity is of least advantage to them. As far as the traders of Ernakulam are concerned, increase in liquidity in trading, increased trade volume and time saving are the most available advantages to the non farmer traders, while price discovery seemed to be the least available advantage for them. Pair wise comparison of benefits of futures trading to various groups of respondents by means Mann-Whitney U test revealed that there is significant difference between the traders and farmers with respect to the extent of benefits of futures trading enjoyed by them. It is also proved that there is no significant difference between the different categories of traders, irrespective of whether they are farmers or hill produce merchants or exporters or speculators. The criterion for enjoying the benefits is not whether the trader is a farmer or a non farmer, but whether he trades in futures or not. Starting of terminal outlets in remote areas, extensive campaign for awareness creation about futures trading and computer education to remove the aversion towards screen based trading will attract more number of participants to futures trading. Compulsory delivery of the underlying asset is to be enforced by the regulatory authorities to make the real farmers the beneficiaries of futures trading and thereby ensuring a remunerative price. Also co-operative marketing societies in the field of spice market should be strengthened to give farmers benefits of remunerative prices through large scale marketing and processing.