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January 2015

 

Investment Preferences towards Commodity market and other investment options

(An Empirical analysis with Reference to Selected Residents in Pondicherry)

 

 

Dr.N.S.PANDEY

 

P.KATHAVARAYAN

 

Assistant Professor

PG and Research Department of Commerce

KanchiMamunivar Centre for PG-Studies

drnspandey@gmail.com

Ph. No:9443974657

Doctoral Research Scholar

 PG and Research Department of Commerce

KanchiMamunivar Centre for PG-Studies

kathavarayan.raman007@gmail.com

Ph. No: 9597990829

 

 

 

 

 

 

 

KanchiMamunivar Centre for PG- Studies

[Autonomous “A” Grade by NAAC & Centre with Potential for Excellence by UGC]

(Government of Puducherry) Pondicherry University

Puducherry – 605 008, India

ABSTRACT

The objective of this paper is to examine the investment preference towards commodity market and other investment options, this study deals with investment preference from commodity market, equity market, debenture and mutual fund. The investigation is conducted primary data on a sample of 116 respondents from Puducherry region. The study based on the level of  preference in the process of investment in commodity market, analysis the perception and involvement in commodity market and awareness of  commodity market, using the multiple regression technique(Y=a+b1x1+b2x2+b3x3+b4x4+b5x5) . The results of the multiple regression analysis significance among are of investors’ awareness, perception and involvement and preference, also there was a highly significant relationship between age, education and annual income. Therefore, this study proves that majority of the respondents are having full awareness about commodity market and most of the respondents prefer to invest in commodity market.

KEY WORDS: Commodity, Perception, Preference, Investors, Investment

JEL CODE: D81, G11, G14, G

INTRODUCTION

Commodity refers to any good that possesses a physical attribute (Chatani,2010). Every commodity that is produced (or grown) must eventually come to a market place where it can be bought and sold (Chatani, 2010). Commodity market is extremely liquid, risky and complex by nature. Futures  market is centralized market place for buyers and sellers from around the world who meet and enter into commodity futures contracts. Pricing is mostly based on an open cry system, or bids and offers that can be matched electronically. The commodity contract will state the price that will be paid and the date of delivery. Almost all futures contracts end without the actual physical delivery of commodity.

The history of organized commodity derivatives in India goes back to the nineteenth century when Cotton Trade Association started futures trading in 1875, about a decade after they started in Chicago. Over the time derivatives market developed in several commodities in India. Following Cotton, derivatives trading started in Oilseed in Bombay (1900), raw jute and jute goods in Calcutta (1912), Wheat in Hapur (1913) and Bullion in Bombay (1920)

            In India, there are four important commodity exchanges are in operation to facilitate global investors. NMCE2002 (National Multi Commodity Exchange of India Ltd.) 26th Nov., NCDEX2003 (National Commodity & Derivates Exchange Ltd.) on April, ICEX (Indian Commodity Exchange Ltd.) 27 Nov, 09 and MCX (Multi Commodity Exchange of India Ltd.)

Nov, 2003

IMPORTANCE OF THE STUDY

The main idea behind the study is to find out the investment preference of commodity market. This study deals with investment preference from commodity market to find out the characteristics of investors who invest under the guidance of different share brokers. It also concentrates on whether they are satisfied with the service and earnings from the commodity market to provide by the investment and also the brokers service on different types of commodity from their investment guide.

The study entitled “Investment Preference in Commodity Trading” has been conducted in Puducherry region. The study has undertaken to know the preference of the investors towards various investment avenues in relation to commodity market. The sample from the population is taken based on commodity investor and other investors. The expectations of the investors are quite high and many expect high rate of return for further investment through commodity market.

REVIEW OF LITERATURE

 

 

Senthil Kumar (2012) studied titled “An analysis of Postal Investment and Small investors Savings”, have shown that mobilization of domestic financial resource has remained a major concern in many developing countries. Despite the variety of vehicles that are intended to mobilize and allocate financial resources, Savings are increasingly beings acknowledged as a powerful tool for poverty reduction. Postal savings funds play a significant role in financing public debt and in a number of countries, the funds are intermediated through a variety of policy based financial institutions with developmental objectives, returning the funds to the direct benefits of the community of savers. Savings is the excess of income over consumption expenditure. Savings are meant to meet contingencies and raise standard of living of individual savers. Shobana V.K. and Jayalakshmi J.(2009) in the study title on “Investors’ awareness and preferences”, studied the investors’ preferences and investors’ awareness and the factor influencing investors’ awareness. The study discloses that real estate, bank deposit and jewelers were the preferred investments. Nirmal Kumar R. T. (2006) in his study recognized that a perception lies with popular of investors that future trading will lead to returns and it is not used for other purpose like hedging. The nature of the derivatives instruments are to reduce the risk involved in trading but in real time investors are not taking derivatives trading for reducing their risk involved in trading and profit making is considered to be an important factor for the them. On the other side a number of reforms and initiatives are still needed in supporting India as a major futures trading for the top five producers of most of the commodities. Radha (1995) study titled “a study on Investment Behaviour of Investors in Securities”, studied the investment plan of corporate securities investors’ analysis discloses that the largest segment of sample constituted by young generation model investors.

 

OBJECTIVES OF THE STUDY

·         To find out the Trading Mechanism in the Commodity Market.

·         To examine the level of Awareness in Commodity trading and Market.

·         To measure the level of Preferences in the Process of Investment in Commodity Market.

·         To assess the Perception and Involvement in Commodity trading.

HYPOTHESES OF THE STUDY

·         H01 There is no significant relationship among the demographic variables (age, education) and awareness of commodity trading and market.

·         H02 There is no significant relationship among the demographic variables (age, education) and preferences in the process of investment in commodity market.

·         H03 There is no significant relationship among the demographic variables (age, education) and involvement of commodity trading.

·         H04 There is no significant relationship among the demographic variables (age, education) and perception of commodity market.

 

METHODOLOGY

The source of the data for the study has been collected from primary sources. A survey was conducted to collect the primary data from the selected respondents of general public in Pondicherry. The total number of sample is 116 from whom data is collected among the total number of respondents 41 are investors and among the investors 25 respondents were involved in commodity trading. The remaining 75 respondents are non-investors. Adopting convenience sampling technique, the data were collected through interview schedule from the selected respondents. Data were analysed through statistical tools like multiple regression analysis and percentage analysis.

Demographic Profile of Respondents (Table - 1)

STATUS

RESPONDENTS

PERCENTAGE %

Gender

 

 

Male

Female

109

07

94

6

Total

116

100

Age

 

 

Below 20 years

20 to 40 years

Above 40 years

3

93

20

3

80

17

Total

116

100

 

 

 

 

Education

 

 

SSLC

Higher secondary

UG

PG

Others

15

5

62

32

2

13

4

53

28

2

Total

116

100

Occupation

 

 

Government

Private sector

Self-employment

Others

1

59

28

28

1

51

24

24

Total

116

100

Annual income

 

 

Below Rs.100000

Rs.100000 to Rs.300000

Above Rs. 300000

85

31

0

73

27

0.0

Total

116

100

 

 

MULTIPLE REGRESSION ANALYSIS

 

V. Analysis on Investors’Behaviour

I. Level of Awareness on Commodity Market

Influence of investors’ demographic variables (Independent variable) on level of awareness on commodity market (Dependent variable) was analysed with multiple regression analysis the demographic variables like age, gender, occupation, annual income, education on level of awareness on commodity market was considered for analysis (Y=a+b1x1+b2x2+b3x3+b4x4+b5x5)

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.585(a)

.343

.170

.302

2

.585(b)

.343

.211

.295

3

.583(c)

.340

.246

.288

4

.581(d)

.337

.277

.282

5

.538(e)

.290

.259

.286

 

Table - 2

 

 

 

 

 

 

 

 

 

 

 

 

ANOVA f(Table -3)

 

Model

 

 

Sum of squares

 

df

 

Mean squares

 

       F

 

 

Sig.

1      Regression

        Residual

        Total

 

.905

1.735

2.640

5

19

24

 

.181

.091

1.982

.128a

2      Regression

        Residual

        Total

 

.905

1.735

2.640

4

20

24

.226

.087

2.607

.067b

3      Regression

        Residual

        Total

 

.899

1.741

2.640

3

21

24

 

.300

.083

3.612

.030c

4      Regression

        Residual

        Total

 

.890

1.750

2.640

2

22

24

.445

.080

5.594

.011d

5      Regression

        Residual

        Total

 

.765

1.875

2.640

1

23

24

.765

.082

9.384

.006e

 

 

Interpretation with Regression Model (Table- 4)

 

Model

R  square

Sig

Result

Selected Model

 

1

 

.343

 

.128

 

Non-significant

 

 

2

 

.343

 

.067

 

Non-significant

 

 

3

 

.340

 

.030

 

Significant

 

Selected

 

4

 

.337

 

.011

 

Significant

 

 

5

 

.290

 

.006

 

Significant

 

 

[

The Multiple regression analysis was carried out to find out the influence of demographic variables of investors’ on their level of awareness. Multiple regression models were generated to find significant model. Out of five regression models generated, three models were significant (p value < 0.05).

­­­

Out of the three significant models generated, the highest R2 value is selected as fit model that is Model 3 (0.030) and since the regression value is more among the significant models. There is significant relationship between demographic variables is highly significant on awareness of commodity trading, it means thatHo1is rejected.

 

Multiple Regression Model (Model 3)

 

Y=a+b1x1+b2x2+b3x3+b4x4+b5x5

                                                 

 

Y (Level of awareness on commodity market) = a (Constant) + b1 (Age) +

 

b2 (Education) +b3 (Annual income)

 

 

Y= (Constant) 2.312 + (-0.241) (Age) +0.080(Education) + (-0.052) (Annual income)

 

II. Level of Preference on commodity market

 

Influence of investors demographic variables (Independent variables) on level of preference on commodity market ( dependent variables) was multiple  regression analysis the demographic details like age, gender, occupation, annual income, education  on level of preference on commodity market was considered for analysis

(Y=a+b1x1+b2x2+b3x3+b4x4+b5x5)

                                                       Table -5

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.537(a)

.288

.101

.190

2

.535(b)

.286

.144

.185

3

.524(c)

.274

.171

.182

4

.501(d)

.251

.183

.181

 

Table – 6 ANOVAa

 

Model

 

 

Sum of squares

 

df

 

Mean squares

 

       F

 

 

Sig.

1      Regression

        Residual

        Total

 

.277

.683

.960

 

5

19

24

.055

.036

 

1.538

.225a

2      Regression

        Residual

        Total

 

.275

.685

.960

 

4

20

24

 

.069

.034

 

.2.008

.132b

3      Regression

        Residual

        Total

 

.263

.697

.960

 

3

21

24

 

.088

.033

 

2.646

0.76c

4      Regression

        Residual

        Total

 

.241

.697

.960

 

2

22

24

.121

.033

 

3.688

.042d

 

 

               

 

 

 

 

 

 

 

 

 

 

 

 

 

      Table - 7 Interpretations with Regression Model

 

Model

R  square

Sig. value

Result

Selected Model

 

1

.288

.225

Non-significant

 

2

.286

.132

Non-significant

 

3

.274

.076

Non-significant

 

4

.251

.042

significant

Selected

 

The Multiple regression analysis was carried out to find out the influence of demographic variables of investors’ on their level of preference. Multiple regression models were generated to find significant model. Out of four regression models generated, one model was significant (p value < 0.05).

 

Thus, the significant model generated, the highest R2 value is selected as fit model that is Model 4 (0.042) and since the regression value is significant among all models generated. There is significant relationship between demographic variables is highly significant on preferences of commodity trading, it means that H02 is rejected.

 

Multiple Regression Models (Model 4)

 

                    Y=a+b1x1+b2x2+b3x3+b4x4+b5x5

                                     

 

Y (Level of Preference  on commodity market) = a (Constant) +b1 (Age) 

+b2 (Education)

 

 

 

Y= (Constant) 1.843 + (-0.225) (Age) + (-0.111) (Education)

 

III. Level of Involvement on Commodity Market

Influence of investors’ demographic variables (Independent variable) on level of Involvement on commodity market (Dependent variables) was analysis with multiple regression analysis was carried out on investors’ demographic details like age, gender, occupation, annual income, education on level of Involvement influence of investors’. A demographic detail on level of Involvement on commodity market was considered for analysis.

( Y=a+b1x1+b2x2+b3x3+b4x4+b5x5  )

                                                       Table - 8

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.848(a)

.720

.646

.470

2

.848(b)

.719

.663

.458

3

.843(c)

.711

.669

.454

4

.824(d)

.679

.650

.467

5

.811(e)

.658

.644

.471

 

 

Table -9           ANOVAf

 

Model

 

 

Sum of squares

 

df

 

Mean squares

 

       F

 

 

Sig.

1      Regression

        Residual

        Total

 

10.765

4.195

14.960

5

19

24

 

2.153

.221

 

9.751

.000a

2      Regression

        Residual

        Total

 

10.757

4.203

14.960

 

4

20

24

2.689

.210

 

12.799

.000b

3      Regression

        Residual

        Total

 

10.632

4.328

14.960

 

3

21

24

 

3.544

.206

17.198

.000c

4      Regression

        Residual

        Total

 

10.765

4.797

14.960

 

2

22

24

5.081

.218

23.303

.000d

5      Regression

        Residual

        Total

 

9.850

5.110

14.960

 

1

23

24

9.850

.222

44.331

.000e

 

Interpretation with Regression Model (Table - 11)

 

Model

R  square

Sig. value

Result

Selected Model

 

1

 

.720

 

.000

 

Significant

 

Selected

 

2

 

.719

 

.000

 

Significant

 

 

3

 

.711

 

.000

 

Significant

 

 

4

 

.679

 

.000

 

Significant

 

 

5

 

.658

 

.000

 

Significant

 

 

The Multiple regression analysis was carried out to find out the influence of demographic variables of investors’ on their level of Involvement. Multiple regression models were generated to find significant model. Out of five regression models generated, five models were significant (p value < 0.05).

Five significant models generated, the highest R2 value is selected as fit model that is Model 1(0.000) and since the regression value is more among the significant models. There is significant relationship between demographic variables is highly significant on involvement of commodity trading, it means that H03 is rejected.

 

Multiple Regression Models (Model 1)

  Y=a+b1x1+b2x2+b3x3+b4x4+b5x5

                                     

 

Y   (Level of  Involvement on commodity market) = a (Constant) +b1 (Age) +b2

 

(Gender) +b3 (Education) +b4(Occupation) +b5 (Annual income)

 

 

Y= (Constant ) 0.856+1.222( Age)+(-0.733)( Gender) +(-0.086)( Education)+(-0.264)

 

(Occupation)+(-0.049) (Annual income)

 

IV. Level of Perception on Commodity Market

 

         Influence of investors demographic variables (Independent variables) on level of Perception on commodity market (Dependent variable). Multiple regression analysis the demographic details like age, gender, occupation, annual income, education on level of Perception influence of investors’. A demographic detail on level of perception on commodity market was considered for analysis.(Y=a+b1x1+b2x2+b3x3+b4x4+b5x5)

 

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.641(a)

.411

.256

1.362

2

.641(b)

.411

.293

1.328

3

.640(c)

.409

.325

1.297

4

.610(d)

.372

.315

1.307

5

.542(e)

.293

.263

1.356

 

 

Model

 

 

Sum of squares

 

df

 

Mean squares

 

       F

 

 

Sig.

1      Regression

        Residual

        Total

 

24.575

35.266

59.540

5

19

24

 

4.915

1.856

2.648

.056a

2      Regression

        Residual

        Total

 

24.575

35.266

59.840

4

20

24

6.143

1.763

3.484

.026b

3      Regression

        Residual

        Total

 

24.499

35.341

59.840

3

21

24

 

8.166

1.683

4.852

.010c

4      Regression

        Residual

        Total

 

22.250

37.590

59.840

2

22

24

11.125

1.709

6.511

.006d

5      Regression

        Residual

        Total

 

17.554

42.286

59.840

1

23

24

17.554

1.839

9.548

.005e

 

Table-  12

 

 

 

 

Table-13

 

 

 

 

Table-14

Interpretation with Regression Model (Table - 15)

 

Model

R  square

Sig.value

Result

Selected Model

 

1

 

.411

 

.056

 

Non-Significant

 

 

2

 

.411

 

.026

 

Significant

 

Selected

 

3

 

.409

 

.010

 

Significant

 

 

4

 

.372

 

.006

 

Significant

 

 

5

 

.293

 

.005

 

Significant

 

The Multiple regression analysis was carried out to find out the influence of demographic variables of investors’ on their level of perception. Multiple regression models were generated to find significant model. Out of five regression models generated, four models were significant (p value < 0.05).

Out of the four significant models generated, the highest R2 value is selected as fit model that is Model 2(0.026) and since the regression value is more among the significant models. There is significant relationship between demographic variables is highly significant on perception of commodity market, it means that H04 is rejected.

 Multiple Regression Models (Model 2)

                    Y=a+b1x1+b2x2+b3x3+b4x4+b5x5

                               

Y  (Level of Perception on commodity market) = a ( Constant) + b1(Gender) +b2( Education) +b3( Occupation) +b4(Annual income)

 

 

Y= (Constant) (-3.490) + (-0.290) (Gender) +0.283 (Education) +0.819(Occupation) +2.583 (Annual income)

FINDINGS OF THE STUDY

I. Profile of the Respondents

·         Age wise classification of the respondents: Majority of the respondents are in the age of 20 to 40 years (80 per cent) than above 40 years (17 per cent), and below 20years (3 per cent).

 

·         Gender wise classification of the respondents: Majority of the respondents are   male (94 per cent) than female (6 per cent), because male are higher interested in investing.

 

·         Educational wise classification of the respondents: Most of the respondents’ educational qualification is UG (53 per cent) than PG (28 per cent), SSLC (13 per cent), HSC (4 per cent), and others (1 per cent).

 

·         Occupation wise classification of the respondents: Most of the respondents are working in Private sector (51 per cent), than self-employment and others for (24per cent), and Government sector (1 per cent).

 

·         Annual income wise classification of the respondents: Most of the respondents annual income is below Rs.100000 (73 per cent) than Rs.100000 to Rs300000 (27 per cent), and above Rs.300000 no respondents.

 

II. Awareness and Involvement in Commodity Trading

·         Awareness on commodity market: Most of the respondents are having awareness on commodity market (54 per cent) than not aware about commodity market (46 per cent), because more respondents are educated.

·         Involvement in commodity trading: Almost one fourth of the respondents are involved in investment in commodity market, because more respondents trading knowledge very low.

 

 

·         Reason for not trading in commodity market: Most of the respondents are not interested in trading in commodity market (56 per cent) than not having money (29 per cent) and high risky (15 per cent).

 

·         Participation in awareness programs on commodity trading: Almost half of the respondents attended the awareness programs (43 per cent)

 

·         Organizer of the program on commodity market: Most of the respondents attended program organized by educational institution (28 per cent) than brokers (13 per cent), investor association (4 per cent), and commodity market (MCX, NCDEX), .not attended program (55 per cent).

·         Willingness to know about commodity trading: Most of the respondents are willing to trade in the commodity market (72 per cent).

III. Investors’ Perception on Investment

·         Period of Involvement in investment: Most of the respondents are involved between the period of investing for 1 to 3 years (61 per cent) than less than 1 year (37 per cent), and 3 to 5 years (2 per cent).

·         Funds for investment: Majority of the respondents are investing from their savings (98 per cent), than loans (2 per cent), pledging and others. So investors are investing from their savings which makes them to make high return with low risk through their confidence.

·         Resource for investment: Most of the respondents are aiming for high income on investment (51 per cent), than for future welfare (32 per cent), reasonable income (12 per cent), safety (5 per cent), retirement protection and tax benefit, because the main aim of the investing is to generate more income.

·         Portion of income in investment: Majority of the respondents are investing below 25% of their income (90 per cent), than 25% to 50% (10 per cent), 50% to 75% and above 75%, because of change in prices and low risk taking capacity.  

·         Risk taking capacity of investor:  Most of the respondents are risk taking capacity is medium (63 per cent) than low (20 per cent), high (17 per cent), because changing volatility of price and not having sufficient money for investing.

·         Person to get investment advises:  Most of the respondents get advice from their friends (68 per cent), than family (17 per cent), consultants/brokers (15 per cent), newspapers, web source, and others.

·          Preference for investment: Most of the respondents are preferred to invest in commodity market (61%) than shares (20 per cent), Insurance (19 per cent), mutual funds, and debenture.

IV. Investors’ Perception in Commodity Market

·         Period of investment in commodity market: Most of the respondents are in investing in commodity market for 1 to 2 years (40 per cent) than below 1 year (32 per cent), above 2 years (28 per cent).

·         Frequency of trading in commodity market: Majority of the respondents are trading daily in the commodity market (96 per cent) than weekly (4 per cent), monthly and rarely, because they are interested to watch daily market conditions and to gather more knowledge about the commodity market.

·          Level of awareness on commodity market: Majority of the respondents are having full awareness about commodity market (88 per cent) than good awareness (12 per cent), unaware, and totally unaware, because the respondents discuss with their trading friends who make high return in the market.

·         Reason for choosing commodity market: Majority of the respondents are choosing the commodity market for getting high return (100 per cent) than moderate return, safe return, easy procedure and others.

·         Investment preferences on commodity trading: Majority of the respondents are in investing in interested metal (80 per cent) than energy (20 per cent), the agriculture, and bullion. Because price of the metal is increasing day by day in the present scenario.

·         Specialty of Trading in Commodity Market: Most of the respondents are trading for price hedging (3.36) than low risk (3.24), quality products (1.76) and regulated marketing (1.64).

·         Recommendation to others about commodity trading: All the investors in the commodity market are recommending about commodity market to others. Because to make others experience the commodity they experienced.

 

V. Analysis on Investors’ Behaviour (Multiple Regression Analysis)

·         Level of Awareness on Commodity Market:, Model 3 (0.030) was selected as fit     model, since the regression value is more among the significant models.

Level of awareness on

       commodity market = 2.312 + (-0.241) (Age) +0.080(Education) +

                                    (-0.052) (Annual income)

 

The Age, Education. Annual income influences the Level of awareness on commodity market among the selected independence variables are analyzed.

·         Level of Preference on commodity market: Model 4 (0.042) was selected as fit model, since the regression value is more among the significant models.

Level of preferences on

    commodity market =  1.843 + (-0.225) (Age) + (-0.111) (Education)

 

 The Age, Education influence the Level of preferences on commodity market among the selected independence variables are analysed.

·         Level of Involvement on commodity market:  Five models were significant (p value < 0.05). Model 1 (0.000) was selected as fit model,

Level of  Involvement on

         commodity market = 0.856+1.222( Age)+(-0.733)( Gender) +(-0.086)

                                              ( Education)+(-0.264) (Occupation)+(-0.049)AI                                             

The Age, Education, Gender, Education, Occupation, Annual income influence the Level of preferences on commodity market among the selected independence variables are analysed.

·         Level of Perception on Commodity Market: Model 2 (0.026) was selected as fit model, since the regression value is more among the significant models.

Level of Perception on

         commodity market = (-3.490) + (-0.290) (Gender) +0.283 (Education)                                                +0.819(Occupation)   +2.583 (Annual income)

 

The, Education, Gender, Education, Occupation, Annual income influence the Level of preferences on commodity market among the selected independence variables are analysed.

CONCLUSION

 The investor has their own choices and preferences in making decisions for investment there is a need for understand investors’ preferences. This study dealt with investors’ preference in commodity trading by finding out the characteristics of investors who invest under the guidance of different share brokers, trading mechanism in the commodity market, level of awareness, level of preferences in the process of investment and perception and involvement in commodity trading and market.

 A survey is carried out with general public. The analysis was made on awareness, involvement and perception on investment in commodity market. It is found that, investors are having willingness to know about commodity trading, most of the respondents are willing to trade in the commodity market, investors’ are investing to make high return with low risk through their confidence, most of the respondents prefer to invest in commodity market than shares, Insurance, mutual funds and debenture, majority of the respondents are having full awareness about commodity market. It is suggested to investors’ that, discuss not only with friends but also with share brokers, investors has to take high-risk, invest in other commodity traded in the market, and the investor has to have interest to know more about trading in commodity market.

The non-investors’ have to get interest to invest in securities and commodity market, invest to earn return and to manage influencing factors. Market and brokers has to make settlement of transaction quickly, improve and increasing promotional activities, and develop trading technology. The regulated market and government has to provide support and encouragement for investors and non-investors’, introduce new schemes in the commodity market and margin amount may be reduced to encourage small investors.

Thus, the investors prefer to have more return with adequate risk and assistance of the brokers’ expertise for trading in the commodity market but the investors has to have interest towards learning about the commodity market by their participation to improve their investment choices and preferences.

SUGGESTIONS AND RECOMMENDATIONS

Suggestions to Investors

·         Investor has to discuss about the market condition and performance with the share broker and dealers beyond discussing only with friend to make efficient investment decisions.

·         Investors’ may take high risk in investment in commodity market to earned high return since many of the investors are only taking moderate return.

·          Investors’ are highly interested investing only in metal in the commodity market but they have to invest in other commodity traded in the market to build portfolio to diversify risk.

·         The investor has to have interest to know more about trading in commodity market to make more return on investment.

·         The investor has to attended online trading programs to take efficient investment decision.

Suggestions to Non Investors

·         Non investors have to get interest to invest in securities and commodity to earn return and to manage the influence of inflection effect.

·         Non investor has to have interest on investment and know about trading in market including commodity market.

·         Investors’ may start investing in commodity market since the Forward Market Commission (FMC) and Regulated Commodity market, (MCX, NCDEX, NMX, and ICEX) and government of India in providing lot of support and encouragement to the general public.

Suggestions to Commodity Market and Broker

·         The Settlement of commodity trading transaction has to be reduced and quick settlement has to carried out to make frequent trading in the market.

·         Increase promotions activity on commodity trading for the wide reach of investor to increase participation in commodity trading.

·         Update the technology for speedy transaction in trading.

·         The stock brokers highly concentrate in share market than commodity market thus there may be exclusive broking office for commodity trading.

 Suggestions to Forward Market Commission and the government

·         The investors’ are provided with adequate possibility and support for investment still they have to penetrate among the rural investors’ and non-investors’.  

·         The investors’ has to be encouraged with new schemes in the commodity market, as recently introduced, Rajiv Gandhi Equity Savings Scheme for investor in equity market.

The margin for trading in the commodity market may be reduced to encourage small investors in the commodity market.

References

1.      Chatani, Niti Nandini (2010). Commodity Markets, New Delhi: Tata Mcgraw Hill Education Pvt. Ltd. 2.

2.      Ibid. 5.

3.      Nirmal Kumar, R., &Balaji, K. (2011).An Empirical Investigation on the Investors’ Perception towards Commodities Futures Trading in India with special reference to Puducherry.International Journal of Business Economics&Management research.

1(2), 6-13.

4.      Radha,V.(1995).A study on Investment Behaviour of Investors in Corporate Securities.(Doctoral Dissertation). Allagappa University, Karaikudi

5.      Shobana,V.K., &Jayalakshmi, J.(2006).Investors’ Awareness and Preferences.Organizational Management. Xxv(3),16-18..

6.      Senthilkumar,K. (2012).An analysis of Postal Investment and SmallSavings.Banking Finance.Xxv(02) February,18-22.

 
 

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