# The Behaviour of Small Investors in the Hong Kong Derivatives Markets: A Factor Analysis

## Abstract

**:**

## Introduction

## Study Background

## Literature Review

## Methodology

**Z**may be obtained by multiplying the matrix of factor loading ${{\displaystyle A}}_{u}$ by the matrix of factor scores ${{\displaystyle F}}_{u}$ The common factor portion of ${{\displaystyle A}}_{u}$ will be called matrix

**A**(without the subscript u), and the common factor portion of ${{\displaystyle F}}_{u}$ will be called matrix

**F**. This makes the factor structure more interpretable. The initial extracted factor matrix must be rotated before the final factor solution is achieved. A factor matrix may be transformed to a rotated factor matrix by the matrix operation

**V**=

**A**Λ, where

**V**is the rotated matrix,

**A**is the unrotated matrix, and Λ is an orthogonal transformation matrix in which rows and columns have sums of squares equal to 1.0 and inner products of non-identical rows or columns equal to zero. Such a transformation does not affect the capacity of the factor matrix to reproduce the original correlation matrix because

**VV’**=

**(A**Λ

**) (A**Λ

**)**’ =

**A**ΛΛ’

**A’**=

**AIA’**=

**A A’**=

**R**

**V**when multiplied by its transpose

**V’**will reproduce the

**R**matrix just as well as

**A**multiplied by its transpose

**A’**does. These rotations are carried out using “positive manifold” and “simple structure,” rotational criteria that have been traditional guides in carrying out the rotation process in factor analysis. Trying to rotate to obtain non-negative loadings is known as rotating to “positive manifold”. The idea behind positive manifold is that if the entire set of data items in a matrix have inter-correlations that are either zero or positive, it is unreasonable to anticipate an underlying factor with substantial negative loadings for any of the data items. Thurstone (1947) developed the criterion of “simple structure” to guide the investigator in carrying out rotations of factor axes to positions of greater “psychological meaningfulness” [25]. Bartlett’s test of sphericity and Kaiser-Meyer-Olkin’s measure of sampling adequacy are both tests that can be used to determine the factorability of the matrix as a whole. If Bartlett’s test of sphericity is large and significant and the Kaiser-Meyer-Olkin measure is greater than 0.6, then factorability is assumed. If the sums of squares of the loadings on the extracted factors are no longer dropping but are remaining at a low and rather uniform level, factor extraction may be reasonably terminated. Cattell’s (1966) Scree test is based on this principle. SPSS use a default option of extracting all principal factors with eigenvalues of 1.0 or more (i.e., the Kaiser-Guttman rule). The main thing to consider in deciding when to stop factoring is that it is better to err on the side of extracting too many factors rather than too few [26]. One of the most commonly used is Cronbach’s coefficient α, which is based on the average correlation of items within a reliability test if the items are standardised. Cronbach’s coefficient α can be interpreted as a correlation coefficient; it ranges in value from 0 to 1.

## Data

## Results

Items and responses | No. | % of Total |
---|---|---|

1. Age group: | ||

18 – 24 years old | 172 | 33.0 |

25 – 34 years old | 156 | 29.8 |

35 – 44 years old | 76 | 14.5 |

45 – 54 years old | 79 | 15.3 |

55 – 64 years old | 34 | 6.5 |

over 65 years old | 5 | 1.0 |

2. Average monthly income: | ||

Below HK$5,000 | 110 | 21.1 |

HK$5,000 -HK$9,999 | 71 | 13.6 |

HK$10,000 - HK$14,999 | 88 | 16.9 |

HK$15,000 - HK$19,999 | 94 | 18.0 |

HK$20,000 - HK$24,999 | 77 | 14.8 |

HK$25,000 - HK$29,999 | 32 | 6.1 |

HK$30,000 - HK$49,999 | 38 | 7.3 |

HK$50,000 or above | 12 | 2.3 |

3. How long have you invested in the financial market? | ||

Never invested | 43 | 8.2 |

Less than 1 year | 95 | 18.1 |

1 year to under 3 years | 178 | 34.0 |

3 years to under 5 years | 92 | 17.6 |

5 years to under 10 years | 71 | 13.5 |

10 years or above | 45 | 8.6 |

4. What is your average return on investment in derivative products? | ||

Loss | 76 | 18.2 |

Average Return less than 10% | 143 | 34.2 |

Average Return 10% to under 30% | 137 | 32.8 |

Average Return 30% to under 50% | 48 | 11.5 |

Average Return 50% to under 100% | 12 | 2.9 |

Average Return 100% or above | 2 | 0.5 |

5. During January 2011 to January 2012, were you satisfied with the average returns of your financial derivatives investment? | ||

Very satisfied | 9 | 2.2 |

Satisfied | 127 | 30.4 |

Neutral | 157 | 37.6 |

Dissatisfied | 89 | 21.3 |

Very dissatisfied | 36 | 8.6 |

6. What is your personal level of tolerance for investment risk? | ||

Very Low | 9 | 2.2 |

Low | 62 | 14.8 |

Medium | 171 | 40.9 |

High | 152 | 36.4 |

Very High | 24 | 5.7 |

7. As a percentage of the total amount in your investment portfolio, how much do you invest in derivative products: | ||

Less than 10% | 92 | 22.0 |

10% to under 30% | 192 | 45.9 |

30% to under 50% | 91 | 21.8 |

50% to under 100% | 31 | 7.4 |

100% | 12 | 2.9 |

8. What do you think is the risk level in investing in financial derivatives? | ||

Very Low Risk | 2 | 0.4 |

Low Risk | 18 | 3.4 |

Medium Risk | 125 | 23.9 |

High Risk | 281 | 53.7 |

Very High Risk | 97 | 18.5 |

9. When did you mostly sell or close out your position when you invested in financial derivatives between January 2011 and January 2012? | ||

Within one day | 14 | 3.4 |

Within one week | 120 | 28.6 |

Within one month | 170 | 40.8 |

Within three months | 82 | 19.7 |

Within one year | 28 | 6.7 |

After more than one year | 3 | 0.7 |

10. Do you think the small investor education provided by the related government department is adequate? | ||

Very Inadequate | 72 | 13.8 |

Inadequate | 233 | 44.6 |

No Opinion | 165 | 31.5 |

Adequate | 48 | 9.2 |

Very Adequate | 5 | 1.0 |

11. Which type of information and opinion will most affect your decisions in investing in financial derivatives? | ||

None | 12 | 2.9 |

Newspapers, TV, magazines, etc. | 108 | 25.8 |

Relatives and friends | 43 | 10.3 |

Internet | 158 | 37.8 |

Investment Consultants | 72 | 17.2 |

Companies’ Annual Reports | 20 | 4.8 |

Others | 5 | 1.2 |

Item | Item name | Mean | Std. Deviation | T | Df | Sig. (two-tailed) |
---|---|---|---|---|---|---|

1 | Age | 2.35 | 1.303 | 41.236 | 521 | 0.000 |

2 | Personal Income | 3.51 | 1.947 | 41.167 | 521 | 0.000 |

3 | Investment Experience | 3.36 | 1.369 | 56.152 | 523 | 0.000 |

4 | Average return | 2.48 | 1.037 | 48.916 | 417 | 0.000 |

5 | Satisfaction | 3.04 | 0.974 | 63.793 | 417 | 0.000 |

6 | Risk Tolerance | 3.29 | 0.864 | 77.750 | 417 | 0.000 |

7 | Investment Portfolio | 2.23 | 0.970 | 47.038 | 417 | 0.000 |

8 | Risk Level | 3.87 | 0.761 | 116.120 | 522 | 0.000 |

9 | Sell/Close Out Position | 3.00 | 0.977 | 62.661 | 416 | 0.000 |

10 | Investor Education | 2.39 | 0.869 | 62.880 | 522 | 0.000 |

11 | Information/Opinion | 3.60 | 1.307 | 56.278 | 417 | 0.000 |

Item | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
---|---|---|---|---|---|---|---|---|---|---|---|

1 | 1.000 | ||||||||||

2 | 0.449** | 1.000 | |||||||||

3 | 0.595** | 0.408** | 1.000 | ||||||||

4 | 0.007 | 0.200** | 0.109* | 1.000 | |||||||

5 | -0.087* | -0.169** | -0.101* | -0.607** | 1.000 | ||||||

6 | -0.028 | 0.035 | 0.045 | 0.101* | 0.044 | 1.000 | |||||

7 | -0.215** | -0.084* | -0.092* | 0.265** | -0.022 | 0.305** | 1.000 | ||||

8 | -0.089* | -0.063 | -0.080 | -0.197** | 0.168** | 0.039 | -0.136** | 1.000 | |||

9 | 0.065 | 0.158** | 0.077 | 0.107* | -0.086* | -0.097* | -0.008 | -0.168** | 1.000 | ||

10 | 0.094* | 0.044 | 0.126** | 0.137** | -0.161** | 0.093* | 0.151** | 0.171** | 0.146** | 1.000 | |

11 | -0.058 | 0.154** | -0.007 | 0.129** | -0.120** | -0.006 | 0.094* | -0.055 | 0132** | 0.071 | 1.000 |

Item | Item name | Communality | Factor | Eigenvalue | Per cent of variance | Cumulative per cent |
---|---|---|---|---|---|---|

1 | Age | 0.761 | 1 | 2.319 | 21.077 | 21.077 |

2 | Personal Income | 0.653 | 2 | 1.812 | 16.470 | 37.547 |

3 | Investment Experience | 0.702 | 3 | 1.267 | 11.520 | 49.067 |

4 | Average Return | 0.810 | 4 | 1.13 | 10.030 | 59.097 |

5 | Satisfaction | 0.811 | 5 | 1.017 | 9.244 | 68.342 |

6 | Risk Tolerance | 0.717 | ||||

7 | Investment Portfolio | 0.656 | ||||

8 | Risk Level | 0.542 | ||||

9 | Sell/Close Out Position | 0.583 | ||||

10 | Investor Education | 0.501 | ||||

11 | Information/Opinion | 0.782 |

Factors | |||||||
---|---|---|---|---|---|---|---|

Item | I | II | III | IV | V | Item name | Factor |

1 | 0.851 | Age | A | ||||

2 | 0.713 | Personal Income | A | ||||

3 | 0.826 | Investment Experience | A | ||||

4 | 0.864 | Average Return | B | ||||

5 | -0.885 | Satisfaction | B | ||||

6 | 0.833 | Risk Tolerance | C | ||||

7 | 0.718 | Investment Portfolio | C | ||||

8 | -0.707 | Risk Level | D | ||||

9 | 0.540 | Sell/Close out Position | D | ||||

10 | 0.655 | Investor Education | D | ||||

11 | 0.873 | Information/Opinion | E |

Factors and items | Item-total correlation | α value | Decision |
---|---|---|---|

Factor A (Personal Background) | |||

Age | 0.5060 | 0.6662 | Retained |

Personal Income | 0.4744 | ||

Investment Experience | 0.5123 | ||

Factor C (Risk Tolerance) | |||

Risk Tolerance | 0.3036 | 0.4634 | Eliminated |

Investment Portfolio | 0.3036 | ||

Factor D (Cognitive Style) | |||

Sell/Close out Position | 0.1458 | 0.2527 | Eliminated |

Investor Education | 0.1458 |

Items | Number of items | Item-total correlation | α value |
---|---|---|---|

Factor A (Personal Background) | |||

Age | 3 | 0.5060 | 0.6662 |

Personal Income | 0.4744 | ||

Investment Experience | 0.5123 | ||

Factor B (Return Performance) | |||

Average Return | 1 | ||

Factor E (Reference Group) | |||

Information/Opinion | 1 |

- Return performance
- Reference group
- Personal background

## Conclusion

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## Share and Cite

**MDPI and ACS Style**

Hon, T.-Y.
The Behaviour of Small Investors in the Hong Kong Derivatives Markets: A Factor Analysis. *J. Risk Financial Manag.* **2012**, *5*, 59-77.
https://doi.org/10.3390/jrfm5010059

**AMA Style**

Hon T-Y.
The Behaviour of Small Investors in the Hong Kong Derivatives Markets: A Factor Analysis. *Journal of Risk and Financial Management*. 2012; 5(1):59-77.
https://doi.org/10.3390/jrfm5010059

**Chicago/Turabian Style**

Hon, Tai-Yuen.
2012. "The Behaviour of Small Investors in the Hong Kong Derivatives Markets: A Factor Analysis" *Journal of Risk and Financial Management* 5, no. 1: 59-77.
https://doi.org/10.3390/jrfm5010059