| Table V.4: Scoring of non-financial information indicators of JSC A by the modified model proposed by the topic | |||||
| Targets | Evaluate | Point Initial | Weight | Weighted Score | |
| first | Management qualifications and internal environment | 20% | |||
| 1.1 | Judicial history of the head of the business/business owner | Good criminal record, no criminal record, no criminal record | 100 | 2% | 2 |
| 1.2 | Education level of the head of the business/business owner | University | 80 | 2% | 1.6 |
| 1.3 | Experience, executive capacity and management quality of the Owner/Board of Directors | Management experience and quality are quite good, the leadership is stable | 80 | 5% | 4 |
| 1.4 | Reputation and relationship of the business owner in the market, with relevant agencies | Normal relationship | 60 | 4% | 2.4 |
| 1.5 | Internal control environment, organizational structure of enterprises | Internal control processes are established but not regularly updated and checked. Good organizational structure | 80 | 2% | 1.6 |
| 1.6 | Internal HR environment enterprise | Rather | 60 | 3% | 1.8 |
| 1.7 | Business strategic vision of the enterprise | Having vision and business strategy, but feasibility in 1 some cases is still limited | 60 | 2% | 1.2 |
| 2 | Factors outside the business | ten% | |||
| 2.1 | Industry development prospects | Stability | 60 | 2% | 1.2 |
| 2.2 | Influence from policies of the State, Government, Government local authorities | Does not have its own policy or is not heavily influenced by the government policy (if any) | 40 | 3% | 1.2 |
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| Table V.4: Scoring of non-financial information indicators of JSC A by the modified model proposed by the topic | |||||
| Targets | Evaluate | Initial score | Weight | Weighted Score | |
| 2.3 | Stability of input materials | Relatively stable or fluctuate but little effect on business activity and profitability now | 60 | 2% | 1.2 |
| 2.4 | The likelihood of a company's products being replaced by "substitute products" as assessed by GMOs | Relatively difficult | 80 | first% | 0.8 |
| 2.5 | The ability of new enterprises to enter the market (in the same industry/business field) as assessed by GE | Difficult, requiring large investment of capital and labor, high qualifications | 80 | first% | 0.8 |
| 2.6 | Dependency of the activity the enterprise's business activities on natural conditions | Very few dependencies | 100 | first% | first |
| 3 | Relationship with credit institutions | 24% | |||
| 3.1 | Overdue debts/total current outstanding loans of enterprises at credit institutions | 0% | 100 | 4% | 4 |
| 3.2 | Number of times of debt restructuring, Late payment of interest, Number of times of insolvency/late payment commitments in the past 12 months at credit institutions | 0 times | 100 | 4% | 4 |
| 3.3 | Debt repayment history of enterprises with Lien Viet Bank | Always pay your debt on time | 100 | 4% | 4 |
| 3.4 | Using loan capital for wrong purposes when borrowing capital at Lien Viet Bank | Never used capital for the wrong purpose | 100 | 3% | 3 |
| 3.5 | Percentage of average deposit balance (in the last 12 months) / Average outstanding balance of enterprises at Lien Viet Bank (in the last 12 months) | <2% | 20 | 4% | 0.8 |
| 3.6 | Average number of transactions with Lien Viet Bank | 3 - 4 | 60 | 5% | 3 |
| 4 | Operational characteristics of the business | forty six% | |||
| 4.1 | Position and competitiveness of enterprises in the market | Image building in progress. Products/services have a small market share. Competitive pressure is great, competitiveness is average. | 40 | 5% | 2 |
| Table V.4: Scoring of non-financial information indicators of JSC A by the modified model proposed by the topic | |||||
| Targets | Evaluate | Initial score | Weight | Weighted Score | |
| 4.2 | Scope of business activities (scope of product consumption) | Only within Vietnam or the surrounding border area | 80 | 4% | 3.2 |
| 4.3 | Supplier relationship | Dependent, but still able to arrange if there is a change from the supplier | 60 | 3% | 1.8 |
| 4.4 | Relationship with output partners | Normal relationship, both sides need to rely on each other to develop together | 60 | 5% | 3 |
| 4.5 | Financial reporting quality | Honest report, full and submitted on time but not audited up | 60 | 5% | 3 |
| 4.6 | Applying modern management model (ISO) and advanced technological processes | Do not apply | 20 | 2% | 0.4 |
| 4.7 | Achievements are widely recognized | Never received awards from organizations | 20 | 2% | 0.4 |
| 4.8 | Net cash flow trends | Downtrend ( positive period net cash flows) | 60 | 3% | 1.8 |
| 4.9 | The growth rate evaluation quarter revenue compared with the same period a year ago | No growth | 60 | 2% | 1.2 |
| 4.10 | Coverage of property subject to loss | <50% | 60 | 3% | 1.8 |
| 4.11 | separation of duties, powers in the business leadership | There is separation, but it is not complete and reasonable | 60 | 3% | 1.8 |
| 4.12 | Medium and long-term debt repayment capacity | 1 time | 60 | 2% | 1.2 |
| 4.13 | Diversify industries and business fields | Diversify around core areas | 100 | 2% | 2 |
| 4.14 | Source of debt repayment of enterprises according to the assessment of the CBA | A reliable source of debt repayment, the business is fully capable of paying its debts on time | 100 | 5% | 5 |
| Total weighted score | 68.2 | ||||
| (Source: Grading according to the proposed model of the topic) | |||||
| Table V.5: Summary score of corporate credit society of JSC A by the modified model proposed by the topic | ||||
| STT | Targets | Scores are not weighted | Proportion | Points have been weighted |
| first | Financial indicators | 59.2 | 30% | 17.8 |
| 2 | Forecast indicators | twelfth | 30% | 3.6 |
| 3 | Non-financial indicators | 68.2 | 55% | 37.5 |
| total score | 100% | 58.9 | ||
| (Source: Grading according to the proposed model of the topic) | ||||
THE BLACK Swan Theory
In the past, it was believed that all swans were white. But until it was discovered that black swans exist in the world (in Australia), people gave up thinking like the white color of swans.
The Black Swan Theory by Nassim Taleb, a professor of financial mathematics at New York University, points out that, "black swans" lie beneath nearly everything about our world, "All of us." Everyone turns a blind eye to rare events and fancies themselves to be able to predict every risk and every opportunity . Once uncertainty exists in all phenomena around us, especially in financial markets, when events of low probability of occurrence but with the potential for large losses can exist in Anywhere, should investors trust analysts' forecasts when these forecasts often fail to indicate risks of uncertainty and, as has been shown, are sometimes wrong? intentional omission.
Taleb argues that people tend to ignore large events with low probability because experts often make predictions based on associations that have been observed in the past. Economic forecasts have long been relatively accurate because people share a belief that if they do this, they will have the same results.
For example, if interest rates are lowered, people will borrow more money to do business. Taleb believes that the human brain is more suited to a simple world than the complex world we have today. Humans still tend to see, believe, and remember for a long time the facts that support our thinking, events that are consistent with our predictions about the future. But when suddenly the economic and financial crisis broke out, all values were reversed, beliefs disappeared, and all predictions turned out to be wrong.
Taleb also argues that major events are more common in finance than in real life, and gives an example: “If we take randomly from the global population two people with a combined height of 3.4 m. What is the probability that each person is high? The answer “3 m and 0.4 m” is impossible and the highest probability is 1.7 m and 1.7 m. But in finance, the opposite is true. If also randomly taken from the global population two people have a combined wealth of £14 million. The most likely probability is not that each person has £7 million, but usually £5,000 on one side and £13.5 million on the other." Humans can accurately calculate to the second when there will be a solar eclipse, but also, it is impossible to predict exactly how stock prices will be tomorrow.
That's because all economic laws must be projected through the prism of human psychology and then change immeasurably like a kaleidoscope.
In finance, we humans still believe in the predictions of experts, and that's a problem called "confirmation bias". When expert predictions are made regularly and systematically, and assuming that when the market stabilizes, those expert predictions are correct, people will believe that the experts' predictions are correct. .
And then, people will always look for proofs that the statement is true, and then of course it will. When crude oil prices peaked at $147/barrel, who would say it would fall below $50 within four months? Or like in Vietnam, when VnIndex was up to 1200 points, who would have thought that it would drop below 300 points just over a year later? But when unexpected events occur, such as a financial crisis, or repeated false predictions, people begin to doubt and rebuild their propositions.
Many people in the financial world believe that financial forecasting is constantly updating new parameters to make new forecasts, not ignoring Taleb's accusations. But Taleb also said that those updates are still based on the past, so it is not possible to predict what "unusual" or "extreme" he is talking about.
The advent of the "Black Swan Theory", as well as the alarm among policymakers about the quality of credit ratings, suggest a common conclusion that financial markets (or their lives) me too) is always more complicated than we thought it would be. The sanity of new investors is the most important basis for determining their performance (not blindly trusting the ratings).