In the course of human history, people have dreamed of predicting the future. At first, they tried to read nature and stars, and then shamans became “priests”. There is perhaps a very simple explanation for this: an enemy who knows the future can’t lose. He can judge when the game is worth the price, but we can only guess and our guesses are often wrong. Even weather forecasts are often wrong. However, with time, the science of prediction has evolved and now, despite not being 100% accurate, we can build a model that will suggest the probability of the particular event happening in the near future.
The projects bidders, the banks, investors, lawyers, government advisers and the project sponsor – all of them use modelling. The methodology and stakeholders have changed, but the purpose remains the same – who knows the future, controls the present. In case of financial markets, well-developed mathematical model may help in designing an accurate portfolio that will not only bring benefits but also protect investors from the market reversal.
According to a research provided by Erasmus University Rotterdam, there are three roles of financial modelling:
(1) To get a better idea of the set of alternative decision strategies, i.e. to get insight into the feasibility of different strategies and possibly also to generate new alternatives.
(2) To clarify the relations between decision alternatives and the (potential) results of these alternatives. This may vary from the assessment of probabilities through: simulation and econometric techniques to the identification of sources of risk and estimating response parameters.
(3) To help finding a (set of) suitable stream(S) of decision alternatives. Depending on the problem characteristics, this may vary from searching feasible solutions, to constructing a partial ordering of the set of alternatives (for instance eliminating all inferior alternatives) to the construction of a complete ordering of the alternatives. Defined in this way, financial modelling not only involves 'hard core' optimization and econometrics, but also softer techniques like simulation and heuristics, and decision support techniques and problem structuring methods.
What are the indicator that may affect the stock market?
It is not difficult to assume that GDP, unemployment rate/jobs report, the consumer price/ produce price indexes and retail sales can be a huge influence on your investment returns. However, according to a study by School of Business Victoria University Melbourne, it has been discovered that the S&P 500 can also influence the rest of the world’s stock markets. The study results also indicate that the movements of major stock markets and political uncertainty have direct effects on stock market volatility. The effect of movements of oil prices has an indirect effect on firm performance. In brief, the empirical results of the contagion tests on South-East Asian stock markets show that the movement of S&P 500 and oil price can cause contagion effects in the South-East Asia stock markets. These results conclude that stock market volatility and transmission can be caused by the movement of S&P 500 and oil price while the BSI can initially affect only Thailand’s stock market volatility.
Well, if everything is so simple, then why aren’t we all millionaires?
For example, theoretically, more people with jobs equates to higher economic output, retail sales, savings and corporate profits. As such, stocks should rise or fall with good or bad employment reports, as investors digest the potential changes in these areas.
Unfortunately, the reality is not so simple. Last Friday, stocks fell from all-time highs after the release of stronger jobs data (the U.S. economy managed to create 224,000 additional jobs in June. Economists had forecast the U.S. added 165,000 jobs in June, after a stunningly low 75,000 jobs were created in May). The reason lies in the fact that weak results would automatically an easier Federal Reserve monetary policy.
The Dow Jones Industrial Average decreased by 43.88 points to 26,922.12, marking the end of a four-day winning streak. The S&P 500 fell 0.2% to 2,990.41 and ended a five-day winning streak. The Nasdaq Composite fell for the first time in seven sessions, dropping 0.1% to 8,161.79. Earlier in the session, the Dow dropped as much as 232.67 points, while the S&P 500 and Nasdaq slid nearly 1% each.
Treasury yields also jumped on the data. The benchmark 5-year yield traded at 6.17%. Bank shares, in turn, dropped from the higher rates. Citigroup, Bank of America, J.P. Morgan Chase and Wells Fargo all traded below.
In conclusion, no indicator can ensure you that the market will go this way or the other. It is important to take into consideration all the possible factors that may affect the market trend.