These statistics are also data which many t... ... middle of paper ... ...act costly information because the costs surpass the gains, so trading on less information doesn’t always imply irrationality. Nevertheless traders can also make noise based on their irrational and unpredictable changes in feelings. The reliance on unreliable data, aggressive trading by investors with little information and the collection of inappropriate information helps to understand overreactions. Conclusion Many people believe the efficient market hypothesis is inefficient and Bloomfield presents an alternative to this hypothesis. Bloomfield posits the meaning of costly statistics is not fully revealed in the market.
Deviations from rationality cannot be random always. In fact, almost all investors believe that current performance is a mirror of future performance. These investors adjust quickly to new information and there is a bubble in the market. On the other hand, some conservative investors are slow and unwilling to adapt to new information. This results in slower adjustment of prices to new information, which is against the concept of market
Recent empirical studies imply that most appraisal error is nonrandom, which suggests that strategies that advocate portfolio assembly over individual property selection may be defective. Each step of the appraisal process involves an unknown amount of estimation error. The combination of these errors is unlikely to produce a perfect, error-free estimate of value. Thus, appraisal error is virtually unavoidable. Investors need reasonable estimates of value when buying, selling, or retaining commercial property, so an unknown amount of appraisal error adds uncertainty to the decision-making process.
I think there at least some of the causes must originate from a rational framework, but I also think that they alone are not convincing enough; one has to invoke some irrational exuberance in order to explain the bullish stock market during the late 90s. Psychological experience shows that there are patterns of behaviour in the stock market which cannot be contributed to ignorance, but which nevertheless cannot be classed as rational behaviour. People tend to use past prices as anchors for predicting present prices, so when certain shares are seen as valuable, people tend to regard them as increasing in value. This obviously creates a feedback loop, leading to the bubbles. Also, herd behaviour can dictate how an individual will react.
The domain knowledge implemented in the module is thus limited to methods and techniques in technical analysis. The technical analysis literature includes a wealth of different stock analysis techniques, some of which involve complicated and intricate price patterns subjective in both detection and interpretation. These methods would be both expensive to detect and evaluate, and have consequently been disregarded. They thus apply Occam’s razor to the choice of methods in technical analysis, focusing on the most popular indicators that can be efficiently operationalized and are intuitive in interpretation. It seems overly presumptuous to believe that historical price fluctuations alone can be used to predict the direction of future prices.
The most important thing I took out of the simulation though was not the language. Although useful, it was learning and experiencing, a little bit, of the risk involved in investing in stock. If I had not learned about the stock market, or the risk involved, I could have invested in the future and lost all my life savings. Or I could have not done it and missed out on making a lot of money. Although the simulation was helpful and I learned a lot from it, there were times when I did not even look at the website.
For most people, there are three probabilities; the event can’t happen, the event might happen or the event will happen. Prospect theory explains much of what happens in finance, but prospect theory doesn’t explain everything. Other biases, such as overconfidence and cognitive dissonance, cloud thinking. The tendency for overconfidence produces anomalies and opportunities for manipulation. Cognitive dissonance is a judgmental bias people tend to make as they can’t admit when they are wrong.
The lack of transparency on price and sales makes it more difficult to sustain collusion. If firms do not adhere to individual prices it is harder to detect deviation and punish it. Tacit collusion It is an illegal agreement thus the absence of a written agreement. When, firms that are competing do not want to engage in competitive behavior such as cutting the price, advertisements and promotion they come up with unwritten rules of collusive behavior such as: price leadership. A price leader then emerges setting a general industry price high enough that the least cost-efficient firm in the market may earn some return above the competitive level.
Furthermore, this can be a bias for new companies as they might do not have complete financial report the required by the statute. Thus, trading in stock market can be more difficult than being privately held. All of information should be discover to the public and shouldn’t remain any secret. Besides the disadvantages of disclosure, trading in a stock market publicly might cost higher than being privately held for a company. Due to the requirement of Securities Exchange Act 1934 as well as Sarbanes-Oxley Act 2002 (SOX), a company that want to trade in a stock market basically has to spend a lot on financial reporting documents, audit fees, investor relation departments and accounting oversight committees.
As a result, manipulation reduces the efficiency in futures market. Regulators, therefore, are set to prevent the spread of manipulation but it turned out that the regulators were not able to stop the manipulation. The main reason for unsuccessfulness was that neither regulations nor acts have clear definition of manipulation. The most frequently discussed among the market manipulation is “long” market power manipulation also known as a “corner” or a “squeeze” (Pirrong, 2010). These occurs when a trader buy a vast number of future contracts.