Impossibility of efficient markets--论文代写范文精选

有效市场假说的支持者认为,回应这些挑战,行为偏差和相应的低效率确实存在,因为相反的力量致力于这样的机会。非理性的信仰产生概率，保证精明投资者的利润。下面的paper代写范文进一步阐述。

Abstract
Grossman and Stiglitz (1980) go even farther – they argue that perfectly informationally efficient markets are an impossibility for, if markets are perfectly efficient, there is no profit to gathering information, in which case there would be little reason to trade and markets would eventually collapse. Alternatively, the degree of market inefficiency determines the effort investors are willing to expend to gather and trade on information, hence a nondegenerate market equilibrium will arise only when there are sufficient profit opportunities, that is, inefficiencies, to compensate investors for the costs of trading and information gathering. The profits earned by these attentive investors may be viewed as ‘economic rents’ that accrue to those willing to engage in such activities. Who are the providers of these rents? 

Black (1986) gave us a provocative answer: ‘noise traders’, individuals who trade on what they consider to be information but which is, in fact, merely noise. The supporters of the EMH have responded to these challenges by arguing that, while behavioural biases and corresponding inefficiencies do exist from time to time, there is a limit to their prevalence and impact because of opposing forces dedicated to exploiting such opportunities. A simple example of such a limit is the so-called ‘Dutch book’, in which irrational probability beliefs give rise to guaranteed profits for the savvy investor. Consider, for example, an event E , defined as ‘the S&P 500 index drops by five per cent or more next Monday’, and suppose an individual has the following irrational beliefs: there is a 50 per cent probability that E will occur, and a 75 per cent probability that E will not occur. This is clearly a violation of one of the basic axioms of probability theory – the probabilities of two mutually exclusive and exhaustive events must sum to 1 – but many experimental studies have documented such violations among an overwhelming majority of human subjects.

But this last conclusion relies on the assumption that market forces are sufficiently powerful to overcome any type of behavioural bias, or equivalently that irrational beliefs are not so pervasive as to overwhelm the capacity of arbitrage capital dedicated to taking advantage of such irrationalities. This is an empirical issue that cannot be settled theoretically, but must be tested through careful measurement and statistical analysis. The classic reference by Kindleberger (1989) – where a number of speculative bubbles, financial panics, manias, and market crashes are described in detail – suggests that the forces of irrationality can overwhelm the forces of arbitrage capital for months and, in several wellknown cases, years.

The current state of the EMH Given all of the theoretical and empirical evidence for and against the EMH, what can we conclude? Amazingly, there is still no consensus among economists. Despite the many advances in the statistical analysis, databases, and theoretical models surrounding the EMH, the main result of all of these studies is to harden the resolve of the proponents of each side of the debate. One of the reasons for this state of affairs is the fact that the EMH, by itself, is not a well-defined and empirically refutable hypothesis. 

To make it operational, one must specify additional structure, for example, investors’ preferences or information structure. But then a test of the EMH becomes a test of several auxiliary hypotheses as well, and a rejection of 13 such a joint hypothesis tells us little about which aspect of the joint hypothesis is inconsistent with the data. Are stock prices too volatile because markets are inefficient, or due to risk aversion, or dividend smoothing? All three inferences are consistent with the data. Moreover, new statistical tests designed to distinguish among them will no doubt require auxiliary hypotheses of their own which, in turn, may be questioned. More importantly, tests of the EMH may not be the most informative means of gauging the efficiency of a given market. 

What is often of more consequence is the efficiency of a particular market relative to other markets – for example, futures vs. spot markets, auction vs. dealer markets. The advantages of the concept of relative efficiency, as opposed to the allor-nothing notion of absolute efficiency, are easy to spot by way of an analogy. Physical systems are often given an efficiency rating based on the relative proportion of energy or fuel converted to useful work. Therefore, a piston engine may be rated at 60 per cent efficiency, meaning that on average 60 per cent of the energy contained in the engine’s fuel is used to turn the crankshaft, with the remaining 40 per cent lost to other forms of work, such as heat, light or noise. 

Few engineers would ever consider performing a statistical test to determine whether or not a given engine is perfectly efficient – such an engine exists only in the idealized frictionless world of the imagination. But measuring relative efficiency – relative, that is, to the frictionless ideal – is commonplace. Indeed, we have come to expect such measurements for many household products: air conditioners, hot water heaters, refrigerators, and so on. Therefore, from a practical point of view, and in light of Grossman and Stiglitz (1980), the EMH is an idealization that is economically unrealizable, but which serves as a useful benchmark for measuring relative efficiency. 

The desire to build financial theories based on more realistic assumptions has led to several new strands of literature, including psychological approaches to risk-taking behaviour (Kahneman and Tversky, 1979; Thaler, 1993; Lo, 1999), evolutionary game theory (Friedman, 1991), agent-based modelling of financial markets (Arthur et al., 1997; Chan et al., 1998), and direct applications of the principles of evolutionary psychology to economics and finance (Lo, 1999; 2002; 2004; 2005; Lo and Repin, 2002). Although substantially different in methods and style, these emerging sub-fields are all directed at new interpretations of the EMH. 

In particular, psychological models of financial markets focus on the the manner in which human psychology influences the economic decision-making process as an explanation of apparent departures from rationality. Evolutionary game theory studies the evolution and steady-state equilibria of populations of competing strategies in highly idealized settings. Agent-based models are meant to capture complex learning behaviour and dynamics in financial markets using more realistic markets, strategies, and information structures. And applications of evolutionary psychology provide a reconciliation of rational expectations with the behavioural findings that often seem inconsistent with rationality. 

For example, in one agent-based model of financial markets (Farmer, 2002), the market is modelled using a non-equilibrium market mechanism, whose simplicity makes it possible to obtain analytic results while maintaining a plausible degree of realism. Market participants are treated as computational entities that employ strategies based on limited information. Through their (sometimes suboptimal) actions they make profits or losses. Profitable strategies accumulate capital with the passage of time, and unprofitable strategies lose money and may eventually disappear. A financial market can thus be viewed as a co-evolving ecology of trading strategies. 

The strategy is analogous to a biological species, and the total capital deployed by agents following a given strategy is analogous to the population of that species. The creation of new strategies may alter the profitability of pre-existing strategies, in some cases replacing them or driving them extinct. Although agent-based models are still in their infancy, the simulations and related theory have already demonstrated an ability to understand many aspects of financial markets. Several studies indicate that, as the population of strategies evolves, the market tends to become more efficient, but this is far from the perfect efficiency of the classical EMH. Prices fluctuate in time with internal dynamics caused by the interaction of diverse trading strategies. Prices do not necessarily reflect ‘true values’; if we view the market as a machine whose job is to set prices properly, the inefficiency of this machine can be substantial. Patterns in the price tend to disappear as agents evolve profitable strategies to exploit them, but this occurs only over an extended period of time, during which substantial profits may be accumulated and new patterns may appear.(paper代写)

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