Economical Analysis of Asset Prices
Economic Analysis of Asset Prices
The most recent economic crisis, from which the global economy is still reeling, started in 2007, approximately one year after the ‘sub-prime’ housing market in America buckled under its own weight, putting pressure on the financial markets across the world. This economic crisis, argued to be the worst financial crisis since the Great Depression in the 1930s (Brunnermeier, 2009), led to a dramatic reduction in the volume of bank lending along with non-price rationing of credit, which is known as a ‘credit crunch’ (Brunnermeier, 2009; Shaffer and Hoover, 2007). The financial crisis was felt all through the economy in many countries and led to the failure of many businesses including major banks and financial houses, a reduction in consumer wealth, considerable financial commitments incurred by governments, and an overall significant reduction in economic activity for approximately two years (Nataste et al.
This paper assesses how and to what extent events of the financial crisis beginning in 2007 reflect asset-pricing inefficiencies in stock markets and housing markets. The discussion begins with an overview of the events that led up to the financial crisis. The second substantive section explicitly discusses the criteria used in assessments of ‘efficiency,’ while the third substantive section assesses how these criteria can be applied in the context of the crisis. The paper concludes with a discussion of some insights from behavioural economics.
Background: The Financial Crisis of 2007
In 2007, approximately one year after the ‘sub-prime’ housing market in America crumbled, the most recent global economic crisis began, straining the global financial markets (Nataste et al., 2009). There are three main, interrelated factors that led to the crisis: a preceding period of exceptional macro-stability, the global savings surplus, and innovation within the financial markets (Dimsdale, 2009, Mizen, 2008, Pomfret, 2010). First, one of the precursors of the economic crisis was a period over which there was extraordinary stability in the American and European economies. Second, there was a global savings surplus from emerging economies, which supported extremely low long-term interest rates in these countries, which allowed those in the money market to have access to cheap money. These credit booms led to excessive debt burdens (Claessens, 2009). Third, there were several innovative financial products being introduced on the market, such as mortgage-backed securities, but financial innovation also led to more complexity, higher leverage, and weaker underlying assets (as they were dependent on ‘sub-prime’ mortgages, which is explained in more detail below). This point is supported by Pomfret (2010) and others, who argues that the financial system has become more vulnerable to crisis because of innovation and development in the financial sector combined with easy monetary policy stemming from the stable macroeconomy and very low interest rates at the beginning of the millennium.
Sub-prime mortgages were offered based on ‘self-certification of income,’ and therefore allowed a lot of people who previously lacked the financial capacity to purchase property under the existing system (which was based on applicants’ income), were able to access these mortgages (Chatterjee and Lefcovitch, 2009). And even at higher interest rates it was an attractive offer at the beginning of the millennium because the macroeconomy was stable, interest rates were very low, and the housing market in the USA was buoyant (Crouhy et al., 2008). Houses prices in America and in other markets, such as the UK and Iceland, rose sharply in the period preceding the crisis, generally fuelled by quickly increasing levels of available credit, which resulted in sharply increased household debt (Brunnermeier, 2009; Claessens, 2009).
Given the extended period of macroeconomic stability, a fall in house price across the entire US was not anticipated, indeed such an occurrence had not been accounted for in the models used to assess the risk of the sub-prime mortgages and the other sources of credit that were readily available during this period (Mizen, 2008). When house prices did fall, the number of borrowers defaulting on their payments increased greatly in the sub-prime mortgage sector, and this was the eventual trigger for the economic crisis (Brunnermeier, 2009; Mizen, 2008). So one of the key features of the most recent crisis was the increases in asset price (particularly the price of houses) that turned out to be unsustainable, which caused a housing bubble (Claessens, 2009). When the housing bubble burst, banks and other financial houses had to write down many hundred billion of dollars in bad loans that had been caused by the fact that many mortgage holders were unable to pay their loans and so became delinquent (Brunnermeier, 2009). Additionally, the stock market capitalisation of the major banks was reduced by more than twice as much as the amounts that had to be written down (Brunnermeier, 2009).
Asset Pricing and the Efficient Market Hypothesis
How are assets, like houses, pricedAccording to Brunnermeier (2001), asset prices are determined by information that is public available and generally dispersed among a lot of market participants who try to deduce the information that other participants have by analysing price processes. Additionally, asset prices are determined by market participants’ expectations about the future profits on the assets. Whenever new information becomes available, market participants may have to re-evaluate these expectations about the future asset prices. It can therefore be expected that the information available in the market is important such that asymmetric information, for example, would affect asset prices and traders’ information inference.
The efficient market hypothesis (EMH) is the idea that market, such as the stock market or the housing market, is informationally efficient, meaning that all information about a security or asset is known by the participants in market, and consequently by all potential investors (Ehrhardt and Brigham, 2008). More specifically, informational efficiency refers to how much information is revealed by the price process and prices are deemed to be informationally efficient if they fully and correctly contain all the available information (Brunnermeier, 2001). There are three types of informational efficiency, strong, semi-strong, and weak, and this depends on the amount and type of information reflected in the asset price (Brunnermeier, 2001).
According to Ehrhardt and Brigham (2008), EHM holds that (1) stocks are in equilibrium at all times and (2) it is not possible for an investor to constantly get better than average returns on the market than the risk of her investor warrants. EHM essentially suggests that, beyond the normative utility maximising market participants, market participants have rational expectations and on average the market prices are correct, even though any one or all market participants may be incorrect. That is, even if individuals are wrong, the people as a community will be engaged in forecasting the stock prices, which will be done by using all the available information. As soon as some new information is available in the market these people will change their estimates immediately. As a result of this conduct, the prices in the stock market totally reflect the existing information as well as reflect the precise inherent value (Ehrhardt and Brigham, 2008).
EMH depends on the fact that stock prices follow a ‘random walk,’ meaning that price changes are not dependent on each other (Ehrhardt and Brigham, 2008). This suggests that all information is equally known and considered by the market as individuals, and as such there is little or no chance for arbitrage in the market. It is not considered to hold in all cases, but in enough to promote the capital market line, a correlation between the market and the equities and securities and assets that make it up (Granger, 1992). In an efficient market, competition ensures that (Ehrhardt and Brigham, 2008):
New information is quickly and fully assimilated into prices;
All available information is reflected in the stock price;
Prices reflect the known and expected, and respond only to new information; and
Price changes occur in a random manner.
There are three forms of the theory, weak, semi-strong, and strong (Ehrhardt and Brigham, 2008; Granger, 1992). Weak form efficiency posits that current market prices reflect all information from history. This suggests that prices in the market reflect all the information that has been made available in the past. As a result it would not be possible to get surplus returns by use of methodological analysis but could be done through fundamental studies of the market. Hence, the fluctuations in the price of the stock should be unpredictable and unsystematic (Ehrhardt and Brigham, 2008). Semi-strong form efficiency is based on the notion that market prices reflect all publicly available information, and this means that availability of any new public information makes the markets react spontaneously in a particular fashion. Thus, agents react quickly to such information making the discovery of possible missed stock prices through deep analysis useless (Granger, 1992).
Finally, strong form efficiency is based on the notion that market prices reflect all information, both public and private (Ehrhardt and Brigham, 2008). In the case of strong-form efficiency hypothesis, it is assumed that not only the public information but also private information has a bearing on the stock prices, this might include information which is available only to a handful of individuals and they would use this information to make enormous profits (Granger, 1992). Even so, such huge returns are not achievable because stock prices tend to immediately adjust by accounting for the most sensitive information. As a result, it would be of no benefit to engage in insider trading as the trader would be in the same position as to that of the person trading without this information (Ehrhardt and Brigham, 2008).
The benefit of the EHM over ad hoc formulations of expectations is that it gives market participants a simple, general and credible manner of dealing with expectations (Ehrhardt and Brigham, 2008). However, the soundness of the hypothesis has been questioned by many, some of whom accuse the notion that markets are rational for much of the recent financial crisis. The next section assesses how and to what extent events of the financial crisis beginning in 2007 reflect asset-pricing inefficiencies in stock markets and housing markets, specifically assessing how these criteria can be applied in the context of the most recent financial crisis.
How and to What Extent Events of the Financial Crisis Beginning in 2007 Reflect Asset-Pricing Inefficiencies in Stock Markets and Housing Markets?
This section discusses the extent of asset-pricing inefficiencies in the stock markets and housing markets based on the four criteria outlined above. First, was new information quickly and fully assimilated into pricesSecond, was all available information reflected in the stock priceThird, did prices reflect the known and expected, and respond only to new informationAnd finally, did market prices changes occur in a random manner?
In examining the questions, the role of complexity has to be acknowledged. In neoclassical economics model, agents (investors) make the best (optimal) choices regardless of the difficultly of the problem with which they are dealing (Ehrhardt and Brigham, 2008). However, examining the recent economic crisis, one of the key lesson is not that mortgage takers in the sub-prime sector of the housing market did not understand the complicated terms of the mortgages they had been offered, rather the key lesson is that the lenders (the firms that bought these securitised mortgages) did not seem to fully understand the risks that were intrinsic in these assets (Brunnermeier, 2009; Thaler, 2008). As previously noted, innovative financial products introduced into the market, such as mortgage-backed securities, also introduced greater complexity (Mizen, 2008). Acharya et al. (2009, p. 4) outline innovations in financial products that made it unlikely that stock prices and housing prices (1) reflected all available information or (2) assimilated new information quickly and fully. These are:
(1) New exotic and illiquid ?nancial instruments that were hard to value and price; (2) Increasingly complex derivative instruments; (3) The fact that many of these instruments traded over the counter rather than on an exchange; (4) The revelation that there was little information and disclosure about such instruments and who was holding them; and (5) The fact that many new ?nancial institutions were opaque with little or no regulation.
Additionally, even when the crisis had been exposed, the magnitude of the bank’s and other financial institutions’ exposure remained unclear, as well as full information on who was at risk through counterparty failure (Acharya et al., 2009). This supports the idea that the lenders did not fully understand the intrinsic risks that in the securitised assets they held as argued by Thaler (2008). According to Acharya et al. (2009, p. 5):
Private ?nancial markets cannot function properly unless there is enough information, reporting, and disclosure both to market participants and to relevant regulators and supervisors. When investors cannot appropriately price complex new securities, they cannot properly assess the overall losses faced by ?nancial institutions, and when they cannot know who is holding the risk for so-called toxic waste, this turns into generalised uncertainty.
Based on this it can be argued that new information was not quickly and fully assimilated into prices nor was all available information reflected in the stock price during the 2007 crisis. This leaves two questions to be discussed: did prices reflect the known and expected, and respond only to new information and did market prices changes occur in an unpredictable wayThe evidence seems to suggest that neither of these happened.
Discussion and Conclusion
The EHM has been disputed based on both empirical and theoretical bases, particularly by behavioural economists who ascribe the imperfections in financial markets (such as asset price inefficiencies discussed above) to a range of cognitive biases that include overconfidence (or ‘irrational exhuberance’), overreaction, representative bias, information bias, as well as a range of other unsurprising human errors in reasoning and information processing (Addleson, 1995). For example, DeBondt and Thaler (1985) argue that investors are likely to be affected and involved with the optimism as well as the pessimism of shown by the overall market. This leads to systematic deviation in the prices from the usual fundamental values. This overreaction owing to the past events falls on the same lines as the theory outlined by Kahneman and Tversky (1979), in which investors tend to be overconfident and overoptimistic about the forecasting of their future corporate earnings and stock prices. The findings support the ‘contrarian strategy’ in which an investors would buy stocks, or at times a group of stocks which have not been performing for long periods of time, while avoiding the ones that have had a good long run over the last few years (DeBondt and Thaler, 1985).
Speculative economic bubbles such as the housing market bubble discussed here, tend to be clear anomalies in the market, that is, the market often seems to be driven by buyers operating on irrational exuberance, who then disregard the underlying value of the asset being traded (Ehrhardt and Brigham, 2008). This seems to be the case in the housing bubble. As outlined above, the boom in credit available to households was connected with the creation of marginal assets whose practicability was dependent on favourable macroeconomic conditions continuing for a long period. In America, to some extent the UK (such as with Northern Rock), a great percentage of the mortgage expansion consisted of loans extended to subprime borrowers with little or no credit and employment histories, as outlined above (Claessens, 2009). Debt servicing and repayment were, thus, susceptible to economic downturns and variances in credit and monetary conditions. (Claessens, 2009, p. 3) therefore argues that “[t]his maximised default correlation across loans, generating portfolios highly exposed to declines in house prices – confirmed ex-post through the large non-performing loans when house prices declined.”
Other explanation of motives could also be presented here. For example, Brunnermeier (2009, p. 82) noted that there was a decline in the quality of credit leading up to the crisis as “[m]ortgage brokers offered teaser rates, no-documentation mortgages, piggyback mortgages (a combination of two mortgages that eliminates the need for a down payment), and NINJA (‘no income, no job or assets) loans.” While this can be blamed on other motives, such as predatory lending, this also occurred because of irrational exhuberance as outlined by Brunnermeier (2009, p. 82): “All these mortgages were granted under the premise that background checks are unnecessary because house prices could only rise, and a borrower could thus always refinance a loan using the increased value of the house.”
These bubbles are typically followed by an overreaction of frantic selling because, the fall in the value of the asset backed by high leverage eventually leads to the forced ?re sale of the asset (Acharya et al., 2009; Brunnermeier, 2009). This was seen in the most recent financial crisis. For example, Bear Stearns’ the funds had lost over 90 percent of their value before the firm almost went bankrupt (Acharya et al., 2009). Similarly, the run on the assets of three structured investment vehicles (SIVs) of BNP Paribas was so severe that BNP Paribas had to suspend redemptions (Acharya et al., 2009). Overall, the discussion contained in this paper indicates that asset-pricing inefficiencies in stock markets and housing markets had a big impact on the events of the financial crisis beginning in 2007.
Acharya, V., Philippon, T., Richardson, M., and Roubini, N. (2009). Prologue: A bird’s-eye view – The financial crisis of 2007-2009: Causes and remedies. In Acharya, V. and Richardson, M. (eds.), Restoring Financial Stability: How to Repair a Failed System (p. 1-56). Wiley.
Addleson, M. (1995). Equilibrium versus Understanding: Towards the Restoration of Economics as a Social Science. New York, NY: Routledge.
Brunnermeier, M. (2001). Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding. Oxford: Oxford University Press.
Brunnermeier, M. (2009). Deciphering the liquidity and credit crunch 2007-2008. Journal of Economic Perspectives, 23 (1): 77-100.
Claessens, S. (2009). The road ahead to a sustainable global economic system. Presented at the Annual Bank Conference on Development Economics (ABCDE) Seoul, Korea, June 22-24. Available online at http://siteresources.worldbank.org/ INTABCDESK2009/Resources/Stijn-Claessens.pdf [accessed 20 January 2011].
Crouhy, M., Jarrow, R., and Turnbull, S. (2008). The sub-prime credit crisis of 2007. The Journal of Derivatives, 16 (1): 81-110
De Bondt, W. and Thaler, R. (1985). Does the stock market overreactThe Journal of Finance, 40 (3): 793-805.
Ehrhardt, M. and Brigham, E. (2008). Corporate Finance: A Focused Approach.Mason,OH: South-Western Cenage Learning.
Granger, C. (1992). Forecasting stock market prices: Lessons for forecasters. International Journal of Forecasting, 8 (1): 3-13.
Kahneman, D. and Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47 (2): 263-292.
Mizen, P. (2008). The Credit Crunch of 2007-2008: A discussion of the background, market reactions, and policy responses. Federal Reserve Bank of St Louis Review, September/October: 531-568.
Nastase, M., Cretu, A., and Stanef, R. (2009). Effects of global economic crisis. Review of International Comparative Management, 10 (4): 691-699.
Shaffer, S. and Hoover, S. (2007). Endogenous screening, credit crunches, and competition in laxity. Review of Financial Economics, 17 (4): 296-314.
Thaler, R. (2008). 3Q2008. Fuller & Thaler Asset Management. Available online at http://www.fullerthaler.com/reviews/newsltr2008Q3.pdf [accessed 20 January 2011].