Behavior Of Asset Prices Research Articles

The dynamic behaviour of asset prices in disequilibrium: a survey

This article surveys boundedly rational heterogeneous agent (BRHA) models of financial markets. We give particular emphasis to the role of the market clearing mechanism used, the utility function of the investors, the interaction of price and wealth dynamics, and calibration of this class of models. Due to agents' behavioural features and market noise, the BRHA class of models are both non-linear and stochastic. We show that BRHA models produce both a locally stable fundamental equilibrium corresponding to that of the standard paradigm, as well as instability with a consequent rich range of possible complex behaviours that are analysed by both simulation and deterministic bifurcation analysis. A calibrated model is able to reproduce quite well the stylised facts of financial markets. The BRHA framework seems able to better accommodate market features such as fat tails, volatility clustering, large excursions from the fundamental and bubbles than the standard financial market paradigm.

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The Emerging Markets’ Investor Sentiment Composite Index: A Test on Bursa Malaysia

During the recent global stock market crash in 2007 to 2008, the MSCI World Index of developed markets fell approximately 50 percent in value; hence the contagion effect to the emerging markets was inevitable that it fell further. In early 2009, the MSCI Emerging Markets Index has fallen 66 percent from peak to trough, which had plunged deeper than the stock markets of developed countries. It would be of no surprises for academics and practitioners to link the local stock markets behaviours to other regional stock markets as one of the contributions in their research papers and write ups. Theoretical wise, it has for decades, a vast number of explanations been offered in attempts to explain the behaviour of asset prices from the perspective of investor’s psychology. The theory of noise trader by Black (1986) and Trueman (1988) initiated the attempt by modeling that noise trading no longer exists as a temporarily shock or short term movement in asset prices as previously discussed in Efficient Market Hypothesis. This paper introduces the investor sentiment composite index constructed specifically for the emerging markets, in particular the Bursa Malaysia. The composite index is constructed comprising of liquidity proxy, the information IPOs and advancer decliners ratio. Unlike the study done on developed market, this paper introduces a measurement of liquidity that has been used in study of liquidity on emerging market by Amivest (1997). A proxy known as oversubscription ratio is taken from the IPO literature is also added that signifies investors demand in the market. Bursa Malaysia is expected to closely represent the emerging markets as to study the impact investor sentiment has on the returns and also the contribution to the bull and bear stock market defined by the leading indicator KLCI.

Chaotic processes of common stock index returns: An empirical examination on Istanbul Stock Exchange (ISE) market

The nonlinearity and accompanying concept, namely the chaos receive great attention from researchers. This study employs nonlinearity and chaos theories to examine the behavior of the Istanbul Stock Exchange (ISE) all share equity indices. The main purpose was to explore the existence or nonexistence of nonlinearity and chaotic behavior in the ISE market. Therefore, the efficient markets’ characteristics, which are the random behavior of asset prices and nonlinear chaotic dynamics, were contrasted and the probabilistic and deterministic behaviors of the asset prices were compared. Our results based on BDS, Hinich Bispectral, Lyapunov Exponent and NEGM tests reject the efficient market hypothesis that the index series examined in this study is not random, independent and identically distributed (i.i.d). Key words: Efficient market hypothesis, nonlinearity, chaotic dynamics.

Chaotic Processes of Common Stock Index Returns: An Empirical Examination on Istanbul Stock Exchange (ISE) Market

The nonlinearity and accompanying concept, namely the chaos receive great attention from researchers. This study employs nonlinearity and chaos theories to examine the behavior of the Istanbul Stock Exchange (ISE) all share equity indices. The main purpose was to explore the existence or nonexistence of nonlinearity and chaotic behavior in the ISE market. Therefore, the efficient markets’ characteristics, which are the random behavior of asset prices and nonlinear chaotic dynamics, were contrasted and the probabilistic and deterministic behaviors of the asset prices were compared. Our results based on BDS, Hinich Bispectral, Lyapunov Exponent and NEGM tests reject the efficient market hypothesis that the index series examined in this study is not random, independent and identically distributed (i.i.d).

Asset pricing implications of a New Keynesian model

We investigate the behavior of asset prices in a typical New Keynesian macro model. Using a second-order approximation, we examine bond and equity returns, the equity risk premium, and the behavior of the real and nominal term structure. As documented in the literature, our results suggest that introducing real rigidities to the model increases risk premia. Nevertheless we that find that, in a world dominated by productivity shocks, increasing nominal rigidities reduces risk premia. Such rigidities only enhance risk premia when economic dynamics are mainly driven by monetary policy shocks. The results imply that, unlike in endowment frameworks, matching asset pricing facts in macro models will require attention to the composition of shocks, not just the specification of investor preferences.

Asset Pricing Under Heterogeneous Information

In an asset market where agents have heterogeneous information, asset prices not only depend their expectations of the true fundamentals but also depend on their expectations of the expectations of others.Iterations of such expectations lead to the so-called infinite regress'' problem, which makes the analysis of asset pricing under heterogeneous information challenging. In this paper, we solve the infinite-regress problem in a simple economic setting under a fairly general information structure. This allows us to examine how different forms of information heterogeneity impacts the behavior of asset prices, their return dynamics, trading volume as well as agents' welfare. We find that in general current prices exhibit long-range dependence on past shocks. Moreover, we show that information heterogeneity tends to lower the level of asset prices, increase price volatility and return variability, and reduce trading volume. It also tends to decrease agents' welfare, including those with superior information.

Spectral analysis for intrinsic time processes

This paper discusses an estimation procedure for the spectral density of intrinsic time processes because there has been no argument of the spectral analysis for subordinated processes. Such processes have been proposed in a variety of contexts to describe asset price behavior. They are used when the movement of prices is tied to the number of market transactions, trading volume or the more illusive concept of information arrival. We develop the asymptotic theory for an estimated spectral density of intrinsic time processes and elucidate the asymptotics, which show some interesting structures. Also, numerical studies are given to confirm the results.

The Crisis of 1873: Perspectives from Multiple Asset Classes

This article analyzes asset pricing behavior during the period leading up to the Crisis of 1873. Evidence is presented that equities, options, and bonds priced risks consistently, suggesting that investors were actively monitoring the risk of investing and were not caught up in an irrational, speculative mania. Implied probability density functions for stock returns suggest that option markets exhibited growing concern about substantial price declines prior to the crash. Concerns were concentrated on riskier, more leveraged firms. Deteriorating balance sheet fundamentals for the riskiest U.S. railroads set the stage for a market disruption in 1873 as information asymmetries worsened.

Mixture Distribution Scenarios for Investment Decisions with Downside Risk

Recently considerable attention has been given to downside risk control in the context of portfolio choice; see Sortino and Satchell (2005). We propose an integrated model for portfolio choice in which downside risk is considered explicitly at the stage of the scenario generation which describes asset price behaviour and in the subsequent step of portfolio construction. The scenario generation method is deliberately chosen to create a mixture discrete distribution for future asset returns. The behaviour and dependence of asset returns in the lower tails are captured using a discrete approximation to a multivariate copula model. The upside returns are modelled using a discrete approximation to a multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model. The asset allocation problem is based on an extension of the mean-variance approach, with an additional conditional value at risk (CVaR) constraint. The implementation of the model is that of a long short portfolio of exchange traded funds (ETF) of equity indices. Computational results of validating the model and backtesting are presented.

Asset Pricing and the Credit Market

We study asset pricing and trading behavior in an exchange economy populated by two agents with different risk aversion. We show that the credit market plays a central role in the risk sharing between the two agents. It allows the less-risk-averse agent to borrow in order to take on levered positions in the stock and thus bear more risk. Optimal risk sharing results in the more-risk-averse agent effectively selling covered call options to the less-risk-averse agent. As the state of the economy changes, the equilibrium amount of credit in the market also fluctuates, which in turn influences expected stock returns, stock return volatility, the term structure of interest rates, and trading activity in the stock market. We further explore the immediate empirical implication that variation in the size of the credit market is related to variation in expected stock returns. Using various measures of changes in the size of the credit market, we find that they have significant power in forecasting one-year excess returns of the stock market. Our results suggests that the credit sector is of fundamental importance to the behavior of asset prices.

Variance Risk Premiums

We propose a direct and robust method for quantifying the variance risk premium on financial assets. We show that the risk-neutral expected value of return variance, also known as the variance swap rate, is well approximated by the value of a particular portfolio of options. We propose to use the difference between the realized variance and this synthetic variance swap rate to quantify the variance risk premium. Using a large options data set, we synthesize variance swap rates and investigate the historical behavior of variance risk premiums on five stock indexes and 35 individual stocks. (JEL G10, G12, G13) It has been well documented that return variance is stochastic. When investing in a security, an investor faces at least two sources of uncertainty, namely the uncertainty about the return as captured by the return variance, and the uncertainty about the return variance itself. It is important to know how investors deal with the uncertainty in return variance to effectively manage risk and allocate assets, to accurately price and hedge derivative securities, and to understand the behavior of financial asset prices in general. We develop a direct and robust method for quantifying the return variance risk premium on an asset using the market prices of options written on this asset. Our method uses the notion of a variance swap, which is an over-thecounter contract that pays the difference between a standard estimate of the realized variance and the fixed variance swap rate. Since variance swaps cost zero to enter, the variance swap rate represents the risk-neutral expected value of the realized variance. We show that the variance swap rate can be synthesized accurately by a particular linear combination of option prices. We propose to

Land Value Determination in an Emerging Market: Empirical Evidence from China

A key asset that is important in international markets is real estate - raw land and developed properties. Also, real estate can clearly have difference local rules for investment and transactions based upon bankruptcy protection, appraisal standards, lending standards, taxation and planning processes across countries. This can be particularly true when assessing a developing country. In this research, we assess the relative pricing behavior for land in Beijing China. We see this as important for three core reasons. First, China has a strong growth economy but is still in many ways an undeveloped country and thus we do not have significant data about asset pricing behavior there. Second, China has not traditional had a market based land and property transfer system - thus, it is interesting to assess how prices are determined relative to typical market expectations. Third, we have extensive evidence on pricing behavior in the USA and Europe but little such evidence on China - are the same variables important in Land pricing in China and are there other unique local variables. For example, there have been 22 articles published in core journals on Chinese land and only two provide empirical estimates of value attributes and none of there are as extensive as our study. Thus, we consider a large data set of land prices in Beijing China and assess the relative pricing behavior.Our key results are that pricing behavior in general follows the traditional expected variables as determined by size, planning use, location and other neighborhood characteristics. However, we also find that land prices are associated with buyer characteristics; for example, foreign investors pay less than local investors.

Asset pricing with adaptive learning

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy. We find that (a) recursive least squares learning has almost no effects on asset price behavior, since the algorithm converges relatively fast to rational expectations, (b) constant gain learning may contribute towards explaining the stock price and return volatility as well as the predictability of excess returns in the endowment economy but (c) in the production economy the effects of constant gain learning are mitigated by the persistence induced by capital accumulation. We conclude that in the context of these two commonly used models, standard linear self-referential learning does not resolve the asset pricing puzzles observed in the data.

Reference point adaptation: Tests in the domain of security trading

According to prospect theory [Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk, Econometrica, 47, 263–292], gains and losses are measured from a reference point. We attempted to ascertain to what extent the reference point shifts following gains or losses. In questionnaire studies, we asked subjects what stock price today will generate the same utility as a previous change in a stock price. From participants’ responses, we calculated the magnitude of reference point adaptation, which was significantly greater following a gain than following a loss of equivalent size. We also found the asymmetric adaptation of gains and losses persisted when a stock was included within a portfolio rather than being considered individually. In studies using financial incentives within the BDM procedure [Becker, G. M., DeGroot, M. H., & Marschak, J. (1964). Measuring utility by a single-response sequential method. Behavioral Science, 9(3), 226–232], we again noted faster adaptation of the reference point to gains than losses. We related our findings to several aspects of asset pricing and investor behavior.

Revisiting Static Portfolio Theory for Hara Investors

The implications of the two-fund separation theorem have been carefully examined in the literature for the case of mean-variance preferences. However, even though the two-fund theorem applies to the whole class of HARA utility functions, its implications for the e¢ ciency sets spanned by these preferences are much less known. Without dealing with general equilibrium issues, the goal of this paper is to show how most of the wellknown constructions which arise in connection with the former subclass, extend in a relatively natural way to the whole latter set of preferences. Furthermore, graphical illustrations of the HARA portfolio problem that parallel mean-variance geometry are also provided. Along the same lines, It is also shown how the general problem can be seen as a choice between two parameters, one measuring reward and the other one measuring risk. The youth years of …nancial economics are clearly dominated by the early results of portfolio choice theory. Among other things, the contributions of Markowitz (1957) together with the derivation by Tobin (1958) of the two-fund theorem, always in the context of mean-variance preferences, play a crucial role in developing the …rst general equilibrium model of asset pricing, i.e. the CAPM. These two …elds of …nance marched closely together until the seminal work of Lucas (1978) which implies a radical change of perspective. From this point onwards, it becomes clear that it is not necessary to solve a portfolio choice problem in order to model the behavior of asset prices. The consumption-based approach allows asset pricing to (partially) abandon its early companion and walk its way mostly alone. The GMM technology of Hansen (1982) pushes further in this direction and it helps creating a new approach where the stochastic discount factor (SDF) is to be the main focus.

MONETARY POLICY AND BEHAVIOURAL FINANCE

Abstract There have been major advances in both theory and econometric techniques in mainstream macro‐models and parallel advances in knowledge of the monetary transmission mechanism acting via asset prices. At the same time, behavioural finance has provided evidence that not all actors in the economy are ‘fully rational’ and this has influenced models of asset pricing on which part of the monetary policy transmission mechanism depends. Such uncertainty about the behaviour of asset prices has in part stimulated a move towards ‘robustness’, as an important criterion for guiding monetary policy. We argue that although we have discovered much, including ‘what not to do’, nevertheless our knowledge of the transmission mechanism is very incomplete. This is because, in spite of all the theoretical advances that have been made, there is still considerable uncertainty over the behaviour of agents, which has been reinforced by insights from behavioural finance.

Monetary Policy and Behavioral Finance

There have been major advances in both theory and econometric techniques in mainstream macro-models and parallel advances in knowledge of the monetary transmission mechanism acting via asset prices. At the same time, behavioral finance has provided evidence that not all actors in the economy are 'fully rational' and this has influenced models of asset pricing on which part of the monetary policy transmission mechanism depends. Such uncertainty about the behaviour of asset prices has in part stimulated a move towards 'robustness', as an important criterion for guiding monetary policy. We argue that although we have discovered much, including 'what not to do', nevertheless our knowledge of the transmission mechanism is very incomplete. This is because, in spite of all the theoretical advances that have been made, there is still considerable uncertainty over the behaviour of agents, which has been reinforced by insights from behavioral finance.

A simple asset pricing model with social interactions and heterogeneous beliefs

This paper investigates the dynamics of a simple present value asset pricing model with social interactions and heterogeneous beliefs. Investors revise their beliefs in each period according to two features: the ‘fitness measure’ which is the past realized profit and the exogenous ‘social interactions measure’ which is the interaction among traders’ expectations of the mean choice level in the economy. The endogenous type of social interactions arises naturally when there exist both exogenous social interactions and heterogeneous beliefs among traders. Furthermore, it is shown that the characteristics of the steady state and the dynamic behavior of asset prices are mainly determined by the strength of the endogenous type of social interactions.

Does Market Incompleteness Matter for Asset Prices?

In this paper we argue that market incompleteness resulting from limited stock market participation is important for understanding the behavior of asset prices. (JEL: E32, E44, G12)