Asset Price Fluctuations Research Articles

Clarification of the price fluctuation mechanism in financial markets: disparity in forecast accuracy among investors and asset price fluctuations

This research analysed the impact of the disparity in forecast accuracy among investors in the financial markets. This analysis has found the following interesting phenomena: 1) depending on market environments, investors with good forecast accuracy do not always survive in the market; 2) where the performance measurement period is short, there may be a negative influence such as deviation from the fundamental value of trading prices. These results suggest the need for examining various factors when considering the impact of information technologies such as the text mining technique on financial markets, and are of great significance from both practical and academic viewpoints.

The role of communication and imitation in limit order markets

In this paper we develop an order driver market model with heterogeneous traders that imitate each other on different network structures. We assess how imitations among otherway noise traders, can give rise to well known stylized facts such as fat tails and volatility clustering. We examine the impact of communication and imitation on the statistical properties of prices and order flows when changing the networks’ structure, and show that the imitation of a given, fixed agent, called “guru", can generate clustering of volatility in the model. We also find a positive correlation between volatility and bid-ask spread, and between fat-tailed fluctuations in asset prices and gap sizes in the order book.

The Leverage Cycle

Equilibrium determines leverage, not just interest rates. Variations in leverage cause fluctuations in asset prices. This leverage cycle can be damaging to the economy, and should be regulated.

The Impact of Capital Inflows on Asset Prices in Emerging Asian Economies: Is Too Much Money Chasing Too Little Good?

In recent years, emerging Asian economies have experienced (i) large capital inflows, especially a surge in portfolio inflows, and (ii) an appreciation of asset prices such as stocks, land, and nominal and real exchange rates. We empirically investigate the effects of capital inflows on asset prices by employing a panel VAR model. The empirical results suggest that capital inflows indeed have contributed to asset price appreciation in the region, although capital inflow shocks explain a relatively small part of asset price fluctuations.

Technology Innovation and Diffusion as Sources of Output and Asset Price Fluctuations

Technology Innovation and Diffusion as Sources of Output and Asset Price Fluctuations

Equilibrium Indeterminacy and Asset Price Fluctuation in Japan: A Bayesian Investigation

This paper investigates sources of asset price fluctuation in Japan using an estimated financial accelerator model. For explicit treatment of expectational beliefs characterized by sunspots, the model is analyzed over the parameter space where the equilibrium can be indeterminate. We show that indeterminacy arises if the financial accelerator effect is sufficiently large. According to our Bayesian estimation results, Japan's economy was affected by sunspot shocks; however, the contribution of the sunspots to asset price volatility was low. Rather, net worth and cost shocks drove the asset price fluctuation. We find, however, that the sunspots substantially affected capital investment.

Idiosyncratic Sentiments and Coordination Failures

Coordination models have been used in macroeconomics to study a variety of crises phenomena. It is well understood that, in these models, aggregate fluctuations can be purely self-fulfilling. In this paper I highlight that cross-sectional heterogeneity in expectations regarding the endogenous prospects of the economy can also emerge as a purely self-fulfilling equilibrium property. This in turn leads to some intriguing positive and normative implications: (i) It can rationalize idiosyncratic investor sentiment. (ii) It can be the source of significant heterogeneity in real and financial investment choices, even in the absence of any heterogeneity in individual characteristics or information about all economic fundamentals, and despite the presence of a strong incentive to coordinate on the same course of action. (iii) It can sustain rich fluctuations in aggregate investment and asset prices, including fluctuations that are smoother than those often associated with multiple-equilibria models of crises. (iv) It can capture the idea that investors learn slowly how to coordinate on a certain course of action. (v) It can boost welfare. (vi) It can render apparent coordination failures evidence of improved efficiency. *An earlier version was entitled Private Sunspots and Idiosyncratic Investor Sentiment.

Learning About the Interdependence between the Macroeconomy and the Stock Market

How strong is the interdependence between the macroeconomy and the stock market? This paper estimates a New Keynesian general equilibrium model, which includes a wealth from asset price fluctuations to consumption, to assess the quantitative importance of interactions among the stock market, macroeconomic variables, and monetary policy. The paper relaxes the assumption of rational expectations and assumes that economic agents learn over time and form near-rational expectations from their perceived model of the economy. The stock market, therefore, affects the economy through two channels: through a traditional ``wealth effect and through its impact on agents' expectations. Monetary policy decisions also affect and are potentially affected by the stock market. The empirical results show that the direct wealth is modest, but asset price fluctuations have had important effects on output expectations. Shocks in the stock market can account for a large portion of output fluctuations. The on expectations, however, has declined over time.

Alternative model for asset price dynamics

There is a wide spectrum of models available today describing the asset price underlying. The paper presents a new model for financial asset price fluctuations in which the changes in price occur at random time moments. The basic probabilistic concepts in modelling are developed, the economic interpretation of the model is discussed, arbitrage opportunities arising within the model are excluded. We also derive the closed form formulas for moments of the price process and investigate the framework of hitting times calculation. The analysis in asymptotics shows further that the process appearing in our model converges to the Wiener process. Some estimation results, obtained by the GMM, are presented.

Asymmetric stock market volatility and the cyclical behavior of expected returns

Recent explanations of aggregate stock market fluctuations suggest that countercyclical stock market volatility is consistent with rational asset evaluations. In this paper, I develop a framework to study the causes of countercyclical stock market volatility. I find that countercyclical risk premia do not imply countercyclical return volatility. Instead, countercyclical stock volatility occurs if risk premia increase more in bad times than they decrease in good times, thereby inducing price–dividend ratios to fluctuate more in bad times than in good. The business cycle asymmetry in the investors’ attitude toward discounting future cash flows plays a novel and critical role in many rational explanations of asset price fluctuations.

ON PORTFOLIO SELECTION UNDER EXTREME RISK MEASURE: THE HEAVY-TAILED ICA MODEL

This paper is devoted to the application of the Independent Component Analysis (ICA) methodology to the problem of selecting portfolio strategies, so as to provide against extremal movements in financial markets. A specific ICA model for describing the extreme fluctuations of asset prices is introduced, stipulating that the distributions of the ICs are heavy tailed (i.e., with power law behavior at infinity). An inference method based on conditional maximum likelihood estimation is proposed for our model, which permits to determine practically optimal investment strategies with respect to extreme risk. Empirical studies based on this modeling are carried out to illustrate our approach.

Long-Run Risks and Financial Markets

The recently developed long-run risks asset pricing model shows that concerns about long-run expected growth and time-varying uncertainty (i.e., volatility) about future economic prospects drive asset prices. These two channels of economic risks can account for the risk premia and asset price fluctuations.

Asset price fluctuations in Japan: 1980–2000

In this paper, we try to account for the recent fluctuations in asset prices in Japan using a dynamic stochastic general equilibrium model. In our model, a key to explain the land-price fluctuation is how people's expectations about future productivity growth evolve over time. Specifically, by assuming adaptive learning on the growth rate of productivity, our model can replicate the Japanese land-price fluctuations over the period 1980–2000. However, even with adaptive learning, habit persistence, and costly capital accumulation, a substantial portion of the stock-price fluctuation is left unexplained, and a puzzle remains.

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.

STOCHASTIC PORTFOLIO OPTIMIZATION WITH LOG UTILITY

A portfolio optimization problem on an infinite time horizon is considered. Risky asset price obeys a logarithmic Brownian motion, and the interest rate varies according to an ergodic Markov diffusion process. Moreover, the interest rate fluctuation is correlated with the risky asset price fluctuation. The goal is to choose optimal investment and consumption policies to maximize the infinite horizon expected discounted log utility of consumption. A dynamic programming principle is used to derive the dynamic programming equation (DPE). The explicit solutions for optimal consumption and investment control policies are obtained. In addition, for a special case, an explicit formula for the value function is given.

Asset price fluctuations without aggregate shocks

We analyze the pricing of a productive asset in a class of dynamic exchange economies with heterogeneous, infinitely-lived agents, and self-enforcing intertemporal trades. Individual incomes fluctuate and are correlated; preferences, dividends and aggregate income are fixed. Almost all economies in this class have a unique stationary Markovian equilibrium with fluctuations in asset prices. As the set of unrationed households changes over time and states, excess demand functions shift, asset returns fluctuate, and some households are shut out of asset markets. Examples suggest that the amplitude of these movements is negatively correlated with the productivity of the asset and with the penalty for default.

The Financial Accelerator: Evidence from International Housing Markets

This paper shows novel evidence on the mechanism through which financial constraints amplify fluctuations in asset prices and credit demand. It does so using contractual features of housing finance. Among agents whose housing demand is constrained by the availability of collateral, those who can borrow against a larger fraction of their housing value (achieve a higher loan-tovalue, or LTV, ratio) have more procyclical debt capacity. This procyclicality underlies the financial accelerator mechanism. Our study uses international variation in LTV ratios over three decades to test whether (a) housing prices and (b) demand for new mortgage borrowings are more sensitive to income shocks in countries where households can achieve higher LTV ratios. The results we obtain are consistent with the dynamics of a collateral-based financial accelerator in international housing markets. Copyright Oxford University Press 2006

The Financial Accelerator in Household Spending: Evidence from International Housing Markets

This paper shows novel evidence on the mechanism through which financial constraints amplify fluctuations in asset prices and credit. It does so using contractual features of housing finance. Among agents whose housing demand is constrained by the availability of collateral, those who can borrow against a larger fraction of their housing value (achieve a higher loan-to-value, or LTV, ratio) have more procyclical debt capacity. This procyclicality underlies the financial accelerator mechanism described by Stein (1995) and Bernanke et al. (1996). Our study uses international variation in maximum LTV ratios over three decades to test whether (a) housing prices and (b) demand for new mortgage borrowings are more sensitive to income shocks in countries where households can achieve higher LTV ratios. The results we obtain are consistent with the dynamics of a collateral-based financial accelerator in housing markets.

Impact of Investor's Varying Risk Aversion on the Dynamics of Asset Price Fluctuations

While the investors' responses to price changes and their price forecasts are well accepted major factors contributing to large price fluctuations in financial markets, our study shows that investors' heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in the dynamics of asset price fluctuations. We propose and study a model of an artificial stock market consisting of heterogeneous agents with DRA, and we find that DRA is the main driving force for excess price fluctuations and the associated volatility clustering. We employ a popular power utility function, $U(c,\gamma)=\frac{c^{1-\gamma}-1}{1-\gamma}$ with agent specific and time-dependent risk aversion index, $\gamma_i(t)$, and we derive an approximate formula for the demand function and aggregate price setting equation. The dynamics of each agent's risk aversion index, $\gamma_i(t)$ (i=1,2,...,N), is modeled by a bounded random walk with a constant variance $\delta^2$. We show numerically that our model reproduces most of the stylized facts observed in the real data, suggesting that dynamic risk aversion is a key mechanism for the emergence of these stylized facts.

Stabilizing non-fundamental asset price movements under discretion and limited information

Inflation, output and interest rate stabilization are all potential central bank objectives. We explore whether monetary policy should respond to asset price fluctuations when they are driven by irrational expectational shocks to the future returns to capital. In our model, an optimistic shock to future returns generates both an increase in equity prices and physical investment. The increased investment is inefficient and, thus, a central bank optimally responds to this expectations shocks. This induces a trade-off between stabilizing nominal prices and non-fundamental asset price movements. We compare the optimal policy under different assumptions: full versus limited information and commitment versus discretion. If the central bank has limited information about whether an asset price movement has a fundamental or non-fundamental origin, then the central bank responds less aggressively to the non-fundamental exuberance shocks than under full information. Without commitment, a central bank responds more aggressively to non-fundamental exuberance shocks.