US Stock Prices Research Articles

Multivariate Heavy-Tailed Models for Value-at-Risk Estimation

For purposes of Value-at-Risk estimation, we consider three multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals to have different tail thickness. After a discussion of relevant estimation and simulation issues, we conduct a backtesting study on a set of portfolios containing derivative instruments, using historical US stock price data.

MULTIVARIATE HEAVY-TAILED MODELS FOR VALUE-AT-RISK ESTIMATION

For purposes of Value-at-Risk estimation, we consider several multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals to have different indices of tail thickness. After a discussion of relevant estimation and simulation issues, we conduct a backtesting study on a set of portfolios containing derivative instruments, using historical US stock price data.

Testing for rational bubbles in a coexplosive vector autoregression

Asset bubbles can be described through the rational bubble solution of the standard stock price model linking stock prices and dividends. We show how the hypothesis of a rational bubble can be tested in the context of a bivariate coexplosive vector autoregression. The methodology is illustrated using US stock prices and dividends for the period 1974–2000.

Stock prices and exchange rates dynamics: Evidence from emerging markets

This study empirically investigates the dynamic relationship between the Turkish stock price and the exchange rates, and also considers the US stock prices as a world market, in the long- and short-run. The study analyzes the period of floating exchange rate in Turkey which spans from 2001:08 to 2009:08 via applying cointegration, Granger causality and impulse response tests. The result from the cointegration reveals that the long run relationship is maintained. Granger causality shows that there are bidirectional relationships between exchange rate and Turkish stock prices. The impulse response results indicate the shocks of Turkish stock price, exchange rates, and US stock price response within a short time; in other words, the shocks are temporary. Key words: Exchange rate, stock price, vector autoregression (VAR).

Stock Prices, Home Prices, and Private Consumption in the US: Some Robust Bilateral Causality Tests

We perform robust bilateral Granger causality tests for the US stock prices, home prices, and private consumption. The robust test procedures involve the use of recently developed time series analysis of non-stationary data with possible structural breaks. We find the underlying data to be generally non-stationary and non-cointegrated. The empirical results indicate the presence of bilateral causality between stock prices and home prices and between stock prices and consumer spending. The results show unilateral causality from home prices to consumer spending. Our findings support the reinforcing effects of stock and home price movements on private consumption, as well as the feedback effect of consumer spending on stock prices.

Rational Speculators, Contrarians and Excess Volatility

The VAR approach for testing present value models is applied to a nonlinear asset pricing model with three types of agents, using historical US stock prices and dividends. Besides rational long-term investors, that value assets according to expected dividends, the model includes rational and contrarian speculators. Agents choose their regime based on evolutionary considerations. Supplementing the standard present value model with speculative agents dramatically improves the model’s ability to replicate the observed market dynamics. In particular the existence of contrarians can explain some of the most volatile episodes including the 1990s bubble, suggesting this was not a rational bubble.

Long-run relationships between international stock prices: further evidence from fractional cointegration tests

The recent empirical literature supports the view that most of the international stock prices are not pairwise cointegrated. However, by using fractional cointegration techniques, this article shows that France, Germany, Hong Kong and Japan's stock prices indices are pairwise fractionally cointegrated with US stock prices. Equilibrium errors are mean reverting with half-life lying between 2 and 12 days. It is worthwhile noting that emerging markets like Brazil and Argentina are not pairwise cointegrated with the US stock market. These new results have important implications for asset pricing and international portfolio strategy.

The weekly structure of US stock prices

In this paper we use fractional integration techniques to examine the degree of integration of four US stock market indices, namely the Standard and Poor, Dow Jones, Nasdaq and NYSE, at a daily frequency from January 2005 till December 2009. We analyse the weekly structure of the series and investigate their characteristics depending on the specific day of the week. The results indicate that the four series are highly persistent; a small degree of mean reversion (i.e., orders of integration strictly smaller than 1) is found in some cases for S&P and the Dow Jones indices. The most interesting findings are the differences in the degree of dependence for different days of the week. Specifically, lower orders of integration are systematically observed for Mondays and Fridays, consistently with the “day of the week” effect frequently found in financial data.

The Weekly Structure of US Stock Prices

In this paper we use fractional integration techniques to examine the degree of integration of four US stock market indices, namely the Standard and Poor, Dow Jones, Nasdaq and NYSE, at a daily frequency from January 2005 till December 2009. We analyse the weekly structure of the series and investigate their characteristics depending on the specific of the week. The results indicate that the four series are highly persistent; a small degree of mean reversion (i.e., orders of integration strictly smaller than 1) is found in some cases for S&P and the Dow Jones indices. The most interesting findings are the differences in the degree of dependence for different days of the week. Specifically, lower orders of integration are systematically observed for Mondays and Fridays, consistently with the day of the week effect frequently found in financial data.

An Analysis on Directional Predictability of Asian Stock Prices Using the US Stock Price and Technical Trading Rules

An Analysis on Directional Predictability of Asian Stock Prices Using the US Stock Price and Technical Trading Rules

The Great Recession: US dynamics and spillovers to the world economy

This paper provides an empirical investigation of both the within-US and international channels of transmission of macroeconomic and financial shocks by means of a 50-country macroeconometric model (estimated over the 1980–2009 period), including measures of excess liquidity and financial fragility, specifically designed in order to evaluate the relevance of the boom-bust credit cycle view put forward as an interpretation of the recent “Great Recession” episode. We find that such a view is consistent with the empirical evidence. Moreover, concerning the real effects of financial shocks within the US, we detect stronger evidence of an asset prices channel, rather than a liquidity channel. Concerning the spillovers to the world economy, we find that while financial disturbances are transmitted to foreign countries through US house and stock price dynamics, as well as excess liquidity creation, the trade channel is the key trasmission mechanism of real shocks.

US and European stock market crashes: Any evidence of interdependence?

This paper examines the response of Stock Prices (SPs) in Germany, Italy, and the UK to shocks to US Stock Prices (USSPs) using Vector Error Correction Models (VECMs) and cross-country stock return correlations. Our results yield clear implications. Positive shocks to USSPs lead to significant, positive, responses in European SPs. Shocks to US stock prices also explain over 43% of the forecast error variance in European SPs. Shocks to domestic variables never cause significant responses in European SPs. These results indicate strong interdependence between the US stock market and stock markets in the UK, Germany and Italy.

The Great Recession: US Dynamics and Spillovers to the World Economy

The paper aims at assessing the mechanics of the Great Recession, considering both its domestic propagation within the US, as well as its spillovers to advanced and emerging economies. A total of 50 countries has been investigated by means of a large-scale open economy macroeconometric model, providing an accurate assessment of the international macro/finance interface over the whole 1980-2009 period. It is found that a boom-bust credit cycle interpretation of the crisis is consistent with the empirical evidence. Moreover, concerning the real effects of the crisis within the US, stronger evidence of an asset prices channel, rather than a liquidity channel, has been detected. The results also support the effectiveness of the expansionary fiscal/monetary policy mix implemented by the Fed and the US government. Concerning the spillovers to the world economy, it is found that while the financial shock has spilled over to foreign countries through US housing and stock price dynamics, as well as excess liquidity creation, the trade channel likely is the key transmission mechanism of the real shock.

Multivariate Contemporaneous Threshold Autoregressive Models

In this paper we propose a contemporaneous threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. The model is a multivariate generalization of the contemporaneous threshold autoregressive model introduced by Dueker et al. (2007). A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. The stability and distributional properties of the proposed model are investigated. The C-MSTAR model is also used to examine the relationship between US stock prices and interest rates.

Multivariate contemporaneous-threshold autoregressive models

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex-ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific noise covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.

Testing for Rational Bubbles in a Co-Explosive Vector Autoregression

We derive the parameter restrictions that a standard equity market model implies for a bivariate vector autoregression for stock prices and dividends, and we show how to test these restrictions using likelihood ratio tests. The restrictions, which imply that stock returns are unpredictable, are derived both for a model without bubbles and for a model with a rational bubble. In both cases we show how the restrictions can be tested through standard chi-squared inference. The analysis for the no-bubble case is done within the traditional Johansen model for I(1) variables, while the bubble model is analysed using a co-explosive framework. The methodology is illustrated using US stock prices and dividends for the period 1872-2000.

A network perspective of the stock market

Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded over two periods of time (from July 2005 to August 2007; and from June 2007 to May 2009). The nodes are the stocks, and the connections are determined by cross correlations of the variations of the stock prices, price returns and trading volumes within a chosen period of time. Specifically, a winner-take-all approach is used to determine if two nodes are connected by an edge. So far, no previous work has attempted to construct a full network of US stock prices that gives full information about their interdependence. We report that all networks based on connecting stocks of highly correlated stock prices, price returns and trading volumes, display a scalefree degree distribution. The results from this work clearly suggest that the variation of stock prices are strongly influenced by a relatively small number of stocks. We propose a new approach for selecting stocks for inclusion in a stock index and compare it with existing indexes. From the composition of the highly connected stocks, it can be concluded that the market is heavily dominated by stocks in the financial sector.

The Weekly Structure of US Stock Prices

The Weekly Structure of US Stock Prices

DOMESTIC AND FORIGN FACTORS FOR STOCK PRICES IN INDONESIA

Indonesia has been developing various sectors of its economy, and so it needs a huge amount of capital. Therefore, it has been putting a lot of efforts to develop its capital market. This paper analyzes the impacts of domestic and foreign factors on Indonesia stock price. Some considered domestic factors are interest rates, production index, and foreign exchange rates. Various considered foreign factors are Singapore and US stock prices. The paper uses Vector Error Correction Mechanism model to analyze the data. The estimation results suggest that all variables significantly influence Indonesia stock price, with Singapore stock price as the dominant factors. Keywords: Stock price, interest rates, exchange rates, production index JEL classification numbers: G12, G15

Co‐movements between US and UK stock prices: the role of time‐varying conditional correlations

AbstractWe provide evidence on the nature of co‐movement in monthly US and UK stock returns by investigating time‐varying correlations in returns since 1980. There is a marked increase in correlations between these markets around 2000, which we attribute to globalization and model with a time‐varying smooth transition conditional correlation (STCC) GARCH specification. A double transition correlation model with time and US stock price volatility indicates that correlations not only increase over time but also during periods of high volatility. The STCC models perform well in comparison with constant and dynamic conditional correlation models in terms of both statistical and economic criteria, but we demonstrate that an investor will gain little from portfolio diversification across these two important markets. Copyright © 2009 John Wiley & Sons, Ltd.