Financial Econometics Series
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[1-20]  [21-39]  
No. 2014_09   (Download full text)
Paresh Kumar Narayan and Susan S Sharma
Do Oil Prices Predict Economic Growth? New Global Evidence
In this paper, we test whether oil price predicts economic growth for 28 developed and 17 developing countries. We use predictability tests that account for the key features of the data, namely, persistency, endogeneity, and heteroskedasticity. Our analysis considers a large number of countries, shows evidence of more out-of-sample predictability with nominal than real oil prices, finds in-sample predictability to be independent of the use of nominal and real prices, and reveals greater evidence of predictability for developed countries.
Keywords: Economic Growth; Predictability; Oil Price.
No. 2014_08   (Download full text)
Paresh Kumar Narayan, Susan S Sharma and Kannan Thuraisamy
An Analysis of Price Discovery from Panel Data Models of CDS and Equity Returns
We propose a panel data model of price discovery. We find that the stock market contributes to price discovery in most sectors while the Credit Default Swap (CDS) market contributes to price discovery in only a few sectors. We discover that in sectors where both the stock market and the CDS market contribute to price discovery, it is the stock market that dominates the price discovery process. When we consider investment grade stocks, the importance of the CDS market in price discovery improves but the stock market still dominates the price discovery process. The results for different sizes of stocks generally suggest that both markets are important for price discovery but it is the stock market that dominates. We also find that while the price discovery process was affected by the 2007 global financial crisis, the stock market still dominated the price discovery process. Finally, in an economic significance analysis, we show that investors in the CDS market are able to make relatively more profits from a forecasting model that takes into account price discovery compared to a model that simply ignores the role of price discovery.
Keywords: Price Discovery; CDS Spread; Panel Data; Sectors; Sizes.
No. 2014_07   (Download full text)
Joakim Westerlund
On the Importance of the First Observation in GLS Detrending in Unit Root Testing
First-differencing is generally taken to imply the loss of one observation, the first, or at least that the effect of ignoring this observation is asymptotically negligible. However, this is not always true, as in the case of GLS detrending. In order to illustrate this, the current paper considers as an example the use of GLS detrended data when testing for a unit root. The results show that the treatment of the first observation is absolutely crucial for test performance, and that ignorance causes test break-down.
JEL-Codes: C12; C13; C33.
Keywords: Unit root test; GLS detrending; Local asymptotic power.
No. 2014_06   (Download full text)
Joakim Westerlund
Pooled Panel Unit Root Tests and the Effect of Past Initialization
This paper analyzes the role of initialization when testing for a unit root in panel data, an issue that has received surprisingly little attention in the literature. In fact, most studies assume that the initial value is either zero or bounded. As a response to this, the current paper considers a model in which the initialization is in the past, which is shown to have several distinctive features that makes it attractive, even in comparison to the common time series practice of making the initial value a draw from its unconditional distribution under the stationary alternative. The results have implications not only for theory, but also for applied work. In particular, and in contrast to the time series case, in panels the effect of the initialization need not be negative but can actually lead to improved test performance.
JEL-Codes: C22; C23.
Keywords: Panel unit root test; Initial value; Local asymptotic power.
No. 2014_05   (Download full text)
Joakim Westerlund, Mehdi Hosseinkouchack and Martin Solberger
The Local Power of the CADF and CIPS Panel Unit Root Tests
Very little is known about the local power of second generation panel unit root tests that are robust to cross-section dependence. This paper derives the local asymptotic power functions of the CADF and CIPS tests of Pesaran (A Simple Panel Unit Root Test in Presence of Cross-Section Dependence, Journal of Applied Econometrics 22, 265–312, 2007), which are among the most popular tests around.
JEL-Codes: C12; C13; C33.
Keywords: Panel unit root test; common factor model; cross-sectional averages; crosssectional dependence; local asymptotic power.
No. 2014_04   (Download full text)
Johan Blomquist and JoakimWesterlund
Testing Slope Homogeneity in Large Panels with Serial Correlation
Pesaran and Yamagata (Testing slope homogeneity in large panels, Journal of Econometrics 142, 50–93, 2008) propose a test for slope homogeneity in large panels, which has become very popular in the literature. However, the test cannot deal with the practically relevant case of heteroskedastic and/serially correlated errors. The present note proposes a generalized test that accommodates both features.
JEL-Codes: C32; C33.
Keywords: Homogeneity; Panel data; Serial correlation; Heteroskedasticity
No. 2014_03   (Download full text)
Joakim Westerlund
On the Asymptotic Distribution of the DF–GLS Test Statistic
In a very influential paper Elliott et al. (Efficient Tests for an Autoregressive Unit Root, Econometrica 64, 813–836, 1996) show that no uniformly most powerful test for the unit root testing problem exits, derive the relevant power envelope and characterize a family of point-optimal tests. As a by-product, they also propose a “GLS detrended” version of the conventional Dickey–Fuller test, denoted DF–GLS, that has since then become very popular among practitioners, much more so than the point-optimal tests. In view of this, it is quite strange to find that, while conjectured in Elliott et al. (1996), so far there seems to be no formal proof of the asymptotic distribution of the DF–GLS test statistic. By providing three separate proofs the current paper not only substantiates the required result, but also provides insight regarding the pros and cons of different methods of proof.
JEL-Codes: C12; C22.
Keywords: Unit root test; GLS detrending; Asymptotic distribution; Asymptotic local power; Method of proof.
No. 2014_02   (Download full text)
Joakim Westerlund
Heteroskedasticity Robust Panel Unit Root tests
This paper proposes new unit root tests for panels where the errors may be not only serial and/or cross- orrelated, but also unconditionally heteroskedastic. Despite their generality, the test statistics are shown to be very simple to implement, requiring only minimal corrections and still the limiting distributions under the null hypothesis are completely free from nuisance parameters. Monte Carlo evidence is also provided to suggest that the new tests perform well in small samples, also when compared to some of the existing tests.
JEL-Codes: C13; C33
Keywords: Unit root test; Panel data; Unconditional heteroskedasticity; GARCH; Crosssection dependence, Common factors.
No. 2014_01   (Download full text)
Joakim Westerlund and Paresh Kumar Narayan
Testing for Predictability in Conditionally Heteroskedastic Stock Returns
The difficulty of predicting stock returns has recently motivated researchers to start looking for more powerful tests, and the current paper takes a step in this direction. Unlike existing tests, the test proposed here exploits the information contained in the heteroskedasticity of returns, which is expected to lead to higher power, a result that is confirmed by our results. In order to also maintain good size accuracy, subsample critical values are used.
JEL-Codes: C12; C22; G1.
Keywords: Predictability; FQGLS; Conditional heteroskedasticity; Subsampling; Stock returns.
No. 2013_06   (Download full text)
Paresh Kumar Narayan and Sagarika Mishra
Determinants of Stock Price Bubbles
In this paper we propose a cross-sectional model of the determinants of asset price bubbles. Using 589 firms listed on the NYSE, we find conclusive evidence that trading volume and share price volatility have statistically significant effects on asset price bubbles. However, evidence from sector-based stocks is mixed. We find that for firms belonging to electricity, energy, financial, and banking sectors, and for the smallest size firms, trading volume has a statistically significant and positive effect on bubbles. We do not discover any robust evidence of a statistically significant effect of share price volatility on bubbles at the sector-level.
Keywords: Asset Price; Bubbles; Cross-section; Trading Volume; Volatility.
No. 2013_05   (Download full text)
Sagarika Mishra and Sandeep Dhole
Least Squares Learning and the US Treasury Bill Rate
Understanding how agents formulate their expectations about Fed behavior is important for market participants because they can potentially use this information to make more accurate estimates of stock and bond prices. Although it is commonly assumed that agents learn over time, there is scant empirical evidence in support of this assumption. Thus, in this paper we test if the forecast of the three month T-bill rate in the Survey of Professional Forecasters (SPF) is consistent with least squares learning when there are discrete shifts in monetary policy. We first derive the mean, variance and autocovariances of the forecast errors from a recursive least squares learning algorithm when there are breaks in the structure of the model. We then apply the Bai and Perrron (1998) test for structural change to a forecasting model for the three month T-bill rate in order to identify changes in monetary policy. Having identified the policy regimes, we then estimate the implied biases in the interest rate forecasts within each regime. We find that when the forecast errors from the SPF are corrected for the biases due to shifts in policy, the forecasts are consistent with least squares learning.
Keywords: Survey forecasts, Least Squares Learning
No. 2013_04   (Download full text)
Kannan Thuraisamy
Intra-market Sovereign Linkages of Latin American International Bonds
This paper tests the intra-market dynamics in a regional setting using country specific international bonds differentiated only by maturity within individual markets in the Latin American region. We use 2001 Argentine default as a natural experiment in this study to examine how intra-market dynamics evolved in the presence of a credit event in the region. This paper argues that emerging market instruments have a stronger tendency to tie up with instruments within markets rather than across markets as found in the literature. The long-run equilibrium relationships tend to be stronger across instruments within each market and generate economically insignificant portfolio adjustment weights. Strong interaction across instruments within markets in terms of first order dependencies has important implications for market participants, practitioners and policy makers.
Keywords: Intra-market dynamics; Sovereign linkages; Common stochastic component
No. 2013_03   (Download full text) (Published)
Paresh Kumar Narayan, Susan S Sharma and Deepa Bannigidadmath
Does Tourism Predict Macroeconomic Performance in Pacific Island Countries?
In this paper we examine whether tourism predicts macroeconomic variables in Pacific Island countries (PICs), namely, Fiji, the Solomon Islands, PNG, Vanuatu, Samoa, and Tonga. We form seven panels of PICs—one full panel of six countries and six panels where, one-by-one, each country is excluded from the panel. We apply the Westerlund and Narayan (2012a) panel regression framework, where the null hypothesis is that visitor arrivals do not predict macroeconomic variables, which we proxy with 11 indicators, for panels of countries. We find that visitor arrivals consistently predict exports and money supply, and to a lesser extent, exchange rates and GDP.
Keywords: Tourism; Macroeconomic variables; GDP; Money Supply; Panel Data; Predictive Regression Model.
No. 2013_02   (Download full text) (published)
Paresh Kumar Narayan, Seema Narayan and Susan S Sharma
An analysis of commodity markets: What gain for investors?
In this paper we study whether the commodity futures market predicts the commodity spot market. Using historical daily data on four commodities—oil, gold, platinum, and silver—we find that they do. We then show how investors can use this information on the futures market to devise trading strategies and make profits. In particular, dynamic trading strategies based on a mean-variance investor framework produce somewhat different results compared with those based on technical trading rules. Dynamic trading strategies suggest that all commodities are profitable and profits are dependent on structural breaks. The most recent global financial crisis marked a period in which commodity profits were the weakest.
JEL-Codes: C22; G11; G17
Keywords: Commodity Futures; Commodity Spot; Trading Strategies; Profits
No. 2013_01   (Download full text)
Sandip Dhole, Sagarika Mishra and Ananda M Pal
Further Evidence on the Importance of Analysts’ Cash Flow Forecasts
Analysts’ cash flow (CPS) forecasts have been the topic of much recent research. While some prior research (for example, Givoly et al., 2009) suggests that these forecasts have very limited usefulness, Call et al. (2012) find evidence to the contrary. We take this body of research forward and find that CPS forecasts improve the firm’s information environment by reducing the information asymmetry, as evidenced by lower post-earnings announcement drift and bid-ask spread around the earnings announcement. We also examine the usefulness of CPS forecasts as a source of value-relevant information and construct a composite earnings forecast, based on the EPS forecast and the CPS forecast. We find a significant market reaction to the composite forecast error, controlling for the EPS forecast error. Finally, we show that the composite forecast performs better than the EPS forecast in capturing the market’s expectations under some situations.
JEL-Codes: G14, M41
Keywords: Analysts’ Cash Flow Forecasts, Analysts’ Earnings Forecasts, Information Asymmetry, Bid-Ask Spread, Post-Earnings Announcement Drift, Analyst Forecast Dispersion, Earnings Volatility, Firm Size
No. 2012_11   (Download full text)
Sandip Dhole, Saleha B Khumawala, Sagarika Mishra and Tharindra Ranasinghe
Executive Compensation and Regulation Imposed Corporate Governance: Evidence from the California Non-Profit Integrity Act (2004)
This study focuses on the impact of the California Non-Profit Integrity Act (2004) on executive compensation costs in affected nonprofit organizations. We find that, for affected organizations, executive compensation costs during post-regulation periods have gone up in comparison to control groups of comparable nonprofits that are not affected by the Act. Moreover, we find a relative deterioration in pay performance sensitivity for affected nonprofits. We do not find evidence to suggest that the observed increase in compensation is more pronounced for executives who were likely underpaid during the pre-Act period. Our findings thus raise questions with respect to the efficacy of the provisions of the Act aimed at ensuring that executive compensation is “just and reasonable” and draw attention to some unintended and costly consequences of regulatory attempts at improving governance.
Keywords: Executive compensation, Governance, Regulation, Nonprofits, California Non-Profit Integrity Act (2004)
No. 2012_10   (Download full text)
Matthew L Higgins and Sagarika Mishra
State Dependent Asymmetric Loss and the Consensus Forecast of Real U.S. GDP Growth
It has been well documented that the consensus forecast from surveys of professional forecasters show a bias that varies over time. In this paper, we examine whether this bias may be due to forecasters having an asymmetric loss function. In contrast to previous research, we account for the time variation in the bias by making the loss function depend on the state of the economy. The asymmetry parameter in the loss function is specified to depend on set state variables which may cause forecasters to intentionally bias their forecasts. We consider both the Lin-Ex and asymmetric power loss functions. For the commonly used Lin-Ex and Lin-Lin loss functions, we show the model can be easily estimated by least squares. We apply our methodology to the consensus forecast of real U.S. GDP growth from the Survey of Professional Forecasters. We find that forecast uncertainty has an asymmetric effect on the asymmetry parameter in the loss function dependent upon whether the economy is in expansion or contraction. When the economy is in expansion, forecaster uncertainty is related to a negative bias in the median forecast of real GDP growth. In contrast, when the economy is in contraction, forecaster uncertainty is related to a positive bias in the median forecast of real GDP growth. Our results are robust to the particular loss function that is employed in the analysis.
JEL-Codes: C53; D83
Keywords: Survey forecasts, Asymmetric loss, Time-varying bias
No. 2012_09   (Download full text)
Sagarika Mishra
Do Agents Learn by Least Squares? The Evidence Provided by Changes in Monetary Policy
Understanding how agents formulate their expectations about Fed behavior is critical for the design of monetary policy. In response to a lack of empirical support for a strict rationality assumption, monetary theorists have recently introduced learning by agents into their models. Although a learning assumption is now common, there is practically no empirical research on whether agents actually earn. In this paper we test if the forecast of the three month T-bill rate in the Survey of Professional Forecasters (SPF) is consistent with least squares learning when there are discrete shifts in monetary policy. Discrete shifts in policy introduce temporary biases into forecasts while agents process data and learn about the policy shift. We first derive the mean, variance and autocovariances of the forecast errors from a recursive least squares learning algorithm when there are breaks in the structure of the model. We then apply the Bai and Perrron (1998) test for structural change to a Taylor rule and a forecasting model for the three month T-bill rate in order to identify changes in monetary policy. Having identified the policy regimes, we then estimate the implied biases in the interest rate forecasts within each regime. We find that when the forecast errors from the SPF are corrected for the biases due to shifts in policy, the forecast are consistent with least squares learning.
JEL-Codes: D83; D84
Keywords: Survey forecasts, Least Squares Learning
No. 2012_08   (Download full text)
Christoph Riedel, Kannan Thuraisamy and Niklas Wagner
Conditional Spread Determinants for Emerging Sovereign Debt
This paper addresses conditional sovereign credit risk determinants. In our model, the spread determinants' magnitude is conditional on an unobservable endogenous sovereign credit cycle as represented by the underlying state of a Markov regime switching process. Our explanatory variables are motivated in the tradition of structural credit risk models and include changes in asset price, interest rate, volatility and foreign exchange variables. We examine daily frequency variations of U.S. dollar denominated Eurobond credit spreads of four major Latin American sovereign issuers with liquid bond markets. We nd that spread determinants are statistically signi cant and consistent with theory while their magnitude varies with the states of our cycle variable, which characterizes low and high spread change uncertainty.We also uncover the presence of additional premium under Regime 1 where the spread volatility is stable. This premium is negatively related to the changes in credit spreads. The term structure factors exhibit much higher economic magnitudes under the high volatility sate. The response from the asset price factor to changes in credit spread is rather stable. We document that not only changes of local currencies, but also changes of the Euro with respect to the U.S. dollar are signi cant spread drivers and show that this is consistent with the sovereigns ability to meet its obligations.
Keywords: sovereign bonds; sovereign spreads; sovereign credit cycle; structural models of credit risk; Eurobonds; regime switching; sovereign debt crises
No. 2012_07   (Download full text)
Kannan Thuraisamy, Susan S Sharma and Huson A Ahmed
The relationship between Asian equity and commodity futures markets
In this paper, we test spillover effects between Asian equity market volatility and the volatility of the two most dominant commodities, namely, crude oil and gold futures. We consider a total of 14 Asian markets. We find that volatility shocks in established and mature equity markets, such as the Japanese market, spill over to the crude oil and gold futures markets, while immature markets tend to have spillover effects from commodity futures to equity markets. We also report evidence of increased bi-directional volatility transmission during the recent global financial crisis period. Like the volatility of crude oil futures, the volatility of gold futures matters to the equity market. As far as quity market volatility is concerned, the impact of volatility shocks from the gold futures market is as important as the volatility shocks from the crude oil futures market.
Keywords: Equity Markets; Gold Futures; Oil Futures; Volatility Spillover
 
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