Forecasting multivariate realized stock market volatility

We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of lagged volatility, lagged returns and other forecasting variables. The model has several advantages: it is parsimonious; it does not require imposing parameter restrictions; and, it results in a positive-definite estimated covariance matrix. We apply the model to the covariance matrix of size-sorted stock returns and find that two factors are sufficient to capture most of the dynamics.     

Functional data analysis for volatility

We introduce a functional volatility process for modeling volatility trajectories for high frequency observations in financial markets and describe functional representations and data-based recovery of the process from repeated observations. A study of its asymptotic properties, as the frequency of observed trades increases, is complemented by simulations and an application to the analysis of intra-day volatility patterns of the S&P 500 index. The proposed volatility model is found to be useful to identify recurring patterns of volatility and for successful prediction of future volatility, through the application of functional regression and prediction techniques.     

Volatility contagion: A range-based volatility approach

This article proposes a new approach to evaluate volatility contagion in financial markets. A time-varying logarithmic conditional autoregressive range model with the lognormal distribution (TVLCARR) is proposed to capture the possible smooth transition in the range process. Additionally, a smooth transition copula function is employed to detect the volatility contagion between financial markets. The approach proposed is applied to the stock markets of the G7 countries to investigate the volatility contagion due to the subprime mortgage crisis. Empirical evidence shows that volatility is contagious from the US market to several markets examined.     

The conditional autoregressive Wishart model for multivariate stock market volatility

We propose a Conditional Autoregressive Wishart (CAW) model for the analysis of realized covariance matrices of asset returns. Our model assumes an autoregressive moving average structure for the scale matrix of the Wishart distribution. It accounts for positive definiteness of covariance matrices without imposing parametric restrictions, and can be estimated by Maximum Likelihood. We also propose extensions of the CAW model obtained by including a Mixed Data Sampling (MIDAS) component and Heterogeneous Autoregressive (HAR) dynamics for long-run fluctuations. The CAW models are applied to realized variances and covariances for five New York Stock Exchange stocks.     

NAFTA and North American stock market linkages: an empirical note

This paper provides tests of the co-movement of the North American stock markets. We find over the post-US stock market crash period, 1987:11 through 1997:03, there is no cointegration present in these markets even when the passage of NAFTA is taken into account. The absence of cointegration allows us to draw several conclusions. First, the stock markets of North America are segmented. Second, the passage of NAFTA has not resulted in a greater integration of these stock markets. Finally, the data do not support the notion of a contagion effect from the 1987 U.S. stock market crash. In conclusion, the potential for long-run international diversification across the markets of North America still exists.     

Determinants of European stock market integration

We analyse the determinants of stock market integration among EU member states for the period 1999–2007. First, we apply bivariate DCC-MGARCH models to extract dynamic conditional correlations between European stock markets, which are then explained by interest rate spreads, exchange rate risk, market capitalisation, and business cycle synchronisation in a pooled OLS model. By grouping the countries into euro area countries, “old” EU member states outside the euro area, and new EU member states, we also evaluate the impact of euro introduction and the European unification process on stock market integration. We find a significant trend toward more stock market integration, which is enhanced by the size of relative and absolute market capitalisation and hindered by foreign exchange risk between old member states and the euro area. Interest rate spreads and business cycle synchronisation are also significant factors in explaining equity market integration.     

Emerging market mutual fund performance: Evidence for Poland

This paper provides evidence on the performance of mutual funds in a prominent emerging market; Poland. Studying an emerging market provides an excellent opportunity to test whether the consensus on the inability of mutual funds in developed and highly efficient markets to beat the market, also holds in less efficient markets. While the weaknesses of legal institutions and underdeveloped capital markets in emerging countries could negatively contribute to performance, a certain level of market inefficiency might also enable fund managers to successfully apply security selection and therefore beat the market. This paper presents an overview of the Polish mutual fund industry and investigates mutual fund performance using a survivorship bias controlled sample of 140 funds. The latter is done using the Carhart (1997) 4-factor asset-pricing model. In addition, we investigate whether Polish fund managers exhibit “hot hands”, persistence in performance. Finally the influence of fund characteristics on risk-adjusted performance is considered. Our overall results suggest that Polish mutual funds on average are not able to add value, as indicated by their negative net alphas. Interestingly, domestic funds outperform internationally investing funds, which points at informational advantages of local over foreign investors. Finally, we detect strong persistence in mean returns up to 1 year. It is striking that “winning” funds are able to significantly beat the market, based on their significantly positive alpha's. These results deviate from studies on developed markets that conclude that even past winners are not able to significantly beat the market.     

A bootstrap algorithm for testing cointegration rank in VAR models in the presence of stationary variables

In this paper, a bootstrap algorithm for a reduced rank vector autoregressive (VAR) model which also includes stationary regressors, is analyzed. It is shown that the bootstrap distribution for estimating the rank converges to the distribution derived from the usual asymptotic framework. Because the asymptotic distribution will typically depend on unknown parameters, bootstrap distributions are of considerable interest in this context. The result of an application and some Monte Carlo experiments are also presented.     

Trade credit versus bank credit: Evidence from corporate inventory financing

In this study, I introduce capital market imperfections into a structure framework of inventory investments and investigate impacts of trade credit on firms’ inventory dynamics and analyze the relationship between trade credit and bank loans. As a result, firms end up using a mix of trade credit and bank loans. I find that the use of trade credit and bank credit can be either complements or substitutes. During tight monetary periods, trade credit operates mainly as a substitute for bank borrowing while during looser monetary episodes even when the economy is weak, trade credit and bank loans are dominated by a complementary effect.     

Should the government directly intervene in stock market during a crisis?

Unlike foreign exchange markets where central banks frequently intervene, the governments strive not to intervene in the stock markets since intervention transmit negative signals and carry market-related side effects. The main reasons often cited in support of intervention are to bring price stability and to restore investors’ confidence. During the recent economic turmoil, opportunities for the governments to intervene in the stock markets were mainly exploited in emerging and developing countries. We study the outcome of the Russian government's intervention in its major stock market between September and October 2008. This intervention was intended to reverse the sudden and swift declining trend in traded security prices by altering the market's expectations. By using a combination of event study and a multivariate GARCH model, our findings does not support direct government intervention in the stock market during a crisis.     

Carbon Financial Instruments, thin trading, and volatility: Evidence from the Chicago Climate Exchange

We provide the first econometric investigation of volatility dynamics for the Carbon Financial Instrument (CFI) traded on the Chicago Climate Exchange (CCX). A CFI is a financial contract with the right to emit 100 metric tons of CO₂ equivalent. In this study, we present evidence of infrequent trading in the CCX, consistent with emerging markets that are inhabited by non-competitive agents trading permits. We explore the relationship between the observed thin trading effects and GARCH model testing and estimation, concluding with some implications for volatility-based Value-at-Risk forecasts. Our results are important for traders of Carbon Financial Instruments and for policy makers seeking to improve the design of the Chicago Climate Exchange.     

The VIX,the variance premium and stock market volatility

We decompose the squared VIX index, derived from US S&P500 options prices, into the conditional variance of stock returns and the equity variance premium. We evaluate a plethora of state-of-the-art volatility forecasting models to produce an accurate measure of the conditional variance. We then examine the predictive power of the VIX and its two components for stock market returns, economic activity and financial instability. The variance premium predicts stock returns while the conditional stock market variance predicts economic activity and has a relatively higher predictive power for financial instability than does the variance premium.     

Regulatory risk, market uncertainties, and firm financing choices: Evidence from U.S. Electricity Market Restructuring

Based on the universe of rate-regulated electric utilities in the U.S., we examine why firms alter their financing decisions when transitioning from a regulated to a competitive market regime. We find that the significant increase in regulatory risk after the passage of the Energy Policy Act, state-level restructuring legislations, and divestiture policies have reduced leverage by 15 percent. Policies that encouraged competition, and hence increased market uncertainty, lowered leverage by another 13 percent on average. The ability to exercise market power allowed some firms to counter this competitive threat. In aggregate, regulatory risk and market uncertainty variables reduce leverage between 24.6 and 26.7 percent. We also confirm findings in the literature that firms with higher profitability and higher asset growth have lower leverage, and those with more tangible assets are more levered. Firms with greater access to internal capital markets and those with a footloose customer segment use less debt, while those actively involved in trading power in the wholesale market use more debt.     

International foreign exchange agreements and nominal exchange rate volatility: a GARCH application

For eight major national currencies, this study estimates, and tests several hypotheses with, a t-distribution GARCH model of daily spot nominal exchange rate changes. The sample period covered is June 1, 1982 through September 30, 1992. By using likelihood ratio and parameter stability tests, it finds that for most of the currencies considered, both the conditional means and variances of unexpected exchange rate changes experienced statistically significant structural breaks across the five subperiods that are associated with four episodes of international foreign-exchange policy coordination. The study also finds that the orderings of the GARCH-estimated unconditional standard deviations roughly match the orderings of the sample standard deviations across the five subperiods. An explanation is provided for what underlying factors contributed to these structural shifts.     

Efficient predictability of stock return volatility: The role of stock market implied volatility

This study examines the predictability of stock market implied volatility on stock volatility in five developed economies (the US, Japan, Germany, France, and the UK) using monthly volatility data for the period 2000 to 2017. We utilize a simple linear autoregressive model to capture predictive relationships between stock market implied volatility and stock volatility. Our in-sample results show there exists very significant Granger causality from stock market implied volatility to stock volatility. The out-of-sample results also indicate that stock market implied volatility is significantly more powerful for stock volatility than the oil price volatility in five developed economies.     

The number of banking relationships and the business cycle: New evidence from Colombia

We study the determinants of multiple bank–firm relationships using a uniquely rich data set comprised of information on individual loans of a large number of firms in Colombia. We control for firm-specific variables and find that the business cycle exerts important influence on the number of bank relationships sustained by firms. Our evidence suggests that the number of bank relationships is counter-cyclical, decreasing during macroeconomic expansions and increasing during contractions. However, this effect is stronger for large firms which have more access to alternative sources of funding.     

Private debt, unused credit lines, and seasoned equity offerings

We study a sample of SEOs to examine the impact of private debt and unused credit lines on SEO underpricing and long-run stock and operating performance. We do not find significant effects of private debt financing on SEO underpricing and long-run stock underperformance. However, firms with more bank debt and unused lines of credit exhibit significantly better pre-issue operating performance. Changes in operating performance from the pre-issue year to the post-issue period are negatively related to the size of unused credit lines. Capital spending decreases with the size of unused credit lines in the year prior to SEOs, but increases following SEOs. Our overall evidence suggests that the post-issue operating performance we observed may be a result of overinvestment, which is enhanced by unused credit lines.     

Order aggressiveness, pre-trade transparency, and long memory in an order-driven market

Recent empirical research has documented that the state of the limit order book influences stock investors' strategies. Investors place more aggressive orders when the same side of the order book is thicker, and less aggressive orders when it is thinner. We conjecture and demonstrate that this behavior is related to long memories of trading volume, volatility, and order signs in stock markets. We investigate our conjecture in two types of artificial stock markets: a transparent market, in which agents observe all limit orders on both sides of the book and order volumes at those prices before they trade; and a less transparent market, in which agents observe only the best five bid and ask quotes with the depth available at these limit prices. The first market structure resembles certain actual stock exchanges in the level of pre-trade transparency, such as the Australian Stock Exchange, NYSE OpenBook, and the London Stock Exchange, whereas the second market structure is consistent with stock exchanges such as Euronext Paris, the Toronto Stock Exchange, the Tokyo Stock Exchange, and Hong Kong Exchanges and Clearing. We demonstrate that our long memory results are robust with different levels of pre-trade transparency, implying that the strategy constructed by the state of the order book is key for explaining long memories in many actual stock exchanges.