Search results

The authors analyse the nature of nonlinear long-run causal dynamics between VIX futures and exchange-traded products (ETPs).

Nonlinear long-run causal relations between daily price movements in ETPs and futures are established through a Markov switching vector error correction model (MS-VECM).

The authors observe time variation in causality with the volatility of volatility. In particular, demand pressures for VIX ETNs and futures can change in different regimes. The authors observe two regimes where regime 1 is classified as low-mean low-volatility, while regime 2 is classified as high-mean high-volatility. The convergence to the long-run equilibrium in the low-mean low-volatility regime is faster than the high-mean high-volatility regime. The nature of the time varying lead lag relations demonstrates the opportunities for arbitrage.

The linear causal relations between VXX and VIX futures are well established, with leads and lags generally found to be short-lived with arbitrage relations holding. The authors go further to capture the time-varying causal relationships through a Markovian process. The authors establish the nonlinear causal relations between inverse and leveraged products where causal relations are not yet documented.

The purpose of this paper is to bridge the gap between the existing theoretical and empirical studies by examining the asymmetric return–volume relationship. Indeed, the authors aim to shed light on the return–volume linkages for French-listed small and medium-sized enterprises (SMEs) compared to blue chips across different market regimes.

This study includes both large capitalizations included in the CAC 40 index and listed SMEs included in the Euronext Growth All Share index. The Markov-switching (MS) approach is applied to understand the asymmetric relationship between trading volume and stock returns. The study investigates also the causal impact between stock returns and trading volume using regime-dependent Granger causality tests.

Asymmetric contemporaneous and lagged relationships between stock returns and trading volume are found for both large capitalizations and listed SMEs. However, the causality investigation reveals some differences between large capitalizations and SMEs. Indeed, causal relationships depend on market conditions and the size of the market.

This paper explains the asymmetric return–volume relationship for both large capitalizations and listed SMEs by incorporating several psychological biases, such as the disposition effect, investor overconfidence and self-attribution bias. Future research needs to deepen the analysis especially for SMEs as most of the literature focuses on large capitalizations.

This empirical study has fundamental implications for portfolio management. The findings provide a deeper understanding of how trading activity impact current returns and vice versa. The authors’ results constitute an important input to build and control trading strategies.

This paper fills the literature gap on the asymmetric return–volume relationship across different regimes. To the best of the authors’ knowledge, the present study is the first empirical attempt to test the asymmetric return–volume relationship for listed SMEs by using an accurate MS framework.

Risk and return are the most important components in the financial and investment world and the existence of a better balance between them with the goal of the best solution for investing in different assets has always been studied and discussed by researchers. For this purpose in this study introduced the Hybrid Balanced Justified Treynor ratio (HBJTR) criterion.

This study introduced the HBJTR criterion, which has three major attributes, including combination of both the frequency and severity of the risk using Markov regime switching model which was modeled on the Justified Beta (Jßi). The second is the merger of data of both the cycles of boom and recession, which was modeled on the Hybrid Justified Treynor Ratio (HJTR). The third was the balancing act in two periods of boom and recession, which was introduced on the HBJTR model.

Based on a weighted averaging of the Justified Treynor ratio of both the cycles of boom and recession, which was introduced by the HJTR term in this study, the superiority in the first grade related to the two indexes were sugar index (0.0096) and insurance index (0.0053). Finally, using the final model in this study, namely HBJTR, the overall advantage was the defensive index, i.e. the insurance index of 1.23.

In other words, the HBJTRi criterion consists of three steps: first, the Justified Beta (Jßi) and Justified Treynor ratio of each index using two regimes of Markov switching model were calculated for each of the cycles of boom and recession separately according to formulas 8 and 9. In the second step, the weighted average was taken from both Justified Treynor ratios of boom and recession cycles, which was called the HJTR. In the third step, to calculate the HBJTR criterion

This chapter considers the relationship between stock market autocorrelation and (i) the presence of international investors which is proxied by the level of capital market integration and (ii) stock market volatility. Drawing from a sample of nine Asia-Pacific stock indices, significant evidence of a relationship between the presence of international investors and the level of stock market autocorrelation is found. This evidence is consistent with the view that international investors are positive feedback traders. Robustness testing of this model suggests that the trading strategy of international investors changed as a result of the Asian currency crisis. The evidence for the role of volatility in explaining autocorrelation is, however, is generally weak and varies across the sample countries.

The purpose of this paper is to investigate linkages between households’ expectations and credit markets in the housing crisis.

In the Markov-switching framework, the sample period is classified into high- and low-impact regimes based on impacts of expectations on default rates, and the good-time-to-buy (GTTB) index is chosen to proxy for expectations toward the housing-market dynamics.

The results suggest that in high-impact regimes, optimistic expectations are substantially associated with lower defaults for all default rates analyzed, and second mortgage defaults are more sensitive to households’ expectations than first mortgage defaults. In low-impact regimes, the GTTB index significantly influences composite and first-mortgage default rates, but its impact is insignificant for second mortgage and bankcard default rates.

The results provide compelling evidence that households’ expectations play more important roles in credit markets in turmoil periods.

This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour.

By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles.

This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles.

This paper fills the literature gap by establishing the cyclical behaviour of stock markets.

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modeling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present study focuses on the latter device. Some possible setups for identification via heteroskedasticity are reviewed and their potential and limitations are discussed. Two detailed examples are considered to illustrate the approach.

The purpose of this study is to determine if the Brazilian electricity sector is differently affected by the characteristics of the content in the regulatory legislation.

For better robustness of the research, the authors analyzed the period from 1995 to 2013, totaling 4,510 observations. To this end, the selection of regulatory legislation was conducted through Markov regime switching. To identify the characteristics of profile and intensity of regulatory content in each legislation, we applied the content analysis technique.

The main findings of this study position this research in the vanguard regarding other research in the area by showing that all regulatory measures whose characteristics denote market profile of strong and medium intensity affect the risk of electric utilities in Brazil. As contribution from this research, it can be hypothesized that for provisional measures/laws events, the profile and intensity of regulatory content are relevant and have different impact on the risk of stocks and, therefore, should be considered in the design and development of public policies.

The paper investigates by means of content analysis, the profile and intensity characteristics of the content present in the regulatory legislation and to present the impact of these characteristics on the risk of the electric energy Sector in Brazil. The research results showed that it is not all regulatory events that impact the stock market. Therefore, regulatory risk estimates must consider the intensity and scope of each legislation, given that legislation with a higher regulatory content that seeks to modify the sector’s operating rules more deeply tends to have a greater impact on the risk of companies that operate in regulated sectors. Therefore, the paper shows originality and evolution for the researchers in the area, with new and significant information.

This study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural land prices is important when considering sound investment decisions.

This study applies threshold autoregression to model agricultural land prices. The data includes quarterly observations on Finnish agricultural land prices.

The study shows that Finnish agricultural land prices exhibit regime-switching behaviour when using past changes in prices as a threshold variable. The threshold autoregressive model not only fits the data better but also improves the accuracy of price forecasts compared to the linear autoregressive model.

The results show that a sharp fall in agricultural land prices temporarily changes the regular development of prices. This information significantly improves the accuracy of price predictions.

This paper aims to study the asset pricing implications for stock and bond markets in a long-run risks (LRR) model with regime shifts. This general equilibrium framework can not only generate sign-switching stock-bond correlations and bond risk premium, but also quantitatively reproduce various other salient empirical features in stock and bond markets, including time-varying equity and bond return premia, regime shifts in real and nominal yield curves, the violation of the expectations hypothesis of bond returns.

The researchers study the joint determinants of stock and bond returns in a LRR model framework with regime shifts in consumption and inflation dynamics. In particular, the means, volatilities, and the correlation structure between consumption growth and inflation are regime-dependent.

The model shows that the term structure of interest rates and stock-bond correlation are intimately related to business cycles, while LRR play a more important role in accounting for high equity premium than do business cycle risks.

This paper studies the joint determinants of stock and bond returns in a Bansal and Yaron (2004) type of LRR framework. This rational expectations general equilibrium framework can (1) jointly match the dynamics of consumption, inflation and cash flow; (2) generate time-varying and sign-switching stock and bond correlations, as well as generating sign-switching bond risk premium; and (3) coherently explain another long list of salient empirical features in stock and bond markets, including time-varying equity and bond return premia, regime shifts in real and nominal yield curves, the violation of the expectations hypothesis of bond returns.