Detection of high and low states in stock market returns with MCMC method in a Markov switching model

To detect abnormal states in stock market returns, this study considers seven indices, over a 21-year period, the Dow Jones, S&P500, Nasdaq, Nikkei225, FTSE100, DAX, and CAC40. Three states are possible, namely a state of high rate of return, a state of low rate of return, both with high volatility and an intermediate state with low volatility. To determine the state of the market at each date, we study the returns using Markov chain Monte Carlo method (Metropolis–Hastings algorithm). Then at a second time, using a Cramer's coefficient, we deduce association coefficients or “correlations” among the different states of the major stock exchange markets around the world. First, the associations were globally stronger during the subprime crisis than during the dot-com bubble period. Second, among European markets Cramer's V is higher regardless of the period. Third, the associations between the Nikkei and the other market indices are systematically lower, indicating the relative disconnection of the Japanese market.     

我国股票市场指数与国际股票市场主要指数的联动性研究——基于协整分析

本文对2002—2009年中国股票市场与国际主要股票市场的每日收盘数据进行统计分析,运用相关性检验、协整检验和格兰杰因果关系检验实证了上证综合指数、深圳成分指数分别与香港恒生指数、道.琼斯指数、日经225指数、法国CAC40指数和伦敦金融时报指数之间存在相关、协整关系。进一步研究我国股票市场与国际股票市场的联动性,结果表明,国际股票市场对我国股票市场的影响越来越明显。这表明中国股票市场日趋成熟,逐渐与相对完善的国际股票市场接轨。     

Can technical oscillators outperform the buy and hold strategy?

This study compares returns from the traditional buy and hold (B&H) strategy to well-known technical oscillators applied to diverse indices leading the global market (DJI, FTSE, NK225 and TA100) during the period 2007–2012. Our aim was to establish whether technical tools can consistently achieve returns exceeding those of the B&H strategy across various financial markets. We found the relative strength index (RSI) to be the best oscillator, outperforming the DJIA, the FTSE100 and the NK225 for five of the six years examined. The only index that did better than the RSI was TA100, which outperformed all the examined oscillators. In second place was the moving average convergence/divergence (MACD) oscillator, which outperformed the NK225 B&H strategy and came in second for TA100. The results show that during bear markets the RSI and MACD generally produce better gains than the indices, while the opposite occurs during bull markets.     

Calendar anomalies in cash and stock index futures: International evidence

This paper examines calendar anomalies (day-of-the-week and monthly seasonal effects) in cash and stock index futures returns. We consider daily data from FTSE100 (UK), FTSE/ASE-20 (Greece), S&P500 (US) and Nasdaq100 (US) spot and future indexes over the period 2004–2011. We employ a Regime-Switching specification which allows us to distinguish between different regimes corresponding to high and low volatile periods. The results show differences in the seasonal patterns in cash and futures indexes due to the existence of basis risk. Calendar effects are also conditioned to the market situation. During a low volatile situation these calendar effects tend to be positive, but these effects turn negative if the market is under a high volatile period. These findings are recommended to financial risk managers dealing with futures markets.     

Investor sentiment,variance risk premium and delta-hedged gains

Delta-hedged gains are supposed to be negative and represent a volatility risk premium. Using a sample of Standard & Poor 500 index options from 2006 to 2009, this study documents two anomalies that cannot be explained by the volatility risk premium. First, delta-hedged gains are more negative for out-of-money options than for at-the-money options. Second, delta-hedged gains are significantly positive during financial crisis period. We propose a behavioural explanation in which both option prices and stock prices are affected by investor’s sentiment, but pessimistic sentiment has a greater impact on stock market than option market. This asymmetric response to pessimistic mood in turn affects the relative expensiveness of option prices.     

Pairs trading: does volatility timing matter?

Pairs trading is a dollar-neutral trading strategy. Using the components of two major stock indices, the S&P 500 and the Nikkei 225, this article deals with the performance of a pairs trading system based on various pairs selection methods (distance, stationarity, cointegration) over a 10-year period. On both markets, using a classical framework, cointegration appears superior and effective. On the U.S. market and also in Japan to a lower extent, pairs trading strategies exhibited an impressive performance during the 2008 financial crisis. Bearish periods are associated with a high level of the VIX index: the ‘investor fear gauge’. Using a modified trading system, this article examines the link between pairs trading performance and volatility/VIX timing. It is shown that for the best selection technique (cointegration), timing volatility has no economic value in a pairs trading context.     

A new test procedure for the choice of dependence structure in risk measurement: application to the US and UK stock market indices

The choice of an appropriate dependence structure in modelling multivariate risks is an important issue because different tail structure embedded in copula leads to a different capital requirement for the institution. We present how to select a well-specified dependence structure to given application data. Using a simple simulation technique, we develop a statistical test to assess the adequacy of a specific dependence structure. We examine the sensitivity of risk estimates to the choice of copulas using the S&P 500 and FTSE 100 stock indices.     

Zero Lower Bound Monetary Policy’s Effect on Financial Asset’s Correlations

We investigate the hypothesis that zero lower bound monetary policy has an effect on the correlations of financial assets. Using an event-study approach, we evaluate the impact of the zero lower bound monetary policies of the Bank of Japan, the Bank of England, and the Federal Reserve on the bond and equity markets in Japan, the UK, the US, and the Eurozone. We evaluate the bond markets using the Japanese 10-year Sovereign bond (JGB), UK 10-year bond (Gilt), US 10-year Treasury note (T-note), and German 10-year bond (Bund). For the equity markets we use the Nikkei 225, FTSE 100, S&P 500, and Euro STOXX 600 as proxies for each regional market. We also include gold and silver as control commodities. Our analyses demonstrate significant changes not only in the evaluated assets’ correlations with each other, but also in their general behavior. This has major implications for investment portfolio construction and provides useful insight for financial service regulators and the central banks themselves in monitoring the fragility and stability of the financial system.     

Time-varying relationship of news sentiment,implied volatility and stock returns

I examine the relationship between aggregate news sentiment, S&P 500 index (SPX) returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. Vector autoregression (VAR) analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take short (long) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions. The investor fear gauge (VIX) appears to perform better than news sentiment measures in forecasting future returns.     

An information theoretic analysis of stock returns,volatility and trading volumes

Information theory is used to examine the dynamic relationships between stock returns, volatility and trading volumes for S&P500 stocks. This provides an alternative approach to traditional Granger causality tests when dealing with nonlinear relationships. The article highlights the dominant role played by trading volumes in all of these relationships – even in the return–volatility relation – and finds evidence of a market level feedback effect from index returns to the return–volatility relation at the stock level. The article also produces a number of stylized facts from an information theoretic perspective.     

A change in market responses to the environmental management ranking in Japan

This article investigates stock price reactions to the release of the environmental management ranking issued by Nihon Keizai Shimbun (Nikkei newspaper) from 1998 to 2005, by using a standard event study methodology. An examination of stock price movements of the top 100 manufacturing companies reveals that stock prices during the sample period did not respond significantly to the release of the ranking within a 3-day event window. However, market responses became significantly positive after 2003, while they were significantly negative in 1999 and 2000. The stock prices of upgraded companies in particular reacted negatively before 2000, but positively after 2002. These results indicate that market reactions were changed between 2001 and 2002, when the Japanese government showed its strong commitment to environmental policies by establishing the Ministry of the Environment and signing the Kyoto Protocol, following a number of legislations.     

Analysis of contagion from the dynamic conditional correlation model with Markov Regime switching

Over the last decades, the transmissions of international financial events have been the subject of many academic studies focused on multivariate volatility models. This study evaluates the financial contagion between stock market returns. The econometric model employed, regime switching dynamic correlation (RSDC). A modification was made in the original RSDC model, the introduction of the GJR-GARCH-N and also GJR-GARCH-t models, on the equation of conditional univariate variances, thus allowing us to capture the asymmetric effects in volatility and also heavy tails. A database was built using series of indices in the United States (S&P500), the United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) from 1 February 2003 to 20 September 2012. Throughout this study the methodology is compared with those frequently found in literature, and the model RSDC with two regimes was defined as the most appropriate for the selected sample with t-Student distribution in the disturbances. The adapted RSDC model used in this article can be used to detect contagion – considering the definition of financial contagion from the World Bank called very restrictive – with the help of the empirical exercise.     

The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

Dynamic hedge ratio for stock index futures: application of threshold VECM

This study represents one of the first papers in stock-index-futures arbitrage literature to investigate the effects of arbitrage threshold on stock index futures hedging effectiveness by using threshold vector error correction model (hereafter threshold VECM). Moreover, in contrast to prior studies focusing on examining case studies involving mature stock markets, this study not only adopts US S&P 500 stock market as the sample but also adds an analysis of one emerging stock market, Hungarian BSI and examines the differences between them. Finally, this investigation employs a rolling estimation process to examine the impact of arbitrage threshold behaviours on the setting of futures hedging ratio. The empirical findings of this study are consistent with the following notions. First, arbitrage behaviour reduces co-movement between futures and spot markets and increases the volatility of both futures and spot markets. Second, this article denotes the outer regime of futures-spot market for the case of Hungarian BSI (US S&P 500) as a crisis (an unusual) condition. Moreover, arbitrage threshold behaviours make remarkable (unremarkable) shift on optimal hedge ratio between two different market regimes for the case of Hungarian BSI (US S&P 500). Finally, the framework involving regime-varying hedge ratio designed in this study provides a more efficient futures hedge ratio design for Hungarian BSI stock market, but not for US S&P 500 stock market.     

Volatility spillover and multivariate volatility impulse response analysis of GFC news events

This article applies two measures to assess spillovers across markets: the Diebold and Yilmaz’s (2012) spillover index and the Hafner and Herwartz’s (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility (RV) estimates taken from the Oxford-Man RV library, for the S&P500 and the FTSE, plus 10 years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index. Both data sets capture both the global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The Volatility Impulse Responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. We explore the impact of three different shocks, the onset of the GFC, the height of the GFC, and the impact of the ESDC. Our modelling includes leverage and asymmetric effects applying a multivariate GARCH model, and further analysis using both BEKK and diagonal BEKK (DBEKK) models. We find the impact of negative shocks is larger, but shorter in duration, in this case a difference between 3 and 6 months.     

Projection Bias and Financial Risk Tolerance

Behavioral finance theories explain "why" individuals exhibit behaviors that do not maximize expected utility. This study explores how projection bias, as explained by regret theory, may shape financial risk tolerance attitudes. The results suggest that gender, income, and stock market price changes, as measured by the NASDAQ, the Dow Jones Industrial Average, and the Standard & Poor's 500 indexes, help explain risk attitudes. Risk tolerance appears to be an elastic and changeable attitude. This research expands on the work of Shefrin [2000], who reported that recent stock market price changes exert a strong influence on risk tolerance attitudes and behaviors.     

Early warning signals using AVaRs of infinitely divisible GARCH models — evidence from stock index markets

Classical time series models have failed to properly assess the risks that are associated with large adverse stock price behaviour. This article contributes to autoregressive moving average model–GARCH (ARMA–GARCH) models with standard infinitely divisible innovations and assesses the performance of these models by comparing them with other time series models that have normal innovation. We discuss the limitations of value at risk (VaR) and aim to develop early warning signal models using average value at risk (AVaRs) based on the ARMA–GARCH model with standard infinitely divisible innovations. Empirical results for the daily Dow Jones Industrial Average Index, the England Financial Times Stock Exchange 100 Index and the Japan Nikkei 225 Index reveal that estimating AVaRs for the ARMA–GARCH model with standard infinitely divisible innovations offers an improvement over prevailing models for evaluating stock market risk exposure during periods of distress in financial markets and provides a suitable early warning signal in both extreme events and highly volatile markets.     

Forecasting volatility of futures market: the S&P 500 and FTSE 100 futures using high frequency returns and implied volatility

We show that historical volatility from high frequency returns outperforms implied volatility when standardized returns by historical volatility tends to be normally distributed. For the FTSE 100 futures, we find that historical volatility using high frequency returns outperforms implied volatility in forecasting future volatility. However, we find that implied volatility outperforms historical volatility in forecasting future volatility for the S&P 500 futures. The results also indicate that historical volatility using high frequency returns could be an unbiased forecast for the FTSE 100 futures.     

The Brexit effect: the case of UK ADR performance one year later

In an unexpected outcome, UK voters decided that it was time to exit the European Union based on the results of a vote held on 23 June 2016. Studies of the affects and implication of Brexit include a study showing that the vote was met with a negative short-term wealth effect for UK American depository receipts (ADRs). This study examines the one-year anniversary holding period returns of these ADRs along with the British Pound and the FTSE 100 to discover any lingering effects from the historical vote. Results indicate that the one-year holding period returns for the ADRs averaged 5.8% for the year while the FTSE gained 4.8%, the S&P 500 gained 15.4% and the Pound lost 13.2% of its value.     

The Availability Heuristic and Reversals Following Large Stock Price Changes

The author explores the effect of the availability heuristic on large daily stock price changes and on subsequent stock returns. He hypothesizes that if a major positive (negative) stock price move takes place on a day when the stock market index rises (falls), then its magnitude may be amplified by the availability of positive (negative) investment outcomes. In both cases, the availability heuristic may cause price overreaction to the initial company-specific shock, resulting in subsequent price reversal. In line with the hypothesis, the author documents that both positive and negative large price moves accompanied by the same-sign contemporaneous daily market returns are followed by significant reversals on the next 2 trading days and over 5- and 20-day intervals following the event, the magnitude of the reversals increasing over longer postevent windows, while large stock price changes taking place on the days when the market index moves in the opposite direction are followed by nonsignificant price drifts. The results remain robust after accounting for additional company (size, beta, historical volatility) and event-specific (stock's return and trading volume on the event day) factors, and are stronger for small and volatile stocks.