Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.     

Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using Pacific Basin stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property, and that the asymmetric reverting property of stock returns is exploitable in generating profitable buy and sell signals for technical trading rules. We show that the positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric dynamics of stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical analysis.     

Is asymmetric mean-reverting pattern in stock returns systematic? Evidence from Pacific-basin markets in the short-horizon

This paper applies asymmetric nonlinear smooth transition generalized autoregressive conditional heteroskedasticity (ANST-GARCH) models to the analysis of mean-reversion and time-varying volatility in weekly index returns of the stock markets of nine countries in the Pacific-basin. It finds that the returns exhibit an asymmetric pattern of return reversals, viz., on average, a negative return reverts more quickly, with a greater magnitude, to a positive return than a positive return reverting to a negative one. The asymmetric pattern of return reversals is directly associated with the unequal pricing behavior on the part of investors. Following a negative return shock, investors do not appear to require any additional premium to the leverage effect; instead they actually neutralize the risk in the form of a reduced premium! The reduction in risk premium causes not only the current stock price to rise but also the realized negative return to revert faster with a greater magnitude.     

Asymmetric reverting behavior of short-horizon stock returns: An evidence of stock market overreaction

This paper investigates the uneven mean reverting pattern of monthly return indexes of the NYSE, AMEX and NASDAQ, using asymmetric non-linear smooth-transition (ANST) GARCH models. It also evaluates the extent to which time-varying volatility in the index returns support the stock market overreaction hypothesis. The models illuminate patterns of asymmetric mean reversion and risk decimation. Between 1926:01 and l997:12, not only did negative returns reverse to positive returns quicker than positive returns reverted to negative ones, but negative returns, in fact, reduced risk premiums from predictable high volatility. The findings support the market overreaction hypotheses. The asymmetry is due to the mispricing behavior on the part of investors who overreact to certain market news. The findings also corroborate arguments for the “contrarian” portfolio strategy.     

Asymmetric mean-reversion and contrarian profits: ANST-GARCH approach

This paper investigates the time-series evidence of asymmetric reverting patterns in stock returns that is attributable to “contrarian profitability.” Using asymmetric nonlinear smooth-transition (ANST) GARCH(M) models, we find that, for monthly excess returns of US market indexes over the period of 1926:01–1997:12, negative returns on average reverted more quickly, with a greater reverting magnitude, to positive returns than positive returns revert to negative returns. The results are quite consistent when the models are implemented not only for the different sample periods, such as 1926:01–1987:09 and 1947:01–1997:12, but also for portfolios with different characteristics, such as different firm-size portfolios and Fama–French risk-adjusted factor portfolios. We interpret the asymmetrical reversion as evidence of stock market overreaction.     

Asymmetric mean reversion of Bitcoin price returns

Non-linearity is characterised by an asymmetric mean-reverting property, which has been found to be inherent in the short-term return dynamics of stocks. In this paper, we explore as to whether cryptocurrency returns, as represented by Bitcoin, exhibit similar asymmetric reverting patterns for minutely, hourly, daily and weekly returns between June 2010 and February 2018. We identify several differences in the behaviour of Bitcoin price returns in the pre- and post-$1000 sub-periods and evidence of asymmetric reverting patterns in the Bitcoin price returns under all the ANAR models employed, regardless of the data frequency considered. We also present evidence indicating stronger reverting behaviour of negative price returns in terms of both reverting speed and magnitude compared to positive returns and evidence of positive serial correlation with prior positive price returns. Finally, we also investigated asymmetries in Bitcoin price return series' persistence by employing higher order ANAR models, finding evidence of a higher persistence of positive returns than negative returns, a result that further supports the existence of asymmetric reverting behaviour in the Bitcoin price returns.     

Asymmetric return dynamics and technical trading strategies

We investigate the profitability of technical trading strategies based on an asymmetric reverting property of stock returns. We identify an asymmetry in return dynamics for daily returns on the S&P 500 index. Return dynamics evolve along a positive (negative) unconditional mean after a prior positive (negative) return. The trading strategies based on this asymmetry generate a positive return for buy signals, a negative return for sell signals, and a positive return for the spread between buy and sell signals. Our results imply that the observed asymmetry in return dynamics is the main source of profitability for the implied strategies, thereby corroborating arguments for the usefulness of technical trading strategies.     

Asymmetric Mean Reversion in European Interest Rates: A Two-factor Model

Abstract

This paper tests for asymmetric mean reversion in European short-term interest rates using a combination of the interest rate models introduced by Longstaff and Schwartz (Longstaff, F.A., Schwarts, E.S. (1992) Interest rate volatility and the ferm structure: A two factor general equilibrium model, Journal of Finance, 48, pp. 1259–1282.) and Bali (Bali, T. (2000) Testing the empirical performance of stochastic volatility models of the short-term interest rates, Journal of Financial and Quantitative Analysis, 35, pp. 191–215.). Using weekly rates for France, Germany and the United Kingdom, it is found that short-term rates follow in all instances asymmetric mean reverting processes. Specifically, interest rates exhibit non-stationary behavior following rate increases, but they are strongly mean reverting following rate decreases. The mean reverting component is statistically and economically stronger thus offsetting non-stationarity. Volatility depends on past innovations past volatility and the level of interest rates. With respect to past innovations volatility is asymmetric rising more in response to positive innovations. This is exactly opposite to the asymmetry found in stock returns.     

A behavioural explanation to the asymmetric volatility phenomenon: Evidence from market volatility index

This study examines how the behavioural explanations, in particular loss aversion, can be used to explain the asymmetric volatility phenomenon by investigating the relationship between stock market returns and changes in investor perceptions of risk measured by the volatility index. We study the behaviour of India volatility index vis‐à‐vis Hong Kong, Australia and UK volatility index, and provide a comprehensive comparative analysis. Using Bai‐Perron test, we identify structural breaks and volatility regimes in the time series of volatility index, and investigate the volatility index‐return relation during high, medium and low volatility periods. Regardless of volatility regimes, we find that volatility index moves in opposite direction in response to stock index returns, and contemporaneous return is the most dominating across the four markets. The negative relation is strongest for UK followed by Australia, Hong Kong and India. Second, volatility index reacts significantly different to positive and negative returns; negative return has higher impact on changes in volatility index than positive return across the markets over full‐sample and sub‐sample periods. The asymmetric effect is stronger in low volatility regime than in high and medium volatility periods for all the markets except UK. The strength of asymmetric effect is strongest for Hong Kong and weakest for India. Finally, negative returns have exponentially increasing effect and positive returns have exponentially decreasing effect on the changes in volatility index.     

The bivariate GARCH approach to investigating the relation between stock returns,trading volume,and return volatility

We use a bivariate GJR-GARCH model to investigate simultaneously the contemporaneous and causal relations between trading volume and stock returns and the causal relation between trading volume and return volatility in a one-step estimation procedure, which leads to the more efficient estimates and is more consistent with finance theory. We apply our approach to ten Asian stock markets: Hong Kong, Japan, Korea, Singapore, Taiwan, China, Indonesia, Malaysia, the Philippines, and Thailand. Our major findings are as follows. First, the contemporaneous relation between stock returns and trading volume and the causal relation from stock returns and trading volume are significant and robust across all sample stock markets. Second, there is a positive bi-directional causality between stock returns and trading volume in Taiwan and China and that between trading volume and return volatility in Japan, Korea, Singapore, and Taiwan. Third, there exists a positive contemporaneous relation between trading volume and return volatility in Hong Kong, Korea, Singapore, China, Indonesia, and Thailand, but a negative one in Japan and Taiwan. Fourth, we find a significant asymmetric effect on return and volume volatilities in all sample countries and in Korea and Thailand, respectively.     

Failed takeovers, methods of payment, and bidder returns

This study documents bidding-firm stock returns upon the announcement of takeover terminations. On average, bidding firms that offer common stock experience a positive abnormal return, and firms that offer cash experience a negative abnormal return. The positive performance is primarily driven by bidders initiating the takeover termination. Commonstock-financed bidders earn a return not significantly different from that earned by cashfinanced bidders when terminations are initiated by the target firm. The results are consistent with the asymmetric information hypothesis, that the decision not to issue common stock conveys favorable information to the market. In addition, bidder returns at takeover termination are positively related to the amount of undistributed cash flow, supporting the free cash flow hypothesis.     

Asymmetric risk premium in value and growth stocks

There are two competing explanations for the existence of a value premium, a rational market risk explanation, whereby value stocks are inherently more risky than growth stocks, and a market over-reaction hypothesis, where agents overstate future returns on growth stock. Using asymmetric GARCH-M models this paper tests the predictions of the two hypotheses. Specifically, examining whether returns exhibit a positive (negative) risk premium resulting from a negative (positive) shock and the relative size of any premium. The results of the paper suggest that following a shock, volatility and expected future volatility are heightened, leading to a rise in required rates of return which depresses current prices. Further, these effects are heightened for value stock over growth stock and for negative shocks over positive shocks. Thus, in support of the rational risk interpretation, with a volatility feedback explanation for predictive volatility asymmetry.     

The negative news threshold—An explanation for negative skewness in stock returns

Abstract

A vast literature documents negative skewness in stock index return distributions on several markets. In this paper the issue of negative skewness is approached from a different angle to previous studies by combining the Trueman's 1997 model of management disclosure practices with symmetric market responses in order to explain negative skewness in stock returns. Empirical tests reveal that returns for days when non-scheduled news items are disclosed are the source of negative skewness in stock returns, as predicted. These findings suggest that negative skewness in stock returns is induced by asymmetries in the news disclosure policies of firm management. Furthermore, it is found that the returns are negatively skewed only for non-scheduled firm-specific news disclosures for firms where the management is compensated with stock options.     

Asymmetry in spillover effects: Evidence for international stock index futures markets

The paper investigates the asymmetry in return and volatility spillovers across futures markets with non-overlapping stock exchange trading hours. The transmission of positive and negative return and volatility shocks is analysed for 104 channels of information conveyance identified by combining 9 developed and 11 emerging markets in markets pairs with non-overlapping trading hours. The asymmetric causality test is employed to daily stock index futures returns and volatilities for the period from 03 October 2010 to 03 October 2014. The paper sheds light on the relatively little explored concept of asymmetry in return and volatility spillovers across markets, providing novel evidence on stabilizing and destabilizing spillover effects.     

Personal Taxation and Investment Incentives in a Small Open Economy

A simple portfolio model is used to investigate the effects of personal taxes on real investment incentives in a small open economy with large and small firms. When shares in large firms can be traded internationally and their rate of return is exogenously determined on international equity markets, a tax on the return on riskless bonds will induce a portfolio shift from bonds to shares in large firms. This shift reduces the impact of the bond tax on the required rate of return on shares in domestically owned small firms, provided that returns on shares in small and large firms are positively correlated. The total impact of the bond tax may even change from a negative to a counter-intuitive positive one if the “beta” between the returns on small and large firms is above unity. A personal tax on equity returns does in general have an ambiguous impact on the pre-tax rate of return requirement of domestically owned firms. An exogenous rate of return on large company shares is shown to enhance the possibility for the equity tax to reduce the required pre-tax rate of return in small domestic firms. A sufficient condition for a negative relationship is again that the “beta” between the returns in small and large firms is above unity. This revised version was published online in July 2006 with corrections to the Cover Date.     

Alternatives to the normal model of stock returns: Gaussian mixture, generalised logF and generalised hyperbolic models

Simple parametric models of the marginal distribution of stock returns are an essential building block in many areas of applied finance. Even though it is well known that the normal distribution fails to represent most of the “stylised” facts characterising return distributions, it still dominates much of the applied work in finance. Using monthly S&P 500 stock index returns (1871–2005) as well as daily returns (2001–2005), we investigate the viability of three alternative parametric families to represent both the stylised and empirical facts: the generalised hyperbolic distribution, the generalised logF distribution, and finite mixtures of Gaussians. For monthly return data, all three alternatives give reasonable fits for all sub-periods. However, the generalised hyperbolic distribution fails to describe some features of the marginal distributions in some sub-periods. The daily return data are much more symmetric and expose another problem for all three distributions: the parameters describing the behaviour of the tails also influence the scale so that simpler alternatives or restricted parameterisations are called for.      

Overreaction in the thrift IPO aftermarket

We study the initial returns and long-run performance of a unique sample of thrifts that have recently converted from mutual to stock form. In addition to a full claim on all IPO proceeds, new investors in a converted thrift also receive a claim on all pre-conversion market value at no cost. Thus, the average firm in our sample has a degree of underpricing automatically built into its offer price. We find that after removing the large initial returns, cumulative excess returns for the firms in our sample are positive for 12 months after the IPO. Beginning in the second year after the IPO, the average firm in our sample undergoes a significant price correction that lasts approximately 18 months and which produces negative cumulative abnormal returns for up to 5 years post-issue. Differences in risk-adjusted returns also indicate negative long-run returns, with poor performance concentrated in the second and third years following the IPO. The return differences are most pronounced among the small thrifts in our sample, and are broadly consistent with investor overreaction at the time of the IPO that continues for 6–12 months before prices begin reverting back to fundamental value.     

How asymmetric is U.S. stock market volatility?

This paper explores differences in the impact of equally large positive and negative surprise return shocks in the aggregate U.S. stock market on: (1) the volatility predictions of asymmetric time-series models, (2) implied volatility, and (3) realized volatility. Following large negative surprise return shocks, both asymmetric time-series models (such as the EGARCH and GJR models) and implied volatility predict an increase in volatility and, consistent with this, ex post realized volatility normally rises as predicted. Following large positive return shocks, asymmetric time-series models predict an increase in volatility (albeit a much smaller increase than following a negative shock of the same magnitude), but both implied and realized volatilities generally fall sharply. While asymmetric time-series models predict a decline in volatility following near-zero returns, both implied and realized volatility are normally little changed from levels observed prior to the stable market. The reasons for the differences are explored.     

Nonlinear mean reversion in stock prices

This paper provides new evidence on the time-series predictability of stock market returns by introducing a test of nonlinear mean reversion. The performance of extreme daily returns is evaluated in terms of their power to predict short- and long-horizon returns on various stock market indices and size portfolios. The paper shows that the speed of mean reversion is significantly higher during the large falls of the market. The parameter estimates indicate a negative and significant relation between the monthly portfolio returns and the extreme daily returns observed over the past one to eight months. Specifically, in a quarter in which the minimum daily return is −2% the expected excess return is 37 basis points higher than in a month in which the minimum return is only −1%. This result holds for the value-weighted and equal-weighted stock market indices and for each of the size decile portfolios. The findings are also robust to different sample periods, different indices, and investment horizons.