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.     

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.     

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.     

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.     

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.     

Mean Reversion of Short-Horizon Stock Returns: Asymmetry Property

In this paper, we explore nonlinearity inherent in short-horizon return dynamics, which is characterized by an asymmetric mean-reverting property. Over the period of 1962:07–2003:12, both daily and weekly returns of three market indexes and individual stock returns exhibit a strong asymmetric reverting pattern in which a negative return reverts more quickly, with a greater reverting magnitude, than positive returns revert to negative returns. The observed asymmetric reverting pattern is not justified under the positive relationship between future volatility and risk premium, which is a key presumption in the time-varying rational expectation hypothesis. The asymmetric reverting behavior of stock returns explored by this paper corroborates the argument for the relative performance of “winner' and “loser' stocks that has been documented by contrarian literature. JEL Classification: 14, C40, C51     

Earnings Surprises,Growth Expectations,and Stock Returns or Don't Let an Earnings Torpedo Sink Your Portfolio

We provide new evidence that the inferior returns to growth stocks relative to value stocks are the result of expectational errors about future earnings performance. Our evidence demonstrates that growth stocks exhibit an asymmetric response to earnings surprises. We show that while growth stocks are at least as likely to announce negative earnings surprises as positive earnings surprises, they exhibit an asymmetrically large negative price response to negative earnings surprises. After controlling for this asymmetric price response, we find no remaining evidence of a return differential between growth and value stocks. We conclude that the inferior return to growth stocks is attributable to overoptimistic expectational errors that are corrected through subsequent negative earnings surprises.     

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 Volume‐Return Relation and Concentrated Trading in LIFFE Futures

This study demonstrates that intraday volume and return on LIFFE interest rate and currency futures exhibit an asymmetric volume‐return relationship characterised by significantly larger volume associated with negative returns than with non‐negative returns. This finding is unlike the stylised asymmetric relation often observed in equity markets, where the volume on price rise is larger than the volume on price decline. The asymmetric relationship in LIFFE futures is also found to be dynamic as the direction of asymmetry can reverse during the day. It has been argued in the past that a costly short sale restriction that requires a higher transaction cost on a short position than on a long position is responsible for the asymmetric effect in equity markets. Since such a restriction is absent in futures markets, they should not exhibit any asymmetric volume behaviour. Based on the results of this research, the costly short sale hypothesis is rejected. An alternative explanation of the asymmetric relation observed in futures is presented based on recent information models that take into consideration asymmetrically‐informed traders, their dispersion of beliefs, quality and quantity of the information signal, and how the traders process it. The paper also confirms a strong U‐shape trading pattern in 15‐minute volume, but no such pattern is identified in intraday returns.     

Tail dependence between Bitcoin and financial assets: Evidence from a quantile cross-spectral approach

Using daily price data for Bitcoin and 10 representative financial assets from the stock, commodity, gold, foreign exchange and bond markets from 2011 to 2019, we study the tail dependence between returns for Bitcoin and these other financial assets using the novel “quantile cross-spectral dependence” approach of Baruník and Kley (2019). We find evidence of right-tail dependence between Bitcoin returns and the S&P 500 in the long term and weaker normal return dependence between Bitcoin and the US Dollar (USD)–Euro (EUR) foreign exchange rate in the monthly term. In addition, we note that the dependence between Bitcoin and commodity as well as oil, and silver decrease the most within their respective medium return quantiles over the short term. Furthermore, we document a one-way causality running from each of the financial assets considered to Bitcoin in different quantiles of the return distribution. In sum, our findings support the notion that Bitcoin can provide financial diversification in certain return quantiles (i.e., bear, normal, or bull asset conditions) and time frequencies (i.e., short, medium, or long term investment horizon).     

Oil and stock market activity when prices go up and down: the case of the oil and gas industry

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns associated with negative changes in oil prices are higher than that associated with positive changes in oil prices. Stock risk measured by market beta is influenced more due to oil price decreases than due to oil price increases. On the other hand, oil risk exposures (oil betas) and return variances are more influenced by oil price increases than oil price decreases. The results of our study indicate that oil and gas firm returns, market betas, oil betas, return variances respond asymmetrically to oil price changes. We also find that relative changes in oil prices along with firm-specific factors such as firm size, ROA, leverage, market-to-book ratio (MBR) are important in determining the effects of oil price changes on oil and gas firms’ returns, risks, and trading volumes.     

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 EMPIRICAL RELATIONSHIP BETWEEN TRADING VOLUME,RETURNS AND VOLATILITY

This paper presents an empirical analysis of the relationship between trading volume, returns and volatility in the Australian stock market. The initial analysis centres upon the volume-price change relationship. The relationship between trading volume and returns, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market. This finding also provides basic support for a positive relationship between trading volume and volatility. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for non-negative returns, thereby supporting an asymmetric relationship which is hypothesised to exist because of differential costs of taking long and short positions. Analysis at the individual stock level shows weaker support for the relationship. A second related hypothesis is tested in which the formation of returns is conditional upon information arrival which similarly affects trading volume. The hypothesis is tested by using the US overnight return to proxy for expected “news” and trading volume to proxy for news arrival during the day. The results show a reduction in the significance and magnitude of persistence in volatility and hence are consistent with explaining non-normality in returns (and ARCH effects) through the rate of arrival of information. The findings in this paper help explain how returns are generated and have implications for inferring return behaviour from trading volume data.     

Individual Investor Trading and Stock Returns

This paper investigates the dynamic relation between net individual investor trading and short‐horizon returns for a large cross‐section of NYSE stocks. The evidence indicates that individuals tend to buy stocks following declines in the previous month and sell following price increases. We document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell, which we show is distinct from the previously shown past return or volume effects. The patterns we document are consistent with the notion that risk‐averse individuals provide liquidity to meet institutional demand for immediacy.     

Conditional risk–return relationship in a time-varying beta model

We investigate the asymmetric risk–return relationship in a time-varying beta CAPM. A state space model is established and estimated by the Adaptive Least Squares with Kalman foundations proposed by McCulloch. Using S&P 500 daily data from 1987:11–2003:12, we find a positive risk–return relationship in the up market (positive market excess returns) and a negative relationship in the down market (negative market excess returns). This supports the argument of Pettengill et al., who use a constant beta model. However, our model outperforms theirs by eliminating the unexplained returns and improving the accuracy of the estimated risk price.     

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.     

Insights from bitcoin trading

We examine commonality in returns and volume for Bitcoin–fiat currency pairs, each trading in a country with a single time zone. Bitcoin has substantial volume and obeys the theory related to commonality, liquidity, and price discovery. We find evidence that one common factor explains 68% of the variance in hourly volume. Though trading is higher on weekdays, there is substantial weekend trading, reflecting high retail participation. Volume is higher on exchanges during local working hours, as seen in forex markets, supporting the view that trading patterns depend on the location of trade rather than the location of the asset traded.     

Asymmetric Price and Volatility Adjustments in Emerging Asian Stock Markets

This paper tests the hypothesis that stock returns in emerging stock markets adjust asymmetrically to past information. The evidence suggests that both the conditional mean and the conditional variance respond asymmetrically to past information. In agreement with studies dealing with developed stock markets, the conditional variance is an asymmetrical function of past innovations, rising proportionately more during market declines. More importantly, the conditional mean is also an asymmetrical function of past returns. Specifically, positive past returns are more persistent than negative past returns of an equal magnitude. This behaviour is consistent with an asymmetric partial adjustment price model where news suggesting overpricing (negative returns) are incorporated faster into current prices than news suggesting underpricing (positive returns). Furthermore, the asymmetric adjustment of prices to past information could be partially responsible for the asymmetries in the conditional variance if the degree of adjustment and the level of volatility are positively related.     

Does Bitcoin still own the dominant power? An intraday analysis

The study investigates the intraday dynamics and price patterns of the primary cryptocurrencies. The Granger Mackey-Glass (M-G) model is employed to examine the asymmetric and nonlinear dynamic interactions in the first moment using positive and negative returns. The bivariate BEKK-GARCH model is applied to identify cross-market volatility shocks and volatility transmissions in the cryptocurrency market. The intra-cryptocurrency market analysis reveals that Bitcoin contains predictive information that can nonlinearly forecast the performance of other digital currencies when cryptocurrency prices either are rising or declining. The dominant power of Bitcoin is not dismissed using the intraday data. Further, Bitcoin's intraday lagged shocks and volatility induces more rapid and destabilizing effects on the conditional volatility of other currencies than each of the other currencies does on BTC's conditional volatility. The virtual currency markets are dynamically correlated and integrated through first and second-moment spillovers.     

Intraday Returns and the Frequency of Trading at the Ask on the Sydney Futures Exchange: A Research Note

This article documents and provides explanations for intraday patterns in returns for the Share Price Index (SPI) futures contract traded on the Sydney Futures Exchange (SFE). Consistent with overseas futures markets research, a positive and significant overnight return is documented. Unlike overseas futures markets, we find little evidence of an end of day price rise. Our evidence suggests that overnight returns for the SPI contract are largely driven by the way returns are typically measured, which ignores the fact that there is a significantly greater frequency of sellers at the market close and buyers at the start of the day. These patterns are consistent with hedging behaviour by futures traders with long positions in the underlying stock.