The Profitability of Moving Average Rules: Smaller Is Better in the Brazilian Stock Market

This study analyzes the effectiveness of using certain moving average rules in the most important emerging market of Latin America: Brazil. Using different MSCI indices, we find that the best performance is provided by the MSCI Brazil Small Cap Index, which tracks the small cap segment of the Brazilian stock market, as opposed to the MSCI Brazil Index which measures the performance of large and medium firms and has been the main reference for the Brazilian stock market in previous empirical evidence. Additionally, we report clear evidence of the existence of a size effect in the Brazilian stock market due to the superior performance of the index which tracks the smaller companies over those which track larger companies. These results restate the importance of in-depth knowledge of stock market patterns in order to develop correct trading strategies in each case.     

PREDICTING NEXT TRADING DAY CLOSING PRICE OF QATAR EXCHANGE INDEX USING TECHNICAL INDICATORS AND ARTIFICIAL NEURAL NETWORKS

Accurate prediction of stock market price is of great importance to many stakeholders. Artificial neural networks (ANNs) have shown robust capability in predicting stock price return, future stock price and the direction of stock market movement. The major aim of this study is to predict the next trading day closing price of the Qatar Exchange (QE) Index using historical data from 3 January 2010 to 31 December 2012. A multilayer perceptron ANN architecture was used as a prediction model with 10 market technical indicators as input variables. The experimental results indicate that ANNs are an effective modelling technique for predicting the QE Index with high accuracy, outperforming the well‐established autoregressive integrated moving average models. To the best of our knowledge, this is the first attempt to use ANNs to predict the QE Index, and its performance results are comparable to, and sometimes better than, many stock market predictions reported in the literature. The ANN model also revealed that the weighted and simple moving averages are the most important technical indicators in predicting the QE Index, and the accumulation/distribution oscillator is the least important such indicator. The analysis results also indicated that the ANNs are resilient to stock market volatility. Copyright © 2014 John Wiley & Sons, Ltd.     

Stock market prediction using evolutionary support vector machines: an application to the ASE20 index

The main motivation for this paper is to introduce a novel hybrid method for the prediction of the directional movement of financial assets with an application to the ASE20 Greek stock index. Specifically, we use an alternative computational methodology named evolutionary support vector machine (ESVM) stock predictor for modeling and trading the ASE20 Greek stock index extending the universe of the examined inputs to include autoregressive inputs and moving averages of the ASE20 index and other four financial indices. The proposed hybrid method consists of a combination of genetic algorithms with support vector machines modified to uncover effective short-term trading models and overcome the limitations of existing methods. For comparison purposes, the trading performance of the ESVM stock predictor is benchmarked with four traditional strategies (a naïve strategy, a buy and hold strategy, a moving average convergence/divergence and an autoregressive moving average model), and a multilayer perceptron neural network model. As it turns out, the proposed methodology produces a higher trading performance, even during the financial crisis period, in terms of annualized return and information ratio, while providing information about the relationship between the ASE20 index and DAX30, NIKKEI225, FTSE100 and S&P500 indices.     

An analysis of trading strategies in eleven European stock markets

Abstract

In recent years, the validity of the weak form efficient market hypothesis (EMH) has been called into question as several studies have uncovered evidence that technical trading rules have predictive ability with respect to both developed and emerging stock market indices. This study analyses the forecasting power of 2 of the most popular trading rules using index data for a selection of 11 European stock markets over the January 1991 to December 2000 period. The findings indicate that the emerging markets included in this paper are informationally inefficient; these markets displayed some degree of predictability in their share returns, although the developed markets did not. Furthermore, the results point to large differences in the performance of the rules examined; while small size filters consistently outperformed the buy-and-hold strategy in the emerging markets examined even after the consideration of transaction costs, the performance of the moving average rules was erratic and varied dramatically from market to market.     

国外高频交易的发展现状及启示

证券市场上的高频交易模式大体上分为四类:订单拆分策略、做市交易策略、定量化交易策略和其他策略。研究发现:(1)高频交易降低了买卖价差,提高了市场流动性,而并没有增加市场波动率,甚至反而可能降低了市场波动率;(2)没有发现高频交易者存在系统性抢单行为(并不排除有特定高频交易者存在此类行为);(3)学术研究认为高频交易有导致市场风险的可能性,但是事件调查大多认为高频交易不是引发市场风险的罪魁祸首。本文认为,对高频交易的监管应该注重抓住重点区别对待,以维护公平、透明、高效的市场秩序。     

Networks and equity market integration: European evidence

Deregulation, globalization, and technological developments have altered the business strategies of stock exchanges around the world. We investigate whether the adoption of network strategies by stock exchanges creates additional value in the provision of trading services. Using unbalanced panel data from all major European exchanges over the period 1996-2000, we examine the consequences of network cooperation on a number of stock market performance measures. We show that adopting a network strategy is associated with higher market capitalization, lower transaction costs, higher growth, and enhanced international stock market integration.     

Predictability of the simple technical trading rules: An out‐of‐sample test

In a true out-of-sample test based on fresh data we find no evidence that several well-known technical trading strategies predict stock markets over the period of 1987 to 2011. Our test safeguards against sample selection bias, data mining, hindsight bias, and other usual biases that may affect results in our field. We use the exact same technical trading rules that Brock, Lakonishok, and LeBaron (1992) showed to work best in their historical sample. Further analysis shows that this poor out-of-sample performance most likely is not due to the market becoming more efficient – instantaneously or gradually over time – but probably a result of bias.     

New empirical evidence on the investment success of momentum strategies based on relative stock prices

This paper provides significant extensions and tests of momentum trading strategies based on relative prices that were first explored by George and Hwang (2004). We develop new momentum strategies based on the ratio of the current stock price to each of five different reference points in past prices: 52-week high, 52-week median, 52-week low, half-year high, and 2-year high. We measure their investment performance on the basis of the Fama and French 3-Factor and Momentum Model (Carhart four-factor model), and further employ the technique of nested trading strategies to measure incremental performance. The strategy based on the ratio of current stock price to its 52-week high price is the most profitable, and its performance is robust when tested over a wide range of financial and economic factors. Our results provide strong new evidence of the investment merits of a momentum trading strategy based on the 52-week high price ratio, and add new weight to challenges to the hypothesis that the stock market is efficient in the semi-strong sense.     

模糊厌恶下股指期货风险对冲策略设计及实证分析

投资者对股指期货与现货有着不同的模糊厌恶,本文首先将此假设条件引入带交易成本的Garleanu and Pederson (2013)投资模型中,并以指数基金对冲策略为例,构建了一个股指期货动态对冲的理论模型。与非对冲策略相比,基于上述模型设计的对冲策略投资绩效更好,动态最优成交额占目标交易额的比例更小,目标成交额对收益率预测因子的敏感性更大。借助上述模型,本文选取2010年4月至2021年6月的中国ETF指数基金和股指期货数据,并以2015年9月股指期货管理措施实施为界进行区间划分,实证研究发现:(1)中国A股市场的ETF投资组合进行股指期货对冲显著提升了投资绩效,但股指期货管理会削弱该作用;(2)投资绩效改善主要来源于交易成本的下降与目标成交额因子敏感性的提升,该机制受到股指期货管理的约束;(3)与Garleanu and Pederson (2013)、Zhang et al. (2017)相比,本文对冲策略保留“抗跌”特点的同时增加了“易涨”特性。本文研究结果表明,在当前大力发展机构投资者的背景下应不断丰富股指期货、股指期权产品谱系,降低股指期货交易成本并完善持仓约束。     

Time series momentum and moving average trading rules

We compare and contrast time series momentum (TSMOM) and moving average (MA) trading rules so as to better understand the sources of their profitability. These rules are closely related; however, there are important differences. TSMOM signals occur at points that coincide with a MA direction change, whereas MA buy (sell) signals only require price to move above (below) a MA. Our empirical results show MA rules frequently give earlier signals leading to meaningful return gains. Both rules perform best outside of large stock series which may explain the puzzle of their popularity with investors, yet lack of supportive evidence in academic studies.     

限制交易政策如何影响期现关系?——对股指期货价格发现功能的实证检验

本文利用2015年中国股市大幅下跌期间,对股指期货严格限制交易政策这一独特事件前后的高频数据,研究限制交易政策对股指期货与股票市场价格引导关系的影响。利用I-S模型和分位数回归方法的实证结果表明:限制交易政策实施前,股指期货对股票市场的价格影响更强,尤其表现在价格急剧下跌时期;限制交易政策显著增加了期货市场交易成本,从而降低了期货市场的信息份额,削弱了其对股票市场的价格影响,并且改变了期货价格对现货价格“助跌强于助涨”的影响模式,增强了股指期货在价格上涨时对股票市场的影响。研究结果一方面直接量化了期货交易成本变动对其价格发现功能的负面影响,另一方面也从价格引导关系的视角提供了股市危机时期股指期货限制交易政策监管效果的实证证据。     

Trading by bank insiders before and during the 2007–2008 financial crisis

This paper sheds new light on the role bank executives played in the financial crisis. It examines whether they foresaw the poor performance of their own bank by analyzing their insider trading patterns. Insider trading during 2006 predicts stock returns during the crisis: a portfolio strategy based on insider trading information earns a risk-adjusted return of over 40% during the crisis. Further, banks with a high exposure to the housing market and banks with a low exposure exhibit different insider trading patterns starting in mid-2006, when US housing prices first decline: insiders of high-exposure banks are 20% more likely to sell stock than insiders of low-exposure banks. This pattern is more pronounced for CEOs than other insiders. However, insider trading patterns of high- and low-exposure banks do not differ before 2006. Replacing high-exposure banks by too-big-too-fail banks yields similar results. This evidence indicates that insiders of high-exposure and too-big-too-fail banks revised their assessment of their banks’ investments following the reversal in the housing market.     

Seasonality in stock returns and volatility: The Ramadan effect

Calendar anomalies in stock returns are well documented. Less obvious is the existence of seasonality in return volatility associated with moving calendar events such as the Muslim holy month of Ramadan. Using a GARCH specification and data for the Saudi Arabian stock market – now the largest stock market in the Muslim world – this paper documents a systematic pattern of decline in volatility during Ramadan, implying a predictable variation in the market price of risk. An examination of trading data shows that this anomaly appears to be consistent with a decline in trading activity during Ramadan. Evidence of systematic decline in volatility during Ramadan has significant implications for pricing of securities especially option-like products and asset allocation decisions by investors in the Islamic countries.     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

Returns to Initial Shareholders in Savings Institution Conversions: Evidence and Regulatory Implications

In this paper, stock prices for savings institutions that have converted to the stock form of organization are examined. Event-study methodology is used to focus on the returns to initial shareholders in the period immediately following initial trading. The results of the study indicate significant positive returns in savings institution conversions in the first several trading days, suggesting a one-time wealth transfer from depositors not exercising their rights to initial shareholders. The results also provide support for the efficiency of the market as the market price adjusts quickly in the first two days of trading after the public offering. Given the FHLBB's objectives, there appears to be little cause for regulatory concern although initial returns are significant.     

Trading behavior in S&P 500 index futures

This article examines the determinants of trading decisions and the performance of trader types, in the context of the E-Mini S&;P 500 futures and S&;P 500 futures markets. Speculators and small traders tend to follow positive feedback strategies while hedgers dynamically adjust positions in response to market returns. Such strategies apparently reverse during the 2008–09 financial crisis. Investor sentiment and market volatility play an important role in determining the net trading position of traders across the sample period. While all trader types are better at foreseeing market upturns, an out-of-sample test suggests that speculators and small traders have some predictive ability for short-term market returns.     

Gone fishin’: Seasonality in trading activity and asset prices

We use seasonality in stock trading activity associated with summer vacation as a source of exogenous variation to study the relationship between trading volume and expected return. Using data from 51 stock markets, we first confirm a widely held belief that stock turnover is significantly lower during the summer because market participants are on vacation. Interestingly, we find that mean stock return is also lower during the summer for countries with significant declines in trading activity. This relationship is not due to time-varying volatility. Moreover, both large and small investors trade less and the price of trading (bid-ask spread) is higher during the summer. These findings suggest that heterogeneous agent models are essential for a complete understanding of asset prices.     

市场摩擦对特质风险溢价的影响效应——基于A股主板市场的实证分析

与国外发达市场相比,我国A股主板市场的市场摩擦因素对市场微观结构和资产定价的影响更大。在防范和化解系统性风险的过程中,进一步分析市场摩擦如何作用于特质风险定价效应的问题具有重要的理论和现实意义。本文通过采用多维市场摩擦指标来代理信息不对称、交易成本、买卖限制、卖空限制、风险对冲和外部冲击,检验中国股市特质风险和预期收益率的关系,并判断出市场摩擦因素间的差异性影响机制。回归发现,市场摩擦和特质风险因子(特质波动率和特质偏度)都具有定价效应。各维度市场摩擦因素降低了股票流动性,进而增强了特质波动率的负向定价效应,部分解释了“特质波动率之谜”,但市场摩擦对特质偏度因子溢价的影响较为微弱。同时,基于特质波动率和特质偏度因子的投资策略能够产生超越CAPM、三因子和五因子模型的绝对收益,并印证了市场摩擦对特质风险因子绝对收益的影响作用。     

Short-term Dynamics in the Cyprus Stock Exchange

Abstract

This paper investigates the short-term dynamics of stock returns in an emerging stock market namely, the Cyprus Stock Exchange (CYSE). Stock returns are modelled as conditionally heteroscedastic processes with time-dependent serial correlation. The conditional variance follows an EGARCH process, while for the conditional mean three nonlinear specifications are tested, namely: (a) the LeBaron exponential autoregressive model; (b) the Sentana and Wadhwani positive feedback trading model; and finally (c) a model that nests both (a) and (b). There is an inverse relationship between volatility and autocorrelation consistent with the findings from several other stock markets, including the US. This pattern could be the manifestation of a certain form of noise trading namely positive feedback trading or, momentum trading strategies. There is little evidence that market declines are followed with higher volatility than market advances, the so-called ‘leverage effect’, that has been observed in almost all developed stock markets. In out of sample forecasts, the nonlinear specifications provide better results in terms of forecasting both first and second moments of the distribution of returns.     

Momentum strategies and stock returns: Chinese evidence

This paper investigates the profitability of momentum investment strategies for equities listed in the Shanghai Stock Exchange. We also investigate the role of trading volume to examine whether there is any relationship between stock returns and past trading volume for Chinese equities. We find evidence of substantial momentum profits during the period 1995 to 2005 and that momentum is a pervasive feature of stock returns for the market investigated in this paper.Our findings suggest that investors can generate superior returns by investing in strategies unrelated to market movements. We also investigate the potential of past volume to explain momentum profits, and find no strong link between past volume and momentum profits. Our findings also show a strong momentum effect around earnings announcements but the magnitude of these returns is small in relation to the average monthly returns earned in the early months following portfolio formation.