Optimal pair-trading strategy over long/short/square positions—empirical study

Suzuki [Automatica, 2016, 67, 33–45] solves the optimal, finitely iterative, three-regime switching problem for investing in a mean-reverting asset that follows an Ornstein–Uhlenbeck price process and find explicit solutions. The remarkable feature of this model is that the investor can explicitly take either a long, short or square position and can switch the position, with transaction costs, during the investment period. We run empirical simulations of such multiple-regime switching models. There are very few such attempts in the existing literature because it is difficult to find, first, an explicit solution to the problem and second, appropriate financial assets that follow the artificial stochastic process required by the mathematical model. According to the Monte Carlo simulations of the optimal pair-trading strategy, the mean daily Sharp ratio is more than 2.3, whereas the mean Sharp ratio for the historical simulation of the ‘stub’ pairs (combinations of parent/subsidiary companies) is 0.6886. We believe that the results obtained from performing the empirical simulations are remarkable and consider that the optimal switching strategy of the rigorous mathematical model is applicable to businesses in the real world. For the reference many pseudo-program codes are added, which can help to replicate the optimal trading strategies.     

Carbon Disclosure,Financial Transparency,and Agency Cost: Evidence from Chinese Manufacturing Listed Companies

Given the constraints on carbon emissions due to their impact on global warming, carbon disclosure has become an important way to deliver signals to the market. We examine the benefits associated with carbon disclosure from the standpoint of corporate social responsibility (CSR) for China’s manufacturing industries from 2010 to 2014. We divide corporations into heavily polluting and non-heavily polluting groups in order to control the industry factor. Based on the Principal-Agent Theory, we empirically test the relationship between carbon disclosure and financial transparency, and we evaluate the effect of carbon disclosure on agency costs and operations. Our results highlight that carbon disclosure is negatively associated with agency costs. However, we do not find enough evidence to prove what role financial transparency plays in the relationship between carbon disclosure and agency cost. Therefore, the influence of financial transparency as a mechanism is not yet clear. This study provides a way to look at the intentions of firms that disclose carbon information, and it also enhances the literature on carbon disclosure and agency costs in China based on Chinese data.     

Measuring the liquidity part of volume

Based on the concept that the presence of liquidity frictions can increase the daily traded volume, we develop an extended version of the mixture of distribution hypothesis model (MDH) along the lines of Tauchen and Pitts (1983) to measure the liquidity portion of volume. Our approach relies on a structural definition of liquidity frictions arising from the theoretical framework of Grossman and Miller (1988), which explains how liquidity shocks affect the way in which information is incorporated into daily trading characteristics. In addition, we propose an econometric setup exploiting the volatility–volume relationship to filter the liquidity portion of volume and infer the presence of liquidity frictions using daily data. Finally, based on FTSE 100 stocks, we show that the extended MDH model proposed here outperforms that of Andersen (1996) and that the liquidity frictions are priced in the cross-section of stock returns.     

Does high frequency algorithmic trading matter for non-AT investors?

The extant literature has typically measured the impact of high frequency algorithmic trading (HFT) on short term outcomes, in seconds or minutes. We focus on outcomes of concern for longer term non-algorithm investors. We find in some cases HFT increases volatility arising from news relating to fundamentals. Furthermore HFT is associated with the transmission of that volatility across industries, and that transmission is based on short term correlations. Finally, we find that the period since the introduction of algorithmic trading (AT) has seen increases in both the variances and covariances of return volatility in most industries. However increases in the variances has not been uniform in that it has fallen sharply in a few industries. The magnitudes are such that, overall, AT has coincided with reduced return volatility variance.     

Performance of Moving Average Trading Rules in a Volatile Stock Market: The Russian Evidence

This article examines the profitability of dual moving average crossover (DMAC) trading strategies in the Russian stock market over the 2003–12 period. It contributes to the existing technical analysis (TA) literature by testing, for the first time, the applicability of ordered weighted moving averages (OWMA) as an alternative calculation basis for determining DMACs. In addition, this article provides the first comprehensive performance comparison of DMAC trading rules in the stock market that is known as one of the most volatile markets in the world. The results show that the best trading strategies of the in-sample period can also outperform their benchmark portfolio during the subsequent out-of-sample period. Moreover, the outperformance of the best DMAC strategies is mostly attributable to their superior performance during bearish periods and, particularly, during stock market crashes.     

传统能源及碳交易价格与新能源股价——基于VAR和CAPM-GARCH模型的分析

文章构建VAR模型和CAPM-GARCH模型,分析检验了2010年7月初至2013年底期间传统能源和碳排放权交易价格对国内新能源上市公司股价波动的影响及新能源股票收益率的波动特点,研究发现:国内煤价对新能源公司股价有显著的正向影响,而国际油价的影响不显著;碳排放权交易价格也是引起新能源投资价值从而上市公司股价变动的重要因素;新能源公司股价指数对高科技股价指数并不敏感,反映出国内新能源上市公司科技含量不足,资本市场关注更多的是新能源的概念而非技术优势;国内新能源股票整体的系统风险在1.125~1.131之间,利好消息比利空消息能引起新能源股票收益率更大的波动。     

Informal Traders and the Battlegrounds of Revanchism in Cusco,Peru

Informal trading in the global South, particularly in Latin America, is the subject of revanchist urban policy and yet few studies have examined the longer‐term impacts of such intolerant policies on traders. This article explores the evolution and impacts of revanchist policies directed at informal traders in the Andean city of Cusco. It makes two key contributions. First, it documents a shift from early revanchist policies to a post‐revanchist era where policies have become more tolerant of informal traders. However, contemporary policies fall short of a supportive environment for informal trading, hence the authors recommend changes that will ensure informal traders can access the city's streets and become an accepted part of the urban fabric. Second, given the lack of theoretical attention given to the impacts of revanchism, a battlegrounds framework is developed, consisting of spatial, political, economic and socio‐cultural battlegrounds. This framework provides a comprehensive insight into the complex set of interactions that exist between informal traders and the state. It is hoped that the framework will provide a tool for further research into the highly damaging impacts of revanchism across the globe.     

Non-technical skills for managing risk and performance in financial trading

Recent large-scale failures in financial institutions have been found to be caused, in-part, by human factors-related issues in financial trading. In other environments where risk management and performance are intertwined, a human factors approach is often adopted to understand how the ‘non-technical skills (NTS)’ (leadership (LD), decision-making (DM), situation awareness (SA), teamwork) of organisational actors influence outcomes. Yet, to date, there has been minimal application of human factors research in financial trading. This study (i) identifies ‘real-world’ (i.e. non-laboratory) research studies investigating the NTS important for performance in financial trading, (ii) examines and synthesises data on the NTS found to underpin good or poor performance and (iii) considers the quality and coverage of research investigating NTS in financial trading, and identifies potential areas for future research. Nineteen studies were identified through a systematic literature search and then content-analysed for associations between NTS and performance in financial trading. The review found a range of decision-making (e.g. heuristics and biases, intuitive DM, emotional regulation) and LD skills (e.g. setting standards, monitoring behaviour, encouraging speaking-up) to have been identified as important for managing risk and performance in financial trading environments. Furthermore, SA (e.g. information search and assessment strategies, vigilance, identifying ‘noise’ data) and teamwork (e.g. avoiding ‘role’ conflict, communication between traders) were found to be important, yet remain less explored within the literature, and should be the focus of future research. NTS appear essential for effective risk management within the financial sector, yet further field research is required to examine the context-relevant behaviours that underpin safe activity. This will facilitate the development of evidence-based systems for assessing and training NTS competencies.     

Exploring under-utilised low carbon land resources from multiple perspectives: Case studies on regencies in Kalimantan

Mobilising under-utilised low carbon (ULC) land resources for future agricultural production can help reducing pressure on high carbon stock land from agricultural expansion, particularly for deforestation hotspots like Kalimantan. However, the potential of ULC land is not yet well understood, especially at regency level which is the key authority for land-use planning in Indonesia. Therefore, this study explored ULC land resources for all regencies in Kalimantan. By analysing information from six monitoring domains, a range of indicators were derived to provide insights into the physical area of ULC land from various perspectives. It was found that these indicators show largely different values at regency level. For example, regency Pulang Pisau has a substantial area of ‘temporarily unused agricultural land’ but a very limited area of ‘low carbon land’ – this implies that not all ‘temporarily unused agricultural land’ is ready for future exploitation when assessing from different aspects. As a result of such diverging indicators, using a single indicator to quantify available ULC land resources is risky as it can either be an over- or under-estimation. Thus, ULC land resources were further explored in the present paper by taking four regencies as case studies and comparing all the indicators, supported with relevant literature and evidence collected from narrative interviews. This information was used to estimate ULC land area by possible land-use strategies. For example, Gunung Mas was found to have a large area of low carbon land which is not occupied and might be suitable for oil palm deployment. However, the major limitation is that physical estimates cannot provide a complete picture of ‘real’ land availability without considering a broader range of socio-economic factors (e.g. labour availability). Therefore, physical land area indicators from different domains must be combined with other qualitative and quantitative information especially the socio-economic factors underlying land under-utilisation to obtain better estimates.     

Impact of short selling activity on market dynamics: Evidence from an emerging market

With unique daily short sale data of Borsa Istanbul (stock exchange of Turkey), we investigate the dynamic relationship between short selling activity and volatility, liquidity and market return from January 2005 to December 2012 using a VAR(p)-cDCC-FIEGARCH(1,d,1) approach. Our findings suggest that short sellers are contrarian traders and contribute to efficient stock market in Turkey. We also show that increased short selling activity is associated with higher liquidity and decreased volatility. However this relation weakens during the financial turmoil of 2008. Our results indicate that any ban on short sales may be detrimental for financial stability and market quality in Turkey.