Trading Period Research Articles

Multiple duration analyses of dynamic limit order placement strategies and aggressiveness in a low-latency market environment

This study examines dynamic order placement strategies in a low-latency environment together with limit orders' aggressiveness by a new approach which utilises survival analysis with a multiple-spell duration model. Two samples are considered, including the period immediately followed Australian Securities Exchange (ASX)’s migration to Integrated Trading System (ITS) and the period subsequent to the launch of ASX Trade. We find the evidence supporting both the ‘cost of immediacy hypothesis' and the ‘chasing hypothesis' as in Hasbrouck and Saar (2009). Furthermore, several distinctions in the results are found between the samples of ITS period and ASX Trade period as well as between the samples of small-cap stocks and large-cap stocks. The findings of this study are beneficial not only for high-frequency traders in forming dynamic order placement strategies in a low-latency stock market environment, but also for market regulators in helping their attempt to improve regulations for stock exchanges.

Dispersion Trading Based on the Explanatory Power of S&P 500 Stock Returns

This paper develops a dispersion trading strategy based on a statistical index subsetting procedure and applies it to the S&P 500 constituents from January 2000 to December 2017. In particular, our selection process determines appropriate subset weights by exploiting a principal component analysis to specify the individual index explanatory power of each stock. In the following out-of-sample trading period, we trade the most suitable stocks using a hedged and unhedged approach. Within the large-scale back-testing study, the trading frameworks achieve statistically and economically significant returns of 14.52 and 26.51 percent p.a. after transaction costs, as well as a Sharpe ratio of 0.40 and 0.34, respectively. Furthermore, the trading performance is robust across varying market conditions. By benchmarking our strategies against a naive subsetting scheme and a buy-and-hold approach, we find that our statistical trading systems possess superior risk-return characteristics. Finally, a deep dive analysis shows synchronous developments between the chosen number of principal components and the S&P 500 index.

Mechanics of good trade execution in the framework of linear temporary market impact

We define the concept of good trade execution and we construct explicit adapted good trade execution strategies in the framework of linear temporary market impact. Good trade execution strategies are dynamic, in the sense that they react to the actual realisation of the traded asset price path over the trading period; this is paramount in volatile regimes, where price trajectories can considerably deviate from their expected value. Remarkably, however, the implementation of our strategies does not require the full specification of an SDE evolution for the traded asset price, making them robust across different models. Moreover, rather than minimising the expected trading cost, good trade execution strategies minimise trading costs in a pathwise sense, a point of view not yet considered in the literature. The mathematical apparatus for such a pathwise minimisation hinges on certain random Young differential equations that correspond to the Euler–Lagrange equations of the classical Calculus of Variations. These Young differential equations characterise our good trade execution strategies in terms of an initial value problem that allows for easy implementations.

Price discovery, order submission, and tick size during preopen period

Using limit order book data, this study investigates the effects of minimum tick size reduction on price discovery and order submission strategies during the preopen call auction period in the Tokyo Stock Exchange. Studying the largest stocks' changes before and after the tick size reduction, our findings suggest that price discovery becomes more efficient when a smaller tick size is employed. A reduction in tick size induces a decrease in market depth and spread and enhances the speed of price discovery by encouraging more aggressive order to be placed and providing investors a better learning and communicating environment to incorporate information into order decisions. Our results demonstrate that, although orders are not matched and no transaction occurs during the preopen period, the order placement at these moments is neither necessarily noisy nor completely manipulative; factors that impact the investor's order choice during the normal trading period also work in this period.

The impact of closing mechanism changes: evidence from the Shanghai stock market

PurposeThe purpose of this paper is to empirically examine the impact of closing mechanism changes on market quality, investor trading behavior and market manipulation in the Shanghai stock market.Design/methodology/approachA dummy variable is constructed indicating whether the closing mechanism is call auction or continuous auction. Market quality is measured from aspects of liquidity, volatility and price continuity; investor trading behavior is scaled by order timing and order aggressiveness, and a price deviation indicator is the proxy of manipulation. Using panel regression, this study examines the impact of closing mechanism changes based on intraday transaction data from the Shanghai stock market.FindingsThe conclusions are as follows: First, market quality improves after the closing mechanism is reformed in terms of liquidity, volatility and price continuity. Second, order strategy changes significantly in the closing call market, and investors trade more aggressively in the continuous trading period before closing. Third, the closing call mechanism restrains the closing price manipulation and thus prompts an efficient closing price.Originality/valueThis paper examines the policy effects of closing mechanism changes from aspects of market quality, trading behavior and price manipulation, providing pieces of evidence for trading mechanism design and market supervision in emerging markets.

Asymmetric return–volatility relation around the clock

AbstractThis study examines the return‐realized volatility (RV) relation at daily and intraday frequencies. Using daily data, we find the contemporaneous return is the dominating factor for RV, which is in support of the behavioral explanation. For intraday data, we further find a significantly positive (negative) relation between contemporaneous positive (negative) return and RV, which is consistent with prospect theory. Quantile regression analysis documents a U‐shaped (inverted U‐shaped) contemporaneous return‐volatility relation for positive (negative) returns across volatility quantiles during the daytime trading period. In addition, we find the affect heuristic is more aggressive at overnight trading period.

Peer-to-peer electricity trading in grid-connected residential communities with household distributed photovoltaic

With the rapid development of distributed electricity generation technologies such as solar photovoltaics, peer-to-peer (P2P) electricity trading is attracting incremental attention due to the pursuit of decentralized energy autonomy and further economic benefits. The study presented in this paper aims to gain a better understanding of the community P2P electricity trading, including influence of trading strategies, determinants of trading quantity and price, and further factors affecting improvement in community energy welfare. The market mechanism is determined based on the discriminatory continuous double auction, followed by simulations of the trading process in well-designed cases. Results show that P2P trading price and quantity depend on variation of the supply–demand ratio during each trading period, by which in the absence of complex trading strategies and learning abilities, profits are able to be effectively and fairly allocated among participants. For a given community, the total profits that could be obtained from P2P electricity trading are influenced by many factors, and the key is to make those “ineffective supply” available in the P2P market again, through active energy management solutions on all residents rather than focusing only on prosumers’ self-consumption in the past. The ensuing results make significant sense as regards better understanding both the benefits and limitations of P2P electricity trading in residential communities or other similar scenes, thus helping for guiding practical implementation.

Robo-Advisors: Machine Learning in Trend-Following ETF Investments

We examine an application of machine learning to exchange traded fund investments in the U.S. market. To find how the changes in exchange traded fund prices are associated with expected market fundamentals, we propose three parsimonious risk factors extracted from various U.S. economic and market indicators. Based on the information set including these three factors, we build a predictive support vector machine model that can detect long or short investment signals. We find that the high probability of an upward momentum from our forecasting model suggests a long exchange traded fund signal, whereas the low probability of a downward momentum indicates a short exchange traded fund signal. We further design an algorithmic trading system with the support vector machine factor model. We find that the trading system shows practically desirable and robust performances over in-sample and out-of-sample trading periods

Fetishizing the Foot: Mobility and Meaning in Indian Ocean Sandals

Fetishizing the Foot: Mobility and Meaning in Indian Ocean Sandals

Genetic Consequences of the Transatlantic Slave Trade in the Americas

According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery’s abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data. Here, we analyzed genotype array data from 50,281 research participants, which—combined with historical shipping documents—illustrate that the current genetic landscape of the Americas is largely concordant with expectations derived from documentation of slave voyages. For instance, genetic connections between people in slave trading regions of Africa and disembarkation regions of the Americas generally mirror the proportion of individuals forcibly moved between those regions. While some discordances can be explained by additional records of deportations within the Americas, other discordances yield insights into variable survival rates and timing of arrival of enslaved people from specific regions of Africa. Furthermore, the greater contribution of African women to the gene pool compared to African men varies across the Americas, consistent with literature documenting regional differences in slavery practices. This investigation of the transatlantic slave trade, which is broad in scope in terms of both datasets and analyses, establishes genetic links between individuals in the Americas and populations across Atlantic Africa, yielding a more comprehensive understanding of the African roots of peoples of the Americas.

Risk-adjusted Returns from Statistical Arbitrage Opportunities in Indian Stock Futures Market

Statistical arbitrage is a trading strategy that employs time series methods to identify relative mispricing between securities based on the expected values of these assets. The Pairs Trading, one of the techniques of statistical arbitrage, is a market neutral trading strategy. The main objective of this paper is to investigate the profitability and risks of pairs trading strategy for various stocks. The daily future prices of stocks traded and listed on NSE over 2011–2017 are used on rolling basis to compute the performance based on the selection of pairs through minimizing the sum of squared deviation (distance method) and the selection based on cointegration tests (cointegration method) for identifying stocks suited for pairs trading strategies. The pairs trading strategy is performed in two stages: the formation period and the trading period. The strategy is created by long position in one stock and short position in other stock of the pair identified. To examine the risk of pairs trading and the drivers of returns, the portfolio returns are risk-adjusted using Fama and French (J Financ Econ 33:3–56, 1993) three factor asset pricing model. The study reveals that pairs trading in related stocks is significantly profitable with average annualized profitability of up to 34% including transaction costs. The evidence of pairs trading profits in stock futures supports the view that these profits reflect compensation to arbitrageurs for enforcing the law of one price in similarly related markets to ensure market efficiency. Indian financial markets are maturing and are attracting sizable retail and institutional investments. Advanced applications like the one presented in this study are of significance for the investors and investment consultants so that they can benefit from such trading strategies.

Size Matters: Estimation Sample Length and Electricity Price Forecasting Accuracy

Short-term electricity price forecasting models are typically estimated via rolling windows, i.e. by using only the most recent observations. Nonetheless, the literature does not provide guidelines on how to select the optimal size of such windows. This paper shows that determining the appropriate window prior to estimation dramatically improves forecasting performances. In addition, it proposes a simple two-step approach to choose the best performing models and window sizes. The value of this methodology is illustrated by analyzing hourly datasets from two large power markets (Nord Pool and IPEX) with a selection of eleven different forecasting models. Incidentally, our empirical application reveals that simple models, such as a simple linear regression (SLR) with only two parameters, can perform unexpectedly well if estimated on extremely short samples. Surprisingly, in the Nord Pool, such SLR is the best performing model in 13 out 24 trading periods.

Challenges and Improvements based on the First Trading Period of South Korea’s Emissions Trading Scheme (Focusing on Emission Allowance Allocation)

South Korea’s Emissions Trading Scheme (KETS) has received severe criticism regarding allowance allocation issues since its launch in 2015. The primary purpose of this study was to present the allocation issues identified during the first KETS trading period and to suggest feasible approaches to overcoming these challenges that fit within KETS’ overarching development direction. The following four issues were identified as major challenges for KETS at the end of the first trading period: 1) Low trading volumes of emission allowances, 2) fewer allocations based on lower mean emissions during the previous trading period, 3) lack of consideration of adjustment factors for new installations and deployments, and 4) the absence of opportunities for opinion exchange on allocation issues between participating businesses and the government. Feasible approaches to these challenges include 1) setting up guidance for each measure aimed to stabilize the market price of emission allowances, 2) allocating additional allowance amounts as greenhouse gas (GHG) emissions are reduced, 3) lowering the adjustment factor for new installations and deployments, and 4) establishing an official platform managed by a supervising body involving civil experts, governmental and non-governmental organizations, and state-owned banks. These strategies would contribute to future development of KETS.

BIOSIMILAR MEDICINE PRICE ANALYSIS IN BRAZIL: THE ANTIRHEUMATIC CASE

Objective: The introduction of biosimilar medicines in markets can bring savings to health systems, expanding the population’s access to various treatments. This study aims to analyze the price competition of biological agents and their biosimilars in Brazil within the scope of rheumatoid arthritis.
 Methods: Prices for 14 presentations of original and biosimilar medicines were analyzed from January 2003 to October 2019 in Brazil. Prices were taken from official lists and were noted since launch and during the later trading period. Prices were converted to United States dollars and adjusted for inflation for the 2003 base year.
 Results: In Brazil, during this review period, prices of biopharmaceuticals decreased in real values, reaching up to a 50% reduction. The introduction of biosimilars did not affect the price sharing of biological medicines.
 Conclusion: Biosimilar antirheumatics do not yet have a significant impact on the price of biologics marketed in Brazil. A change in this scenario is expected in the medium and long term.

Korean Filmmakers in Shanghai 1920s-1930s: Border-crossing Practices of Shanghai Filmmaking

This article traces the practices of Korean filmmakers in Shanghai film industry during the period between the 1920s and 1930s. By delineating how Shanghai filmmaking in the 1920s and 1930s connected to Korean filmmakers and other cultural workers through key figures and films, this article calls into attention the fact that Shanghai filmmaking in the 1920s and 1930s cannot be fully understood without taking into account the trans-border mobility of filmmakers and the transnationality of anti-colonial and class-conscious discourse in this historical period of colonial expansion and international trade. It was a history of disjuncture, of a transnational screen connection happening long before neoliberalism became an orthodox discourse in globalization. The border-crossing activities of the people active in this network mediated the ideological connection and utilized the visual image to store a popular knowledge and memory that could perhaps transcend the national borders.

Transmission of Information of the Indonesian Dual Listed Shares

Various studies have been carried out in relation to the behavior of dual listing stock prices, unfortunately, study on the effects of changes in dual listing stock prices on the Indonesia Stock Exchange (IDX) is still limited. Differences in trading time and stock exchange class between one stock exchange with another in different countries raise an opportunity for the accumulation of information when one of the exchanges is experiencing a closing trading period. Indonesian companies such as PT. Telekomunikasi Indonesia (Persero) Tbk. (TLKM) whose shares are listed on the New York Stock Exchange (NYSE) and IDX experience the difference in time of their transaction which can affect the shares on the NYSE and on the IDX. This study conducted by using daily data from January 2018 to December 2018. This study found that there is a significant effect of changes in TLKM stock prices on the NYSE in (t-1) period to changes in TLKM stock prices on IDX in t-period. This finding proves that there was the existence of transmission of information between the stock exchanges utilized by investors.

The Role of Banks in EU Emissions Trading

This paper is an empirical investigation of the role of banks in the EU Emissions Trading System (EU ETS). This topic is of particular interest considering that banks are responsible for a large and increasing share of overall transactions under the EU ETS and that they provide regulated companies with services related to emissions trading. Using both semi-structured interviews as well as descriptive and regression analysis, we investigated the different roles banks play in EU emissions trading and whether their importance as trading partners differs in relation to different types of regulated companies. Our regressions based on data from the first trading period of the EU ETS show that large companies with trading experience are more likely to choose a trading strategy involving interaction with a range of financial intermediaries, in particular banks or exchanges, than smaller, less professionalized companies, which tend to follow a trading strategy involving brokers (in particular for selling allowances). These findings can help policymakers decide on the level of involvement of non-regulated companies in their systems, which is currently allowed to varying degrees under different ETS. We recommend that this decision should be closely linked to provisions of market oversight and the level of control over the different types of financial players active in emissions trading.

The effect of short-sale restrictions on the information transmission of extended index futures trading

During the global financial crisis, two types of short-sale restrictions, i.e., the uptick restriction and the naked short-sale ban, were introduced in the Taiwan Stock Exchange (TWSE). This provides an opportunity to examine whether these two types of short-sale restrictions reduce the speed at which the overnight spot returns and the trading period spot returns adjust to the bad news revealed through the index futures returns during the post-close and pre-open extensions. The results of the threshold GARCH(1,1) model show that only the short-sale ban significantly reduced the speed at which the overnight spot returns react to the bad news revealed by the futures returns of the TWSE index during the pre-open extended session

Time Series Analysis of Stock Market Volatility in Pakistan

The stock market in an emerging country like Pakistan has been volatile from the earliest times. This paper studies the volatility of Pakistan Stock Exchange (PSX) (using Karachi Stock Exchange 100 Index (KSE-100) as a proxy) through the application of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family models.
 The sample period consists of 4831 daily observations for the 19 year trading period (from 2000 to 2019). Symmetric GARCH (2, 1), asymmetric EGARCH (1, 1), GJR-GARCH (1, 1) and APARCH (1, 1) models were used under Gaussian distributional assumptions. The results validate the empirical findings of previous studies conducted in Pakistan that log returns of KSE-100 Index are characterized by volatility clustering, time-variability, leptokurtic distribution with dominant ARCH and GARCH effects. An interesting feature of Pakistan Stock Exchange revealed by asymmetric models (used in the study) is that PSX is more volatile to good news than bad news. Moreover EGARCH (1, 1) outperforms all other models of the study on the basis of AIC/BIC criterion. However the comparison of correlations of variances predicted by three asymmetric models reveal that correlations among them are very high, with minimum correlation being 98%. This essentially means that all three asymmetric models provide a good fit to PSX.

Optimizing the Sharpe Ratio with Portfolio Turnover, Reasoning and Methodology

This paper seeks to determine ways that a trading algorithm’s efficiency (specifically Sharpe Ratio over a given time period can be maximized through adjusting portfolio turnover in two ways: explicitly constraining the amount of turnover allowed per rebalance and rebalancing frequency. We test the first way via a Constraint method on Quantopian called “MaxTurnover(),” which, in lieu of sufficient explanation or documentation anywhere, seems to simply reduce average Turnover over a given trading period all else equal, of course. The second method of changing portfolio turnover is tested by simply increasing rebalancing frequency in the absence of “MaxTurnover()” as a constraint, id est turnover per rebalance is not constrained. From there, we examine ways we can generalize the data found. Current thinking dictates that extremely low turnover can be somewhat equated to missing out on too many opportunities and lowered exposure to alpha, but simultaneously that incredibly high turnover leads to too much exposure to risk. We find that accepted rules of thumb are still held true and that the data is consistent with current thinking and literature, but additionally that an unexpected relationship between drawdown and both measures of turnover--a positive correlation, that is. Equally unexpected is that this relationship is seemingly stronger than that between turnover measures and the Sharpe ratio, a proxy for portfolio efficiency. Through all of it, one point is clear, though: a modest rebalancing period and lower turnover is ideally efficient.