A New Deep Learning-Based Zero-Inflated Duration Model for Financial Data Irregularly Spaced in Time

In stock trading markets, trade duration (i. e., inter-arrival times of trades) usually exhibits high uncertainty and excessive zero values. To forecast conditional distribution of trade duration, this study proposes a hybrid model called “DL-ZIACD” for short, which addresses the problem of excessive zero values by a zero-inflated distribution. Meanwhile, dynamics of the distribution time-varying parameters are captured by a specially designed deep learning (DL) architecture in which the behavioral patterns of large traders and small individual traders are represented separately by different blocks. The proposed hybrid model takes advantage of the strong fitting ability of deep learning methods while allowing for providing a probabilistic output. This paper empirically applied the established model to a large-scale dataset, containing 9,900,000 transactions of the Chinese Shenzhen Stock Exchange 100 Index (SZSE 100) constituents. To the best of our knowledge, no previous studies have applied conditional duration models to a dataset of such a large scale. For both the central location forecasting and the extreme quantile forecasting, our proposed model exhibited significant superiority over the benchmark models, which indicates that our DL-ZIACD model can provide accurate forecasts in conditional duration distribution.

Google trends as predictor of grain prices

This paper examines the predictive power of Google trends on the grain's futures price movement. The aim was to validate if an algorithmic trading system designed was profitable and able of beating the market. In the research was used data from soybean futures and corn futures, both contracts are listed in the Chicago Mercantile Exchange. The results of the research show that its forecasting power is high when predicting soybean futures and corn futures prices. According to the findings, the formulation of such predictive analysis is a good option for individual traders, investors, and commercial firms.

Automated trading systems’ evaluation using d-Backtest PS method and WM ranking in financial markets

Given the popularity and propagation of automated trading systems in financial markets among institutional and individual traders in recent decades, this work attempts to compare and evaluate such ten systems based on different popular technical indicators in combination – for the first time – with the d-Backtest PS method for parameter selection. The systems use the technical indicators of Moving Averages (MA), Average Directional Index (ADX), Ichimoku Kinko Hyo, Moving Average Convergence/Divergence (MACD), Parabolic Stop and Reverse (SAR), Pivot, Turtle and Bollinger Bands (BB), and are enhanced by Stop Loss Strategies based on the Average True Range (ATR) indicator. Improvements in the speed of the back-testing computations used by the d-Backtest PS method over weekly intervals allowed examining all systems on a 3.5 years trading period for 7 assets in financial markets, namely EUR/USD, GBP/USD, USD/JPY, USD/CHF, XAU/USD, WTI, and BTC/USD. To evaluate the systems more holistically, a weighted metric is introduced and examined, which, apart from profit, takes into account more factors after normalization like the Sharpe Ratio, the Maximum Drawdown and the Expected Payoff, as well as a newly introduced Extended Profit Margin factor. Among the automated systems examined and evaluated using the weighted metric, the Adaptive Double Moving Average (Ad2MA) system stands out, followed by the Adaptive Pivot (AdPivot), and the Adaptive Average Directional Index (AdADX) systems. AcknowledgmentsWe would like to thank Dr. Christos Schinas for his time and invaluable guidance towards the methodology of the weighted metric. We would also like to thank Michalis Foulos for the hardware setup and support and Nektarios Mitakidis for his contribution to the representation of the results.This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-02342).

Destabilizing momentum trading and counterbalancing contrarian strategy by large trader groups

Purpose The purpose of this paper is to assess trading strategies adopted by each large trader group and examine their effects on the volatility in the interest rate futures markets. Design/methodology/approach The Grinblatt et al.'s (1995) measure of momentum strategy is used to estimate the degree momentum and contrarian strategies. Then, regression analysis is used to determine the effects of trading strategies on volatility. Findings Up until 2005, the trades by non-clearing member firms in the futures market were separated from institutional traders providing us the opportunity to study trading strategies adopted by large distinct trading groups and its effects on volatility in the futures markets. It is found that individual traders use momentum strategy, whereas market makers and institutional traders use contrarian strategy. Momentum strategy adopted by individual traders increases volatility whereas contrarian strategy dampens volatility. Moreover, it is found that institutional traders engage more actively in contrarian trading when individual traders cause excessive volatility. The two distinct trading groups were separately tracked prior to 2005 giving us a unique window to determine the effect of the traders that conduct momentum trading as opposed to the ones that are contrarian traders. After the reclassification, the institutional trading group exhibited weaker contrarian strategy which can be attributed to the inclusion of non-clearing firm traders. Originality/value This study documents the first empirical evidence that shows off-exchange futures trader group is not composed of only pure noise makers, but there are short-term forecasters in its group. The authors also show a unique finding that noises caused by off-exchange group is from momentum strategy that they use, whereas contrarian strategy is used by institutional trader lower volatility.

Egyptian‐Sudanese Trade in the Ottoman Period to 1882

Egypt’s trade in the Ottoman period with the Sudanic kingdoms to its south waxed and waned according to political conditions at either end of its trade routes. During the 16th and 17th centuries, powerful kingdoms developed in the area of Sinnar (near modern-day Khartoum) and to the west in the area of Darfur. The trade route connecting western Sudan to Egypt, known as the Forty Days Road, was ancient, probably dating to the Pharaonic period, but it experienced a remarkable revival in the 17th century when the Keira sultans of Darfur consolidated their rule in western Sudan and engaged in trade with Egypt in order to obtain luxury goods. In the following two centuries, trade between Egypt, Sinnar, and Darfur flourished, the pattern being that Egyptian, Syrian, and European-made goods were exchanged primarily for Sudanic exports of slaves, ivory, ostrich feathers, and livestock. Sudanese merchants, known as jallaba, came to Egypt and Egyptians settled in the Sudan as a result of these developments. Asyut was the town in Upper Egypt chiefly benefiting from the revival of the caravan trade, but the primary trade destination was Cairo, whence most merchants went. In 1820, the Egyptians invaded the Sudan and trade between the two countries fell under a different set of rules and regulations. Initially monopolized by the government, items in the trade began to be sold by individual traders, and after 1839, when the Muhammad Ali, ruler of Egypt, was forced to withdraw from lands his army had conquered in Arabia and the Levant, European free enterprise soon became a major economic force in the Nile Valley. For a brief period, between 1845 and 1860, Egyptian middlemen, working closely with jallaba, profited richly from the Sudan trade, the city of Asyut prospered, but eventually they fell victim to European economic domination.

The Canton Trade, 1700–1842

In 1684, China reopened its doors to trade with the outside world, which had a huge impact on the development of global commerce. Canton quickly emerged as one of the few ports in the world where everyone was welcomed and where everyone (except Japanese and Russians) had access to everything including tea, silk, and porcelain. Unlike other ports, individual traders in Canton could buy and sell the same high-quality products as those handled by the East India companies. As the Canton trade grew, international networks became more sophisticated; as more ships went to China, new forms of remittance such as Letters of Credit and Bills of Exchange became standard, which streamlined international finance; as more money flowed into Canton, more goods were distributed worldwide, which gave rise to globalization; as economies in both the eastern and western hemispheres became more integrated with the Chinese market, there was a parallel decline in the risks of conducting trade, which encouraged the advancement of private enterprise. One by one the large East India companies found it increasingly more difficult to compete and went broke. However, the success of the Canton trade was also its weakness. Because the legal trade was so dependent on silver collected from opium sales, and because a decline in opium sales would likely lead to a decline in rice imports, only minimal efforts were made by local officials to stop the smuggling. Foreigners were eventually able to overcome the system with the outbreak of war in the late 1830s, but this happened because the system had already defeated itself.

Crafting Ethical Connection and Transparency in Coastal Kenya

As connecting to the global economy has torn individual traders from the decades-old co-operative societies, a wave of “witchcraft” accusations and market burnings have helped illuminate the importance of the crafts industry’s moral economy of creativity and innovation and the ongoing debate about what ethical and moral development looks like in Kenya. Ideas of ethics and transparency, as produced through the application of a Fair Trade sticker, strategically erase complex economic and ethical realities while simultaneously indexing ideas of digital modernity and ethical citizenship. A Fair Trade sticker shines a selective light on marketable realities while simultaneously obscuring those inconvenient to marketing crafts. This new wave of ethical branding and NGO aesthetics enables a “race to the bottom” by businesspeople to find and organize the most exploitable artisans (the handicapped, single mothers, homeless children) into workshops and artisan organizations that explicitly market the marginality of the producers.