Forecasting movements of health-care stock prices based on different categories of news articles using multiple kernel learning

—The market state changes when a new piece of information arrives. It affects decisions made by investors and is considered to be an important data source that can be used for financial forecasting. Recently information derived from news articles has become a part of financial predictive systems. The usage of news articles and their forecasting potential have been extensively researched. However, so far no attempts have been made to utilise different categories of news articles simultaneously. This paper studies how the concurrent, and appropriately weighted, usage of news articles, having different degrees of relevance to the target stock, can improve the performance of financial forecasting and support the decision-making process of investors and traders. Stock price movements are predicted using the multiple kernel learning technique which integrates information extracted from multiple news categories while separate kernels are utilised to analyse each category. News articles are partitioned according to their relevance to the target stock, its sub industry, industry, group industry and sector. The experiments are run on stocks from the Health Care sector and show that increasing the number of relevant news categories used as data sources for financial forecasting improves the performance of the predictive system in comparison with approaches based on a lower number of categories

Forecasting price movements using technical indicators: investigating the impact of varying input window length

The creation of a predictive system that correctly forecasts future changes of a stock price is crucial for investment management and algorithmic trading. The use of technical analysis for financial forecasting has been successfully employed by many researchers. Input window length is a time frame parameter required to be set when calculating many technical indicators. This study explores how the performance of the predictive system depends on a combination of a forecast horizon and an input window length for forecasting variable horizons. Technical indicators are used as input features for machine learning algorithms to forecast future directions of stock price movements. The dataset consists of ten years daily price time series for fifty stocks. The highest prediction performance is observed when the input window length is approximately equal to the forecast horizon. This novel pattern is studied using multiple performance metrics: prediction accuracy, winning rate, return per trade and Sharpe ratio

Technical trading and cryptocurrencies

This paper carries out a comprehensive examination of technical trading rules in cryptocurrency markets, using data from two Bitcoin markets and three other popular cryptocurrencies. We employ almost 15,000 technical trading rules from the main five classes of technical trading rules and find significant predictability and profitability for each class of technical trading rule in each cryptocurrency. We find that the breakeven transaction costs are substantially higher than those typically found in cryptocurrency markets. To safeguard against data-snooping, we implement a number of multiple hypothesis procedures which confirms our findings that technical trading rules do offer significant predictive power and profitability to investors. We also show that the technical trading rules offer substantially higher risk-adjusted returns than the simple buy-and-hold strategy, showing protection against lengthy and severe drawdowns associated with cryptocurrency markets. However there is no predictability for Bitcoin in the out-of-sample period, although predictability remains in other cryptocurrency markets

Forecasting stock price directional movements using technical indicators : investigating window size effects on one-step-ahead forecasting

Accurate forecasting of directional changes in stock prices is important for algorithmic trading and investment management. Technical analysis has been successfully used in financial forecasting and recently researchers have explored the optimization of parameters for technical indicators. This study investigates the relationship between the window size used for calculating technical indicators and the accuracy of one-step-ahead (variable steps) forecasting. The directions of the future price movements are predicted using technical analysis and machine learning algorithms. Results show a correlation between window size and forecasting step size for the Support Vector Machines approach but not for the other approaches

Физически неклонируемые функции с управляемой задержкой распространения сигналов

O b j e c t i v e s. The problem of constructing a new class of physically uncloneable functions (PUF) based on controlling the signal propagation delay through the elements lying on the path of its propagation is being solved. The relevance of this problem is associated with the active development of physical cryptography. For its implementation, the following goals are pursued: the construction of the basic elements of the PUF and their modifications, the development of a methodology for constructing controlled ring oscillators based on XOR elements and controlled ring oscillators based on multi-input signal switching.M e t h o d s.  Methods  of  synthesis  and  analysis  of  digital  devices  were  used,  including  those  based  on programmable logic integrated circuits (FPGA), the basics of Boolean algebra and circuitry.R e s u l t s. It is shown that combined PUFs based on RS-flip-flops implement the idea of controlling the signal delay by choosing a path, which is a series-connected elements selected in accordance with the PUF request. A technique for constructing an PUF with a  controlled delay through each element of the path has been developed as a development of the idea of controlling the signal delay along the path. The features and properties of PUF with controlled delay of signals of the ring oscillator type are investigated and possible solutions are shown for the case of two-bit input requests. A basic element and its modifications are proposed for constructing new PUF structures based on the control of the signal propagation delay. It is shown that the signal delay through the basic element, which is a multi-input XOR element, depends not only on the number of inputs to which the active input signal is applied, but also on fixed values of 0 or 1 at its other inputs. A new PUF structure is presented, namely, a controlled ring oscillator, its implementation is considered for the case of control by setting the inputs and their number, by which the active input signal changes.Co n c l u s i o n. The proposed new approach to the construction of physically uncloneable functions, based on the control of signal delay through logical elements, has shown its efficiency and promise. The effect of the influence on the delays of signal propagation through the logic element, both the number of its inputs, along which the input signals change, leading to a change in the output signal, and their composition, is experimentally confirmed. It seems promising to further developing the ideas of constructing controlled ring oscillators and oscillators  with  multi-input  switching of  input  signal,  as  well  as  the  creation  of  new PUF  structures of arbiter type.Ц е л и. Решается задача построения нового класса физически неклонируемых функций (ФНФ), обеспечивающих управление задержкой распространения сигнала через элементы, которые расположены на пути его распространения. Актуальность такого исследования связана с активным развитием физической криптографии. В работе преследуются следующие цели: построение базовых элементов ФНФ и их модификаций, разработка методики построения управляемых кольцевых осцилляторов на базе элементов XOR и управляемых кольцевых осцилляторов, основанных на многовходовом переключении сигнала.М е то д ы . Используются методы синтеза и анализа цифровых устройств, в том числе на программируемых логических интегральных схемах, основы булевой алгебры и схемотехники.Р е з у л ь т а т ы .  Показано, что комбинированные ФНФ, основанные на RS-триггерах, реализуют идею управления задержкой сигнала за счет выбора пути, который представляет собой последовательно подключенные элементы, выбранные в соответствии с запросом ФНФ. Разработана методика построения ФНФ с управляемой задержкой через каждый элемент пути. Исследованы особенности и свойства ФНФ с управляемой задержкой сигналов типа кольцевого осциллятора и показаны возможные решения для случая двухразрядных входных запросов. Предложен базовый элемент и его модификации для построения новых структур ФНФ, основанных на управлении задержкой распространения сигнала. Показано, что задержка сигнала через базовый элемент, представляющий собой многовходовый элемент XOR, зависит не только от количества входов, на которые подается активный входной сигнал, но и от фиксированного значения 0 либо 1 на остальных его входах. Приведена новая структура ФНФ – управляемый кольцевой осциллятор, рассматриваются его реализации для случая управления за счет задания количества входов, на которых изменяется активный входной сигнал.З а к л ю ч е н и е . Предложенный подход к построению физически неклонируемых функций, основанный на управлении задержкой сигналов через логические элементы, показал свою работоспособность и перспективность. Экспериментально подтвержден эффект влияния на задержки распространения сигналов через логический элемент количества его входов, на которых изменяются входные сигналы, приводящие к изменению выходного сигнала. Перспективным представляется дальнейшее развитие идей построения управляемых кольцевых осцилляторов и осцилляторов с многовходовым переключением сигнала, а также создания новых структур ФНФ типа арбитр