Search results for: prediction of financial Markets

Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Yusuf Seedat

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The necessity to understand global financial markets has increased following the unfortunate spread of the recent financial crisis around the world. Financial markets are considered to be complex systems consisting of highly volatile move-ments whose indexes fluctuate without any clear pattern. Analytic methods of stock prices have been proposed in which financial markets are modeled using common network analysis tools and methods. It has been found that two key components of social network analysis are relevant to modeling financial markets, allowing us to forecast accurate predictions of stock prices within the financial market. Financial markets have a number of interacting components, leading to complex behavioral patterns. This paper describes a social network approach to analyzing financial markets as a viable approach to studying the way complex stock markets function. We also look at how social network analysis techniques and metrics are used to gauge an understanding of the evolution of financial markets as well as how community detection can be used to qualify and quantify in-fluence within a network.

Keywords: network analysis, social networks, financial markets, stocks, nodes, edges, complex networks

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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

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Authors: Shota Gulbani

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At the present stage, for the countries with developing economies, studying, and researching financial markets, gains special importance, because the situation of financial markets shapes an exact views about the carried out economic policy of the country. Besides, it’s unimaginable any country with developed economy, without healthy and functioning financial markets, whereas, for any kind of business it has got a great importance in terms of finding diversified and alternative capital. In this regard; it should be noted that the segments of Georgian financial markets are developed quite unequally, as evidenced by the fact that the Georgian financial sector is represented by 93% of commercial banks, what does not create an conformable environment for non-bank financial institutions development. In spite of the fact that Georgia has got one of the best banking system of region, it is important to properly analyze that this system should not hinder the development of other participants of Georgian financial sector.

Keywords: financial markets, macroeconomics, investments, stock exchange

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Authors: Zouari Ezzeddine, Ghraieb Ikram

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From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

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Authors: Fahad Ahmed Qureshi

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There were abundant renowned financial markets in Pre-Islamic Arabs. Most of those were patterned and settled during pre-particularized sunshine. Those markets were classified either as vernacular markets helping the neighboring clans, or habitual markets that people sojourned to from all articulations of the Arabian Peninsula, such as Okaz near Mecca. Some of those markets had leading significance due to their geographical positions, such as Prime market of Eden, because of their entanglement in international trade i.e. with the markets of Sub-Continent, Abyssinia, Persia and China. Other markets such as Market of Yamamah annex its gist from being situated on the caravan crossroads. Islamic worldview and Islamic epistemology base of Financial Market’s realistic theory, pragmatic model and operative approach is moderately constrained in terms of its growth. The existent situation only parasol the form of accommodative-modification and splendid-methodologies, which due to depleted and decorous endeavor in explaining Islamic financial market theoretically. This is the demand of time that particular studies should be conduct to magnify the devours in developing theoretical framework for Islamic Financial Market.

Keywords: Islam, financial market, history, research, product development

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Authors: Vera Jancurova

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The financial theory is dominated by the believe that weekday effect has disappeared from current markets. The purpose of this article is to study anomalies, especially weekday effect, at real markets that disrupt the efficiency of financial markets. The research is based on the analyses of historical daily exchange rates of significant world indices to determine the presence of weekday effects on financial markets. The methodology used for the study is based on the analyzes of daily averages of particular indexes for different time periods. Average daily gains were analyzed for their whole time interval and then for particular five and ten years periods with the aim to detect the presence on current financial markets. The results confirm the presence of weekday effect at the most significant indices - for example: Nasdaq, S & P 500, FTSE 100 and the Hang Seng. It was confirmed that in the last ten years, the weekend effect disappeared from financial markets. However in last year’s the indicators show that weekday effect is coming back. The study shows that weekday effect has to be taken into consideration on financial markets, especially in the past years.

Keywords: indices, anomalies, behavioral finance, weekday effect

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Authors: Sara Ali Alokley, Mansour Saleh Albarrak

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This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.

Keywords: clustring, extremes, returns, dependency, extermal index

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Authors: Mohammad Hossein Ranjbar, Mahdi Bagheri, B. Shivaraj

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This study attempts to investigate the relationship between stock market of Iran and GCC countries stock exchanges. Eight markets were included: the stock market of Iran, Kuwait, Bahrain, Qatar, Saudi Arabia, Dubai, Abu Dhabi and Oman. Daily country market indices were collected from January 2005 to December 2010. The potential time-varying behaviors of long-run stock market relationship among selected markets are tested applying correlation test, Augmented Dick Fuller test (ADF), Bilateral and Multilateral Cointegration (Johansen), and the Granger Causality test. The findings suggest that stock market of Iran is negatively correlated with most of the selected markets in the whole duration. But contemporaneous correlations among the eight selected markets are increased positively in period of financial crises. Bilateral Cointegration between selected markets suggests that there is no integration between Tehran stock exchange and other selected markets. Among other markets, except the stock market of Dubai and Abu Dhabi as a one pair, are not cointegrated in whole, but in duration of financial crises integration between selected markets are increased. Finally, investigation of the casual relationship among eight financial markets suggests there are unidirectional and bidirectional causal relationship among some of stock market indices.

Keywords: financial crises, Middle East, stock market integration, Granger Causality test, ARDL test

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Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

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Authors: Seyed Sajjad Habibi

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The aim of this study is to investigate the impact of global financial crises and corporate financial crisis on tax evasion of companies listed on the Tehran Stock Exchange. For this purpose, panel data in the periods of financial crisis period (2007 to 2012) and without a financial crisis (2004, 2005, 2006, 2013, 2014, and 2015) was analyzed using multivariate linear regression. The results indicate a significant relationship between the corporate financial crisis (bankruptcy risk) and tax evasion in the global financial crisis period. The results also showed a significant relationship between the corporate bankruptcy risk and tax evasion in the period with no global financial crisis. A significant difference was found between the bankruptcy risk and tax evasion in the period of the global financial crisis and that with no financial crisis so that tax evasion increased in the financial crisis period.

Keywords: global financial crisis, corporate financial crisis, bankruptcy risk, tax evasion risk, emerging markets

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Authors: A. J. Regan, F. J. Lidgey, M. Betteridge, P. Georgiou, C. Toumazou, K. Hayatleh, J. R. Dibble

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Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-of-sample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.

Keywords: financial algorithm, GPU, S&P 500, stock market prediction

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Authors: Jitendra Aswani

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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.

Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm

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Authors: Nousheen Tariq Bhutta, Syed Zulfiqar Ali Shah

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Financial crises become a key impediment towards the development of countries especially in emerging economies. Based on standard finance, many researchers investigated the financial crises in different countries in order to find the underlying reason regarding occurrence these event; however they were unable to provide it. In this essence behavioral finance may be helpful in providing answers to some queries regarding occurrence and prevention of financial crises. In this paper, we explore the some psychological factors comprises of our inspiration, emotion, cognition and culture along with their reflection companies, financial markets and governments that present some supportive arguments. Moreover, we compared the views of Keynes and Minsky in order to validate the underling justification towards occurrence of financial crises and their prevention in future. This study helps the practitioners and policy makers through providing valuable recommendation in order to protect the economies.

Keywords: financial crises, behavioral finance, financial markets, emerging economies

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Authors: Adedeji Tejumola Olugboja

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Night markets are physical locations in residential neighbourhoods where market parties interact. It is a kind of market where marketing activities commence by 6pm until after midnight. The problem of the study is to assess marketing activities in the night markets. Specific objectives for this study include determining volume of business activities, numbers of market parties etc in the selected night markets. The purposive sampling technique is adopted for this study and the four night markets in the area of study are selected as sample: Aggregate of 173 retailers and an average of 2583 consumers daily operate in these night markets. The use of tables, simple percentage and descriptive statistics were employed for data analysis and presentation. Findings revealed volume of marketing activities, sales per night, profit per night and savings per day in each of these night markets. Government should erect street lights and repair damaged ones in these night markets to make night markets more lucrative.

Keywords: marketing activities, night markets, Nigerian economy

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Authors: Manel Youssef, Lotfi Belkacem

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This paper employs multivariate long memory GARCH models to simultaneously estimate mean and conditional variance spillover effects between oil prices and different financial markets. Since different financial assets are traded based on these market sector returns, it’s important for financial market participants to understand the volatility transmission mechanism over time and across these series in order to make optimal portfolio allocation decisions. We examine weekly returns from January 1, 2003 to November 30, 2012 and find evidence of significant transmission of shocks and volatilities between oil prices and some of the examined financial markets. The findings support the idea of cross-market hedging and sharing of common information by investors.

Keywords: oil prices, stock indices returns, oil volatility, contagion, DCC-multivariate (FI) GARCH

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Authors: Aleksandra Nocoń (Szunke)

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The study is a review of the literature concerning the consequences of non-standard monetary policy, which are used by central banks during unconventional periods, threatening instability of the banking sector. In particular, the attention was paid to the effects of non-standard monetary policy tools for financial markets. However, the empirical evidence about their effects and real consequences for the financial markets are still not final. The main aim of the study is to survey the consequences of standard and non-standard monetary policy instruments, implemented during the global financial crisis in the United States, United Kingdom and Euroland, with particular attention to the results for the stabilization of global financial markets. The study analyses the consequences for short and long-term market interest rates, interbank interest rates and LIBOR-OIS spread. The study consists mainly of the empirical review, indicating the impact of the implementation of these tools for the financial markets. The following research methods were used in the study: literature studies, including domestic and foreign literature, cause and effect analysis and statistical analysis.

Keywords: asset purchase facility, consequences of monetary policy instruments, non-standard monetary policy, quantitative easing

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Authors: Barbora Chmelikova

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Current financial markets offer a wide range of financial products to the consumers. However, access to the financial products is not always provided or guaranteed, particularly in less developed countries. For this reason, financial inclusion is an important component in the modern society. This paper investigates financial inclusion and what financial products are held by university students majoring in finance fields. The OECD methodology was used to examine the awareness and use of financial products. The study was conducted via online questionnaire at Masaryk University in the Czech Republic among finance students. The results show that the students use current and savings accounts more than any other financial products.

Keywords: financial inclusion, financial products, personal finance, university students

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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Authors: Walid Chkili

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This paper investigates the dynamic relationship between gold and stock markets using data for BRICS counties. For this purpose, we estimate three multivariate GARCH models (namely CCC, DCC and BEKK) for weekly stock and gold data. Our main objective is to examine time variations in conditional correlations between the two assets and to check the effectiveness use of gold as a hedge for equity markets. Empirical results reveal that dynamic conditional correlations switch between positive and negative values over the period under study. This correlation is negative during the major financial crises suggesting that gold can act as a safe haven during the major stress period of stock markets. We also evaluate the implications for portfolio diversification and hedging effectiveness for the pair gold/stock. Our findings suggest that adding gold in the stock portfolio enhance its risk-adjusted return.

Keywords: gold, financial markets, hedge, multivariate GARCH

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Authors: Murad A. Bein

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This paper empirically examines the time-varying relationship and spillover effects between the international crude oil price and ten emerging equity markets, namely three oil-exporting countries (Brazil, Mexico, and Russia) and seven Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czech Republic, Hungary, Poland, Romania, and Slovakia). The results revealed that there are spillover effects from oil markets into almost all emerging equity markets save Slovakia. Besides, the oil supply glut had a homogenous effect on the emerging markets, both net oil-exporting, and oil-importing countries (CEE). Further, the time variance drastically increased during financial turmoil. Indeed, the time variance remained high from 2009 to 2012 in response to aggregate demand shocks (global financial crisis and Eurozone debt crisis) and quantitative easing measures. Interestingly, the time variance was slightly higher for the oil-exporting countries than for some of the CEE countries. Decision-makers in emerging economies should therefore seek policy coordination when dealing with financial turmoil.

Keywords: crude oil, spillover effects, emerging equity, time-varying, aggregate demand shock

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Authors: Shamsuddeen Muhammad Ahmad

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The emergence and operations of Islamic Financial Institutions (IFIs) are being regarded as the new economic and financial pride at the global stage today. Admittedly, therefore, the IFIs has continued to impact positively on the economies of its host countries, especially the Gulf Cooperation Council (GCC) region, Asian and Western countries as well as making a steady in-road into the sub-Saharan Africa. Hence, the number of countries that adopted Islamic financial system in Africa has continued to increase. As a matter of fact, this paper examines the role and contributions of Islamic Financial Institutions (IFIs) to the economic growth and financial development of the big emerging markets in the African continent i.e. South Africa, Nigeria, and Egypt. The methods adopted for this study are descriptive, comparative and analytical in nature. Essentially, the findings from this study reveal that the three sampled countries are benefitting from the presence of IFIs in their economies in terms of contributions to economic growth and real sector participation, particularly for Egypt and South Africa. Similarly, they reap from foreign direct investments and economic diversification among others. However, this study recommends that African countries should integrate IFIs as part and parcel of their economic and financial systems, in order to benefit optimally from this new economic phenomenon.

Keywords: Islamic financial services, Africa, emerging markets, development, operation

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Authors: Miriam Sosa, Edgar Ortiz, Alejandra Cabello

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This paper examines the volatility changes and leverage effects of the MILA stock markets and their changes since the 2007 global financial crisis. This group integrates the stock markets from Chile, Colombia, Mexico and Peru. Volatility changes and leverage effects are tested with a symmetric GARCH (1,1) and asymmetric TARCH (1,1) models with a dummy variable in the variance equation. Daily closing prices of the stock indexes of Chile (IPSA), Colombia (COLCAP), Mexico (IPC) and Peru (IGBVL) are examined for the period 2003:01 to 2015:02. The evidence confirms the presence of an overall increase in asymmetric market volatility in the Peruvian share market since the 2007 crisis.

Keywords: financial crisis, Latin American Integrated Market, TARCH, GARCH

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Authors: Astha Sinha, Anjali Kanagali

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The United Kingdom’s withdrawal from the European Union, also termed as “Brexit,” took place on June 23, 2016 and immediately had global repercussions on the stock markets of the world. It is however expected to have a greater impact on the Banking sector in the UK. There is a two-fold effect on the earnings of banks which is being expected. First is of the trading activity and investment banking businesses being hit due to global weakness in financial markets. Second is that the banks having a large presence in the European Union will have to restructure their operations in order to cover other European countries as well increase their operating costs. As per the analysis, banks are expected to face rate cuts, bad loans, and tight liquidity. The directives in the Brexit negotiations on the Markets in Financial Instruments Directive (MiFID) will be a major decision to be taken for the Banking sector. New regulations will be required since most of the regulations governing the financial services industry allowing for the cross-border transactions were at the EU level. This paper aims to analyze the effect of Brexit on the UK Banking sector and changes in regulations that are expected due to the same. It shall also lay down the lessons learnt from the 2008 financial crisis and draw a parallel in terms of potential areas to be focused on for revival of the financial sector of Britain.

Keywords: Brexit, Brexit impact on UK, impact of Brexit on banking, impact of Brexit on financial services

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Authors: H. Florianová, J. Nešleha

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Financial derivatives are considered to be risky investment instruments which could possibly bring another financial crisis. As prevention, European Union and its member states have released new legal acts adjusting this area of law in recent years. There have been several cases in history of capital markets worldwide where it was shown that legislature may affect behavior of subjects on capital markets. In our paper we analyze main events on selected European stock exchanges in order to apply them on three chosen markets - Czech capital market represented by Prague Stock Exchange, German capital market represented by Deutsche Börse and Polish capital market represented by Warsaw Stock Exchange. We follow time series of development of the sum of listed derivatives on these three stock exchanges in order to evaluate popularity of those exchanges. Afterwards we compare newly listed derivatives in relation to the speed of development of these exchanges. We also make a comparison between trends in derivatives and shares development. We explain how a legal regulation may affect situation on capital markets. If the regulation is too strict, potential investors or traders are not willing to undertake it and move to other markets. On the other hand, if the regulation is too vague, trading scandals occur and the market is not reliable from the prospect of potential investors or issuers. We see that making the regulation stricter usually discourages subjects to stay on the market immediately although making the regulation vaguer to interest more subjects is usually much slower process.

Keywords: capital markets, financial derivatives, investors' behavior, regulation

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Authors: Aparna Viswanath

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Electricity spot prices are highly volatile under optimal generation capacity scenarios due to factors such as non-storability of electricity, peak demand at certain periods, generator outages, fuel uncertainty for renewable energy generators, huge investments and time needed for generation capacity expansion etc. As a result market participants are exposed to price and volume risk, which has led to the development of risk management practices. This paper provides an overview of risk management practices by market participants in electricity markets using financial derivatives.

Keywords: financial derivatives, forward, futures, options, risk management

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Authors: Sarkar Humayun Kabir

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This paper aims to investigate whether ethical investment instruments could contribute to stability in financial markets. In order to address the main issue, the study investigates the stability of return in seven conventional and Islamic equity markets of Asia, Europe and North America and in five major commodity markets starting from 1996 to June 2012. In addition, the study examines the unconditional correlation between returns of the assets under review to investigate portfolio diversification benefits of investors. Applying relevant methods, the study finds that investors may enjoy sustainable returns from their portfolios by investing in ethical financial instruments such as Islamic equities. In addition, it should be noted that most of the commodities, gold in particular, are either low or negatively correlated with equity returns. These results suggest that investors would be better off by investing in portfolios combining Islamic equities and commodities in general. The sustainable returns of ethical investments has important implications for the investors and markets since these investments can provide stable returns while the investors can avoid production of goods and services which believes to be harmful for human and the society as a whole.

Keywords: financial sustainability, ethical investment instruments, islamic equity, dynamic conditional correlation, conditional volatility

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Authors: Cristian Păuna

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In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: algorithmic trading, automated trading systems, high-frequency trading, DAX Deutscher Aktienindex

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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