An exchange rate between two currencies can be described in a binary representation. The binarization algorithm transforms the exchange rate represented by tick data into a binary string. Each course change equal to a given discretization unit is assigned a binary value indicating the direction of the change. The performed statistical analysis confirms the existence of a correlation between previous course changes and the probability of future direction of the changes. In order to conduct a more detailed analysis of the exchange rate in a binary representation, each shift in the trajectory can be assigned a parameter representing the duration of the change. Depending on the current market dynamics, course trajectory changes may occur at different moments in time. The main goal of the presented research is to verify the existence of any dependences between the duration of a change and the probability of future direction of the change.
Application of simple prescriptions of technical analysis on the Warsaw Exchange Market (GPW) has been analyzed using several stocks belonging to WIG20 group as examples. Only long positions have been considered. Three well-known technical-analysis indicators of the market have been investigated: the Donchian channels, the Relative Strength Index, and Moving Average Convergence-Divergence indicator. Optimal values of parameters of those indicators have been found by „brute force“ evaluation of (linear) returns. It has been found that trading based on both Donchian channels and Relative Strength Index easily outperform the „buy and hold“ strategy if supplied with optimal values of parameters. However, those optimal values are by now means universal in the sense that they depend on particular stocks, and are functions of time. The optimal management of capital in the stock market strongly depends on the time perspective of trading. Finally, it has been argued that the criticism of technical analysis which is often delivered by academic quantitative financial science is unjustified as based of false premises.
Japan is one of the cradles of technical analysis. Methods developed there over the centuries are increasingly being used in other parts of the world, including Polish market. One of them is the Ichimoku technique that enables a quick and simple analysis of the market situation based on past price levels. The purpose of this article is to analyze the effectiveness of the investment signals generated by this method on example of WIG20 futures market.
PL
Japonia jest jedną z kolebek analizy technicznej. Metody tworzone tam na przestrzeni wieków są coraz częściej stosowane w innych częściach świata, w tym na rynku polskim. Jedną z nich jest technika Ichimoku, umożliwiająca szybką analizę sytuacji rynkowej w oparciu o przeszłe poziomy cenowe. Celem niniejszego artykułu jest przeanalizowanie skuteczności sygnałów inwestycyjnych, generowanych przez tą metodę, na przykładzie rynku kontraktów terminowych na WIG20.
An exchange rate can be expressed in the form of a binary-temporal representation. Such a representation is based on a discretization of movements in the exchange rate, in which to each change in the value - equal to a given discretization unit – two parameters are allocated: a binary value, consistent with the direction of change in the exchange rate (increase 1, decrease 0) and duration. Statistical examination proves the existence of dependencies between the parameters of previous changes and the direction of future changes. To model the exchange rate using the applied binary-temporal representation, an appropriate model was developed that enables estimation of the probability of the direction of future changes in the currency exchange rate based on the parameters of historical changes. This article presents an analysis of the influence of the chosen discretization unit on the quality of exchange rate modelling. For this purpose, software was written in MQL4 and C++. As a result of the study, an optimal value for the discretization unit and the optimal parameters of the model providing the highest efficiency were determined. The input data used in the analysis involved tick data for the AUD/NZD exchange rate for a five-year time frame 2012–2017.
The paper develops the concept of harnessing data classification methods to recognize patterns in stock prices. The author defines a formation as a pattern vector describing the financial instrument. Elements of such a vector can be related to the stock price as well as sales volume and other characteristics of the financial instrument. The study uses data concerning selected companies listed on the stock exchange in New York. It takes into account a number of variables that describe the behavior of prices and volume, both in the short and long term. Partitioning around medoids method has been used for data classification (for pattern recognition). An evaluation of the possibility of using certain formations for practical purposes has also been presented.
Statistical learning models have profoundly changed the rules of trading on the stock exchange. Quantitative analysts try to utilise them predict potential profits and risks in a better manner. However, the available studies are mostly focused on testing the increasingly complex machine learning models on a selected sample of stocks, indexes etc. without a thorough understanding and consideration of their economic environment. Therefore, the goal of the article is to create an effective forecasting machine learning model of daily stock returns for a preselected company characterised by a wide portfolio of strategic branches influencing its valuation. We use Nvidia Corporation stock covering the period from 07/2012 to 12/2018 and apply various econometric and machine learning models, considering a diverse group of exogenous features, to analyse the research problem. The results suggest that it is possible to develop predictive machine learning models of Nvidia stock returns (based on many independent environmental variables) which outperform both simple naïve and econometric models. Our contribution to literature is twofold. First, we provide an added value to the strand of literature on the choice of model class to the stock returns prediction problem. Second, our study contributes to the thread of selecting exogenous variables and the need for their stationarity in the case of time series models.
Purpose: Stock market participants use technical analysis to seek trends in stock price charts despite its doubtful efficiency. We tested whether technical analysis signals represent typical and common cognitive biases associated with the continuation or reversal of the trend. Methodology: We compared investors’ opinions about the predictive power of technical analysis signals grouped into five conditions: real technical analysis signals associated with trend continuation (real momentum signals) or trend reversal (real contrarian signals), fake momentum or fake contrarian signals, and fluctuation signals. Findings: Investors assigned larger predictive power to real and fake signals associated with trend continuation than to signals associated with trend reversal. Fake signals, which represented cognitive biases, elicited similar predictions about trend continuation or reversal to real technical analysis signals. Originality: Market players assess momentum signals to have greater predictive power than contrarian signals and neutral signals to have the least predictive power. These results are independent of whether technical analysis signals were well-known to investors or made up by experimenters. The hardwired propensity of our brains to detect patterns combined with the non-natural environment of the stock market creates the illusion of expertise that is not easy to dispel.
The purpose of the article/hypothesis: The aim of this article is to examine the effectiveness of trading systems built on the basis of technical analysis tools in 2015–2020 on the DAX stock exchange index. Efficiency is understood as generating positive rates of return, taking into account the risk incurred by the investor, as well as achieving better results than passive strategies. Presenting empirical evidence implying the value of technical analysis is a difficult task not only because of a huge number of instruments used on a daily basis, but also due to their almost unlimited possibility to modify parameters and often subjective evaluation. Methodology: The effectiveness of technical analysis tools was tested using selected investment strategies based on oscillators and indicators following the trend. All transactions were carried out on the Meta Trader 4 platform. The analyzed strategies were comprehensively assessed using the portfolio management quality measures, such as the Sharpe measure or the MAR ratio (Managed Account Ratio). Results of the research: The test results confirmed that the application of described investment strategies contributes to the achievement of effective results and, above all, protects the portfolio against a significant loss in the period of strong turmoil on the stock exchange. During the research period, only two strategies (Ichimoku and ETF- Exchange traded fund) would produce negative returns at the worst possible end of the investment. At the best moment, however, the „passive” investment achieved the lowest result. Looking at the final balance at the end of 2019, as many as four systems based on technical analysis were more effective than the „buy and hold” strategy, and at the end of the first quarter of 2020 – all of them. When analyzing the management quality measures, it turned out that taking into account the 21 quarters, the passive strategy had the lowest MAR index. The Sharpe’s measure is also relatively weak compared to the four leading strategies.
The purpose of the article/hypothesis: The aim of this article is to examine the effectiveness of trading systems built on the basis of technical analysis tools in 2015–2020 on the DAX stock exchange index. Efficiency is understood as generating positive rates of return, taking into account the risk incurred by the investor, as well as achieving better results than passive strategies. Presenting empirical evidence implying the value of technical analysis is a difficult task not only because of a huge number of instruments used on a daily basis, but also due to their almost unlimited possibility to modify parameters and often subjective evaluation.Methodology: The effectiveness of technical analysis tools was tested using selected investment strategies based on oscillators and indicators following the trend. All transactions were carried out on the Meta Trader 4 platform. The analyzed strategies were comprehensively assessed using the portfolio management quality measures, such as the Sharpe measure or the MAR ratio (Managed Account Ratio).Results of the research: The test results confirmed that the application of described investment strategies contributes to the achievement of effective results and, above all, protects the portfolio against a significant loss in the period of strong turmoil on the stock exchange. During the research period, only two strategies (Ichimoku and ETF- Exchange traded fund) would produce negative returns at the worst possible end of the investment. At the best moment, however, the „passive” investment achieved the lowest result. Looking at the final balance at the end of 2019, as many as four systems based on technical analysis were more effective than the „buy and hold” strategy, and at the end of the first quarter of 2020 – all of them. When analyzing the management quality measures, it turned out that taking into account the 21 quarters, the passive strategy had the lowest MAR index. The Sharpe’s measure is also relatively weak compared to the four leading strategies.
The aim of the article is to investigate the impact of algorithmic trading on the returns obtained in the context of market efficiency theory. The research hypothesis is that algorithmic trading can contribute to a better rate of return than when using passive investment strategies. Technological progress can be observed in many different aspects of our lives, including investing in capital markets where we can see changes resulting from the spread of new technologies. The methodology used in this paper consists in confronting a sample trading system based on classical technical analysis tools with a control strategy consisting in buying securities at the beginning of the test period and holding them until the end of this period. The results obtained confirm the validity of the theory of information efficiency of the capital market, as the active investment strategy based on algorithmic trading did not yield better results than the control strategy.
Kurs pary walutowej można zobrazować w postaci reprezentacji binarnej. Algorytm binaryzacji zamienia kurs reprezentowany przez dane tikowe na odpowiedni ciąg binarny. Podstawą algorytmu jest dyskretyzacja kursu, w której każdej zmianie wartości, równej zadanej jednostce dyskretyzacji, jest przypisywana wartość binarna zgodna z kierunkiem zmiany kursu. Badania statystyczne przeprowadzone przez autora potwierdziły istnienie zależności w binarnej reprezentacji kursu między historycznymi zmianami a dalszym kierunkiem zmian. Reprezentowany binarnie kurs może być zatem wykorzystany do wyznaczania kierunku i zakresu przyszłych zmian, a w konsekwencji budowy systemów HFT charakteryzujących się dodatnią stopą zwrotu. Jedną z podstawowych metod analizy technicznej jest analiza falowa. W artykule przedstawiono zastosowanie analizy falowej dla reprezentacji binarnej. W tym celu zaproponowano algorytmy pozwalające na detekcje fal, następnie dokonano analizy odpowiednich parametrów fal oraz ich wpływu na kierunek przyszłych zmian kursu walutowego USD/PLN. Proces binaryzacji kursu i algorytm wyznaczania fal został przeprowadzony na podstawie oprogramowania napisanego przez autora w języku MQL4 i C++.
EN
The exchange rate of a currency pair can be represented in a binary form. The binarization algorithm converts rates presented in tick data into an appropriate binary string. The basis for this algorithm is provided by an exchange rate discretization, in which each change in value equal to a given discretization unit is assigned a binary value, which corresponds to the direction of change. Statistical research performed by the author confirms dependencies of previous changes and future change of direction in binary representation of exchange rates. Thus, the binary representation can be applied in appointing the direction and scope of future changes, and consequently in the construction of HFT systems with positive rates of return. Wave analysis is one of the basic methods of technical analysis. The paper presents the application of wave analysis for binary representation. For this purpose, algorithms for wave detection are proposed, followed by the analysis of relevant wave parameters and their impact on the direction of future changes in the USD / PLN exchange rate. The binarization process and algorithm for appointing pairs is performed based on the author’s proprietary software written in the MQL4 and C++ language.
The phenomenon of technical analysis on financial markets is related to the effectiveness of technical analysis tools on the forex and futures markets, and huge popularity among investors. Classical models of financial markets do not provide the opportunity to examine the influence on prices of investors using technical analysis. Agent-based modeling, in particular, presented Westerhoff’s model, enables better understanding of the prices processes on the financial markets, by taking into account the interaction between different groups of investors. Statistical characteristics of assets’ prices on an artificial financial market did not differ from the values observed on the actual stock exchange. Matching linear regression model to the generated path allows positive verification of the hypothesis of greater volatility in periods of increased activity of investors using technical analysis methods.
PL
Fenomen analizy technicznej na rynkach finansowych jest związany z efektywnością narzędzi analizy technicznej na rynku walutowym i futures oraz ogromną popularnością wśród inwestorów. Klasyczne modele rynków finansowych nie dają możliwości zbadania wpływu inwestorów stosujących analizę techniczną na kształtowanie się cen. Modelowanie agentowe, w szczególności przedstawiony model Westerhoffa, pozwala lepiej zrozumieć mechanizmy działania rynków finansowych przez uwzględnienie interakcji między zwolennikami analizy technicznej i fundamentalnej. Notowania aktywów na sztucznym rynku finansowym nie odbiegały od wartości obserwowanych na rzeczywistej giełdzie pod względem własności statystycznych. Dopasowany model regresji liniowej do wygenerowanej ścieżki pozwolił pozytywnie zweryfikować hipotezę o większej zmienności cen w okresach zwiększonej aktywności inwestorów stosujących analizę techniczną.
Japan is the source of dozens of investment methods and strategies, which, thank to authors like Nison and Murphy are gaining popularity in other regions of the world. One of them, the Ichimoku Kinko Hyo technique, may be an important part of making investment decisions. The purpose of this article is to analyze the possibility of using this technique as a source of information about future changes in GDP growth in Poland.
PL
Japonia jest źródłem wielu metod i strategii inwestycyjnych, które dzięki takim autorom, jak Nison czy Murphy zyskują na popularności w pozostałych regionach świata. Jedna z nich, technika Ichimoku Kinko Hyo, może stanowić istotny element procesu podejmowania decyzji inwestycyjnych. W artykule została przeanalizowana możliwość zastosowania tej techniki jako źródła informacji o przyszłych zmianach dynamiki PKB w Polsce.
Analiza techniczna oraz indeks DJIA stanowią przedmiot rozważań artykułu. Celem publikacji jest przedstawienie teoretycznych oraz empirycznych podstaw analizy technicznej w kontekście indeksu DJIA. Na treść publikacji składa się opis pojęcia i genezy analizy technicznej, jej podstawowe narzędzia oraz historia stosowania indeksu DJIA.
EN
Technical analysis and the DJIA index are the subject of considerations in the article. The aim of the publication is to present the theoretical empirical basis of technical analysis in the context of the DJIA index. The content of the publication consists of a description of the concepts and origins of technical analysis, its basic tools and the history of the DJIA index.
Fluktuacje indeksu DJIA stanowią przedmiot rozważań artykułu. Celem publikacji jest przedstawienie empirycznych podstaw analizy technicznej w kontekście indeksu DJIA. Okres badań – w zależności od przyjętego interwału – obejmuje lata 1989-2012 i 2009-2012. Prognoza zmian wartości indeksu DJIA została przeprowadzona w dwóch etapach, które obejmowały kolejno interwał dzienny, tygodniowy, miesięczny i kwartalny. Pierwszy etap badań został przeprowadzony 8 czerwca 2012 roku. Na tej podstawie opracowano prognozy zmian wartości indeksu DJIA, które zostały następnie zweryfikowane w dniu 6 grudnia dla interwałów dziennego, tygodniowego i miesięcznego oraz w dniu 31 grudnia dla interwału kwartalnego. Analizy zostały sporządzone na podstawie danych zamieszczonych na stronie internetowej www.stooq.pl oraz programu do tworzenia wykresów Amibroker v. 5.50. Podstawowym narzędziem, które wykorzystano do badania były wykresy świecowe oraz pomocniczo – średnie kroczące i oscylator MACD.
EN
DJIA index fluctuations are the subject of considerations in the article. The aim of the publication is to present the empirical basis of technical analysis in the context of the DJIA index. The study period – depending on the particular interval – covers the years 1989-2012 and 2009-2012. Forecast for changes in the DJIA index was carried out in two stages, which included a successively intervals: daily, weekly, monthly and quarterly. The first stage of the research has been carried out on 8 June 2012. On this basis, forecasts for changes in the DJIA index. Then they were verified on 6 December for intervals daily, weekly and monthly on 31 December for quarterly interval. Analyses were based on data published on the website www.stooq.pl and the software to charting Amibroker v. 5.50. The main tool that was used to study Candlestick Patterns and auxiliary - moving averages and MACD oscillator.
Mając na uwadze nieprzypadkowy ruch cen przedmiotów handlu giełdowego, metodami i narzędziami teorii chaosu można pokazać, że zmiany cen podlegają prawom chaosu deterministycznego. Jest to nowe spojrzenie na ten temat w porównaniu z metodami statystycznymi stosowanymi od lat, które w większości przypadków zakładają, że rozkład stopy zwrotu z badanej serii jest normalny. Celem pracy jest określenie charakteru zmian cen ropy, dolara i polskich spółek paliwowych: czy są losowe czy zdeterminowane. Ponadto drugim celem jest zbadanie związku przyczynowo skutkowego między zmianami cen wyżej wymienionych walorów giełdowych. Wykorzystane zostaną narzędzia takie jak analiza przeskalowanego zakresu, analiza stabilności średniej i wariancji oraz analiza techniczna. Wnioski wynikające ze zbadania trzech wskazanych walorów powinny być interesujące dla uczestników rynku kapitałowego. Na końcu zamieszczono krótkookresową prognozę WIG-paliwa.
EN
With the non-random movement of the prices of exchange trading objects in mind, by means of the methods and tools of chaos theory, it is possible to show that price changes are subject to the laws of deterministic chaos. This is a new look at this subject compared to the statistical methods that have been used for years, which in most cases assume that the distribution of the rate of returns of the examined series is normal. The aim of the study is to determine the nature of the changes in oil, dollar and Polish fuel prices: whether they are random or determined. In addition, the second aim is to investigate the cause and effect relationship between the price changes of the above-mentioned stocks. Tools such as rescaled range analysis, mean and variance stability analysis and technical analysis will be used. Conclusions resulting from the examination of the three indicated values should be interesting for capital market participants. The article ends with a short-term forecast for WIG-oil&gas.
Technical analysis (TA) is a tool believed to support investor’s investment decisions. Even if research has demonstrated that TA cannot be used to make systematic profits over a long time period, it could potentially bring psychological payoffs to its users in the form of enhancing their confidence. In an experimental study we show that: (1) chartists demonstrate overconfidence in TA usage, believing that they are better than they actually are in TA formation recognition, and that; (2) the act of naming an observed trend as a TA formation brings extra confidence to the chartist, regardless of whether this is a real TA sequence or a random sequence. Thus, both naming an existing TA formation as a TA formation and naming a random sequence as a TA formation result in greater confidence.Also, irrespective of the high popularity of TA among investors, there are marked individual differences in TA followers. In a questionnaire study, we demonstrate that declared positive attitudes toward TA correlate positively with high need for (cognitive) closure (as measured by the Need for Cognitive Closure Scale; NFCS), specifically, desire for predictability.
PL
Technical analysis (TA) is a tool believed to support investor’s investment decisions. Even if research has demonstrated that TA cannot be used to make systematic profits over a long time period, it could potentially bring psychological payoffs to its users in the form of enhancing their confidence. In an experimental study we show that: (1) chartists demonstrate overconfidence in TA usage, believing that they are better than they actually are in TA formation recognition, and that; (2) the act of naming an observed trend as a TA formation brings extra confidence to the chartist, regardless of whether this is a real TA sequence or a random sequence. Thus, both naming an existing TA formation as a TA formation and naming a random sequence as a TA formation result in greater confidence. Also, irrespective of the high popularity of TA among investors, there are marked individual differences in TA followers. In a questionnaire study, we demonstrate that declared positive attitudes toward TA correlate positively with high need for (cognitive) closure (as measured by the Need for Cognitive Closure Scale; NFCS), specifically, desire for predictability.
According to the Efficient Market Hypothesis, investors cannot achieve above-average returns by using technical analysis tools. This paper attempts to answer the question as to what makes technical analysis popular, regardless of the efficiency of capital markets. The objective is to verify whether investors have certain cognitive inclinations that make them more likely to believe in the efficiency of technical analysis models. We postulate a positive relationship between different forms of overconfidence and faith in the effectiveness of technical analysis methods. This relationship was confirmed only in the case of the “better than average” effect. The two other examined forms of overconfidence, namely, overprecision and illusion of control, did not yield statistically significant results. However, the lack of confirmation by all three forms of overconfidence is in line with the results presented in the literature, namely, that there are no significant relationships between different forms of overconfidence.
PL
Zgodnie z hipotezą efektywności rynków inwestorzy stosujący narzędzia analizy technicznej nie mogą osiągać ponadprzeciętnych stóp zwrotu. Artykuł jest próbą odpowiedzi na pytanie dotyczące dużej popularności analizy technicznej, pomimo braku jej efektywności w świetle hipotezy efektywności rynków. Celem pracy jest weryfikacja, czy pewne inklinacje poznawcze sprawiają, że inwestorzy bardziej wierzą w efektywność modeli analizy technicznej. Postulujemy pozytywną zależność między różnymi formami nadmiernej pewności siebie a wiarą w efektywność metod analizy technicznej. Relacja ta została potwierdzona jedynie w wypadku efektu „lepszy niż średnia”. W przypadku dwóch kolejnych form – nadmiernej pewności siebie, miskalibracji oraz iluzji kontroli nie zanotowano statystycznie istotnych wyników. Brak potwierdzenia postulowanej zależności przez wszystkie trzy formy nadmiernej pewności siebie jest zgodny z wynikami dotychczas opublikowanymi w literaturze, mówiącymi o braku istotnych związków między różnymi formami nadmiernej pewności siebie.
The article discusses the role of the fundamental and technical analysis in investment decision-making on the capital market. An empirical investigation was conducted and exemplified by the Śnieżka S.A paint and varnish manufacturer. In order to estimate the fundamental value of the company, the discounted cash flow method was applied and the obtained company’s share value was compared with the current price on the Warsaw Stock Exchange. The technical analysis was conducted in different investment time horizons and an attempt was made to determine an investment recommendation for each of the horizons.
PL
W artykule omówiono rolę analizy fundamentalnej oraz analizy technicznej w procesie podejmowania decyzji inwestycyjnych na rynku kapitałowym. Badania empiryczne przeprowadzono na przykładzie Spółki Fabryka Farb i Lakierów Śnieżka S.A. Do oszacowania wartości fundamentalnej Spółki wykorzystano metodę zdyskontowanych przepływów pieniężnych, a uzyskaną jej wyniku cenę akcji Spółki porównano z aktualnie obowiązującą ceną na Giełdzie Papierów Wartościowych w Warszawie. Analizę techniczną natomiast przeprowadzono w różnych horyzontach czasowych inwestycji oraz podjęto próbę określenia rekomendacji inwestycyjnej dla każdego z nich.
Celem artykułu jest przedstawienie wybranych strategii inwestycyjnych na polskim rynku kapitałowym wraz z oceną ich zyskowności. Istotą stosowanych strategii jest określenie momentów, w których generowane są sygnały kupna lub sprzedaży walorów notowanych na GPW w Warszawie. W tym celu wykorzystano m.in. różne systemy średnich kroczących obliczonych dla głównych indeksów giełdowych w Polsce. Aby ocenić efektywność stosowanych strategii, przeprowadzono klasyczne testy istotności różnic średnich stóp zwrotu oraz zastosowano analizę symulacji metodą bootstrapową.
EN
The paper presents selected technical trading rules on the Polish stock market along with an estimate of the market’s profitability. Technical trading rules allow one to forecast changes to a stock price and identify buy and sell signals on Warsaw Stock Exchange. To do so, variable-length moving averages are applied to the main Polish stock indexes. To evaluate the economic effectiveness of the technical trading rules, t-statistics are used for testing the significance of the differences between average returns and the bootstrap techniques.
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