Cílem této studie bylo implementovat algoritmické obchodní strategie na dvou nejoblíbenějších měnových párech EUR / USD, USD / JPY. Práce se také zabývá tématy, devizovým trhem FOREX, charakteristikou a vztahem mezi EUR / USD a USD / JPY. a technické ukazatele. Historická data pro vybrané měnové páry sloužila jako základní data pro další výpočty. Exel se ukázal jako překvapivě dostačující, výzkum ukázal schopnost Excelu v backtesting algoritmických obchodních strategií. Pro profesionální obchodníky Excel prostě nepředstavuje dokonalý nástroj pro testování strategií, ale není kontraproduktivní. Existuje řada technických ukazatelů, které pomáhají při určování pohybu finančního trhu. Na závěr, algoritmické obchodování vyžaduje mnoho rozšířených znalostí v počítačových programech a návrhu algoritmů. Exel je veřejně známá platforma se zavedenými funkcemi běžnějšími pro potenciální uživatele.
Anotace v angličtině
This study aimed to implement algorithmic trading strategies on the two most popular currency pairs EUR/USD, USD/JPY. The thesis also covers topics, FOREX exchange market, characteristics and relationship between EUR/USD and USD/JPY. and technical indicators. The historical data for selected currency pairs served as the base data for further computations. Exel has proven to be surprisingly sufficient, the research has shown the capability of Excel in backtesting algorithmic trading strategies. For professional traders, Excel simply does not represent a perfect tool for testing strategies, but it is not counterproductive. There exist a various number of technical indicators, which are helping factors in determinating the financial market's movement. In conclusion, algorithmic trading requires a lot of enhanced knowledge in computer programs and design of algorithms. Exel is a publicly known platform with entrenched features more common to potential users.
Klíčová slova
obchood, algoritmus, měna, indikátor
Klíčová slova v angličtině
trade, currency, algorithm, indicator
Rozsah průvodní práce
55
Jazyk
AN
Anotace
Cílem této studie bylo implementovat algoritmické obchodní strategie na dvou nejoblíbenějších měnových párech EUR / USD, USD / JPY. Práce se také zabývá tématy, devizovým trhem FOREX, charakteristikou a vztahem mezi EUR / USD a USD / JPY. a technické ukazatele. Historická data pro vybrané měnové páry sloužila jako základní data pro další výpočty. Exel se ukázal jako překvapivě dostačující, výzkum ukázal schopnost Excelu v backtesting algoritmických obchodních strategií. Pro profesionální obchodníky Excel prostě nepředstavuje dokonalý nástroj pro testování strategií, ale není kontraproduktivní. Existuje řada technických ukazatelů, které pomáhají při určování pohybu finančního trhu. Na závěr, algoritmické obchodování vyžaduje mnoho rozšířených znalostí v počítačových programech a návrhu algoritmů. Exel je veřejně známá platforma se zavedenými funkcemi běžnějšími pro potenciální uživatele.
Anotace v angličtině
This study aimed to implement algorithmic trading strategies on the two most popular currency pairs EUR/USD, USD/JPY. The thesis also covers topics, FOREX exchange market, characteristics and relationship between EUR/USD and USD/JPY. and technical indicators. The historical data for selected currency pairs served as the base data for further computations. Exel has proven to be surprisingly sufficient, the research has shown the capability of Excel in backtesting algorithmic trading strategies. For professional traders, Excel simply does not represent a perfect tool for testing strategies, but it is not counterproductive. There exist a various number of technical indicators, which are helping factors in determinating the financial market's movement. In conclusion, algorithmic trading requires a lot of enhanced knowledge in computer programs and design of algorithms. Exel is a publicly known platform with entrenched features more common to potential users.
Klíčová slova
obchood, algoritmus, měna, indikátor
Klíčová slova v angličtině
trade, currency, algorithm, indicator
Zásady pro vypracování
ZÁSADY PRO VYPRACOVÁNÍ:
Cíl:
- I will compare multiple algorithmic trading strategies which are applied for trading USD/EUR, USD/JPY
- The strategies are going to be backtested on various types of indicators such as Stocahstic oscillator, CMF indicator or ATR.
- The strategies are going to be backtested on time series of the length of one year
- The performance of the chosen algorithmic trading strategies (in terms of total revenues/losses) will be compared in the respective time-periods and overall and the buy and hold strategy will be used as a universal benchmark.
Metody:
- Excel platform will be employed for calculating indicators applied to foresee of future price movements.
- The platform is going to be used for a purpose of creating the trading rules of algorithmic trading strategies.
- An example of one of the implemented strategies is when the buy signal is generated when the value of Stocahstic oscillator < 20 and the sell singal is generated when Stocahstic oscillator >80.
Data:
- I will process the data acquired from the metatrader platform provided by GKFX brooker.
- My work will take place in ideal conditions, where are applied only historical data
- I will only consider 2017-2019 period for testing my strategies
- The data will be also taken from: www.tradingeconomics.com
- The frequency of the data used for the analysis is four hour data
Zásady pro vypracování
ZÁSADY PRO VYPRACOVÁNÍ:
Cíl:
- I will compare multiple algorithmic trading strategies which are applied for trading USD/EUR, USD/JPY
- The strategies are going to be backtested on various types of indicators such as Stocahstic oscillator, CMF indicator or ATR.
- The strategies are going to be backtested on time series of the length of one year
- The performance of the chosen algorithmic trading strategies (in terms of total revenues/losses) will be compared in the respective time-periods and overall and the buy and hold strategy will be used as a universal benchmark.
Metody:
- Excel platform will be employed for calculating indicators applied to foresee of future price movements.
- The platform is going to be used for a purpose of creating the trading rules of algorithmic trading strategies.
- An example of one of the implemented strategies is when the buy signal is generated when the value of Stocahstic oscillator < 20 and the sell singal is generated when Stocahstic oscillator >80.
Data:
- I will process the data acquired from the metatrader platform provided by GKFX brooker.
- My work will take place in ideal conditions, where are applied only historical data
- I will only consider 2017-2019 period for testing my strategies
- The data will be also taken from: www.tradingeconomics.com
- The frequency of the data used for the analysis is four hour data
Seznam doporučené literatury
SEZNAM DOPORUČENÉ LITERATURY:
Taylor, Mark P, and Helen Allen. 1992. "The Use of Technical Analysis in the Foreign Exchange Market." Journal of International Money and Finance 11 (3): 304-14. https://doi.org/https://doi.org/10.1016/0261-5606(92)90048-3.
HENDERSHOTT, TERRENCE, CHARLES M JONES, and ALBERT J MENKVELD. 2011. "Does Algorithmic Trading Improve Liquidity?" The Journal of Finance 66 (1): 1-33. https://doi.org/10.1111/j.1540-6261.2010.01624.x.
Hendershott, Terrence, and Ryan Riordan. 2009. "Algorithmic Trading and Information." https://econpapers.repec.org/RePEc:net:wpaper:0908.
Neely, Christopher J., 2002, The temporal pattern of trading rule returns and exchange rate intervention: Intervention does not generate technical trading rule profits, Journal of International Economics 58, 211-232
Osler, Carol L, 2005, Stop-loss orders and price cascades in currency markets, Journal of International Money and Finance 24, 219-241.
Chaboud, Alain, Ben Chiquoine, Erik Hjalmarsson, and Clara Vega, 2009, Rise of the machines: Algorithmic trading in the foreign exchange market, Working paper, Federal Reserve System.
Brock, William, Josef Lakonishok, and Blake LeBaron, 1992, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance 47, 1731-1764.
Nick K. Lioudis, June 14, 2018 10:49 PM EDT, Strategies for part-time forex traders, https://www.investopedia.com/articles/forex/11/part-time-forex-strategies.asp.
Jean Folger, August 5, 2018 8:53 AM EDT Automated Trading Systems: The Pros and Cons, https://www.investopedia.com/articles/trading/11/automated-trading-systems.asp.
Crescenzio Gallo, July 20, 2014, The Forex Market in Practice: A Computing Approach for Automated Trading Strategies, https://www.omicsonline.org/open-access/the-forex-market-in-practice-a-computing-approach-for-automated-trading-strategies-2162-6359.1000169.php?aid=28656.
Seznam doporučené literatury
SEZNAM DOPORUČENÉ LITERATURY:
Taylor, Mark P, and Helen Allen. 1992. "The Use of Technical Analysis in the Foreign Exchange Market." Journal of International Money and Finance 11 (3): 304-14. https://doi.org/https://doi.org/10.1016/0261-5606(92)90048-3.
HENDERSHOTT, TERRENCE, CHARLES M JONES, and ALBERT J MENKVELD. 2011. "Does Algorithmic Trading Improve Liquidity?" The Journal of Finance 66 (1): 1-33. https://doi.org/10.1111/j.1540-6261.2010.01624.x.
Hendershott, Terrence, and Ryan Riordan. 2009. "Algorithmic Trading and Information." https://econpapers.repec.org/RePEc:net:wpaper:0908.
Neely, Christopher J., 2002, The temporal pattern of trading rule returns and exchange rate intervention: Intervention does not generate technical trading rule profits, Journal of International Economics 58, 211-232
Osler, Carol L, 2005, Stop-loss orders and price cascades in currency markets, Journal of International Money and Finance 24, 219-241.
Chaboud, Alain, Ben Chiquoine, Erik Hjalmarsson, and Clara Vega, 2009, Rise of the machines: Algorithmic trading in the foreign exchange market, Working paper, Federal Reserve System.
Brock, William, Josef Lakonishok, and Blake LeBaron, 1992, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance 47, 1731-1764.
Nick K. Lioudis, June 14, 2018 10:49 PM EDT, Strategies for part-time forex traders, https://www.investopedia.com/articles/forex/11/part-time-forex-strategies.asp.
Jean Folger, August 5, 2018 8:53 AM EDT Automated Trading Systems: The Pros and Cons, https://www.investopedia.com/articles/trading/11/automated-trading-systems.asp.
Crescenzio Gallo, July 20, 2014, The Forex Market in Practice: A Computing Approach for Automated Trading Strategies, https://www.omicsonline.org/open-access/the-forex-market-in-practice-a-computing-approach-for-automated-trading-strategies-2162-6359.1000169.php?aid=28656.
Přílohy volně vložené
Taylor, Mark P, and Helen Allen. 1992. "The Use of Technical Analysis in the Foreign Exchange Market." Journal of International Money and Finance 11 (3): 304-14. https://doi.org/https://doi.org/10.1016/0261-5606(92)90048-3.
HENDERSHOTT, TERRENCE, CHARLES M JONES, and ALBERT J MENKVELD. 2011. "Does Algorithmic Trading Improve Liquidity?" The Journal of Finance 66 (1): 1-33. https://doi.org/10.1111/j.1540-6261.2010.01624.x.
Hendershott, Terrence, and Ryan Riordan. 2009. "Algorithmic Trading and Information." https://econpapers.repec.org/RePEc:net:wpaper:0908.
Neely, Christopher J., 2002, The temporal pattern of trading rule returns and exchange rate intervention: Intervention does not generate technical trading rule profits, Journal of International Economics 58, 211-232
Osler, Carol L, 2005, Stop-loss orders and price cascades in currency markets, Journal of International Money and Finance 24, 219-241.
Chaboud, Alain, Ben Chiquoine, Erik Hjalmarsson, and Clara Vega, 2009, Rise of the machines: Algorithmic trading in the foreign exchange market, Working paper, Federal Reserve System.
Brock, William, Josef Lakonishok, and Blake LeBaron, 1992, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance 47, 1731-1764.
Nick K. Lioudis, June 14, 2018 10:49 PM EDT, Strategies for part-time forex traders, https://www.investopedia.com/articles/forex/11/part-time-forex-strategies.asp.
Jean Folger, August 5, 2018 8:53 AM EDT Automated Trading Systems: The Pros and Cons, https://www.investopedia.com/articles/trading/11/automated-trading-systems.asp.
Crescenzio Gallo, July 20, 2014, The Forex Market in Practice: A Computing Approach for Automated Trading Strategies, https://www.omicsonline.org/open-access/the-forex-market-in-practice-a-computing-approach-for-automated-trading-strategies-2162-6359.1000169.php?aid=28656.
Přílohy vázané v práci
ilustrace, grafy, tabulky
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Ano
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