Estrategias Trading

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Disclaimer: Trading carries a high level of risk, and may not be suitable for all investors. Before deciding to invest you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment. Therefore you should not invest money that you cannot afford to lose. You should be aware of all the risks associated with foreign exchange trading, and seek advice from an independent financial advisor if you have any doubts.

Los mejores corredores de opciones binarias 2020:
  • Binarium
    Binarium

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    Ideal para principiantes! Entrenamiento gratis! Bonos de registro!

  • FinMax
    FinMax

    Broker honesto!

Disclaimer: Trading carries a high level of risk, and may not be suitable for all investors. Before deciding to invest you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment and therefore you should not invest money that you cannot afford to lose. You should be aware of all the risks associated with foreign exchange trading, and seek advice from an independent financial advisor if you have any doubts.

151 Estrategias de Trading (151 Trading Strategies)

Z. Kakushadze y J.A. Serur. 151 Estrategias de Trading (Spanish Edition, 2020), 398 pp; ISBN 978-1071261873

398 Pages Posted: 19 Jun 2020 Last revised: 24 Sep 2020

Zura Kakushadze

Quantigic Solutions LLC; Free University of Tbilisi

Juan A. Serur

University of CEMA

Date Written: May 30, 2020

Abstract

The English version of this paper can be found at http://ssrn.com/abstract=3247865.

Spanish Abstract: Este libro proporciona descripciones detalladas, que incluyen más de 550 fórmulas matemáticas, para más de 150 estrategias de trading para una gran cantidad de clases de activos y estilos de trading. Esto incluye acciones, opciones, bonos (renta fija), futuros, ETFs, índices, commodities, divisas, bonos convertibles, activos estructurados, volatilidad (como clase de activos), bienes inmuebles, activos en distress, efectivo, criptomonedas, misceláneos (como clima, energía, inflación), macro global, infraestructura y arbitraje impositivo. Algunas estrategias se basan en algoritmos de aprendizaje automático (como redes neuronales artificiales, Bayes, k vecinos más cercanos). El libro también incluye código para backtesting fuera de la muestra con notas explicativas; cerca de 2,000 referencias bibliográficas; más de 900 términos que comprenden el glosario, acrónimos y definiciones matemáticas. La presentación pretende ser descriptiva y pedagógica, y de particular interés para los profesionales de las finanzas, traders, investigadores, académicos y estudiantes de escuelas de negocios y programas de finanzas.

Esto es la versión completa del siguiente libro: Z. Kakushadze y J.A. Serur. 151 Estrategias de Trading (Spanish Edition, 2020), 398 pp; ISBN 978-1071261873. Es la traducción del inglés al español del siguiente libro (cuya versión completa se puede encontrar aquí http://ssrn.com/abstract=3247865): Z. Kakushadze and J.A. Serur. 151 Trading Strategies. Cham, Switzerland: Palgrave Macmillan, an imprint of Springer Nature, 1st Edition (2020), XX, 480 pp; ISBN 978-3-030-02791-9.

English Abstract: This book, which is in Spanish, provides detailed descriptions, including over 550 mathematical formulas, for over 150 trading strategies across a host of asset classes (and trading styles). This includes stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility (as an asset class), real estate, distressed assets, cash, cryptocurrencies, miscellany (such as weather, energy, inflation), global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms (such as artificial neural networks, Bayes, k-nearest neighbors). We also give: source code for illustrating out-of-sample backtesting with explanatory notes; around 2,000 bibliographic references; and over 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.

This is the complete version of the following book: Z. Kakushadze and J.A. Serur. 151 Estrategias de Trading (Spanish Edition, 2020), 398 pp; ISBN 978-1071261873. The latter is a translation from English into Spanish of the following book (whose complete version can be found at http://ssrn.com/abstract=3247865): Z. Kakushadze and J.A. Serur. 151 Trading Strategies. Cham, Switzerland: Palgrave Macmillan, an imprint of Springer Nature, 1st Edition (2020), XX, 480 pp; ISBN 978-3-030-02791-9.

Note: Downloadable document is in Spanish.

Keywords: bond, cash, commodity, convertible bond, cryptocurrency, currency, distressed asset, energy, ETF, futures, global macro, index, infrastructure, market, option, backtesting, real estate, risk management, source code, statistical arbitrage, structured assets, tax arbitrage, trading strategy, weather

JEL Classification: G00, G10, G11, G12, G15, G20, G21, G23, G30, G33, G34

Trading Strategy

What is a Trading Strategy?

A trading strategy is the method of buying and selling in markets that is based on predefined rules used to make trading decisions.

Understanding Trading Strategies

A trading strategy includes a well-considered investing and trading plan that specifies investing objectives, risk tolerance, time horizon and tax implications. Ideas and best practices need to be researched and adopted then adhered to. Planning for trading includes developing methods that include buying or selling stocks, bonds, ETFs or other investments and may extend to more complex trades such as options or futures. Placing trades means working with a broker or broker dealer and identifying and managing trading costs including spreads, commissions and fees. Once executed, trading positions are monitored and managed, including adjusting or closing them as needed. Risk and return are measured as well as portfolio impacts of trades. The longer term tax results of trading are a major factor and may encompass capital gains or tax-loss harvesting strategies to offset gains with losses.

Key Takeaways

  • A trading strategy can be likened to a trading plan that takes into account various factors and exigencies for an investor.
  • It consists of three stages: planning, placing trades, and executing trades. At each stage of the process, metrics relating to the strategy are measured and changed based on the change in markets.

Developing a Trading Strategy

There are many types of trading strategies, but they are based largely on either technicals or fundamentals. The common thread is that both rely on quantifiable information that can be back tested for accuracy. Technical trading strategies rely on technical indicators to generate trading signals. Technical traders believe all information about a given security is contained in its price and it moves in trends. For example, a simple trading strategy may be a moving average crossover whereby a short-term moving average crosses above or below a long-term moving average.

Fundamental trading strategies take fundamental factors into account. For instance, an investor may have a set of screening criteria to generate a list of opportunities. These criteria are developed by analyzing factors such as revenue growth and profitability.

Another third type of trading strategy has gained prominence in recent times. A quantitative trading strategy is similar to technical trading in that it uses information relating to the stock to arrive at a purchase or sale decision. However, the matrix of factors that it takes into account to arrive at a purchase or sale decision regarding a security is considerably larger as compared to technical analysis. A quantitative trader uses several data points – regression analysis of trading ratios, technical data, price – to exploit inefficiencies in the market and conduct quick trades using technology.

Trading strategies are employed to avoid behavioral finance biases and ensure consistent results. For example, traders following rules governing when to exit a trade would be less likely to succumb to the disposition effect, which causes investors to hold on to stocks that have lost value and sell those that rise in value. Trading strategies can be stress tested under varying market conditions to measure consistency.

Profitable trading strategies are difficult to develop, however, and there is a risk of becoming over-reliant on a strategy. For instance, a trader may curve fit a trading strategy to specific back testing data, which may engender false confidence. The strategy may have worked well in theory based on past market data, but past performance does not guarantee future success in real time market conditions, which may vary significantly from the test period.

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