151 Trading Strategies
Z. Kakushadze and J.A. Serur. 151 Trading Strategies. Cham, Switzerland: Palgrave Macmillan, an imprint of Springer Nature, 1st Edition (2018), XX, 480 pp; ISBN 978-3-030-02791-9
271 Pages Posted: 13 Sep 2018 Last revised: 19 Jun 2019
Date Written: August 17, 2018
La versión española de este artículo se puede encontrar en:https://ssrn.com/abstract=3402665.
We provide 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.
Note: This is a preview version containing parts of the following book: Z. Kakushadze and J.A. Serur. 151 Trading Strategies. Cham, Switzerland: Palgrave Macmillan, an imprint of Springer Nature, 1st Edition (2018), XX, 480 pp; ISBN 978-3-030-02791-9.
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
Suggested Citation: Suggested Citation