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Wavelet Neural Networks
A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by...
Weather Derivatives
Weather derivatives are financial instruments that can be used by organizations or individuals as part of a risk management strategy to minimize risk associated with adverse or unexpected weather conditions. Just as traditional contingent claims, a weather derivative has an underlying measure, such as: rainfall, wind, snow or temperature. Nearly $1 trillion of the U.S. economy is directly exposed to weather-related risk. More precisely, almost 30% of the U.S. economy and 70% of U.S. companies are affected by weather. The purpose of this monograph is to conduct an in-depth analysis of financial products that are traded in the weather market. Presenting a pricing and modeling approach for w...
The Palgrave Handbook of FinTech and Blockchain
Financial services technology and its effect on the field of finance and banking has been of major importance within the last few years. The spread of these so-called disruptive technologies, including Blockchain, has radically changed financial markets and transformed the operation of the industry as a whole. This is the first multidisciplinary handbook of FinTech and Blockchain covering finance, economics, and legal aspects globally. With comprehensive coverage of the current landscape of financial technology alongside a forward-looking approach, the chapters are devoted to the spread of structured finance, ICT, distributed ledger technology (DLT), cybersecurity, data protection, artificial intelligence, and cryptocurrencies. Given an unprecedented 2020, the contributions also address the consequences of the current emergency, and the pandemic stroke, which is revolutionizing social and economic paradigms and heavily affecting Fintech, Blockchain, and the banking sector as well, and would be of particular interest to finance academics and researchers alongside banking and financial services professionals.
Wavelet Neural Networks
A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by...
Technical Analysis for Algorithmic Pattern Recognition
The main purpose of this book is to resolve deficiencies and limitations that currently exist when using Technical Analysis (TA). Particularly, TA is being used either by academics as an “economic test” of the weak-form Efficient Market Hypothesis (EMH) or by practitioners as a main or supplementary tool for deriving trading signals. This book approaches TA in a systematic way utilizing all the available estimation theory and tests. This is achieved through the developing of novel rule-based pattern recognizers, and the implementation of statistical tests for assessing the importance of realized returns. More emphasis is given to technical patterns where subjectivity in their identification process is apparent. Our proposed methodology is based on the algorithmic and thus unbiased pattern recognition. The unified methodological framework presented in this book can serve as a benchmark for both future academic studies that test the null hypothesis of the weak-form EMH and for practitioners that want to embed TA within their trading/investment decision making processes.
HERCMA 2001
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Hacia un modelo estocástico eficiente para la valoración de activos financieros basado en el volumen de negociación: fundamentos teóricos e implementación práctica
Mientras que, dentro del Análisis Técnico, el volumen como variable sujeta a estudio ocupa un lugar de especial significación, en el análisis cuantitativo financiero, salvo algunas y remarcables excepciones, su importancia es bastante menor, cuando no marginal. La relativa escasez de fuentes bibliográficas es paralela a la falta de interés casi inherente a la investigación precio-volumen desde sus orígenes. No obstante, siendo ésta la principal razón que justifica el hecho de que no se haya ahondado lo suficiente en su estudio, podemos encontrar otras causas que le han impedido avanzar, causas por otro lado extrapolables a cualquier otra investigación cuantitativa que se sitúe al margen del análisis cuantitativo “convencional”. Entre esas causas destacaríamos: 1. Razones coyunturales y estructurales 2. Estandarización 3. Problemas de orden operativo
Stochastic Modelling of Electricity and Related Markets
The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than ...
