Rengarajan holds a Master of Financial Engineering - University of
California, Berkeley and he works in the investment management
industry and specializes in providing economic and investment outlook
and strategy for global equity and government bond markets. He has an
educational background in financial engineering, business, and
engineering, and professional interests include business,
finance, economics, technology and related areas.
William S. Mallios
William S. Mallios
Forecasting in Financial and Sports Gambling Markets focuses on econometric models that adapt to evolving markets and drift as compared to statistical models which are based on recent information and have a relatively short life.
William Mallios explains the econometric tools
available for modeling financial and sports betting scenarios. In the
course of the book, several examples of applications for sports
gambling markets and financial market are provided with special cases
such as the effect of fixing markets.
Discussion on market
efficiency and its determinants are provided with an introduction to
adaptive drift modeling in the context of quantifying the
opportunities in gambling and financial markets.
The opacity and dynamics of markets is explained by describing the dilemma between social and economic efficiency and the efficient market hypothesis in reality.There is also an explanation about the importance of several recent developments in the financial markets including the financial crisis and how some market players like hedge funds are adapting to these changes.
Basic adaptive model concepts such as the adaptive
ARMA process and time varying volatility are introduced after a
background of modeling practises in quant funds who develop
parsimonious models and compete for staff and similar
Studies in Japanese candlestick charts develop
insights into market psychology and is a very convenient method to
chart simultaneous time series and price volatility. These charts are
used to detect timing points. The impact of special cases such as
Black Monday and insider trading on these charts are also
The extension of the chapter on candlesticks is the
treatment of candlesticks for major league baseball and explanation
into how to apply the concepts to MLB team/player
Modeling details on single equation adaptive drift modeling, variable selection and identifying the reduced model, reduced model estimation, and adaptive GARCH processes are covered. Single equation modeling of sports gambling markets is covered with application of adaptive drift modeling techniques and modeling profile of several sports team and individual players.
based models for simultaneous financial time series and system of
simultaneous time series with feedback between series highlight the
application of adaptive drift and volatility modeling. There are good
case studies of info tech stocks in 2000 and modeling of
co-integrated time series associated with NBA and NFL.
There is a
treatment of additional topics including categorical forecasting,
risk assessment, bayesian discrete analysis and logistic regression
analysis, and allocating monies in sports gambling
Forecasting in Financial and Sports Markets provides a good balance between several cases in financial markets and sports betting markets where statistical methods such as co-integration are of use and the actual mechanics of constructing and using models that deploy these statistical methods. Although not an introductory book, it should appeal to the intermediate readers who are looking not just for a cookbook but a book which will help them gain intuition in using adaptive drift methods to real world applications.