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Fundamentals of Engineering Mathematics bridges the gap between
school mathematics and a first year engineering degree providing
students with an essential foundation of skills that will be
valuable throughout their academic career and beyond. The book
covers the key areas including algebra, trigonometry and calculus
as well as more detailed coverage of topics such as the equilibrium
of bodies, dimensional analysis and experimental data analysis.
Use your programming skills to create and optimize high-frequency
trading systems in no time with Java, C++, and Python Key Features
* Learn how to build high-frequency trading systems with ultra-low
latency * Understand the critical components of a trading system *
Optimize your systems with high-level programming techniques Book
Description The world of trading markets is complex, but it can be
made easier with technology. Sure, you know how to code, but where
do you start? What programming language do you use? How do you
solve the problem of latency? This book answers all these
questions. It will help you navigate the world of algorithmic
trading and show you how to build a high-frequency trading (HFT)
system from complex technological components, supported by accurate
data. Starting off with an introduction to HFT, exchanges, and the
critical components of a trading system, this book quickly moves on
to the nitty-gritty of optimizing hardware and your operating
system for low-latency trading, such as bypassing the kernel,
memory allocation, and the danger of context switching. Monitoring
your system's performance is vital, so you'll also focus on logging
and statistics. As you move beyond the traditional HFT programming
languages, such as C++ and Java, you'll learn how to use Python to
achieve high levels of performance. And what book on trading is
complete without diving into cryptocurrency? This guide delivers on
that front as well, teaching how to perform high-frequency crypto
trading with confidence. By the end of this trading book, you'll be
ready to take on the markets with HFT systems. What you will learn
* Understand the architecture of high-frequency trading systems *
Boost system performance to achieve the lowest possible latency *
Leverage the power of Python programming, C++, and Java to build
your trading systems * Bypass your kernel and optimize your
operating system * Use static analysis to improve code development
* Use C++ templates and Java multithreading for ultra-low latency *
Apply your knowledge to cryptocurrency trading Who This Book Is For
This book is for software engineers, quantitative developers or
researchers, and DevOps engineers who want to understand the
technical side of high-frequency trading systems and the
optimizations that are needed to achieve ultra-low latency systems.
Prior experience working with C++ and Java will help you grasp the
topics covered in this book more easily.
Discover how to build and backtest algorithmic trading strategies
with Zipline Key Features Get to grips with market data and stock
analysis and visualize data to gain quality insights Find out how
to systematically approach quantitative research and strategy
generation/backtesting in algorithmic trading Learn how to navigate
the different features in Python's data analysis libraries Book
DescriptionAlgorithmic trading helps you stay ahead of the markets
by devising strategies in quantitative analysis to gain profits and
cut losses. The book starts by introducing you to algorithmic
trading and explaining why Python is the best platform for
developing trading strategies. You'll then cover quantitative
analysis using Python, and learn how to build algorithmic trading
strategies with Zipline using various market data sources. Using
Zipline as the backtesting library allows access to complimentary
US historical daily market data until 2018. As you advance, you
will gain an in-depth understanding of Python libraries such as
NumPy and pandas for analyzing financial datasets, and explore
Matplotlib, statsmodels, and scikit-learn libraries for advanced
analytics. You'll also focus on time series forecasting, covering
pmdarima and Facebook Prophet. By the end of this trading book, you
will be able to build predictive trading signals, adopt basic and
advanced algorithmic trading strategies, and perform portfolio
optimization. What you will learn Discover how quantitative
analysis works by covering financial statistics and ARIMA Use core
Python libraries to perform quantitative research and strategy
development using real datasets Understand how to access financial
and economic data in Python Implement effective data visualization
with Matplotlib Apply scientific computing and data visualization
with popular Python libraries Build and deploy backtesting
algorithmic trading strategies Who this book is forThis book is for
data analysts and financial traders who want to explore how to
design algorithmic trading strategies using Python's core
libraries. If you are looking for a practical guide to backtesting
algorithmic trading strategies and building your own strategies,
then this book is for you. Beginner-level working knowledge of
Python programming and statistics will be helpful.
Understand the fundamentals of algorithmic trading to apply
algorithms to real market data and analyze the results of
real-world trading strategies Key Features Understand the power of
algorithmic trading in financial markets with real-world examples
Get up and running with the algorithms used to carry out
algorithmic trading Learn to build your own algorithmic trading
robots which require no human intervention Book DescriptionIt's now
harder than ever to get a significant edge over competitors in
terms of speed and efficiency when it comes to algorithmic trading.
Relying on sophisticated trading signals, predictive models and
strategies can make all the difference. This book will guide you
through these aspects, giving you insights into how modern
electronic trading markets and participants operate. You'll start
with an introduction to algorithmic trading, along with setting up
the environment required to perform the tasks in the book. You'll
explore the key components of an algorithmic trading business and
aspects you'll need to take into account before starting an
automated trading project. Next, you'll focus on designing,
building and operating the components required for developing a
practical and profitable algorithmic trading business. Later,
you'll learn how quantitative trading signals and strategies are
developed, and also implement and analyze sophisticated trading
strategies such as volatility strategies, economic release
strategies, and statistical arbitrage. Finally, you'll create a
trading bot from scratch using the algorithms built in the previous
sections. By the end of this book, you'll be well-versed with
electronic trading markets and have learned to implement, evaluate
and safely operate algorithmic trading strategies in live markets.
What you will learn Understand the components of modern algorithmic
trading systems and strategies Apply machine learning in
algorithmic trading signals and strategies using Python Build,
visualize and analyze trading strategies based on mean reversion,
trend, economic releases and more Quantify and build a risk
management system for Python trading strategies Build a backtester
to run simulated trading strategies for improving the performance
of your trading bot Deploy and incorporate trading strategies in
the live market to maintain and improve profitability Who this book
is forThis book is for software engineers, financial traders, data
analysts, and entrepreneurs. Anyone who wants to get started with
algorithmic trading and understand how it works; and learn the
components of a trading system, protocols and algorithms required
for black box and gray box trading, and techniques for building a
completely automated and profitable trading business will also find
this book useful.
India has a rich heritage of knowledge on plant based drugs used in
traditional system of medicine. A large number of plants and
remedies were pharmacologically tested and useful data was
generated for development of therapeutic agents. Scientists are
searching newer avenues and material for drug development and for
that they are search for new medicinal plants, which are till date
not have been exploited to their fullest extent (except traditional
systems). The rich biodiversity of the tropical region all over the
world have attracted scientific attention and tropical region of
lower plane land of West Bengal is not an exception of that trend.
Hygrophila difformis is a tropical plant, accordingly in our
laboratory we have chosen this plant for the detail pharmacological
studies to fulfill our quench of thirst and to reveal whether this
plant could be utilized as an effective source for future medicine
development. In the course of the investigation it was found that
the methanolic fraction of the Hygrophila difformis leaf extract
possesses various kinds of activities.
The primary role of medicinal chemist has become one of improving
upon existing drugs by increasing their potency and duration of
action and by decreasing toxic side effects as well as creating new
drugs by molecular modifications. Very useful synthetic analogue
with improved therapeutic properties can be obtained from a single
lead compound by structural modification. The same applies to the
group of natural lactone of plant origin, one of the diverse and
important system of natural products with a broad spectrum
biological activities. Physiological activity of natural lactone is
known ever since santonine was used as anthelmintic and ascarisidal
agent. The biological importance of unsaturated lactone is well
known. The butenolide system is present in many cardiac glycosides
shows strong cardiotonic activity. In particular, the -alkylidene
butenolide skeleton is a useful entity that is present natural
products such as fibrolides, dihydroxerulin and protoanemonin.
Protoanemonin and its analogues possess antiviral, antibiotic and
anticancer activities."
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