توضیحات

ارسال کتاب های زبان اصلی در بازه ۸ الی ۱۲ روزه انجام میشود.
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https://www.amazon.com/Python-Finance-Cookbook-libraries-financial/dp/۱۷۸۹۶۱۸۵۱۷
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Python for Finance Cookbook

by Eryk Lewinson (Author)
Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas

Key Features
Use powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial data
Explore unique recipes for financial data analysis and processing with Python
Estimate popular financial models such as CAPM and GARCH using a problem-solution approach
Book Description
Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries.

In this book, you’ll cover different ways of downloading financial data and preparing it for modeling. You’ll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you’ll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You’ll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you’ll work through an entire data science project in the financial domain. You’ll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You’ll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you’ll focus on learning how to use deep learning (PyTorch) for approaching financial tasks.