Use powerful Python libraries such as pandas, NumPy, and SciPy
In this book, youâll cover different ways of downloading financial data and preparing it for modeling. Youâll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, and RSI, and backtest automatic trading strategies. Next, youâll cover time series analysis and models such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and Fama-French's Three-Factor Model. Youâll 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, youâll work through an entire data science project in the finance domain. Youâll also learn how to solve credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models.
Use powerful Python libraries such as pandas, NumPy, and SciPy
In this book, youâll cover different ways of downloading financial data and preparing it for modeling. Youâll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, and RSI, and backtest automatic trading strategies. Next, youâll cover time series analysis and models such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and Fama-French's Three-Factor Model. Youâll 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, youâll work through an entire data science project in the finance domain. Youâll also learn how to solve credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models.
BY Python đ Work With Data
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Chinaâs stock markets are some of the largest in the world, with total market capitalization reaching RMB 79 trillion (US$12.2 trillion) in 2020. Chinaâs stock markets are seen as a crucial tool for driving economic growth, in particular for financing the countryâs rapidly growing high-tech sectors.Although traditionally closed off to overseas investors, Chinaâs financial markets have gradually been loosening restrictions over the past couple of decades. At the same time, reforms have sought to make it easier for Chinese companies to list on onshore stock exchanges, and new programs have been launched in attempts to lure some of Chinaâs most coveted overseas-listed companies back to the country.
Telegram auto-delete message, expiring invites, and more
elegram is updating its messaging app with options for auto-deleting messages, expiring invite links, and new unlimited groups, the company shared in a blog post. Much like Signal, Telegram received a burst of new users in the confusion over WhatsAppâs privacy policy and now the company is adopting features that were already part of its competitorsâ apps, features which offer more security and privacy. Auto-deleting messages were already possible in Telegramâs encrypted Secret Chats, but this new update for iOS and Android adds the option to make messages disappear in any kind of chat. Auto-delete can be enabled inside of chats, and set to delete either 24 hours or seven days after messages are sent. Auto-delete wonât remove every message though; if a message was sent before the feature was turned on, itâll stick around. Telegramâs competitors have had similar features: WhatsApp introduced a feature in 2020 and Signal has had disappearing messages since at least 2016.
