In August 2021, the U.S. Department of Justice repatriated an additional $452 million in 1MDB funds to Malaysia. This repatriation took the total amount recovered from the corruption scandal to $1.2 billion. The funds had been laundered through major financial institutions worldwide, including in the United States, Switzerland, Singapore, and Luxembourg. <br/> <br/> While there are multiple global regulations targeting money laundering, multiple estimates peg the size of money laundering between $800 billion to $2 trillion annually. While there are multiple commercially available AML packages, the core technologies are the ability to stream-process vast sources of information and intelligent algorithms to identify money laundering patterns. <br/> <br/> kandi collection on Anti-Money Laundering covers open source libraries across data scraping, stream processing, open source intelligence (OSINT Framework), anti-money laundering algorithms, and case management for anti-money laundering.

Binance operates the world's biggest bitcoin exchange and altcoin crypto exchange in the world by volume. The Financial Conduct Authority (FCA) has ruled that the firm cannot conduct any "regulated activity" in the UK. It also issued a consumer warning about Binance.com, advising people to be wary of adverts promising high returns on crypto-asset investments. The US Securities and Exchange Commission (SEC) and Japan's Financial Services Agency (FSA) had also issued warnings about Binance. <br/> <br/> Crypto exchanges allow customers to trade cryptocurrencies with other assets, such as money or other digital currencies. Exchanges may accept credit card payments, wire transfers, or other forms of charge in exchange for cryptocurrencies. The exchanges can send cryptocurrency to a user's wallet or convert digital currency balances into prepaid cards to withdraw funds from ATMs worldwide. In contrast, other digital currencies are backed by real-world commodities such as gold. The regulation of crypto exchanges differs from country to country. <br/> <br/> While Binance is a market leader, there are multiple other crypto exchanges. kandi collection on Binance Alternatives lists accelerators across other popular exchanges such as Robinhood Crypto, Coinbase, Poloniex, Uphold, and Kraken. Do not construe this as financial or legal advice.

Cryptocurrencies ushered in an era of digital assets that eased the medium of exchange while ensuring secure transaction records. As a result, the entire supply chain of creation and transfer is transparent, secure, and verifiable, making cryptocurrencies a mainstay in Fintech. Bitcoin was released in 2009 as an open source software and a decentralized cryptocurrency. Following Bitcoin, multiple cryptocurrencies have been created with Bitcoin and Ethereum holding market leadership. In April 2021, the total market cap of cryptocurrencies surpassed the USD two trillion mark. <br/> <br/> Cryptocurrencies bring transparency and speed. However, the lack of sovereign guarantees and central banking regulation has raised multiple governance issues. For example, the legality and taxation of cryptocurrencies vary by country and are still evolving. In addition, cryptocurrencies have been the target of speculation, fraud, theft, and darknet transactions that highlight the lack of central regulating authorities. <br/> <br/> Multiple factors impact the value of cryptocurrencies. The most famous factor in recent times is Elon Musk. While actions of leaders of states impacted their economies, cryptocurrencies are open to influence from nonstate actors. Elon Musk's Tesla announced it would buy $1.5 billion worth of bitcoin and said it would accept the virtual currency as payment for its electric cars. However, a few months later, Musk tweeted on the nonsustainable energy consumption of cryptocurrencies, knocking off their value. He increased the value of Dogecoin through his tweets. While there are more significant issues facing cryptocurrencies, Musk's tweets are probably the most visible ones, and accusations range from speculation to conflict of interest. <br/> <br/> kandi collection on Elon Musk Crypto Tweet Trackers provides you with public libraries that you can try for free and provide you functions to automate trades, review the impact of cryptocurrencies based on his tweets, and some other fun projects. Do not construe this as financial or legal advice.

Since 2019, retail trading has surged in the USA. With a combination of digital technology, access to financial advice (not guaranteed to be sound), reducing commissions, and folks confined at home with a pandemic, retail trading has been moving the markets. <br/> <br/> This volatile combination has birthed a class of stocks called 'Meme Stocks'. Meme stocks don't go by the textbook classifications of growth or value stock. They are discussed heavily by retail investors on Reddit, Stocktwits, Twitter, and other channels. They are primarily overpriced, volatile and the valuation does not line up with the hype. Only the early adopters profit from these stocks. Stocks of GameStop, AMC, SPACs have followed this trend. Meme stocks have significantly impacted the markets to the extent that hedge funds see short selling as risky until the retail wave subsides. With the U.S. central counterparty clearinghouses raising margin requirements, the liquidity needs have imposed trading restrictions for individual investors. <br/> <br/> Given the frenzy driven by digital technologies, there are over twenty thousand public libraries available for trading. kandi collection on Meme Stocks and Options Trading showcases public libraries that provide access to real-time and historical stock data, analytics solutions to understand trends and volatility, backtesting solutions to simulate trades, and full-fledged trading engines.

ProPublica* reported that billionaires pay little in income tax compared to their massive wealth, sometimes, even nothing. Their records show that the wealthiest can legally pay income taxes amounting to a tiny fraction of the billions their fortunes grow each year. The median American household earned about $70,000 annually and paid about 14% in federal taxes. The highest income tax rate of 37% applies for couples on earnings above $628,300. However, the 25 wealthiest Americans paid a true tax rate of only 3.4%. <br/> <br/> You will need sound financial advisors to achieve such tax rates. But as technologists, open source can help you in two remarkable ways. You can save significantly by using open source software, and you can use the below personal finance solutions to manage your wealth. <br/> <br/> Personal finance helps individuals and families handle their financial management. Based on the spectrum of personal financial activities, this can span across banking products (checking, savings accounts, cards, wallets, and loans) or investments (shares, bonds, mutual funds) and insurance (life, health, disability) products or retirement plans, social security, and income tax management. <br/> <br/> There are over 1,800 public libraries available for you to adopt personal finance solutions. kandi collection on Personal Finance Solutions showcases libraries across end-to-end personal finance management platforms, frameworks for creating your own accounting solution, simple budgeting solutions, and add-ons like mobile receipt scanners that make your life easier.

Did you know Bitcoin consumes more electricity than the whole country of Sweden? Bitcoin compares to over 10 times the global solar and wind energy produced. On a global scale, Bitcoin uses 0.66% of all electricity consumed worldwide. That is huge for a new-age digital currency! <br/> <br/> The core issue in cryptocurrencies has been mining. Most cryptocurrencies rely on a computational competition called Proof of Work (PoW). In this model, participants are rewarded with cryptocoins for adding transactions to the blockchainÆs globally distributed ledger. More computational capability means a higher chance to earn more cryptocoins. Application-specific ICs (ASICs) that accelerate mining, concentrated power over many cryptocurrencies. EthereumÆs ether-mining algorithm penalizes the use of ASICs. <br/> <br/> However, turning towards energy-efficient approaches, proof of stake (PoS) is a credible alternative to the PoW approach. Replacing the concept of all processors processing duplicate transactions, PoS randomly picks one to do the job to make this efficient. The validatorÆs stake or collateral ensures the authenticity of the validation. <br/> <br/> kandi collection on Sustainable Cryptocurrencies, lists energy efficient cryptocurrency libraries for you to try. Each may follow different approaches to improve sustainability over Bitcoin. <br/> <br/> For other cryptocurrencies or specific implementations, search on kandi.<br/> <br/> <I>Source credit for Bitcoin energy comparisons: <a href='https://cbeci.org/cbeci/comparisons' target='_blank'>https://cbeci.org/cbeci/comparisons</a> </I>

Cryptocurrency wallets are software programs that store your public and private keys and interface with various blockchain so users can monitor their balance, send money and conduct other operations. If you want to use Bitcoin or any other cryptocurrency, you will need to have a digital wallet. A cryptocurrency wallet is a software program designed to store your public and private keys, send and receive digital currencies, monitor their balance, and interact with various blockchains. You need to have a cryptocurrency wallet. The following libraries can be used to generate and manage keys, create wallets, sign transactions and broadcast them to the network among other functionalities.. The best JavaScript Cryptocurrency Wallet libraries in 2022:WalletConnect - A standard for connecting to web wallets using a QR Code; Uport - Self sovereign identity platform; Universal Login SDK - A complete identity and wallet system for Ethereum; Ethers.js - An open source library for building dapps on Ethereum.

Python accounting provides software components that enable powerful features in your financial application, like invoice generation, tax management, tax reminders, risk management, and lots more. Python development is ideal for analytics tools because of its gentle learning curve, flexibility, and open-sourced environment. It helps you build applications of many specializations, like machine learning, data analysis, financials, and cloud computing. Accountants can perform financial modeling in quantitative finance and tax solutions. A Python package enables the effective analysis of big data sets, large lists of numbers, and major financial data. You can also use these accounting libraries to simplify data visualization and statistical calculations. It makes working with invoices and structured data easier. <br/> <br/> Below are our 16 best Python accounting open-source libraries in 2021. InvoiceNet is a deep neural network that can view PDF, JPG, and PNG invoices and extract intelligent information from them. You can train custom models, add or remove fields, and save the extracted information to your system. Another library, Rotki, is a portfolio tracking, analytics, accounting, and tax reporting application that works in the crypto and financial sectors and protects your privacy. On the other hand, LNbits is a free and open-source wallet or accounts system that has unique API keys for each wallet. It has a lightning-network functionality via LNbits extension framework.

<img src="https://kandi.dev/owassets/java-algorithmic-trading-libraries-banner.png" alt="Java Algorithmic Trading" style="height:auto;max-width:100%;"/> Over the past few years, we’ve witnessed a significant rise in the usage of algorithmic trading bots, especially by sophisticated institutions. These bots follow a set of predefined rules and place and place trades to generate high-frequency profits in the stock market. However, the cryptocurrency market is still nascent, and yet algorithmic trading is now accessible to all retail and individual traders alike. Many of these trading bots are developed using Java libraries. Here are some of the best open-source algorithmic trading libraries in Java. Released under the Apache license, Coin Trader is a Java-based backend for trading cryptocurrencies. It is connected to many crypto exchanges and offers various features, including but not limited to simulated crypto trading live order execution, 24-hour OHLC bars, and backorder routing. Knowm’s XChange offers a simple and consistent API connecting more than 60 crypto exchanges with modular components which are under active development. Another one, ta4j, is an open-source, 100% pure Java library with 130+ indicators essential to technical analysis. It comes equipped with basic components which are necessary for creating, testing, and executing a range of trading strategies. Developers tend to use some of the following trending open-source libraries:

<img src="https://kandi.dev/owassets/python-algorithmic-trading-libraries-banner.png" alt="Python Algorithmic Trading" style="height:auto;max-width:100%;"/> Employing the accuracy of computational automation in HFT trading online has a host of benefits for the trader. Especially when using trading libraries written in Python, the developers get the benefit of utilizing a robust backtesting framework for trading strategies, facilitating a highly lucrative, high-speed financial transaction. Pythonic algorithmic trading is extensively supported by a large open-source community and requires fewer LOCs to be written, making it less buggy and faster to deploy than other programming languages. This is critical when playing in ultra-low latency trade in real-time, where bids are sold within the difference of microseconds to the competitors. The Zipline library provides a highly active ecosystem in its code. The second ranker in the list is the abu library, a quantitative trading system written in Python that features machine learning. At the third position in the list is freqtrade, which is a code package of a crypto trading bot that supports all major exchanges and can be controlled through Telegram. Check out some of the top open-source algorithmic trading libraries that provide code packages in Python. Check out some of the top and most widely-used open-source algorithmic trading libraries of 2022 that provide code packages in Python to developers.

The popularity of cryptocurrencies is at an all-time high, especially with the 2021 rush. While getting your head wrapped around how it really works can be frustrating, mining, trading, storing, and of course, creating cryptocurrencies has been made easier with technology. With Python, now you can create your own automated crypto trading bot, a Bitcoin wallet, and even code a blockchain without a lot of, well, coding. </br></br>There are many popular cryptocurrency libraries in Python. Say, Electrum is a Bitcoin wallet that ensures your private keys are encrypted and never leave your system. It guarantees zero downtime and is blazingly fast with cold storage options. Freqtrade is a cryptocurrency algorithmic trading software that enables you to program your strategy using pandas. With it, you can download market data and test your strategy using simulated money or even go directly into the live-trading mode. We also have LBRY which claims to do to publishing what Bitcoin did to money. With millions of people on its platform, it brings you a free and open network for digital content. Another such library, Vyper, is a contract-oriented language that targets the Ethereum Virtual Machine and aims to build secure smart contracts with simpler language implementation and auditability.

When trading in Forex, it is important to develop a trading bot that makes risk management easy - since Forex involves high-level financial market data. Python is one of the most popular programming languages for Forex because it enables the API to be functionally separated to perform buying and selling operations. Python-based open-source software supports both backtesting and live trading operations to help the traders develop sound strategies for a Forex application. Python libraries also provide code for working with real-time currency exchange rates. <br/> <br/> Below is a comprehensive list of the 26 best open-source python libraries for developing Forex algorithmic trading applications. If you are looking for a full-scale, event-driven library that transitions seamlessly from testing to live trading, then qsforex is for you. Yahoofinancials is a code package that enables you to pull data like indices, currencies, ETFs, etc. from Yahoo Finance. If you intend to trade in cryptocurrencies, bitex enables you to do that by using API classes without employing interface classes. Forex-python is a library that shows exchange rates and cyptocurrency price index using ratesapi.io.

A payment processing library can help make your eCommerce application-independent and well-equipped to handle multiple payment gateways. A PHP payment processing software enables multiple features like payment methods, secure authentication, integration with third-party software, etc. With this, you can add popular platforms like PayPal, Apple Pay, Google Pay, Stripe, UnionPay, and more to your web application. PHP allows developers to build fast and scalable applications that provide risk-free solutions to payment woes. With the help of these libraries, you can enable several online payment options like integration with the shopping cart, faster processing, multiple payment platforms, charge back prevention, fraud management, recurring billing, etc. <br/> <br/> Below are our 20 best PHP payment processing open source libraries in 2021. Omnipay is a framework agnostic, multi-gateway payment processing library built for PHP 5.6+. Its consistent API is fully unit tested and comes with an example application for beginners. Here, you can learn an API and use it in multiple projects without rewriting the code. Another library, InvoicePlane is a self-hosted open-source application that manages invoices, clients, and payments. Payum Bundle, on the other hand, is an MIT-licensed open-source project that offers all payment-related solutions. It supports both simple use cases as well as very advanced ones.

All new-age finance professionals committed to data analysis and data science are dependent on Python at some level. It is with Python that they can perform analysis on various financial data points. But Python turns out to be a formidable tool even while developing personal finance applications. For instance, you can scrape the web for personal finance data, download financial transactions, develop a budget tracking app, and so on, all with Python. <br/> <br/> With that in mind, let’s have a quick overview of some of the best open-source Python packages and libraries for personal finance. Ofxstatement is a tool developed with the intention to convert proprietary bank statements to OFX format which is the accepted format for major personal accounting systems. One of the best open-source Python packages, finance-dl is used for scraping personal finance data from various financial institutions. It performs best when used with beancount-import which is a tool for semi-automatic data importing. We also have MyMoney, which is essentially a web application for personal finance built with Django. It can manage your bank account, your transactions, analyze them and schedule them if they’re recurrent. MyMoney a simple tool with the goal to analyze your expenses.

One of the reasons why Python trading libraries are a good choice for analysis of the financial market is that Python is an OOP language. Each function in Python, and the data manipulated by it, belong to a unique object, making it possible to abstract individual functions. Quantitative finance banks on backtesting trading strategies - Python modules provide pre-written code with lowest possible error potential, making it a reliable language for risk analysis. Augmenting a Python code with a robust framework such as Django enables developers to create an analysis tool capable of machine learning and time series analysis of the market. <br/> <br/> Here is a great list of useful Python stock market tracker libraries you can use as a readymade solution for your programs. For crawling the historical data, specifically of China stocks, install the Tushare library. Another great library to have in your collection is yfinance, which gives you the capability of downloading market data. Qlib is a great tool for quantitative investments, providing the trader with capabilities of using AI in their stock trading applications.

Build automated stock trading, running backtests, improving trading algorithms, executing risk analysis, and more. Get ratings, code snippets & documentation for each library.

Build wallets, mine coins, integrate with crypto exchanges, trading bots, and more for Binance .Get ratings, code snippets & documentation for each library.

Build high quality encrypted wallets with other incredible features for your Bitcoin. Get ratings, code snippets & documentation for each library.

Build blockchain applications, smart contracts, distributed ledgers, wallets, token generation, cryptocurrencies and more for your application using Ruby.Get ratings, code snippets & documentation for each library.

Build high quality encrypted wallets with other incredible features for your choice of cryptocurrency. Get ratings, code snippets & documentation for each library.