In this video, John Lockwood from Alto-Logic presents: A Low-Latency Library in FPGA Hardware for High-Frequency Trading (HFT). Recorded at the Hot Interconnects 2012 conference in Santa Clara.
„Current High-Frequency Trading (HFT) platforms are typically implemented in software on computers with high-performance network adapters. The high and unpredictable latency of these systems has led the trading world to explore alternative „hybrid“ architectures with hardware acceleration. In this paper, we describe how FPGAs are being used in electronic trading to approach the goal of zero latency. We present an FPGA IP library which implements networking, I/O, memory interfaces and financial protocol parsers. The library provides pre-built infrastructure which accelerates the development and verification of new financial applications. We have developed an example financial application using the IP library on a custom 1U FPGA appliance. The application sustains 10Gb/s Ethernet line rate with a fixed end-to-end latency of 1μ – up to two orders of magnitude lower than comparable software implementations.“
Learn more at: http://hoti.org
Keep up with daily supercomputing news: http://insidehpc.com
Cryptocurrency can be a high-risk, high-reward game for those willing to deal with the volatility. Can we use AI to help us make predictions about Bitcoin’s future price? In this video, i’ll show you how to build a simple Bitcoin trading bot using an LSTM neural network in Keras. Along the way I’ll explain why we use LSTM networks through code and animations, as well as a review of the vanishing gradient problem.
Code for this video:
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Welcome to the next tutorial covering deep learning with Python, Tensorflow, and Keras. We’ve been working on a cryptocurrency price movement prediction recurrent neural network, focusing mainly on the pre-processing that we’ve got to do. In this tutorial, we’re going to be finishing up by building our model and training it.
Text tutorials and sample code: https://pythonprogramming.net/crypto-rnn-model-deep-learning-python-tensorflow-keras/
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How to save time on Algo trading with Neural Networks? Comparison of main two methods of algorithmic trading
Disclaimer: Trading is a risk. Finance, Time, Psychology. Use this content to learn and practice data and computer science Video Rating: / 5
As a dividend stock investor who wants early retirement (also known as financial freedom), I highly favor individual (taxable) accounts for my stock portfolio. By contrast, retirement accounts (such as the Roth IRA and 401k) do not allow withdrawals before 65 years of age (unless one wants to pay a penalty). Since I plan to tap into my dividend income well before I’m 65 years old, I do not like retirement accounts for my personal situation.
Today’s video compares and contrasts taxable individual accounts vs. retirement accounts, from a dividend growth investing perspective.
Topics covered include:
* Types of stock brokerage accounts. Individual (also known as taxable), Roth IRA, and 401k.
* Pros and cons of individual accounts vs. retirement accounts.
* Why I love individual accounts for my dividend stock portfolio.
* Why I love the concept of an early retirement (or financial freedom). Even if I don’t retire early, I will surely tap into my massive cash flow.
* Why Roth style accounts are the best from a tax standpoint (if one does not plan to utilize funds until a traditional post-65 retirement).
* Why employer match (often in 401k accounts) is pure gold.
* Why 401k accounts could be risky since future taxes (at time of withdrawal) are unknown.
* Why mutual funds are a deal-breaker for me, except in the case of 401k employer match.
* How account optimization is a balancing act.
I hope you enjoy today’s video and please subscribe for more videos about dividend growth investing. Today’s video is a special one, set on the beautiful Ka’anapali Beach in Maui, Hawaii.
Disclaimer: I’m not a licensed investment advisor, and today’s video is just for entertainment and fun. This video is NOT investment advice. Please talk to your licensed investment advisor before making any financial decisions.
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