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In episode 225 of the Desire To Trade Podcast, I interview DesireToTrade collaborator, full-time hybrid trader Alejandro Pérez.
Alejandro has been trading since 2012 and started to get into algo trading since early on, but it was recently when he made the change to mostly algo trading with some discretionary trading to complement. He is our resident algo expert at DesireToTrade and helps consult clients on developing their own algo strategies and automating their existing trading strategies.
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Best Platform: https://desiretotrade.com/tradingview
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VPS (for algo trading): https://desiretotrade.com/vps
Trading Journal: https://desiretotrade.com/journal
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// ABOUT ME
My name is Etienne Crete (from Montreal, Canada). I’m a swing Forex trader and help aspiring Forex traders develop a trading method that works for them so they can produce income allowing them to live with more freedom.
I blog at www.desiretotrade.com and host the Desire To Trade Podcast. I was fed up with the “fake” millionaire traders and the “get-rich-quick-trading guys”. That’s why you can expect more free content from me than what other people charge for!
If you truly want to succeed in Forex trading, I believe you need to keep working on yourself so you can improve your strengths, but also your weaknesses. Do not focus solely on what you’re good at.
This video expresses my personal opinion only. Forex trading is risky. Make sure you are ready to trade. Even this will not guarantee you positive results. I am not responsible for any losses incurred due to your trading or anything else. I do not recommend any specific trade or action.
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Forex Algorithmic Trading Interview, Becoming A Full-Time Algo Trader – Alejandro Perez | Trader Interview.
Can Trading Make You Rich?
Yes, its possible to make ample cash unavailable trading but the journey is long and laborious to become one. You will save a great deal of time and money by their discoverings. you require to have the right understanding of charts and market movements.
Recommended Book for Trading Strategies
Building Algorithmic Trading Systems: A Trader’s Journey From Data Mining to Monte Carlo Simulation to Live Trading, + Website
Book by Kevin J. Davey
Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader’s Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. read more…
Originally published: June 11, 2014
Author: Kevin J. Davey
An Example of Automated Trading
Royal Dutch Covering (RDS) is listed on the Amsterdam Stock Market (AEX) and London Stock Market (LSE).1 We begin by building a formula to identify arbitrage chances. Here are a few fascinating observations:
AEX sells euros while LSE sell British extra pound sterling.
Due to the one-hour time difference, AEX opens up an hour earlier than LSE adhered to by both exchanges trading all at once for the following few hrs and then trading just in LSE during the last hour as AEX closes.
Can we explore the opportunity of arbitrage trading on the Royal Dutch Covering stock listed on these two markets in two different money?
A computer program that can check out current market prices.
Rate feeds from both LSE and AEX.
A foreign exchange (forex) rate feed for GBP-EUR.
- Order-placing capacity that can course the order to the correct exchange.
Backtesting capacity on historical price feeds.
- The computer program ought to do the following:.
- Review the inbound price feed of RDS supply from both exchanges.
- Using the available foreign exchange rates, convert the price of one currency to the various other.
- If there is a huge sufficient price disparity (discounting the broker agent prices) bring about a rewarding possibility, after that the program must put the buy order on the lower-priced exchange and sell the order on the higher-priced exchange.
- If the orders are carried out as wanted, the arbitrage profit will follow.
Basic and easy! Nevertheless, the practice of Automated trading is not that basic to maintain and implement. Bear in mind, if one capitalist can put an algo-generated profession, so can various other market individuals. As a result, prices change in milli- and even microseconds. In the above instance, what takes place if a buy profession is carried out but the sell profession does not because the sell prices alter by the time the order hits the market? The investor will be entrusted to an employment opportunity making the arbitrage strategy worthless.
There are extra threats and challenges such as system failure threats, network connection errors, time-lags between profession orders and implementation and, most important of all, incomplete formulas. The more complex a formula, the much more strict backtesting is needed prior to it is put into action.
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