"Full-Time AUTOMATED TRADING" – Matt DeLong | Trader Interview

Published on July 7, 2020

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In episode 192 of the Desire To Trade Podcast, I interview Matt DeLong, an algorithmic trader & business owner to discuss the process of running a fully automated trading business.

Over time, Matt went from being a manual day trader to making returns in the market through the use of algorithmic trading strategies.

While I find interest in the topic of algorithmic trading, I find a lot of value in speaking with people who are in-the-action and executing on their ideas. That’s primarily why I wanted to bring Matt on the show!

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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.

// Disclaimer
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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"Full-Time AUTOMATED TRADING" – Matt DeLong | Trader Interview

Forex Algorithmic Automated Trading, "Full-Time AUTOMATED TRADING" – Matt DeLong | Trader Interview.


How do you anticipate patterns in supplies?

Share Market Fad Analysis attempts to anticipate patterns in the market. If the predicted trend is advancing market run, you can ride that up until there is a pattern turnaround. As a capitalist, you can make earnings if you relocate with the patterns as well as not against it.

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

"Full-Time AUTOMATED TRADING" – Matt DeLong | Trader InterviewDevelop 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 Instance of Automated Trading

Royal Dutch Covering (RDS) is provided on the Amsterdam Stock Market (AEX) as well as London Stock Market (LSE).1 We start by building an algorithm to identify arbitrage chances. Right here are a couple of fascinating monitorings:

AEX trades in euros while LSE trades in British pound sterling.

Due to the one-hour time difference, AEX opens up a hr earlier than LSE adhered to by both exchanges trading at the same time for the following couple of hours and after that trading just in LSE throughout the last hr as AEX shuts.

Can we check out the opportunity of arbitrage trading on the Royal Dutch Covering stock listed on these 2 markets in 2 various money?


A computer program that can review current market prices.
Rate feeds from both LSE as well as AEX.
A forex (foreign exchange) rate feed for GBP-EUR.

  • Order-placing capacity that can path the order to the correct exchange.
    Backtesting capacity on historic rate feeds.
  • The computer program need to perform the following:.
  • Review the incoming rate feed of RDS stock from both exchanges.
  • Utilizing the available foreign exchange rates, convert the rate of one money to the other.
  • If there is a large adequate rate discrepancy (discounting the broker agent expenses) resulting in a successful possibility, after that the program needs to position the buy order on the lower-priced exchange as well as sell the order on the higher-priced exchange.
  • If the orders are executed as desired, the arbitrage revenue will certainly follow.

Easy as well as easy! However, the method of Automated trading is not that straightforward to keep as well as implement. Keep in mind, if one investor can position an algo-generated trade, so can other market participants. As a result, rates rise and fall in milli- as well as even split seconds. In the above example, what occurs if a buy trade is executed but the sell trade does not due to the fact that the sell rates change by the time the order hits the market? The investor will certainly be left with an employment opportunity making the arbitrage approach useless.

There are extra threats as well as challenges such as system failing threats, network connectivity errors, time-lags in between trade orders as well as execution as well as, essential of all, incomplete formulas. The even more complicated an algorithm, the more stringent backtesting is required prior to it is put into action.

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