Pros and Cons of Trading Software vs. Manual Trading

I want to tell you the benefits of utilizing software to trade for yourself. Now, I have been a manual trader for many, many years. Now, utilizing software to trade for me over the last 30 days, I just want to go over my experience and the pros and cons on both sides of the coin.

One side of the coin, manual trading. The other side of the coin, software trading. Without further ado, let’s jump right to it. My name is Matt Jimenez, and if you don’t know who I am, I’m an entrepreneur who has worked with the greatest minds in finance over the last several years. I’m here to pour into you guys everything that they poured into me.

So today, I just want to be a realist. Let’s get down to manual trading pros and cons. On the flip side of it, I will talk about the pros and cons of software trading.

The first thing that I like to touch on is the implications of an emotional bias. As a manual trader, simply put, emotions come into play when making investments. Being so hands-on, quite literally hands-on, executing trades, you have an emotional bias to the position that you’re taking.

Whether it be in a certain asset that you love, or long or short, or your friend told you about it, there’s some type of bias there that will always give you an emotional input to what your action is. Utilizing software completely eliminates that. Forex god.

I’ve seen so many people, including myself, take positions based on emotion. But not only that, I’ve seen positions go south. You’ll execute a trade, and after X amount of time, the trade turns around. But it was going so well, and you’ve made such a big emphasis on your friends about this trade that you just simply don’t want it to go wrong. So you either continuously add more margin into the position and end up wiping yourself out.

There are so many caveats to how your emotions play into you executing trades that I simply cannot make a video long enough to elaborate on how in-depth your emotions play in your decision-making. Forex god. Literally, let’s break down the word emotion: it’s energy plus motion. Put them together, and you’re doing something with your energy at that current moment, translating it into a motion. Energy, motion, emotion—makes sense, right?

And the best thing about software is I don’t really have any intellectual input onto the software to say, ‘Do this trade or do that trade.’ There’s no bias there whatsoever. In fact, I am not even aware of all the trades it’s taking. Forex god. After a full day of trading, I have to go in and manually look at the log to see what we even did. I have no idea what we did that day because it did all the decision-making for me, which takes out a massive amount of stress.

As a manual trader, you’re thinking that you have to find a trade for the day, multiple trades for the day, multiple trades for the week, and so forth. Because now I’m not making any of the decisions myself, software trading eliminates all emotion. That is the number one benefit that I’ve felt thus far utilizing the software.

The next point I’d like to make is how omnipresent you could be on the charts as a manual trader. Let’s be real, there’s no possible way that you can be watching 24 pairs, which the software is always watching for me. I don’t have to watch any of it. There’s no way as a manual trader that you’re able to do that; it’s merely impossible. You could have as many monitors as you want. Even if you did fill up 24 charts on your monitors, you…

Please visit Pros and Cons of Trading Software vs. Manual Trading to watch the full video!

author avatar
Jeff Sekinger
Jeff Sekinger | Wealth Strategies

Search Posts

Algorithmic Trading Accelerator

Schedule a meeting with us!

Jeff Sekinger

Jeff Sekinger | Wealth Strategies

Latest Posts

The programming languages most widely used for automated and algo trading are Python, C++, Java, C#, and increasingly Rust, with

The three most widely deployed forex automated trading strategies are trend-following systems on major currency pairs, mean-reversion systems on range-bound

The five best algo trading books to read are “Advances in Financial Machine Learning” by Marcos Lopez de Prado, “Algorithmic

Professional headshot of an Asian man in a black suit, white shirt, and light blue tie against a white background.

AI Quantitative
Researcher

Bingham Zhou

Bingham Zhou, CFA, has over 15 years of experience as a quantitative researcher. His expertise spans systematic equity strategies, CTA trend-following, and interest rate proprietary trading in both U.S. and Asian markets. He holds advanced degrees from MIT, Carnegie Mellon, and Yale.

Portrait of a man with shoulder-length light brown hair and stubble, wearing a white shirt and black blazer against a gray background.
Quant–Investment Strategist
Greg doscher

Greg Doscher was a CFO for many years who built out many quantitative strategies and investment tools to manage and enhance risk adjusted returns in the company’s pension plan. Prior to joining Nurp, he consolidated his skills in coding and discretionary trading to develop a comprehensive and fully automated algorithmic trading system deployed across 200+ futures markets and cryptocurrencies that encompassed all of the trading strategies he had honed over the last 22 years in finance

Quant–Investment Strategist
Marcin Borratynski

Marcin was Head of Quant IT at the USD 4bn+ CERN Pension Fund, where he spent nearly a decade building quantitative asset allocation systems and implementing algorithmic investment strategies for a multi-asset institutional portfolio.Before joining Nurp Marcin was also Senior Quant Strategist at Evooq, a Swiss-based fund managing four strategies across equities, gold, and equity derivatives.Marcin holds a degree in Computer Science an MBA from the University of Geneva and the Certificate in Quantitative Finance (CQF).

Product Manager

Abhayjit Anand

Abhay has worked with Nurp since 2022. As a Product Strategist, he focuses on building, refining, and commercializing algorithmic trading strategies. He brings seven years of experience in financial trading – combining macro research, technical analysis, quantitative strategy development, and market psychology. Alongside his work at Nurp, Abhay also serves as an Investment Analyst at Orca Capital. Before entering financial markets professionally, he spent eight years at IBM, including three years in the AI & data division as a Delivery Lead managing complex implementation projects.