Algo Trading 101: Get Started With Bot Trading

Most traders who fail a funded account evaluation don’t have a strategy problem. According to Push Button Trading, 70% to 80% fall short because their discipline breaks down, and automation can help address exactly that.

In this webinar, Push Button Trading founder and CEO Matt DeLong showed how to get started with algo trading on NinjaTrader. DeLong has been a stock, options, and futures trader for 10 years, including seven years in trading automation. His pitch is simple: systems, not shortcuts.

 

Portfolios, not single bots

 

Algo trading, or bot trading, means software watches the market and places trades for you. DeLong explained that each bot monitors market conditions tick by tick and waits for a signal, which is the strategy coded into the bot. When the conditions are met, the bot places the order automatically instead of sending an alert for you to act on. Once it’s in a trade, it calculates a stop loss, a profit target, and exit rules, so you’re not sitting in a position all day. Push Button Trading’s technology is geared toward funded account programs that require traders to be in cash at the end of the day.

The common mistake is running a single bot. One strategy works in one market condition, and it can stop working when the environment changes. DeLong compared it to a thin t-shirt that works in summer but not winter, or a heavy coat that does the opposite. A Holy Grail strategy that never loses doesn’t exist.

The alternative is a portfolio: a handful of bots running different strategies, each suited to different conditions. When one strategy struggles, the others can pick up the slack, which can lead to more consistent results than a win-lose-win-lose pattern.

Push Button Trading’s top bot strategies draw from 586+ pre-built settings, each designed for a specific market condition, asset, and timeframe. DeLong walked through 15 of the company’s top bots, which NinjaTrader refers to as strategies. Each one can load a template, a set of preconfigured settings. The lineup includes the Mega Orb, a 10 exponential moving average (EMA) trend-following bot, a scalping bot, a mean-reversion bot called Snapback, breakout bots, and a volume-spike bot.

The Mega Orb is Push Button Trading’s adaptation of the opening range breakout (ORB), a popular strategy and one of the first DeLong learned. The template he showed trades the Micro E-mini S&P 500 Index (MES) on a 10-minute chart, exits automatically at a dynamically calculated profit target, and runs from 7:00 am to 9:00 am on Thursdays and Fridays. His second example, a volume bot, trades the MYM on a nine-minute chart with a 1:3 risk-reward ratio and runs from 6:00 am to 12:30 pm three days a week. Either can work well in some conditions and poorly in others, so running both together means one will typically perform while the other doesn’t, or vice versa. Both are only examples; traders decide what works for them.

 

Traders fail from execution, not strategy

 

DeLong calls it operator error, and it usually looks the same: emotions such as FOMO (fear of missing out) and revenge trading, inconsistency from trade to trade, and broken rules under pressure. Overleveraging, blowing up an account, and ignoring drawdown limits fall in the same category. None of those is a strategy problem, even though a losing streak makes the strategy the first thing traders want to blame.

The rules leave little room for those habits. DeLong used a $50,000 evaluation account as an example: the goal is to grow it to $53,000 with no time limit, without losing more than $2,000 overall or more than $1,000 in a single day. It can be trickier than it sounds because the drawdown grows as the account balance grows. Rules also vary by prop firm, including daily loss limits, maximum drawdown, and contract size limits.

Automation can help with each of those. Bots pull the trigger regardless of mood, sleep, or a bad day. Push Button Trading’s technology and NinjaTrader can also auto-exit and stop trading once limits are hit, which DeLong compared to a circuit breaker. Entries, exits, contract sizing, and risk calculations stay identical across thousands of trades, and that consistency matters because most strategies have a small edge that shows up over time. It can also help traders pass evaluations faster, though nothing is guaranteed.

 

Risk a small prop firm fee, not your life savings

 

Prop firm funded accounts let traders use third-party capital instead of their own. Traders pay a one-time evaluation fee, then pass a challenge by growing the account a set amount without breaking the loss rules. According to Push Button Trading, accounts range from $25,000 to $150,000 in third-party capital, evaluation fees can be as low as $100, and traders can keep 80% to 90% of the profits. Traders who pass can request payouts and scale to as many as 20 accounts.

Push Button Trading’s technology runs on NinjaTrader, so if a funded account works with NinjaTrader, DeLong said, it works with their system.

His advice for getting started: don’t bet the farm. Start with a single $50,000 account, prove the concept, and then scale. That can reduce potential losses, though nothing is guaranteed.

 

How backtests can provide insights

 

DeLong closed with a live demo of the Push Button Portfolio, which includes a builder and an analyzer for planning. Traders enter their funded account requirements, such as account size and drawdown, and set risk criteria. In the demo, he filtered for strategies that risk between $100 and $250, which he described as conservative to moderate for an account that allows up to $2,000 in losses. The tool then returned suggested portfolios from the pre-built settings.

Those results are combined backtests: the individual backtests of many bots, run together as a single portfolio. The example included bots trading micros, minis, and crude oil, tested back to January 2022. That produced 4,167 trades, which DeLong called a good sample size, across up, down, sideways, and wild markets.
From there, the analyzer breaks results down by month, year, and day of the week, and compares how the bots diversify across asset classes, strategies, days, and times of day. DeLong’s favorite feature is a simulation that launches the portfolio every month or week since January 2022 to show how often it would have passed an account versus blown up. In the example shown, the pass rate was 98%, and the same portfolio can be modeled across one account or five.

The caveats matter. These results are historical, not future profit, and with hundreds of millions of possible bot combinations, traders need to do their own research and set their own criteria.

 

Watch the full session

 

DeLong covers the live demo, the example bots, and the funded account rules in the full session. Watch the full webinar on YouTube.