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Micah Lamar's Payday Cycle Strategy

Micah has been trading options for over 12 years. He’s done everything from buying and selling calls and puts, to spreads, to butterflies, and advanced trading. He loves the complexity of options trading. Micah is also the CEO of, which is a social network for traders. They’ve also built the fastest stock and options backtesting tool in the world. They’re using it to backtest and crowdsource ideas to help their community improve their trading strategies. Micah shares details on their platform as well as his Payday Cycle Strategy in this episode of How To Trade It!

In this episode of How To Trade It, learn @WallStreet_io Payday Cycle Strategy! #stocks #stock #trading #StockMarket #Investing #DayTrading #StockPicks #options #OptionsTrading #Payday Click To Tweet

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You’ll want to hear this episode if you are interested in…

  • [1:22] What Micah is doing now
  • [2:53] The complexity of options
  • [4:55] How a member made $1.5 million
  • [7:53] The payday cycle strategy
  • [12:59] Creating a social network with tools
  • [18:21] Crowdsourcing to create data
  • [21:23] The future of
  • [24:05] What you get when you sign up

How a community member made $1.5 million

One of Micah’s community members took $250,000 and followed the Payday Cycle Strategy and turned it into $1.5 million. How? He has used the strategy six times a quarter since 2019. Every time he got a signal for the strategy he bought options 90 days out. When the payday cycle exited, he sold them. In the beginning, he started by buying 20 calls and now he’s buying 200 at a time. The last position he closed was a $200,000 gain.

Every time he made a huge chunk of money he bought Apple stock. He now has 3,500 shares of Apple and is expecting to make $250,000–$300,000 a year by selling covered calls off of the shares that he owns. He goes out of the money and collects income every time the stock rallies. He’s taken an aggressive approach with call options, bought a permanent asset (Apple), he’s collecting dividends, he’s got cashflow, etc. He could retire off of this after 2 years of work.

The Payday Cycle Strategy

When Micah first started trading, he struggled with everything. He couldn’t find anything that stuck. He was looking at some charts one night and found the Heikin-Ashi chart. It really helped smooth out the trend and made it easier to see direction and momentum. It turned a candlestick chart into something that was either green or red. It was a light-bulb moment for Micah. He started trading it and immediately improved.

Over the years, he’s added a few things to it. The Heikin-Ashi chart smooths out the trend. So if you buy Apple on the first green when at the close and sell at the first red, over the course of the year it’s very profitable. A cycle lasts 4–8 days. Micah discovered that if you use a secondary indicator like a moving average or a MACD, you can increase your profitability by reducing pump-fake or false starts.

It has a 50% batting average, but the risk-reward is a 2—so you make twice as much as you lose. But if you add a MACD into the mix, and take the trade when the MACD is bearish, the batting average drops to 37%. So they’ve learned you don’t take the trade when it’s bearish. Only taking the trade when it’s bullish lowers the number of trades you’re taking but bumps your batting average up to 67% and increases your risk-reward.

It’s a trend-based strategy. When Apple is in an uptrend, you want to be trading the payday cycle to the upside. If it’s selling off or in a temporary downtrend, you can make profits by buying puts, shorting stock, etc. It’s designed to catch trades in both directions.

What is the Payday Cycle Strategy? @WallStreet_io shares all about it in this episode of How To Trade It! #stocks #stock #trading #StockMarket #Investing #DayTrading #StockPicks #options #OptionsTrading #Payday Click To Tweet

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How Micah moved to creating tools

Micah discovered the strategy around 2012. He started publishing his ideas for trading Apple and it gained some traction. So he created a website called “Apple Trader” which grew into one of the largest Apple trading communities in the world. In 2015, they found so much success that they expanded and rebranded to In that process, they rebuilt a whole new social network. Because of the way they built it, they can apply features, tools, and software to the network (like charts, backtesting, and notification signals).

They built software to help identify setups for the community. It’s a web-based application you log in to. You get access to social forums and their charting app. When you’re on any charting tool, you have charts with thousands of indicators—but you don’t know if they work. So they backtested popular indicators to create a performance grid for how well the indicators work. One of the first indicators they tested was the Heiken-Ashi chart and it’s evolved from there.

How did he build out the platforms? What were the results? What strategies do they test? Listen to learn more!

Crowdsourcing to create data for the community

They’ve been doing backtesting for 5–6 years. They now have the world’s fastest stock and options backtesting engine. Every time one of their clients backtests an idea, it pings their server and they store the idea. They then push it through a ten-factor weighting system to see if the strategy is good based on profitability, risk-reward, batting average, and other factors. If the idea is good, they display it to everyone in the community on a discovery feature. Some of their community members made improvements and shared them with everyone. The community itself has created an atmosphere of improving trading for everyone.

Where is headed? Listen to the whole episode for Micah’s vision for the future.

How is @WallStreet_io using crowdsourcing to create actionable data for their community? He shares more in this episode of How To Trade It. Don’t miss it! #stocks #stock #trading #StockMarket #Investing #DayTrading #StockPicks #options… Click To Tweet

Resources & People Mentioned

Connect with Micah Lamar

Connect With Casey Stubbs

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