Many traders (and even investors) get started without understanding basic mathematical principles. Luckily, if you never got passed high school algebra, you’re still going to be okay. That’s because there are countless resources on the web to learn from, but also, as a trader who is just starting out, the math you need to know is arithmetic – you know, things like 1 + 1 = 2 and 2 + 2 = 4.

Below, I’ve compiled the most helpful mathematical use cases for new traders, including what the math is, why it matters, and how to use it, along with examples for each concept:

Risk-Reward Ratio: This ratio measures the potential reward of a trade in relation to its potential risk. A common risk-reward ratio used by many day traders is 1:2, meaning the potential profit of a trade is twice as large as its potential loss. For instance, if a trader risks $100 on a trade, they should aim for a potential profit of $200.

Position Sizing: One of the most critical mathematical concepts in trading is position sizing. It refers to the number of shares or contracts a trader buys or sells in a particular trade. The Kelly Criterion is a formula that can help determine the optimal size of a series of trades. For example, if a trader’s edge is 60% and the average win/loss ratio is 1.5, the Kelly Criterion suggests that the trader should risk 10% of their capital on each trade. Please keep in mind that this depends on your own inputs, and rigorous tracking of your trading capabilities. Plug the data into the equation and get your answer. I’ve pasted equation to plug your inputs at the bottom of this post.

Compounding: The concept of compounding is crucial in day trading. It’s the process in which an asset’s earnings, from either capital gains or interest, are reinvested to generate additional earnings over time. It’s often expressed in terms of percentage return per year. For example, if a trader makes a 10% return per month and reinvests their earnings, their account will grow exponentially over time.

Volatility: Volatility is a measure of the price movements of an asset or a market. It’s often calculated as the standard deviation of returns over a given period. High volatility can mean more significant profit opportunities but also comes with higher risk. For instance, if a stock has a standard deviation of 2%, its price is expected to move by 2% on average from its mean price.

Probability: Probability is used to estimate the likelihood of an event happening. In day trading, probability is often used to estimate the likelihood of a trade being successful. For example, if a trader has a 60% probability of winning a trade, it means that out of every 10 trades, they can expect to win 6 and lose 4.

Expected Value: The expected value is a measure of the average outcome of a trade, calculated by multiplying the probability of each outcome by its value and then summing these values. It’s a way to estimate the average return of a trade over many repetitions. For instance, if a trade has a 70% chance of making $100 and a 30% chance of losing $50, the expected value is (0.7 * $100) + (0.3 * -$50) = $55.

Drawdown: This is a measure of the decline from a historical peak in trading account value. It’s expressed as a percentage of the peak value. For example, if a trader’s account value peaks at $10,000 and then falls to $8,000, the drawdown is 20%.

Win Rate: Win rate is the percentage of winning trades out of the total number of trades. It’s a measure of a trader’s success rate. For example, if a trader has 40 winning trades out of 100, their win rate is 40%.

Average Profit Per Trade: This is the average profit a trader makes on each trade. It’s calculated by dividing the total profit by the number of trades. For example, if a trader makes $5,000 in total profit from 50 trades, their average profit per trade is $100.

Average Loss Per Trade: This is the average loss a trader incurs on each trade. It’s calculated by dividing the total loss by the number of trades. For example, if a trader incurs a total loss of $2,000 from 20 losing trades, their average loss per trade is $100.

I believe that these mathematical concepts will help any trader, or investor, get a head start into markets and have a much better chance at success than those who spend no time studying these basic facts.

Note for those looking for Kelly Criterion formula:

Sure, in simpler terms, the Kelly criterion can be written as:

Now here’s how you can plug in your own numbers to the above formula:

• ( f* ) is the fraction of your total capital to bet.
• ( p ) is the probability of winning.
• ( b ) is the net odds received on the bet (for example, if you bet $1 and win $2, then ( b = 2 )).
• ( 1 – p ) is the probability of losing.

Thanks for reading!

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