Leverage is the use of borrowed funds, margin, or derivatives to amplify a trading position beyond the trader's available capital. A 2:1 leverage ratio means the trader controls $200,000 worth of positions with $100,000 of their own capital. Leverage is a double-edged sword: it magnifies profits when trades go well but equally magnifies losses when trades go poorly. Understanding leverage is essential for any algorithmic trader because it directly affects risk of ruin.
How leverage works
In margin trading, a broker lends the trader money to increase their buying power. If a trader has $50,000 and uses 2:1 margin, they can buy $100,000 worth of securities. If those securities rise 10%, the profit is $10,000, which is a 20% return on the trader's $50,000 capital. If they fall 10%, the loss is $10,000, a 20% loss on capital. Without leverage, the same move would produce a 10% gain or loss.
Futures and options provide built-in leverage through their contract structure. A futures contract might require a margin deposit of only 5-10% of the contract's notional value, providing 10-20x leverage. Options provide leverage because a small premium controls a much larger position in the underlying asset.
The risk of leverage
Leverage increases the probability of large losses and potentially the risk of ruin, meaning a drawdown so severe that recovery is practically impossible. Without leverage, a portfolio can survive a 50% market decline and eventually recover. With 2:1 leverage, the same decline wipes out the entire account. With 3:1 leverage, a 33% decline eliminates all capital.
Margin calls add another risk. When losses erode the account below the minimum margin requirement, the broker forces position liquidation, often at the worst possible time. This can lock in losses that the portfolio might have recovered from without leverage.
Leverage in backtesting
Backtesting leveraged strategies requires careful modeling of margin requirements, borrowing costs, and margin call mechanics. Many backtesting platforms ignore these factors, allowing unlimited leverage with zero cost. This produces unrealistic results because leveraged strategies in reality face interest charges on borrowed capital, margin constraints that limit position sizes, and forced liquidation during drawdowns.
A strategy that shows a 50% annual return with 4:1 leverage in a backtest might achieve only 40% after borrowing costs and might experience margin calls that the backtest does not simulate, potentially resulting in catastrophic losses that never appear in the simulated results.
Practical example
A trader with $100,000 uses 3:1 leverage to hold $300,000 in equity positions. The portfolio's beta is 1.0, so during a month when the market drops 15%, the portfolio loses $45,000 (15% of $300,000). This represents a 45% loss on the trader's $100,000 capital. The broker's maintenance margin requirement is 30%, meaning the account needs at least $90,000 in equity. With $55,000 remaining and $200,000 in borrowed funds, equity is only 22% of the position value, triggering a margin call and forced liquidation.
How Tektii helps
Tektii models leverage constraints and margin requirements in its backtesting engine so that traders see realistic results for leveraged strategies. The platform accounts for borrowing costs and simulates margin call scenarios that would force position reductions. By providing honest leverage modeling, Tektii helps traders understand the true risk of leveraged strategies rather than being misled by frictionless simulations.