🚀 Are You Trading Nvidia After the Stock Split? Read this!

Unveiling the Hidden Costs 🔍

How Does NVIDIA's Stock Split Affects Your Trades?

Last Friday (6/7), the financial world was abuzz as NVIDIA executed a 10-for-1 stock split after market close. Historically, NVIDIA's stock has been a hotbed of volatility following major events such as financial disclosures, earnings reports, and legislative news. This heightened trading activity often results in market imbalances, which significantly widens bid-ask spreads and exacerbates the market impact of all trades. During these periods, traders face the highest risk of slippage costs, or the difference between the expected price of a trade and the actual executed price.

For NVIDIA traders, these unseen “transaction costs” can severely degrade the profitability (PnL) of your trades. Each incremental cost chips away at potential gains, transforming a theoretically profitable strategy into a loss under real market conditions. So, in the aftermath of such volatile market events, how do you craft an optimal trading strategy to minimize these transaction costs and maximize your returns?

Mastering NVIDIA Trades: What You'll Learn 📊

In this article, you will discover:

• How timing and order size exactly affect trading costs and ultimately, the returns on your strategy.
• How to construct a cost-minimizing execution strategy based on historical market data for nine different periods of volatility following news events for NVIDIA, to optimize returns.

Dangers of Trading Now: Heightened Trading Costs Due to Volatility ⚠️

Before delving into specific strategies, it’s critical to understand the risks associated with trading during volatile periods, particularly the implicit costs of trading. These costs extend far beyond the obvious exchange fees, taxes, and broker commissions. Many traders only become aware of implicit costs after realizing their profits are significantly lower than expected. The main implicit costs are:

1. Bid-Ask Spread: This is the difference between the highest price a buyer is willing to pay and the lowest price a seller is willing to accept. It is a fixed cost per share and is linear relative to trade size. A wider spread means paying more when buying and receiving less when selling, directly eating into potential profits.
2. Market Impact: This refers to the price movement caused by executing a large trade. It is quadratic relative to trade size. This effect is more pronounced in volatile periods, where even moderately large orders can lead to significant price shifts.

Using a Stochastic Process Approach to Quantify Trading Costs 📈

To calculate these implicit costs, we use a stochastic process approach as described in this paper. As shown in the figure below, this approach considers how large buy orders influence the market price of a security over time.

The curve demonstrates the initial price surge due to a substantial buy order and how it stabilizes as the market absorbs the trade. The stochastic model incorporates variables such as constant volatility and the flattening impact trajectory to forecast how these costs evolve as the trade is executed.

By employing this technique, we can accurately predict the total cost impact on trades of many different sizes, particularly during turbulent market conditions. Understanding and applying this approach ensures that traders can strategically navigate through volatility, minimize adverse cost impacts, and optimize their trading outcomes.

Minimizing Transaction Costs While Trading Nvidia on May 25, 2022 🗓️

On May 25, 2022, NVIDIA surprised the stock market by announcing a 46% increase in revenue from the previous year and projected strong returns for the following quarter, causing the stock to rise 13% in a week. Now, if you were a trader wanting to capitalize on this news, while also looking to minimize transaction costs - what would be the best way to trade?

The heat maps illustrate the transaction costs and returns of buying NVIDIA immediately after the earnings report. Key observations include:

1. Transaction Costs: These decrease as time passes. The greatest order book imbalance occurs right after a news event.
2. Order Size: Transaction costs become exponentially more important as order size increases.

The heat map on the right demonstrates that returns depend heavily on the holding period or exit timing—essentially, how much the stock has moved since the purchase. Therefore, it is crucial for us to pay attention to transaction costs displayed by the heatmap on the left. It is evident that for a fixed holding period, the size of the order significantly impacts profit and loss (PnL).

Adjusting the timing of the trade can also reduce transaction costs, thereby improving PnL. For example, if an investor buys 10,000 shares six hours after the announcement instead of one minute after, they could save $480 in transaction costs, regardless of the subsequent stock price movements.

Constructing a Return-Maximizing + Cost-Minimizing Execution Strategy ⚙️

Based on our analysis of nine volatile periods similar to the one in the case study, we found two key strategies to create a winning portfolio:

1.  Split Your Orders: Avoid large market impact by incrementally sending smaller orders. Analysis of the transaction cost per share heat map implies that this can decrease the amount paid through market impact by up to 75%.
2. Place Larger Weights Earlier, Smaller Weights Later: Investors should enter positions around the 60-minute mark to maximize profits. Increasing order size until the 60-minute mark and then decreasing order size from there is recommended.

Example Scenario with Sample Traders

In the strategy represented by Trader 1, assuming a trade size of 10,000 shares, you can minimize trading costs by splitting this into 10 batches of 1,000 shares each. By sending each order in half-hour increments starting one hour after the event, you can reduce transaction costs by around 60% on average. This translates to a 0.24% return over the trading period. Assuming these volatile events happen around six times a year, this means saving 1.44% per year through six trades.

The strategy represented by Trader 2 aims to maximize returns by entering at 1 minute, 15 minutes, 30 minutes, and 60 minutes after the event with 2,500 shares each, and hold until close, as this allows maximum exposure at the lowest prices. Over the nine volatile periods studied, this would have translated to 2.96% profits per trade.

Combining these strategies, you could order 1,200 shares at 1, 20, 40, 60, and 80 minutes after the event, and 1,000 shares at half-hour increments after that until all 10,000 shares are ordered. Over the nine volatile periods, this would result in an average 0.19% saved in transaction costs and a 3.10% average profit. Trader 3 follows the PnL maximizing strategy in the chart above.

Testing: How These Strategies Performed in The Market 📈

In an extension of this piece, we test this strategy in other volatile periods it has not been optimized for. These events are the 10-for-1 stock split, its August 2023 earnings report where it outperformed expectations greatly, and the announcement of the release of many products, including the A100 Tensor Core GPU.

Unlock Personalized Alpha: Optimize Your NVIDIA Trades with Expert Analysis 📈

Understanding and managing transaction costs are key to boosting your returns when trading NVIDIA during volatile periods. We provide a strategy for splitting your orders and timing your trades effectively, allowing you to minimize hidden fees and maximize your profits with a boost of around 0.5%-1.9% to your PnL every time you see an opportunity. If you want to implement these strategies to get the most out of your NVIDIA investments and protect your portfolio from unnecessary losses - you can read the entire piece on our Medium publication linked here.

If you want us to analyze specific equities or conduct a personal analysis of your portfolio and trade history, please email us at accounts@blockhouse.capital.