References and Formulas

The Max Margin Opportunities analysis identifies items in the market that offer the highest profit margins. This analysis compares the highest buy orders with the lowest sell orders to find opportunities where you can buy low and sell high, maximizing your profits. The ranking is based on the estimated daily profit, calculated as:

The margin is calculated using the following formula:

$$M = \frac{P_s - P_b}{P_s} \times 100\%$$

Where:

• $M$ = Margin percentage
• $P_s$ = Sell price
• $P_b$ = Buy price

The estimated daily profit is calculated as:

$$EDP = (P_s - P_b) \times V_d$$

Where $V_d$ is the average daily volume.

By focusing on the items with the highest estimated daily profit, this analysis helps you target the most lucrative trades. Users can filter results by minimum margin or maximum sell price to focus on specific opportunities.

The Items In Low Supply analysis highlights products that are in high demand but have a limited supply on the market. It considers key factors such as margin, max days of supply, and logarithmic weighting on daily volume. The analysis ranks items based on a combination of these factors to help identify scarce items with high market demand, allowing you to capitalize on opportunities where prices may rise due to limited supply.

The supply shortage analysis uses the following key metrics:

• Days of Supply (DoS): The number of days the current sell volume can satisfy market demand, calculated as:

$$DoS = \frac{S_v}{V_d}$$

Where:

• $S_v$ = Current sell volume
• $V_d$ = Average daily volume

You can now filter items by a maximum days of supply to focus on items with lower availability.

In addition, the logarithmic weighting of volume helps prioritize items with higher market activity. This weight is calculated using:

$$\text{Log Volume Weight} = \log_{10}(V_d + 1)$$

Where $V_d$ is the average daily volume.

This ensures that higher-volume items receive more attention in the analysis, even when other factors like margin or supply are similar to lower-volume items.

The High Demand, Low Supply analysis finds items that are currently in high demand but have limited availability. By comparing the volume of buy and sell orders, it calculates a buy/sell ratio and a margin percentage. The analysis ranks items based on a ranking score:

The demand-supply imbalance factor (DSIF) is computed as:

$$DSIF = \left(\frac{B_v}{S_v}\right)^2 \times \frac{V_d}{S_v} \times \log_{10}(P_s - P_b + 1)$$

Where:

• $B_v$ = Total buy volume
• $S_v$ = Total sell volume
• $V_d$ = Average daily volume
• $P_s$ = Lowest sell price
• $P_b$ = Highest buy price

This function helps you focus on items with favorable demand-supply dynamics and high potential profitability. Users can adjust parameters to refine the results.

The Price Movement Analysis provides insights into market trends by comparing price fluctuations and volume changes across major trade hubs. The analysis involves calculating several important metrics including margins, volume change percentage, and price change percentage.

The following key metrics are used in this analysis:

• Margin (%) is calculated to understand the price difference between buy and sell orders: $$M = \frac{P_s - P_b}{P_s} \times 100$$ Where:
  • $M$ = Margin percentage
  • $P_s$ = Sell price
  • $P_b$ = Buy price
• Price Change Percentage calculates how much the price has changed over a given period: $$P_c = \frac{P_{\text{last\_week}} - P_{\text{last\_month}}}{P_{\text{last\_month}}} \times 100$$ Where:
  • $P_c$ = Price change percentage
  • $P_{\text{last\_week}}$ = Average price over the last week
  • $P_{\text{last\_month}}$ = Average price over the last month
• Volume Change Percentage reflects how much the trade volume has fluctuated: $$V_c = \frac{V_{\text{last\_week}} - V_{\text{last\_month}}}{V_{\text{last\_month}}} \times 100$$ Where:
  • $V_c$ = Volume change percentage
  • $V_{\text{last\_week}}$ = Average daily volume over the last week
  • $V_{\text{last\_month}}$ = Average daily volume over the last month
• Correlation is a qualitative measure used to assess the relationship between price and volume movements. If both price and volume move in the same direction, the correlation is labeled as "Positive," otherwise "Negative."
• Weighted Score is a logarithmic weighting of the average daily volume, which prioritizes high-activity items: $$\text{Weighted Score} = \log_{10}(V_d + 1)$$ Where:
  • $V_d$ = Average daily volume

This analysis ranks items based on their price and volume movements across major trade hubs such as Jita, Amarr, and Dodixie. The data is fetched from the EVE Online API and processed using a combination of SQL queries and Python-based calculations to provide traders with actionable insights on market movements.

The analysis allows filtering based on minimum average daily volume and margin percentage, helping users target specific price movements in the marketplace.