6️⃣Dynamic Spread Factor Against Price Manipulation

RogueX acknowledges the potential for price manipulation and arbitrage when a token lacks external liquidity, and spot trading essentially dictates the asset's price. In such scenarios, price manipulation becomes a significant concern, as it can become relatively straightforward if the cost of manipulating the spot price is lower than the profit achievable through perpetual trading and thus, users have the potential to manipulate prices in spot trading and capitalize on those manipulated prices to profit in perpetual trading.

6.1.Price Manipulation Attack

As Roguex platform offers spot trading and perpetual trading, one of the most commonly used profit-generating strategies involves opening a perpetual trading position and manipulating the price, either pushing it higher or lower, to close the perpetual trading position at a profit as Figure 3 shows.

The cost of price manipulation includes: spot trading fees($\gamma_\text{swap}$)and additional losses ($\gamma_\text{add}$) caused by other users' trades. This refers to the expenses associated with controlling or manipulating the price of an asset. It encompasses the fees incurred during spot trading, as well as any additional losses that might result from the trading activities of other users. These extra losses occur when other users' trades have an adverse impact on the market and contribute to a less favorable price for the individual manipulating the price.

Recall that the profit made by perpetual trading is defined as:

$\pi = s \cdot \Delta_\text{Price} - \gamma_\text{f,p,r}$ (9)

so the price manipulation profit is:

\begin{split} \text{Profit} &= \pi - \text{Cost}\\ &= s \cdot \Delta_\text{Price} - \gamma_\text{f,p,r} - \gamma_\text{swap}^{\Delta_\text{Price}} - \gamma_\text{add} \end{split} (10)

In situations where the trading activity in the spot trading pool is low enough, and we assume that $\gamma_\text{add} \approx 0$, there will always be a price variance point where, when the price variance exceeds this point, users will always makes $\text{Profit} > 0$ as figure 4 represents.

6.2. Solution

To address the issue of price manipulation attacks, the Roguex project takes a two-pronged approach:

$\text{Profit} = \overbrace{\pi}^{\text{make it dynamic}} - \overbrace{\text{Cost}}^{ \text{Increase~} \gamma_\text{add} }$ (11)

1. Relative Lag in Perpetual Trading Price Movements - Using TWAP Price to Allow the Market to Determine Token's True Value

First, it aims to make the profits in perpetual trading dynamic. Roguex accomplishes this by identifying trading patterns in spot trading and adjusting them dynamically. This way, it ensures that the manipulation does not impact the settlement profits of regular perpetual trading users and minimizes the profit potential for price manipulation attacks.

• Utilizing TWAP Price: RogueX implements a strategy that introduces a relative lag in price movements by employing the Time-Weighted Average Price (TWAP). This pricing mechanism allows the market time to collectively decide the true value of the token.

• Market-Driven Valuation: The use of TWAP prices gives prominence to market-driven valuation. Rather than reacting to immediate price changes, RogueX allows for a more considered assessment of an asset's worth, taking into account a broader spectrum of market participants and trading data.

• Mitigating Price Manipulation: By introducing this relative lag, RogueX discourages abrupt and potentially manipulated price fluctuations. Price manipulators often exploit rapid moves in prices to their advantage, and TWAP helps reduce this vulnerability.

• Market Stability: This method contributes to market stability by ensuring that price determinations align more closely with the collective wisdom of the market. It promotes a fairer and less volatile trading environment.

1. Recognizing Patterns of Price Manipulation Behavior - Dynamic Spread Factor $k_d$ Adjustment

Secondly, Roguex strives to increase the impact of opposing users' trades, thus raising the cost of price manipulation. This means that the influence of users engaging in legitimate trades is enhanced, making it more expensive for potential attackers to manipulate prices.

• Pattern Recognition: RogueX utilizes pattern recognition to identify and address unusual trading behavior that may indicate price manipulation. This involves dynamic adjustments to the spread coefficient, which doesn't affect regular trading but becomes active when a pattern suggestive of price manipulation emerges.

• Real-Time Detection: Pattern recognition allows RogueX to swiftly detect and respond to potential price manipulation. When it identifies unusual trading patterns, it can take immediate measures to mitigate further manipulation attempts.

• Proactive Prevention: In addition to responding to manipulation, pattern recognition enables proactive prevention. RogueX can impose trading restrictions and safeguards on accounts or assets displaying consistent manipulative behavior, deterring future manipulation efforts.

• Enhancing Market Transparency: The ability to detect and address manipulation reinforces market transparency. Traders have greater confidence in the fairness and integrity of the trading environment when they know that manipulation is actively monitored and addressed.

By combining these methods, RogueX creates a more secure and fair trading environment. These strategies protect against price manipulation, support market transparency, and ensure that the true value of tokens is determined collectively by the market.

6.3. Dynamic Spread Factor

In a normal market situation, prices exhibit fluctuations, and trading occurs between buying and selling. However, when price manipulation occurs, the price can swiftly be pushed in one direction, such as an abrupt increase or decrease, with very little or no counter-directional movement. This situation can make market participants uneasy because the price behavior no longer adheres to regular supply and demand dynamics but is influenced by manipulation.

The dynamic spread factor in RogueX serves as a critical tool with two primary objectives: 1) Suppression of Price Manipulation} and 2) Minimal Impact on Normal Trading Activities. RogueX's approach to implementing the dynamic spread factor is rooted in the observation of price movement patterns. By recognizing specific behavior in the market, it can apply the spread factor judiciously, only in cases where there's a likelihood of price manipulation. This ensures that the protective measures are triggered when needed, maintaining a balance between safeguarding the market and facilitating smooth, normal trading practices.

RogueX employs a dynamic slippage system to address these concerns. This system ensures that spot prices are less susceptible to manipulation by automatically adjusting the slippage based on market conditions, order sizes, and trading activity. The dynamic slippage mechanism helps maintain fair and stable pricing by making it less profitable for malicious actors to manipulate prices and exploit arbitrage opportunities.

The dynamic slippage system is designed to strike a balance between providing a smooth trading experience for users while deterring malicious actors from attempting price manipulation. By dynamically adjusting slippage, RogueX can reduce the incentive for price manipulation, thereby promoting a fair and transparent trading environment.

Dynamic spread factor is defined as:

$k_d = \sigma_\text{pv}^m \cdot \left( \frac{s_g(S_o-S_i)}{(S_o+S_i)^2} \right)^n + 1$ (12)

where $S_o$, $S_i$ represent the outside and inside spot trading size within perpetual trading duration respectively. $\sigma_\text{pv}$ is the price variance coefficient.

Recall that the perpetual trading profit is defined as:

$\text{Profit } \pi = s \cdot \frac{(P_\text{c} - P_\text{o} ) }{P_\text{o}} - (\gamma_f + \gamma_p + \gamma_r)\\ P_o = \text{TWAP} ( \lambda_o ) \cdot ( 1 + \delta(\frac{s_\text{OI} + s_\text{position} }{2}))\\ P_c = \text{TWAP} ( \lambda_c ) \cdot ( 1 - k_d \delta(\frac{s_{\Sigma(\lambda_t)} + s_\text{position} }{2})$ (13)

We can see that by introducing the dynamic factor $k_d$, the perpetual trading profit is deliberately reduced in situations where price manipulation takes place. This adjustment serves as a proactive measure to counteract the impact of price manipulation and maintain the integrity of the trading environment. It helps mitigate the profitability for manipulative actions in the perpetual trading system.