Mathematical Formulas Reference
This appendix provides a comprehensive reference of all mathematical formulas used throughout the use.com whitepaper. Formulas are organized by category for easy reference.
Trading & Order Book
Order Matching
Price-Time Priority: Priority=(Price_Level,Timestamp)Priority = (Price_Level, Timestamp)Priority=(Price_Level,Timestamp)
Orders at better prices execute first; at same price, earlier orders execute first.
Order Book Depth: Depth=∑i=1nVolumei at price level PiDepth = \sum_{i=1}^{n} Volume_i \text{ at price level } P_iDepth=∑i=1nVolumei at price level Pi
Mid Price: Mid_Price=Best_Bid+Best_Ask2Mid_Price = \frac{Best_Bid + Best_Ask}{2}Mid_Price=2Best_Bid+Best_Ask
Spread: Spread=Best_Ask−Best_BidSpread = Best_Ask - Best_BidSpread=Best_Ask−Best_Bid
Spread Percentage: Spread_%=Best_Ask−Best_BidMid_Price×100%Spread_\% = \frac{Best_Ask - Best_Bid}{Mid_Price} \times 100\%Spread_%=Mid_PriceBest_Ask−Best_Bid×100%
Order Execution
Market Order Fill Price (with slippage): Fill_Price=∑i=1nVolumei×Pricei∑VolumeiFill_Price = \sum_{i=1}^{n} \frac{Volume_i \times Price_i}{\sum Volume_i}Fill_Price=∑i=1n∑VolumeiVolumei×Pricei
Limit Order Execution:
Execute=1(Pricemarket≤Pricelimit, buy)Execute=1(Pricemarket≥Pricelimit, sell)Execute=0otherwise\begin{aligned} Execute &= 1 && (Price_{market} \le Price_{limit},\ \text{buy}) \ Execute &= 1 && (Price_{market} \ge Price_{limit},\ \text{sell}) \ Execute &= 0 && \text{otherwise} \end{aligned}ExecuteExecuteExecute=1=1=0(Pricemarket≤Pricelimit, buy)(Pricemarket≥Pricelimit, sell)otherwise
Time-Weighted Average Price (TWAP): TWAP=∑i=1nPriceinTWAP = \frac{\sum_{i=1}^{n} Price_i}{n}TWAP=n∑i=1nPricei
Volume-Weighted Average Price (VWAP): VWAP=∑i=1n(Pricei×Volumei)∑i=1nVolumeiVWAP = \frac{\sum_{i=1}^{n} (Price_i \times Volume_i)}{\sum_{i=1}^{n} Volume_i}VWAP=∑i=1nVolumei∑i=1n(Pricei×Volumei)
Risk Management
Margin & Leverage
Initial Margin: Initial_Margin=Position_ValueLeverageInitial_Margin = \frac{Position_Value}{Leverage}Initial_Margin=LeveragePosition_Value
Maintenance Margin: Maintenance_Margin=Position_Value×Maintenance_RateMaintenance_Margin = Position_Value \times Maintenance_RateMaintenance_Margin=Position_Value×Maintenance_Rate
Available Margin: Available_Margin=Equity−Used_MarginAvailable_Margin = Equity - Used_MarginAvailable_Margin=Equity−Used_Margin
Margin Level: Margin_Level=EquityUsed_Margin×100%Margin_Level = \frac{Equity}{Used_Margin} \times 100\%Margin_Level=Used_MarginEquity×100%
Maximum Position Size: Max_Position=Available_Balance×LeverageMax_Position = Available_Balance \times LeverageMax_Position=Available_Balance×Leverage
Liquidation
Liquidation Price (Long): Liquidation_Price=Entry_Price×Leverage−Maintenance_Rate×LeverageLeverageLiquidation_Price = Entry_Price \times \frac{Leverage - Maintenance_Rate \times Leverage}{Leverage}Liquidation_Price=Entry_Price×LeverageLeverage−Maintenance_Rate×Leverage
Simplified: Liquidation_Pricelong=Entry_Price×(1−1Leverage+Maintenance_Rate)Liquidation_Price_{long} = Entry_Price \times (1 - \frac{1}{Leverage} + Maintenance_Rate)Liquidation_Pricelong=Entry_Price×(1−Leverage1+Maintenance_Rate)
Liquidation Price (Short): Liquidation_Priceshort=Entry_Price×(1+1Leverage−Maintenance_Rate)Liquidation_Price_{short} = Entry_Price \times (1 + \frac{1}{Leverage} - Maintenance_Rate)Liquidation_Priceshort=Entry_Price×(1+Leverage1−Maintenance_Rate)
Example (Long position):
- Entry: $50,000
- Leverage: 10×
- Maintenance: 0.5%
- Liquidation: $50,000 × (1 - 0.1 + 0.005) = $45,250
Distance to Liquidation: Distance=∣Current_Price−Liquidation_Price∣Current_Price×100%Distance = \frac{|Current_Price - Liquidation_Price|}{Current_Price} \times 100\%Distance=Current_Price∣Current_Price−Liquidation_Price∣×100%
Profit & Loss
Unrealized PnL (Long): PnLlong=(Current_Price−Entry_Price)×Position_SizePnL_{long} = (Current_Price - Entry_Price) \times Position_SizePnLlong=(Current_Price−Entry_Price)×Position_Size
Unrealized PnL (Short): PnLshort=(Entry_Price−Current_Price)×Position_SizePnL_{short} = (Entry_Price - Current_Price) \times Position_SizePnLshort=(Entry_Price−Current_Price)×Position_Size
PnL Percentage: PnL_%=PnLInitial_Margin×100%PnL_\% = \frac{PnL}{Initial_Margin} \times 100\%PnL_%=Initial_MarginPnL×100%
Return on Equity (ROE): ROE=PnLEquity×100%ROE = \frac{PnL}{Equity} \times 100\%ROE=EquityPnL×100%
Risk Metrics
Value at Risk (VaR): VaR=Position_Value×Volatility×ZscoreVaR = Position_Value \times Volatility \times Z_{score}VaR=Position_Value×Volatility×Zscore
Where Z-score for 95% confidence = 1.645
Portfolio Risk: Portfolio_Risk=∑i=1n∑j=1nwiwjσiσjρijPortfolio_Risk = \sqrt{\sum_{i=1}^{n} \sum_{j=1}^{n} w_i w_j \sigma_i \sigma_j \rho_{ij}}Portfolio_Risk=∑i=1n∑j=1nwiwjσiσjρij
Sharpe Ratio: Sharpe=Return−Risk_Free_RateVolatilitySharpe = \frac{Return - Risk_Free_Rate}{Volatility}Sharpe=VolatilityReturn−Risk_Free_Rate
Maximum Drawdown: Max_Drawdown=Trough_Value−Peak_ValuePeak_Value×100%Max_Drawdown = \frac{Trough_Value - Peak_Value}{Peak_Value} \times 100\%Max_Drawdown=Peak_ValueTrough_Value−Peak_Value×100%
Fee Calculations
Trading Fees
Base Trading Fee: Fee=Trade_Volume×Fee_RateFee = Trade_Volume \times Fee_RateFee=Trade_Volume×Fee_Rate
Fee with Volume Discount: Fee=Trade_Volume×Base_Rate×(1−Volume_Discount)Fee = Trade_Volume \times Base_Rate \times (1 - Volume_Discount)Fee=Trade_Volume×Base_Rate×(1−Volume_Discount)
Fee with Token Discount: Fee=Trade_Volume×Base_Rate×(1−Volume_Discount)×(1−Token_Discount)Fee = Trade_Volume \times Base_Rate \times (1 - Volume_Discount) \times (1 - Token_Discount)Fee=Trade_Volume×Base_Rate×(1−Volume_Discount)×(1−Token_Discount)
Effective Fee Rate: Effective_Rate=Base_Rate×(1−Volume_Discount)×(1−Token_Discount)Effective_Rate = Base_Rate \times (1 - Volume_Discount) \times (1 - Token_Discount)Effective_Rate=Base_Rate×(1−Volume_Discount)×(1−Token_Discount)
Example:
- Volume: $1M
- Base rate: 0.10%
- Volume discount: 20%
- Token discount: 25%
- Effective rate: 0.10% × 0.80 × 0.75 = 0.06%
- Fee: $1M × 0.06% = $600
Maker-Taker Model
Maker Rebate: Rebate=Trade_Volume×Maker_Rebate_RateRebate = Trade_Volume \times Maker_Rebate_RateRebate=Trade_Volume×Maker_Rebate_Rate
Net Fee (Maker): Net_Fee=Trade_Volume×(Maker_Fee−Maker_Rebate)Net_Fee = Trade_Volume \times (Maker_Fee - Maker_Rebate)Net_Fee=Trade_Volume×(Maker_Fee−Maker_Rebate)
Net Fee (Taker): Net_Fee=Trade_Volume×Taker_FeeNet_Fee = Trade_Volume \times Taker_FeeNet_Fee=Trade_Volume×Taker_Fee
Fee Tiers
Volume Tier Calculation: Tier=f(30_Day_Volume)Tier = f(30_Day_Volume)Tier=f(30_Day_Volume)
Fee Savings: Savings=(Base_Fee−Discounted_Fee)×Annual_VolumeSavings = (Base_Fee - Discounted_Fee) \times Annual_VolumeSavings=(Base_Fee−Discounted_Fee)×Annual_Volume
Tokenomics
Token Supply
Circulating Supply: Circulating=Total_Supply−Locked_Tokens−Burned_TokensCirculating = Total_Supply - Locked_Tokens - Burned_TokensCirculating=Total_Supply−Locked_Tokens−Burned_Tokens
Inflation Rate: Inflation=New_TokensExisting_Supply×100%Inflation = \frac{New_Tokens}{Existing_Supply} \times 100\%Inflation=Existing_SupplyNew_Tokens×100%
Deflation Rate (with burns): Deflation=Burned_TokensTotal_Supply×100%Deflation = \frac{Burned_Tokens}{Total_Supply} \times 100\%Deflation=Total_SupplyBurned_Tokens×100%
Token Valuation
Market Capitalization: Market_Cap=Circulating_Supply×Token_PriceMarket_Cap = Circulating_Supply \times Token_PriceMarket_Cap=Circulating_Supply×Token_Price
Fully Diluted Valuation (FDV): FDV=Total_Supply×Token_PriceFDV = Total_Supply \times Token_PriceFDV=Total_Supply×Token_Price
Price-to-Sales Ratio: P/S=Market_CapAnnual_RevenueP/S = \frac{Market_Cap}{Annual_Revenue}P/S=Annual_RevenueMarket_Cap
Token Velocity: Velocity=Transaction_VolumeAverage_Token_HoldingsVelocity = \frac{Transaction_Volume}{Average_Token_Holdings}Velocity=Average_Token_HoldingsTransaction_Volume
Vesting
Linear Vesting: Unlocked=Total_Allocation×Time_ElapsedVesting_PeriodUnlocked = Total_Allocation \times \frac{Time_Elapsed}{Vesting_Period}Unlocked=Total_Allocation×Vesting_PeriodTime_Elapsed
Cliff Vesting:
Unlocked={0t<TcliffAtotal t−TcliffTvestt≥TcliffUnlocked= \begin{cases} 0 & t < T_{cliff} \ A_{total}\,\dfrac{t-T_{cliff}}{T_{vest}} & t \ge T_{cliff} \end{cases}Unlocked=⎩⎨⎧0AtotalTvestt−Tclifft<Tclifft≥Tcliff
Vesting Schedule: Monthly_Unlock=Total_AllocationVesting_MonthsMonthly_Unlock = \frac{Total_Allocation}{Vesting_Months}Monthly_Unlock=Vesting_MonthsTotal_Allocation
Buyback & Burn
Quarterly Burn Amount: Burn_Amount=Quarterly_Profit×Burn_PercentageBurn_Amount = Quarterly_Profit \times Burn_PercentageBurn_Amount=Quarterly_Profit×Burn_Percentage
Tokens Burned: Tokens_Burned=Burn_BudgetToken_PriceTokens_Burned = \frac{Burn_Budget}{Token_Price}Tokens_Burned=Token_PriceBurn_Budget
Annual Burn Rate: Burn_Rate=∑Quarterly_BurnsTotal_Supply×100%Burn_Rate = \frac{\sum Quarterly_Burns}{Total_Supply} \times 100\%Burn_Rate=Total_Supply∑Quarterly_Burns×100%
Supply After Burns: Supplyt=Supply0×(1−Burn_Rate)tSupply_t = Supply_0 \times (1 - Burn_Rate)^tSupplyt=Supply0×(1−Burn_Rate)t
Price Impact (theoretical): Price_New=Price_Old×Supply_OldSupply_NewPrice_New = Price_Old \times \frac{Supply_Old}{Supply_New}Price_New=Price_Old×Supply_NewSupply_Old
Staking Rewards
Annual Percentage Yield (APY): APY=(1+rn)n−1APY = \left(1 + \frac{r}{n}\right)^n - 1APY=(1+nr)n−1
Where r = nominal rate, n = compounding periods
Staking Rewards: Rewards=Staked_Amount×APY×Time_Staked365Rewards = Staked_Amount \times APY \times \frac{Time_Staked}{365}Rewards=Staked_Amount×APY×365Time_Staked
Effective Staking Rate: Effective_Rate=Base_APY×(1+Loyalty_Bonus)×(1+Volume_Bonus)Effective_Rate = Base_APY \times (1 + Loyalty_Bonus) \times (1 + Volume_Bonus)Effective_Rate=Base_APY×(1+Loyalty_Bonus)×(1+Volume_Bonus)
Market Making
Spread Management
Optimal Spread: Spread∗=γσ2λSpread^* = \gamma \sigma \sqrt{\frac{2}{\lambda}}Spread∗=γσλ2
Where:
- γ = risk aversion
- σ = volatility
- λ = order arrival rate
Bid-Ask Quotes: Bid=Mid_Price−Spread2Bid = Mid_Price - \frac{Spread}{2}Bid=Mid_Price−2Spread Ask=Mid_Price+Spread2Ask = Mid_Price + \frac{Spread}{2}Ask=Mid_Price+2Spread
Inventory Management
Inventory Risk: Risk=Position×Volatility×TimeRisk = Position \times Volatility \times \sqrt{Time}Risk=Position×Volatility×Time
Optimal Inventory: q∗=−δγσ2q^* = -\frac{\delta}{\gamma \sigma^2}q∗=−γσ2δ
Where:
- δ = drift
- γ = risk aversion
- σ = volatility
Inventory Skew: Skew=Current_Inventory−Target_InventoryMax_InventorySkew = \frac{Current_Inventory - Target_Inventory}{Max_Inventory}Skew=Max_InventoryCurrent_Inventory−Target_Inventory
Pricing
Mid-Price Adjustment: Midadjusted=Midmarket+α×Inventory_SkewMid_{adjusted} = Mid_{market} + \alpha \times Inventory_SkewMidadjusted=Midmarket+α×Inventory_Skew
Quote Adjustment: Bidadjusted=Bid−β×InventorylongBid_{adjusted} = Bid - \beta \times Inventory_{long}Bidadjusted=Bid−β×Inventorylong Askadjusted=Ask+β×InventoryshortAsk_{adjusted} = Ask + \beta \times Inventory_{short}Askadjusted=Ask+β×Inventoryshort
Performance Metrics
Latency
Average Latency: Latencyavg=∑i=1nLatencyinLatency_{avg} = \frac{\sum_{i=1}^{n} Latency_i}{n}Latencyavg=n∑i=1nLatencyi
Percentile Latency (e.g., P99): P99=99th percentile of latency distributionP99 = \text{99th percentile of latency distribution}P99=99th percentile of latency distribution
Throughput: Throughput=Total_TransactionsTime_PeriodThroughput = \frac{Total_Transactions}{Time_Period}Throughput=Time_PeriodTotal_Transactions
Transactions Per Second (TPS): TPS=TransactionsSecondsTPS = \frac{Transactions}{Seconds}TPS=SecondsTransactions
System Performance
Uptime Percentage: Uptime=Available_TimeTotal_Time×100%Uptime = \frac{Available_Time}{Total_Time} \times 100\%Uptime=Total_TimeAvailable_Time×100%
Error Rate: Error_Rate=Failed_RequestsTotal_Requests×100%Error_Rate = \frac{Failed_Requests}{Total_Requests} \times 100\%Error_Rate=Total_RequestsFailed_Requests×100%
Success Rate: Success_Rate=100%−Error_RateSuccess_Rate = 100\% - Error_RateSuccess_Rate=100%−Error_Rate
Financial Metrics
Revenue Metrics
Average Revenue Per User (ARPU): ARPU=Total_RevenueActive_UsersARPU = \frac{Total_Revenue}{Active_Users}ARPU=Active_UsersTotal_Revenue
Customer Lifetime Value (LTV): LTV=ARPU×Average_Lifetime×Gross_MarginLTV = ARPU \times Average_Lifetime \times Gross_MarginLTV=ARPU×Average_Lifetime×Gross_Margin
Customer Acquisition Cost (CAC): CAC=Marketing_SpendNew_CustomersCAC = \frac{Marketing_Spend}{New_Customers}CAC=New_CustomersMarketing_Spend
LTV/CAC Ratio: LTV/CAC=LTVCACLTV/CAC = \frac{LTV}{CAC}LTV/CAC=CACLTV
Target: >3:1
Payback Period: Payback=CACMonthly_ARPUPayback = \frac{CAC}{Monthly_ARPU}Payback=Monthly_ARPUCAC
Profitability Metrics
Gross Margin: Gross_Margin=Revenue−COGSRevenue×100%Gross_Margin = \frac{Revenue - COGS}{Revenue} \times 100\%Gross_Margin=RevenueRevenue−COGS×100%
EBITDA: EBITDA=Revenue−Operating_ExpensesEBITDA = Revenue - Operating_ExpensesEBITDA=Revenue−Operating_Expenses
EBITDA Margin: EBITDA_Margin=EBITDARevenue×100%EBITDA_Margin = \frac{EBITDA}{Revenue} \times 100\%EBITDA_Margin=RevenueEBITDA×100%
Net Profit Margin: Net_Margin=Net_IncomeRevenue×100%Net_Margin = \frac{Net_Income}{Revenue} \times 100\%Net_Margin=RevenueNet_Income×100%
Return on Equity (ROE): ROE=Net_IncomeShareholders_Equity×100%ROE = \frac{Net_Income}{Shareholders_Equity} \times 100\%ROE=Shareholders_EquityNet_Income×100%
Return on Assets (ROA): ROA=Net_IncomeTotal_Assets×100%ROA = \frac{Net_Income}{Total_Assets} \times 100\%ROA=Total_AssetsNet_Income×100%
Growth Metrics
Year-over-Year Growth: YoY_Growth=Valuecurrent−ValuepreviousValueprevious×100%YoY_Growth = \frac{Value_{current} - Value_{previous}}{Value_{previous}} \times 100\%YoY_Growth=ValuepreviousValuecurrent−Valueprevious×100%
Compound Annual Growth Rate (CAGR): CAGR=(Ending_ValueBeginning_Value)1Years−1CAGR = \left(\frac{Ending_Value}{Beginning_Value}\right)^{\frac{1}{Years}} - 1CAGR=(Beginning_ValueEnding_Value)Years1−1
Month-over-Month Growth: MoM_Growth=Valuecurrent−ValuepreviousValueprevious×100%MoM_Growth = \frac{Value_{current} - Value_{previous}}{Value_{previous}} \times 100\%MoM_Growth=ValuepreviousValuecurrent−Valueprevious×100%
Derivatives
Perpetual Futures
Funding Rate: Funding_Rate=Mark_Price−Index_PriceIndex_PriceFunding_Rate = \frac{Mark_Price - Index_Price}{Index_Price}Funding_Rate=Index_PriceMark_Price−Index_Price
Funding Payment: Payment=Position_Size×Funding_RatePayment = Position_Size \times Funding_RatePayment=Position_Size×Funding_Rate
Mark Price: Mark_Price=Index_Price×(1+Funding_Basis)Mark_Price = Index_Price \times (1 + Funding_Basis)Mark_Price=Index_Price×(1+Funding_Basis)
Liquidation Price (Perpetual Long): Liq_Price=Entry_Price×Leverage−Maintenance_Margin×Leverage−FundingLeverageLiq_Price = Entry_Price \times \frac{Leverage - Maintenance_Margin \times Leverage - Funding}{Leverage}Liq_Price=Entry_Price×LeverageLeverage−Maintenance_Margin×Leverage−Funding
Options
Black-Scholes Call Option: C=S0N(d1)−Ke−rTN(d2)C = S_0 N(d_1) - K e^{-rT} N(d_2)C=S0N(d1)−Ke−rTN(d2)
Where: d1=ln(S0/K)+(r+σ2/2)TσTd_1 = \frac{\ln(S_0/K) + (r + \sigma^2/2)T}{\sigma\sqrt{T}}d1=σTln(S0/K)+(r+σ2/2)T d2=d1−σTd_2 = d_1 - \sigma\sqrt{T}d2=d1−σT
Black-Scholes Put Option: P=Ke−rTN(−d2)−S0N(−d1)P = K e^{-rT} N(-d_2) - S_0 N(-d_1)P=Ke−rTN(−d2)−S0N(−d1)
Option Greeks:
Delta: Δ=∂V∂S\Delta = \frac{\partial V}{\partial S}Δ=∂S∂V
Gamma: Γ=∂2V∂S2\Gamma = \frac{\partial^2 V}{\partial S^2}Γ=∂S2∂2V
Theta: Θ=∂V∂t\Theta = \frac{\partial V}{\partial t}Θ=∂t∂V
Vega: V=∂V∂σ\mathcal{V} = \frac{\partial V}{\partial \sigma}V=∂σ∂V
Rho: ρ=∂V∂r\rho = \frac{\partial V}{\partial r}ρ=∂r∂V
Implied Volatility
Implied Volatility (from option price): σimplied=f−1(Option_Price,S,K,r,T)\sigma_{implied} = f^{-1}(Option_Price, S, K, r, T)σimplied=f−1(Option_Price,S,K,r,T)
Solved numerically using Newton-Raphson method.
Statistical Formulas
Volatility
Historical Volatility: σ=∑i=1n(Ri−Rˉ)2n−1\sigma = \sqrt{\frac{\sum_{i=1}^{n}(R_i - \bar{R})^2}{n-1}}σ=n−1∑i=1n(Ri−Rˉ)2
Annualized Volatility: σannual=σdaily×252\sigma_{annual} = \sigma_{daily} \times \sqrt{252}σannual=σdaily×252
Exponentially Weighted Moving Average (EWMA): σt2=λσt−12+(1−λ)rt−12\sigma_t^2 = \lambda \sigma_{t-1}^2 + (1-\lambda) r_{t-1}^2σt2=λσt−12+(1−λ)rt−12
Correlation
Correlation Coefficient: ρxy=∑(xi−xˉ)(yi−yˉ)∑(xi−xˉ)2∑(yi−yˉ)2\rho_{xy} = \frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum(x_i - \bar{x})^2 \sum(y_i - \bar{y})^2}}ρxy=∑(xi−xˉ)2∑(yi−yˉ)2∑(xi−xˉ)(yi−yˉ)
Covariance: Cov(X,Y)=∑(xi−xˉ)(yi−yˉ)n−1Cov(X,Y) = \frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{n-1}Cov(X,Y)=n−1∑(xi−xˉ)(yi−yˉ)
Moving Averages
Simple Moving Average (SMA): SMAn=∑i=1nPriceinSMA_n = \frac{\sum_{i=1}^{n} Price_i}{n}SMAn=n∑i=1nPricei
Exponential Moving Average (EMA): EMAt=Pricet×k+EMAt−1×(1−k)EMA_t = Price_t \times k + EMA_{t-1} \times (1-k)EMAt=Pricet×k+EMAt−1×(1−k)
Where $k = \frac{2}{n+1}$
Liquidity Metrics
Order Book Liquidity
Bid-Ask Spread: Spread=Ask−BidMid_Price×100%Spread = \frac{Ask - Bid}{Mid_Price} \times 100\%Spread=Mid_PriceAsk−Bid×100%
Market Depth: Depth±x%=∑Volume within ±x% of mid priceDepth_{\pm x\%} = \sum Volume \text{ within } \pm x\% \text{ of mid price}Depth±x%=∑Volume within ±x% of mid price
Liquidity Score: Liquidity=VolumeSpread×VolatilityLiquidity = \frac{Volume}{Spread \times Volatility}Liquidity=Spread×VolatilityVolume
Slippage
Expected Slippage: Slippage=Execution_Price−Expected_PriceExpected_Price×100%Slippage = \frac{Execution_Price - Expected_Price}{Expected_Price} \times 100\%Slippage=Expected_PriceExecution_Price−Expected_Price×100%
Slippage Cost: Cost=Order_Size×Slippage_%Cost = Order_Size \times Slippage_\%Cost=Order_Size×Slippage_%
Conversion Formulas
Interest Rate Conversions
Daily to Annual: Annual_Rate=(1+Daily_Rate)365−1Annual_Rate = (1 + Daily_Rate)^{365} - 1Annual_Rate=(1+Daily_Rate)365−1
Annual to Daily: Daily_Rate=(1+Annual_Rate)1/365−1Daily_Rate = (1 + Annual_Rate)^{1/365} - 1Daily_Rate=(1+Annual_Rate)1/365−1
APR to APY: APY=(1+APRn)n−1APY = \left(1 + \frac{APR}{n}\right)^n - 1APY=(1+nAPR)n−1
Where n = compounding periods per year
Price Conversions
Basis Points to Percentage: Percentage=Basis_Points10,000Percentage = \frac{Basis_Points}{10,000}Percentage=10,000Basis_Points
Percentage to Basis Points: Basis_Points=Percentage×10,000Basis_Points = Percentage \times 10,000Basis_Points=Percentage×10,000
Conclusion
This comprehensive formula reference provides the mathematical foundation for all calculations used throughout the use.com platform. These formulas ensure consistent, accurate, and transparent operations across trading, risk management, tokenomics, and financial reporting.
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Updated on: 10/03/2026
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