Analysis of Net Value Estimation Error for Silver LOF: A Case Study on Differences Between Settlement Price and Closing Price
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Listed Open-End Funds (LOF) have unique technical characteristics in their net value estimation mechanism:
- Deriving based on real-time market prices of the fund’s portfolio holdings
- Using the latest futures contract prices as core parameters for precious metal funds
- Considering adjustment factors such as exchange rates, holding proportions, and fee deductions
| Feature | Settlement Price | Closing Price |
|---|---|---|
Calculation Method |
Volume-weighted average over the entire trading period | Last matched transaction price |
Time Range |
Entire trading session | Closing moment |
Purpose |
Margin calculation, profit and loss settlement | Price marking |
Representativeness |
Reflects the average trading level throughout the day | May be affected by late-session fluctuations |
For silver futures, the
The main source of net value estimation error for Silver LOF is
- Intraday estimation time point: Usually uses the previous trading day’s settlement price or the current day’s latest price
- Actual net value confirmation time point: Reviewed by the fund custodian after market close on day T
- Futures settlement price announcement time point: Usually between 15:00-15:30 after closing
This time difference means intraday estimation cannot use the day’s final settlement price, forming inherent information lag.
Portfolio composition of a Silver LOF fund:
- Long position in silver futures main contract: 80%
- Cash and cash equivalents: 20%
Market data on day T:
- Silver futures closing price: 7,500 CNY/kg
- Silver futures settlement price: 7,450 CNY/kg
- Difference rate: (7,500-7,450)/7,450 = 0.67%
Estimated net value based on closing price: 1.025 CNY
Actual net value based on settlement price: 1.018 CNY
Estimation error: +0.69%
| Impact Factor | Impact Direction | Impact Degree |
|---|---|---|
Futures contract rollover |
Positive/negative deviation | High (during contract switching) |
Market volatility |
Expands deviation | High (greater volatility leads to larger differences) |
Late-session anomalies |
Uncertain direction | Medium |
Liquidity conditions |
Expands deviation | Medium (when liquidity is low) |
Exchange rate fluctuations |
Superimposed effect | Medium |
Differences between settlement prices and closing prices create theoretical space for
- Positive arbitrage: When the estimated net value is significantly higher than the actual net value, buying on-exchange may yield additional returns
- Reverse arbitrage: The opposite applies
- Risk reminder: Arbitrage needs to consider transaction costs, time delays, execution risks, etc.
- Focus on estimation accuracy: Choose platforms that use more precise estimation methods
- Understand time windows: Recognize the time difference between intraday valuation and actual net value
- Verify large transactions: For large subscriptions/redemptions, it is recommended to rely on the actual net value
- Be cautious in volatile markets: Estimation errors may expand during periods of severe market volatility
Recommended estimation formula:
Estimated net value = Σ (latest price of holding instruments × holding weight) × (1 - fee rate)
+ cash balance / total shares
Improvements:
1. Use estimated futures settlement prices (based on intraday volume-price relationships)
2. Consider the impact of rollover factors on contract prices
3. Add liquidity discount factors
- Short-term traders: Focus on intraday price fluctuations rather than estimated net value
- Long-term holders: Focus on actual net value performance and ignore short-term estimation deviations
- Arbitrage participants: Establish error monitoring models and set reasonable deviation thresholds
The net value estimation error for Silver LOF is essentially an
- More rationally view fluctuations in intraday valuations
- Identify potential investment opportunities and risks
- Choose reference indicators more suitable for their own trading strategies
With advancements in market data service technology, estimation accuracy is expected to continue improving in the future, but completely eliminating errors has objective technical limitations.
[0] Analysis of LOF Fund Operation Mechanism and Pricing Principles (Theories related to financial product design)
[1] Research on Futures Settlement Price Calculation Methods and Market Functions (Shanghai Futures Exchange Rules and Financial Engineering Theories)
[2] Net Value Estimation Methodology for Precious Metal ETFs/LOFs (Fund Valuation Technology and Practice)
[3] Cross-Market Arbitrage and Price Discovery Mechanisms (Theories on Price Relationships in Financial Markets)
Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.
About us: Ginlix AI is the AI Investment Copilot powered by real data, bridging advanced AI with professional financial databases to provide verifiable, truth-based answers. Please use the chat box below to ask any financial question.
