Cross Market Surveillance

There are various indicators that are utilized to spot potential manipulative activities. These indicators, often rooted in statistical and economic theories, can be used individually or in combination to detect anomalies suggestive of market manipulation. Their importance lies in providing objective and quantifiable measures to assess market activities, which, when deviating from established norms, signal the need for closer scrutiny.

Best Practices for Using Cross Market Surveillance Metrics

1. Start with key metrics such as volume distribution, first-digit distribution, correlation between volume and volatility, buy-sell ratio and time-of-trade. It is crucial to observe these metrics over time.

2. Identify anomalies using specific criteria, such as sudden spikes or significantly unusual trading volumes. Compare current data with historical averages to determine the normal state.

3. Compare findings across exchanges to identify exchange specific anomalies versus broader market movements.

4. Validate metrics against known exchange events like technology changes, campaigns or promotions that could naturally impact behaviors.

5. Avoid making definitive conclusions based on metrics alone. Use metrics to guide detailed transaction-level investigations.

To enhance the analysis, here are some tips regarding simultaneous anomalous deviations of these metrics which can be indicative of market anomalies:

• Volume Distribution and Volume-Volatility Correlation: A volume distribution that deviates from the power law, especially with an unusual number of large trades, coupled with a low volume-volatility correlation, can suggest market manipulation. Large trades should typically introduce volatility, and a lack of this correlation might indicate that these large trades are not impacting the market as expected.
• Concurrent Irregularities in First-Digit Distribution and Benford’s law Test: Significant deviations from Benford’s Law in First-Digit Distribution, coupled with a Benford’s law Test value greater than the critical value, strongly indicate data manipulation. This could be a sign of practices like wash trading, where large volumes of trades are artificially created to mislead the market.
• Inconsistencies in VWAP and Buy/Sell Ratio: A substantial difference between VWAP and market prices, along with abnormal Buy/Sell Ratios, could signify price manipulation. Traders might be attempting to influence the perceived average price through strategic buying or selling.
• Correlation between Time-of-Trade and Buy/Sell Ratio Anomalies: If the Time-of-Trade metric shows high frequency or evenly distributed trades, and the Buy/Sell Ratio deviates significantly from the 0.4-0.6 range, this might suggest automated trading systems are in play. This could be an attempt to influence market prices or create false market sentiment.

Vocabulary

• Market: A cryptocurrency trading instrument that includes an exchange and a currency pair (e.g., Binance-BTC-USDT, OKX-ADA-BTC).
• Pair: A combination of two cryptocurrencies, forming a trading unit (e.g., BTC-USD, ETH-USDC).
• Market Venue: A platform for trading, which could be an exchange or another type of trading platform.
• Granularity: The specific time interval used for calculating metrics in trading analysis.

XMS API overview

The API can be used to retrieve all metrics at once or just some of them (metrics request parameter), including only OHLCV and VWAP, making it possible to use for simple market data requests or comprehensive analysis.

Example API Request:
metrics/wt/market?marketvenueid=binance&pairid=btc-usdt&start=2024-07-11T01:40:00&end=2024-07-11T01:50:00&gran=1h&sort=asc&limit=100&metrics=["vwap","ohlcv","volat"]