For most purposes of technical analysis, valuation metrics and many other relevant financial methods, the price of the last transaction is considered representative of the market price. The straightforward argument is that at this price, supply and demand have last met. However, on closer examination, the question arises as to why a past event should be relevant to the future, and why other, potentially more recent information should not be used to discover a future price.
Building on this question, we apply a range of new price formation models to current data available on crypto currency exchanges that depict level II market data, and compare their short-term forecast accuracy against the common-used ticker price and mid-price. Data on cryptocurrencies is used as the closest example to free markets, since cryptocurrency trading is continuous, markets never close, and interferences through oversight is extremely rare.
We find that two of the five price formation models investigated outperform the widely used ticker as a price indicator for the next trade. We conclude that the volume-limited clearing price best predicts the price of subsequent trades. Its usage can thus enhance the explanatory power of various financial analyses.
Keywords: price discovery; high-frequency trading; short-term price prediction; limit order book; mid-price; micro-price; clearing price
Meyer, A. & Fiedler, I. (2019). Discovering market prices: Which price formation model best predicts the next trade?. doi: 10.2139/ssrn.3414972