• Media type: E-Book
  • Title: Mind the Gaps : Short-Term Crypto Price Prediction
  • Contributor: Martin, Payton [Author]; Line Jr., William [Author]; Feng, Yuxin [Author]; Yang, Yunfan [Author]; Zheng, Sharon [Author]; Qi, Susan [Author]; Zhu, Beiming [Author]
  • Published: [S.l.]: SSRN, 2023
  • Extent: 1 Online-Ressource (28 p)
  • Language: English
  • DOI: 10.2139/ssrn.4351947
  • Identifier:
  • Keywords: Crypto ; Bitcoin ; Market Microstructure ; Micro-price
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 15, 2022 erstellt
  • Description: Quant methods for short-term price prediction of tradable assets have been studied by academics and practitioners throughout finance. One such robust predictor of price movements is the micro-price. The micro-price “can be considered to be the ‘fair’ price of an asset, conditional on the information in the order book”, and has been shown to be a better short-term price predictor in equity markets than the mid-price and weighted mid-price (Stoikov 2017). In this study we seek to apply this idea to define a robust estimator of the micro-price for Bitcoin (BTC). Sourcing high-frequency, limit order book (LOB) data from Bitstamp, we construct three mid-price adjustment estimators of the micro-price. We show that the Volume-Adjusted Mid-Price (VAMP) outperforms trade and quote imbalance adjusted mid-prices in both prediction of short-term price direction and larger, one standard deviation price movements
  • Access State: Open Access