Created at 10am, Jan 5
TarikCrypto
1
RISKS AND RETURNS OF CRYPTOCURRENCY
BKv0p25Fk1L16VDrBEPkL7WKIgsfPdsYWnteXfGOscw
File Type
PDF
Entry Count
146
Embed. Model
jina_embeddings_v2_base_en
Index Type
hnsw

We establish that the risk-return tradeoff of cryptocurrencies (Bitcoin, Ripple, and Ethereum) is distinct from those of stocks, currencies, and precious metals. Cryptocurrencies have no exposure to most common stock market and macroeconomic factors. They also have no exposure to the returns of currencies and commodities. In contrast, we show that the cryptocurrency returns can be predicted by factors which are specific to cryptocurrency markets. Specifically, we determine that there is a strong time-series momentum effect and that proxies for investor attention strongly forecast cryptocurrency returns. Finally, we create an index of exposures to cryptocurrencies of 354 industries in the US and 137 industries in China.

R-Squared 2.75 2.26 1.86 (-2.20) (-2.70) (-3.30) [-2.01] [-2.52] [-3.53] 0.01 0.02 0.03 1.54 (-1.82) [-1.85] 0.01 2.18 (-2.58) [-2.58] 0.02 1.18 (-1.43) [-1.38] 0.01 0.96 (-1.16) [-0.88] 0.00 Table 29: Bitcoin Hack by Groups Weekly Level (Percentage) Rank Low 2 3 4 5 Dierence Hack -1.21 -0.65 -0.11 0.49 1.54 Rank Low 2 3 4 5 Dierence Hack -1.21 -0.65 -0.11 0.49 1.54 Rt+1 8.62 5.59 2.36 1.14 1.09 -7.52 Rt+3 7.64 3.49 4.00 1.86 1.70 -5.95 T-Statistics 2.91 2.69 1.54 1.28 1.11 T-Statistics 2.95 1.60 1.93 1.76 1.85 Sharpe 0.33 0.30 0.18 0.14 0.13 Sharpe 0.33 0.18 0.22 0.20 0.21 Rt+2 8.18 4.23 2.16 3.09 1.09 -7.09 Rt+4 6.08 4.85 4.00 1.86 1.75 -4.33 T-Statistics 3.17 1.76 1.26 3.13 1.11 T-Statistics 2.10 2.55 2.19 1.43 1.86 Sharpe 0.36 0.20 0.15 0.35 0.13 Sharpe 0.24 0.29 0.25 0.16 0.21
id: d8edac33370094fc8af9b8793de7ce5a - page: 30
4.4 Crypto Price-to-Dividend and Crypto Volatility Obviously, there is no direct measure of dividend for the cryptocurrencies. However, in its essence, the price-to-dividend ratio is a measure of the gap between the market value and the fundamental value of an asset. The market value of cryptocurrency is just the observed price. We proxy the fundamental value by using the number of Bitcoin Wallet users. We regress the Bitcoin returns on the lagged Bitcoin price-todividend ratio and the results are reported in Table 30. Overall, there is very weak relation between the future Bitcoin returns and the current price-to-dividend ratio. For Ripple and Ethereum, the data on the number of users is not immediately available. Table 30: Bitcoin Market Price-to-Dividend Ratio Bitcoin Predictive regression at the daily level Rt+5 (5) Rt+1 (1) Rt+2 (2) Rt+3 (3) Rt+4 (4) Rt+6 (6) Rt+7 (7)
id: 71ece06f46685c5acbbd7b7ebe8abddb - page: 30
Bitcoin PD 0.13 (1.34) 0.05 (0.49) 0.13 (-1.36) 0.12 (-1.25) 0.05 (0.57) 0.09 (0.99) 0.05 (0.55) R-Squared 0.00 0.00 0.00 0.00 0.00 0.00 0.00 29 We also investigate whether realized volatility predicts cryptocurrency returns. We regress cryptocurrency returns for the past month realized return volatility and the results are reported in Table 31. Overall, there is very weak relation between future cryptocurrency returns and the realized volatility for Bitcoin and Ethereum. For Ripple, there is some evidence that realized volatility positively predicts 4-day, 5-day, and 7-day ahead Ripple returns. Table 31: Market Volatility as Predictor Predictive regressions are at the daily level. Bitcoin Rt+1 (1) Rt+2 (2) Rt+3 (3) Rt+4 (4) Rt+5 (5) Rt+6 (6) Rt+7 (7) Bitcoin Volatility
id: 6de615fafe257835b90fa4415e8f7cbc - page: 30
R-Squared Ripple 1.27 (1.52) [0.79] 0.00 Rt+1 (1) 0.79 (0.95) [0.50] 0.00 Rt+2 (2) 0.57 (0.69) [0.38] 0.00 Rt+3 (3) 0.03 (0.03) [0.02] 0.00 Rt+4 (4) 0.02 (0.03) [0.01] 0.00 Rt+5 (5) 0.21 (-0.25) [-0.18] 0.00 Rt+6 (6) 0.15 (-0.18) [-0.11] 0.00 Rt+7 (7) Ripple Volatility R-Squared Ethereum 0.62 (1.03) [0.61] 0.00 Rt+1 (1) 0.97 (1.61) [1.43] 0.00 Rt+2 (2) 0.87 (1.45) [1.37] 0.00 Rt+3 (3) 1.14 (1.90) [1.37] 0.00 Rt+4 (4) 1.05 (1.75) [1.13] 0.00 Rt+5 (5) 0.99 (1.65) [1.13] 0.00 Rt+6 (6) 1.22 (2.03) [1.63] 0.00 Rt+7 (7) Ethereum Volatility R-Squared 1.89 (0.94) [0.89] 0.00 1.51 (0.75) [0.76] 0.00 0.58 (0.29) [0.26] 0.00 0.20 (0.10) [0.09] 0.00 0.08 (-0.04) [-0.04] 0.00 0.22 (0.11) [0.14] 0.00 0.30 (-0.15) [-0.15] 0.00
id: 6bc8947381af22b72d1edea2d7a96a65 - page: 31
How to Retrieve?
# Search

curl -X POST "https://search.dria.co/hnsw/search" \
-H "x-api-key: <YOUR_API_KEY>" \
-H "Content-Type: application/json" \
-d '{"rerank": true, "top_n": 10, "contract_id": "BKv0p25Fk1L16VDrBEPkL7WKIgsfPdsYWnteXfGOscw", "query": "What is alexanDRIA library?"}'
        
# Query

curl -X POST "https://search.dria.co/hnsw/query" \
-H "x-api-key: <YOUR_API_KEY>" \
-H "Content-Type: application/json" \
-d '{"vector": [0.123, 0.5236], "top_n": 10, "contract_id": "BKv0p25Fk1L16VDrBEPkL7WKIgsfPdsYWnteXfGOscw", "level": 2}'