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10 Dorit Ron, Adi Shamir scheme actually enables sending micro transactions, which are of the order of 10−8 BTC (this is the smallest fraction into which a BTC can be broken, and is called a satoshi). When we also consider midsize amounts, we see that 73% (84%) of the transactions involve fewer than 10 BTC’s. On the other hand, large transactions are rare at Bitcoin: there are only 364 (340) transactions larger than 50,000 BTC’s. We have carefully inspected all these large transactions and describe our findings in the next section. Figure 5.1: Size Distribution of Bitcoin Transactions (Ron and Shamir, 2013) Larger or equal to Smaller than Number of transactions in the graph of entities Number of transactions in the graph of addresses 2,315,582 4,127,192 2,930,867 2,230,077 1,219,401 574,003 262,251 67,338 6,000 1,796 340 0 0.001 0.001 0.1 0.1 1 1 10 10 50 50 100 100 500 381,846 1,647,087 1,553,766 1,628,485 1,071,199 490,392 283,152 70,427 6,309 1,809 364 500 5,000 20,000 50,000 5,000 20,000 50,000 It is intere0s.t35ing to investigate the most active entities in the Bitcoin system, thosewhohavelnumberoftrans- actions.19suchendingorderofthe either maximal incoming BTC’s or maxima entities are shown in Table 7 sorted in desc ulated incoming BTC’s shown in the third sociates the entities with letters between A ed: B is Mt.Gox, G is Instawallet and L is F, H, J, M, N, O, P, and Q are pointed o actions (Fig. 1) which is presented in the ne s the number of addresses merged into each the number of transactions the entity is inv s that Mt.Gox has the maximal number of ulated incoming BTC’s nor the largest num first row of Table 7 owns the next largest n 0.3 number of accum 0.2 column. The left- to S out of which Deepbit. Eight ad- most column as three are identifi 0.25 ditionalentities:utinthegraphof thelargesttransxtsection.Thesec- 0.15 ond column give column present0.s1 Table 7 show entity. The fourth olved with. addresses, but not ber of transactions. umber of addresses, the largest accum Entity A in the 0.05 0 about 50% of t−h15ose of M−10t.Gox’s,−5but recei0ved 31%5 more BT10C’s than Mt.Gox. log(ε) Deepbit had sent 70% more transactions than Mt.Gox. It is interesting to re- alize that the number of addresses of 13 of these entities is a fifth or more of 70 60 40 30 20 10 ransactions they have executed, which may d used for just a few transactions. It is also s in the table have each sent fewer than 30 more than 400,000 BTC’s. Since these entiti were able to isolate them and to follow the indicate that each clear that six out transactions with a totalvolumeof50eswereusinglarge the number of t address is indee of the 19 entitie transactions, we flow of their trans- 0 −15 −10 −5 0 5 10 10 10 10 10 10 10 x Figure 5.2: Density of Preference Shocks F(ε) and Confirmation Lag N(x) 30 N(x) f(ε)PDF Image | The Economics of Cryptocurrencies Bitcoin and Beyond
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