Wrote a parimutuel system. Thought it would be cool at gatherings
import numpy as np
from fractions import Fraction
import pandas as pd
from odo import odo
def dec2percent (dec):
"""dec2percent(2)
"""
return np.reciprocal(float(dec))
def fractional2percent (fractional)...
you might be seeing partial fills. no idea what a wall of 100 share orders is. what makes you think a single instrument holds much info? don't you think instruments behave together?
Ok, maybe gamma was an unclear choice. But the etf needs to buy on up days and sell on down days to rebalance NAVs with the reference index. I thought using delta and gamma terminology made things easier, apparently not
In options when you're short gamma and underlying goes up you need to buy to rebalance your position. That's what I was getting at. Leveraged etfs need to buy on up days and sell on down days to rebalance
If you think of the leverage factor as delta then if reference index goes up 1% a 2X etf needs to go up 2% which is where the rebalance comes in. So on huge up/ down days levered etfs exacerbate the move
What does the spec say? Usually levered etfs should multiply what the reference etf did on the day. They are basically short gamma and were front run at end of day years ago, maybe still are. Shorting both leveraged and inverse leveraged probably a good trade depending on costs
Assume the servers are the best available. I remember highly customized kernels, openonload bypass, fpga, microwave networks, a lot of internalized orders, unimaginable fees. Taking advantage of how networks and routers work over tcp and udp