Quant Trader's Journey

Dear people, I would like to share my view on the current state of crypto currency markets. I do not think that this is the right time attack crypto markets with a "quant" approach trying to identify inefficiencies in or between cryptos (I am not talking about structural inefficiencies that can be exploited like cross exchange arbitrage etc.) Inefficiencies that we used to seek in settled assets require some level of macro ground (things like economic purpose, history, role in the value chain of the asset to be modeled) which helps us come up with some hypothesis on possible future behavior. Additionally, pure data driven approaches is a challenge due to the amount and quality of available data. Looking at the current state of crypto markets, I see this more as a value betting opportunity than an inefficiency seeking opportunity. I prefer seeding, which is betting on a set of cryptos after some kind of filtering and keeping the same amount of equity on market leaders...

My latest post at http://quantsjourney.blogspot.co.uk/2017/09/time-of-day-effects-in-fx.html was on time of day effects in FX and I was claiming that you can actually make money with simple strategies depending on time of day. Below you will find 2 very simple strategies you can play with and make some money. Do not forget sending my 20%, I know I can trust you. I will now test these strategies with M15 bars with my quick and dirty backtester on 15 currency pairs including majors. Backtesting period is 01.01.2007 - 05.05.2017. The charts are profit in pips for the pairs where the strategy has positive P&L, these are not equity curves with equally spaced time, the horizontal axis is number of trades. But obviously equity curves will be similar with some gaps due to days with no trades. I almost did not optimize these strategies, there is room for improvement. Strategy one: Short at GMT 09:15 am, do this on Wednesday, Thursday and Friday, close after 5 hours. Check out EURU...

Time of day is critical for trading, it is even possible building trading strategies solely depending on time of day (I will keep this for another post) I will be using the concept of quality and define a high quality market, from an intraday timing perspective, as a market when trading range and volume are high and spread is low. I assume this as a good time to trade as trading cost (spread) is low compared to trading opportunity (range and volume) I start importing libraries, In [23]: import matplotlib.pyplot as plt import pandas as pd import bulk_tester as bt import numpy as np % matplotlib inline I then load data for a couple of years for EURUSD, here I am using my own library for loading it from a csv file containing 15 minute bars and sampling at each 60 minutes. In [24]: pair = "EURUSD" dftest = bt . get_data ( pair , 'BT' , resample_period = '60T' ) ...