I posted this on my private Telegram last night with spreadsheet you can download
Here is an example of last nite. it is up 5.45% for all the positions. Is it worth to stop on the first one? Or continue to risk losing first return of the position of 4.27%? in this case, I was lucky but I can easily lose the profit or go negative entirely. this is my point of what can happen. I am able to control the losing positions when my weight average of the big 5 cryptos coins are >%1. This was the case last night so I include the mock positions. the crypto market is still >1% right now So i reset to see what happens from this point on. what would you do ?
Hi Bryan, I have read https://www.youtube.com/watch?v=A07CBHXq75AI was wondering, are there any codes on github where one could execute an indicator from MT4 or Tradingview via Java, or instead of executing orders, receiving buy sell signals via sms from an MT4 or tradingview indicator, via java, on an sms? How would you construct such indicator?
My answer is in the video but in a nutshell: always use the market data of where you trade or submit orders.
Everything described is in this future.
Also, in this video I addressed the changing situation of brokers due to their Python API support. One example is how Dukascopy seems to become irrelevant since more people want machine learning in their trading. It seems they seek Python for this. You can find all these answers towards the end of the video .
As i have measured this ‘risk’ for thresholds and daily target moves, it is critical to minimize your loss and protect daily profit. You can always do this with market data. You do not want to over trade as I call it. I have shown many examples of achieving a profit level but find you can lose within a few minutes. So why do that? You can now figure why pro readers or the gurus finish their trading within a hour. Now you know why.
In this video, you will find how I am able to quantify the risk. I set different trading ‘modes’ based on the risk results I see. It helps to meet the trading goals I mention above. Some people have difficulties to figure this out. Uh…are they pro traders? Probably not. Let’s put it this way I have learned how many 7-8 digit traders who lead desks do it. This is it! Also, it is very effective and simple. Plus you get more time off if you wanted.
As for me, I am not going to argue with folks who do not generate logs nor analyze them to understand the nuances of the asset class they want to trade. Nor do they focus on trading execution on this same market data. All they do is base it on hunch or do some back test in a severe negative period like 2008/2009. Seriously, they will be surprised when they see how their strategy/algo does against current market data. If you want a conversation, show me a current set of logs of your market data with real trades. Until then, you most likely will wasting all involved with their time.
As you know, there is a cap on the requests to a Binance server for market data. This was suggested for Bitmex which appears not to have such a limit. This was from a Meetup last night which was mentioned. Thanks to this person for the suggestion,
And the solution is
Here is the underlining webservice stream which the Detla server uses from Bitmex to stream the trade/quote data without hitting the rate limit. I think this is what James was pointing out.
If I am not mistaken, this results in a complicate Python dict data structure. Understand this is not an easy object to work with. All you need to do is search on Google for a term related around ‘dict within dict’ to find a solution. This took me a number of hours to figure out.
Hardest part of trading is optimal mark entry. I am tweakting my automated watchlist so I made video on this. This videos shown in the video below is part of Python Infrastructure Building Block course explained below. It is part of my Quant Elite membership which is also below. I am not going to showcase videos like this anymore but I want to stress the the difficulty of find these optimal market indicators.
Working on this automation code for a watchlist for both entry and exit. This includes monitoring for open positions.
#***watchlist for entries
#query for watchist
#iterate through based on each stock pick combo (from report) with no open positions
#use parameter to meet condition of market order
#if met, put position and flag combo as open position since it is put on (check rick management using tool like Kelly Criterion)
#****watchlist for exit
#query for open positions
#iterate open positions where ATR needs to be met in order to close/exit
I tried my reports as explained in the past few weeks. This include various market conditions that I only came across 2 pairs of interest. I may need to develop a watchlist script that will place orders when conditions are met.
Market conditions for an order
As with no difference in a pair trading, you need to use a benchmark to compare your crypto currency pair against. This will be BTCUSD (Bitcoin/US Dollar) as that is the grand daddy in this asset class. If you have followed me years ago, I I use indicators like Beta for those outperform the benchmark. We can place a market order using position sizing from my portfolio optimizer I have demoed numerous times.
Yesterday there were no longs generated after the meltdown of Bitcoin from Friday. it seem that crypto currency was a dead asset class. It got me worried since I had no content for webinar I did earlier. tonight. As a result, I had to rework how I approached using this new script I developed a few weeks ago.
Here are the script changes
1. I reduced the look back period from 1000 to 200 days which makes it more than 6 months.
2. I added some new columns after running a linear regression. 4 new columns were added to ranking spreadsheet which include slope, r-value, p-value, and standard error.
3. A new sorting criteria which is in the order of slope, volume and volatility. Note that I will not report any crypto currency less than a volume of 45 million. This is the latest captured bar of volume with closing price added as well.
There is stlll lots of filtering to do which will makes this more precise as I choose which crypto currency pairs into enter the market via Binance exchange.