Here, I present to you our single-most important data table yet, displaying in all its glory once more that our algorithm is fully capable, dully-tested and confirmed to be generating income directly out of thin air. Thus, in the process of managing investments with a certain asymmetry it trades rather more advantageously than not.
A mesmerizing construct is that which produces such a desired outcome; that it far outweighs the originating elements from which it came from.
Herein, it can be observed that inevitably the total cost varies in polarity, aptly alternating between that which is positive and negative, as though it were dancing in a way as to display a certain level of elegance. So alluring in contradiction to accept its transparency as nothing more than the mere consequence of its immense obfuscated value, hidden in plain sight for the plain masses to dismiss. Patiently awaiting for the glory to surely become more and more evident over time.
For more information visit our home page at: https://zephirex.com/#pricing
Performance report is available.
Hello and welcome to our most recently updated portfolio report, visually it is represented by the percent of Return on Investment.
Please note that the column named Quote 2 is for use of pulling the data that is closely related to the actual market places in USD, we understand the fact that USDT is another form of currency, and thus it does not truly reflect the current market prices per trading pair, but it is sufficiently close enough for the time being. (Market data is being pulled from Poloniex for convenience purposes only.
So we're up $5,000 USD from 30 days ago, let's compare that to what we had before and see if it matches exactly what we are seeing or if there is some type of discrepancy in our numbers.
Noted, so according to my notes this very closely correlates with what I had about 30-days ago, and how my total balance has been increased by this amount, but what kind of earnings am I generating vs simply getting lucky remains to be seen.
For the record, our software has traded over half a million dollars in a 30-day period but this is just to show the capabilities and how it's designed to adapt to uneven changes in the market.
As of the writing of this report a few important key elements are to be taken into account as we observe the only recorded profit from all our 6 trading pairs in the last 30 days as shown below.
- The observed market changed by roughly +11.4% since Nov. 20th
- Net profit in BTC units is roughly 0.0338 BTC
Thus, (hypothetically speaking) if we were to find out what our initial investment should have been 30 days ago for us to have made this profit, we can simply divide 0.0338 by 11.4% and this gives us approximately 0.2965 BTC.
Meaning that 30 days ago we would have had to invest 0.297 BTC to profit by 11.4% and gained a total of 0.0338 BTC.
And 30 days ago a single BTC cost $18,600 USD so the initial investment of 0.297 BTC translates to about $5,500 USD.
However, since the 0.0338 BTC is now worth more than it was back then, this gain is actually close to $800 USD, so that means that if we were to make $800 USD from $5,500 USD, then that would be a 14.54% profit, and since BTC went up by 27% in the last 30 days, that original $5,500 investment would have resulted in an additional $1,485 USD as opposed to the $800.
But hypothetically speaking again, if I made 14.5 in a market where the price only went up by 11.4%, then CORE appears to have gained from the leverages between LTC, BTC, and USD.
All-in-all, the point of Zephirex CORE is to make best use of volatility as possible, and given that I have been making changes to the wallet, then this has not allowed for the software to fully close those open positions, the funds were not fully available for the software to make the safest best investments available at the time.
Calculating losses for this period.
Our performance report for the period of 10.9.2020 to 11.8.2020 shows a loss in most markets, this is due to the fact that the USD has been doing fairly weak against the BTC.
So today we'll look at the worse-performing pair -- that being ZRX-BTC, and find out why it seems to be doing so terribly.
ZRX-BTC chart analysis
When checking the 30-day price change for this pair, we see that it has fallen 32% since this period began, the orange rectangle in the chart above gives us two pieces of information when selecting the start and end range. Firstly, it gives us the 30-day period window we are currently looking at (see bottom, center of large orange section), as well as the net percentage change for this time frame (see right of large orange section rectangle).
Great, so now that we are aware of the net change during this time-frame, let's find our current average per our excel sheet. It shows that we have purchased 5300 ZRX for a total sum of 0.146 BTC, this puts us at the approximate price of 2.75e-5, or 0.0000275. And this price is marked as a gray line from the bottom 30% of the orange rectangle. So far so good, given that BTC has been spent at an average price that is above the current price, this is represented as a loss -- as selling at the current market price would be the equivalent of buying high and selling low.
Feel free to comment below on my trading algorithm's strategy, if proven effective at minimizing losses we hope to confirm this in due time with a more detailed graph of the process, hopefully one that shows both price and position when stacked on a single graph.
A requirement in trading as well as most other things in life, scaling as is defined by the Websters dictionary: v. to find out the size, extent, or amount of. And it is exactly what we are currently working on, is the ability for our software to adapt to certain changes in terms of demands for maintaining a steady volume while steadily decreasing the rate of trades in relation to the size, so in other words; larger size orders at a lower rate of fire should mean that the risk has not been drastically increased (by my current understanding of risk).
This is why the rate of trades has been decreased from an average of 18000 trades every 30 days, to roughly 16,000 trades. And the minimum size orders has been modified to increase by about 5% until a certain condition is met.
If the condition (that being for all balances to become in equilibrium and safely and steadily balance each other correctly), then the scaling can be incremented, otherwise -- if the balances incrementally are in disarray and are unable to achieve a certain balance, then the scaling must be decreased (meaning smaller sized orders at a higher rate of fire).
Correct me if I'm wrong
[Update] A new report has been made with the correct currency pair of ZRX/USD.
Our more costly loss has accounted for less than 4% in losses of our entire portfolio in the last 30 days, yet this same market has fallen 38.7% in the same time frame.
Have we gone mad here? Is there something we are missing? Is our trading algorithm outperforming the market, or have we missed a key component in the math? Why would a drop of 39% only reflect 4% in loss? Please do not misunderstand my concern, I am grateful of this aversion, perhaps this is only wishful thinking. Should there be an even greater loss?
Also, please be advised that the gaps in trades do not fully represent the extend of trades our algorithm has processed. This reminds me that we are in the process of scaling our operations to be slightly more aggressive in terms of trading volume and monitor the situation for any unforeseen events which may arise from it.
Welcome! I'm sure by now you're wondering what this is all about... Zephirex was started as an idea for an automated trading algorithm, "and what is that?" you might ask -- a computer program which buys and sells stocks at high-speeds to make a buck. That being said, trading involves a certain level of risk, and the software aims to do this by overlapping risk-management and automation through the use of real-time data.
Our efforts are aimed at two objectives:
- Generating more money than is invested, and;
- Manage and monitor risk accordingly.
Our software has undergone a few stages in development which have led to the conclusion that great progress has been made in an effort to tackle the previous two objectives. Our reports have shown improvement in performance as far as earnings go, the automated trading algorithm has successfully undergone the changes that are required to fulfill the following requirements:
- Stop losing money
- Generate profits and/or minimize loses for any and all given "trading pairs" or "stocks"
Excellent, so what's the catch? Well, the catch is that as of September of 2020 we rely solely on a single accountant (that being me, the founder and creator of Zephirex CORE). So we are currently looking for skeptics of the matter, tried and true investors and accountants that can corroborate our sheets.
Fully tested in the real markets
Back-testing, by examining the worse case scenarios and observing the results in the real market -- we have obtained amazing results! Truly, starting with the fact that ROI does very well when the market is in great shape, but also recovering from a dreaded steep fall. Our algorithm is absolutely and positively non-linear, meaning it accommodates to market changes big and small, and it does so at the real-time level. Currently trading at the level of volatility of cryptocurrencies, the level of aggression can be adjusted at both the size of the trades and the frequency with three different metrics:
- Aggression level (0% - +100%).
- Minimum Order Size Multiplier -- meaning if minimum order size is $5 and MOSM is x1.5 then it generally trades $7.5.
- Fee -- This is YOUR imaginary fee, it can be your broker fee, or higher. Of course a higher fee means less overall trading volume but it is all contingent on your desires for volume, profit, or speed.
So, a little bit about me, in 2009 I began my journey as a self-taught web developer and went on to develop web applications in sales, reservations, and security fields, as well as mobile and responsive front and back-end programming.
Then, I began school for mechanical engineering in an attempt to harness the universe.
Eventually I came across trading in Bitcoin around 2013 and Ethereum in July 2015, I soon became interested in learning to trade through cryptos, and during those early days there were some losses through some hands-on experience; having learned of a few hacks of the platforms I was using then -- the concept of risk became more and more ominous.
Tying everything together
It was not until I began observing a trend in automated trades that I began the search for a single algorithm which would become the mandate and dictate how the trading world operates inside and out of cryptocurrencies. Obviously, the journey has only just began -- yet in my efforts, I am optimistic that certain factors come into play when trading (or exchanging) any form of value. Inherently, the laws of nature apply to the real world and Zephirex CORE is the closest my interpretation has come to mastering this objective.
My wishes are for Zephirex CORE to amass copious amounts in both earnings value and credibility through hands-on experimentation as I have done so, as well as through the use of secure APIs that would allow others to become direct beneficiaries of this knowledge I have acquired.
Understanding trading psychology is always super important.
So, in pulling a report for the last 30 days we still see a loss of 10% in market value for Bitcoin, yet a profit in the trading algorithm. Please refer to the following screenshots and let us know what you think through a comment.
Please note that the 411.17% on the spreadsheet below is a measure of USD sum spent, and does NOT reflect the total Return on Investment.
ETH-USD - being the biggest loser is where your attention will be drawn to now...
Above we see roughly a 6% downward change in the market price for ETH-USD, so we believe that the software may be over-trading this pair for some reason. An adjustment is required for these type of scenarios where the algorithm over-trades, though to be honest it seems as though the algorithm is not keeping up too well with either saturated markets or very volatile price changes, more detailed data will be obtained.