I am an Alexander Elder’s fan and student, not just because I am a refugee too (my mom is Ukrainian), but because he essentially figured it all out back in the hecking 1993, before trading even became mainstream, and his system withstood the test of more than 25 years and completely, totally different, fully automated markets.
I am also a big fan of the Jane Street “cool story”, at least the part that they shill to the public and which I understand quite well – a man studied at a very good school (Cornell), with the right tradition (ML-family) under the best teachers (Clarkson and Co.), got a PhD (which means got the Right Understanding and proper Indoctrination) and then used the Ocaml language (designed and implemented by correctness-obsessed serious theoreticians and academics) for semi-automation of error-prone tasks, with not just significant, but very large (potentially destructive) costs of errors.
What makes this particular story cool and yet not a stupid meme, is that Jane Street associates actually contributed to the Standard Library, the Compiler, the Runtime System and even provided significant parts of the Multi-Core Ocaml implementation, based on the theoretical work of Leroy himself. Only people with real knowledge could have accomplished this.
Both stories have a lot of similarities at their essence – both men followed their own insights and understanding after building up knowledge and actual experience. One of them actually traded, another actually wrote down most of the trading (market making) automation software. And then just systematically liquidated over-leveraged retards, which is essentially what all the market makers do.
The beauty of both approaches is that both cool guys acted from the /fist principles, which they have to discover, understand and strictly follow. One realized that the markets are drawn by large emotional crowds, staring at essentially the very same charts (nowadays there are algos “starring” at their inner representations of a large set of estimated hidden variables). Another realized that the mathematical rigor of the mostly-functional language (extended with a pragmatic runtime support for concurrency and effective FFI) will eliminate [the most of] the costly runtime errors in principle, and, by enforcing a well-chosen language coding style, based on the universal semantics, captured in the math-inspired syntax, one can actually write order of magnitude less bug-prone, and mostly correct from the first writing code.
I wish I could be this cool.
Anyway, let’s talk about trading crapto, even if “we” are missed out and are way too late.
First. we have to realize (and understand) exactly why neither the Elder’s trading techniques, not naive pattern-recognition bots (even with backtesting) are working consistently and will never work in principle.
The naive views, popularized by all the charting and trading literature, are that the candle-stick chart patterns is what drive the markets (move the prince). This is a classic cognitive illusion, or attribution error – when what is actually being observed used to explain out what is hidden behind the “facade” of the available partially observable and grossly incomplete public market data.
Here, once again, the universal principle of “Seeing Things as They [Really] Are” re-assets itself. The actual forces which drive the markers (actually move the prices) are NOT based on the patterns on candlestick charts. They are large. dynamic execution strategies employed by large (and medium-sized) institutions, which trade a whole bunch asset classes and whole baskets of assets of the same kind, of which crapto is usually a few percentage points of the total capital allocation.
This, by the way, is exactly why crapto moves in a perfect synchrony (which must NOT be the case in a proper market) – institutions load and unload the whole asset class based on their own inner risk assessment fully-automated strategies, and then the arbitrage bots kick in, trading the correlated to BTC pairs of shitcoins (which statistically move together, partially due to what institutions do).
This is a simple part. The difficult one is to understand when institutions move the assets and why.
Basically, the reason they move the full baskets of assets is to take the retarded retail’s (and some of each other’s) money. The “Sell It All, Today” meme is not just a meme – it shows the kind of decisions are being made, semi-automated, and at a huge (compared to crapto meme “market caps”) scale.
Essentially, the institutions only build and run inner proprietary risk-assessment/risk-management models, which they keep evolving and adapting for a few decades, and do not care about anything else (especially the bullshit memes posted on Twatteer or /biz/).
Their “signals” are not some bullshit posts, but so called “risk aversion mode” vs. “risk appetite mode” – the proverbial “greed vs. fear”, FOMO vs. Panic selling, an OOOOOO vs. an AAAAAAA.
And believe me, they put all the available data into their models, not just paid feeds of all retail’s open positions from every exchange, but all the sources behind the Bloomberg Terminal and everything related to “macro”.
And no, they are not event trying to be perfectly accurate in their assessments or predictions, even in their measurements of the latent hidden market variables – all they have to do is to load up and dump shit in a timely manner, so that they lose less than they gain on average.
One of the most important such latent hidden market variables is exactly when (at what price level) and with what leverage the retarded retail FOMO’ed in whatever the social media amplified mania phase they have had recently.
Everything begins with being able to see the right hidden market structure – where exactly the actual money (leveraged entries, stop loses, limit buy and sell orders) are.
This is how the “desks” and “floors” trade. The larger scale trades are, indeed, much closer to the “sell it all, today” meme – some decision triggers the whole cascade of execution strategies to either load or dump a whole asset class, depending on the current state of major exchange’s Order-Books, in order to minimize the slippage and potential loses (everything has been modeled and simulated before execution, of course) and to do not spook the retarded retail too early.
This is what actually moves the prince, but everything is way more complicated that this, since the systems which participate in the markets are reactive, adaptive and keep evolving as we speak.
And yet, one can trade in this environment by following Elder’s system. The key is that one cannot trade at a whim and any time one feels like. A few trades in a month, not even a day, and most of which will be at a small loss, to eventually get lucky and book a rare substantial gain.
To semi-automate this kind of trading a very basic “Trading Assistant” is enough. Ocaml or Rust are your friends here. Or just a Jupyter notebook with the very basic cctx scripts.
The key insights is that one still can build up one’s own understanding and insights and act with a strict discipline, in a principle-guided manner, semi-automating error-prone tasks with basic programming.
Everything else is just bullshit and clickbaits.
And yes, crapto is dead compared to the 65K and then 120k “cycles”. You are way too late to the party