∅xdvn111

Your Motivation Not Your Excuse

[∅xdvn111 @devan0052]

@PositionEx I'm very interested for futute...
@susanto_indraa @DiekNasrulHame1 @xBONDANx

[Bravonoid @dikibagast]

Coba deh kalo experiment buat build bot/agent, logic nya didasari dari 2 hal ini:

1. strict entry
2. sensitive exit

1/ Pertama, untuk entry suatu token/pool, itu harus melewati sekian banyak filters, metrics, atau process yang sedemikian panjang atau banyaknya.

Bukan tanpa alasan, hal ini dimaksudkan supaya token selection nya memang benar-benar yang terpilih sesuai strategy yang dipake.

For screening, its quality over quantity, less noise, better expected result.

2/ Kedua, untuk exit suatu posisi, dibikin sesensitif mungkin, jadi jangan hanya mengandalkan satu atau dua exit condition aja, misal stop loss atau low yield.

Tapi tambahin exit-exit lain yang memang reasonable.

Maksudnya sensitif gimana? Sensitif artinya ketika suatu kondisi exit terpenuhi, langsung exit posisi tersebut, tanpa perlu nunggu konfirmasi lain.

Berbanding terbalik dengan screening karena dia harus lewatin sekian banyak process sebelum akhirnya take decision (deploy/entry).

Di exit, satu condition aja fulfilled, dia langsung take decision (close/exit).

Simple nya di logika pemrograman dan matematika, entry itu pake AND, sedangkan exit itu pake OR.

3/ Contoh, misal strategy kita entry ketika suatu token harga dan volume nya spike naik, kita expect itu akan terus naik atau at least ada rebound setelah pullback, dan ketika dia slow bleed atau trend nya balik jadi downtrend, berarti strategy kita invalidated.

Nah, exit condition secara default kan udah banyak ya kaya:

1. stop loss
2. low yield
3. out of range
4. dll

Tapi dari strategy itu, kita tau kalo trend nya udah jadi downtrend, strategy kita udah invalidated sebenernya, kenapa ga kita bikin juga exit condition untuk detect ketika token tersebut berubah jadi downtrend dan exit ketika rebound di antara downtrend tersebut.

Ini bisa dilakukan lewat indicators dan price actions, dua duanya diturunkan dari OHLCV.

Trend, bisa di-detect dari short EMA dan long EMA, ketika short EMA < long EMA berarti dia udah mulai downtrend.

Rebound, bisa didetect dari RSI atau Stoch RSI, ketika value nya tinggi berarti dia udah overbought atau di local optimal nya.

Gabungan kedua ini bisa jadi exit condition untuk manage position supaya ketika trend nya berubah jadi downtrend DAN exit ketika ada rebound.

Coba lihat gambar buat visualisasi dan contoh implementasi eksekusinya, panah ijo open position, panah merah close position.

4/ Hal ini dilakukan supaya kita bisa manage position secara dinamis sesuai dengan berbagai kondisi market yang ada, sekaligus supaya tidak hanya tergantung hanya pada PnL, tapi juga pada realita pasar.

Tapi hal ini punya trade off (atau bayaran), ini bisa berarti juga kita mengurangi potensial keuntungan yang mungkin didapat karena exit lebih awal terlebih dahulu.

In my belief, its almost practically impossible to always catch the exact top and bottom or maximal and minimal of almost everything, especially in this kind of thing.

Realistically, what we can do is estimate the risk and reward so that we could rely and trust the system in the longer run.

Its our job to find and estimate the sweet spot between expected risk and reward for our strategies.

That's why autonomous system exists, if you can't trust the system of the strategy logic, then why bother build it in the first place.

Losses are expected, winnings are also expected.

[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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[∅xdvn111 @devan0052]

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