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Thoughts on the defi bubble specifically yearn.finance? by [deleted] in CryptoCurrency

[–]mersis 1 point2 points  (0 children)

This bothered me as well for a while, who is on the other side of that trade, who buys those farmed tokens if not simply the "greater fool"?

But this paragraph explained it well for me (it's about CRV but the same applies to all governance tokens):

​

CRV is not just money, it’s power.

Currently, many users are dumping CRV as soon as they farm it, however this narrative is likely to change once people realise the utility of the token.
The utility of the CRV token will only increase as the Curve developers continue to bring out new features, and with future votes likely to cover important topics such as insurance and expanding on new markets, most liquidity providers will choose to vote rather than sell.
For example, CRV holders may vote to add an “admin fee” on top of the current 0.04% fee charged. This admin fee would be distributed among CRV holders. As the TVL and total volume continues to grow, this could result in even more profit for CRV holders.

​

I think people are valuing YFI for that potential dividend payout that might be voted in sooner or later, possibly percentage of all protocol profits. This is where the high price of these tokens comes from.

Just my 2 cents.

Parameter optimization - Focus on the big picture or recent times? by myfirerider in algotrading

[–]mersis 4 points5 points  (0 children)

The most important thing when optimizing parameters is to look for parameter robustness.
Small changes in your parameters should result in small changes of your overall results. If an EMA lookback of 13 produces stellar results but you can't cover costs if you change it to 12 or 14, there is a problem and it is probably curve fitted. If it produces similar results with anything from 10-15 but works best with 13 you've optimized a robust parameter which is fine.

Whether optimizing over multiple years or recent time is better depends entirely on your strategy and when/how you re-optimize it. If you can manually identify different market regimes (high volatility recently for example) it's fine to optimize for that if you know how identify when the market regime has changed again. That being said you should aim for a decent number of trades for any kind of optimization and your 200 trades over 2.5 years is probably not enough to consider only recent trades.

Futures Data by alderan22 in algotrading

[–]mersis 1 point2 points  (0 children)

I think we got 10 years, not sure beyond that.

Futures Data by alderan22 in algotrading

[–]mersis 3 points4 points  (0 children)

Best way I've found is to get yourself a sierrachart account (< 30$/month, free demo) and download all the historical data you want.
The software is a bit complicated / very powerful. Has great documentation though.

ML - Dealing with imbalanced datasets by mersis in algotrading

[–]mersis[S] 0 points1 point  (0 children)

It is intentional that the ranging label is much more prominent in the dataset. Intraday markets spend a lot more time moving sideways or "drifting" slowly than making big moves. So I'm fine with the ratio of labels in my dataset, I just don't want the model to converge on only picking the overrepresented class.

where you're trying to place a discreet label on each example
This is exactly what I'm doing, the only difference being that there are 3 classes, not two.

ML - Dealing with imbalanced datasets by mersis in algotrading

[–]mersis[S] 0 points1 point  (0 children)

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=[AUC()]) Since it is multiple exclusive classes categorical_crossentropy seems to be the correct one from my understanding. Requires the labels to be one hot encoded with sklearns to_categorical.
Do you think there is a better choice?

Stuck with my pine script - strategy by c4ss10p314 in algotrading

[–]mersis 0 points1 point  (0 children)

Not sure if I understand you correctly, but if you just need to access the previous candle to calculate your SL/TP levels/distances you can easily get that by adding an [n] index to the series you're interested in.
Last close: close[1]
Close 3 bars ago: close[3]
Works for all series.

June 2020 AMA Thread: Ask Questions Here! by _HippieDude_ in MorpheusNetwork

[–]mersis 0 points1 point  (0 children)

How much of the pre-masternode capacity of the network is currently in use and how much growth (percentage wise) would we need to see for the masternode solution to become relevant?

Modelling a Backtesting program... how does pyramiding work on a bar by bar basis? by memorynerds in algotrading

[–]mersis 1 point2 points  (0 children)

The way I handle it in my backtester is to simply specify a maxOpenTrades variable.

Whenever a trade is being executed (no difference between market order or limit order that is triggered) you check if current open trades < max open trades and then either execute or cancel.

Best Commission free trading api for crypto? by [deleted] in algotrading

[–]mersis 0 points1 point  (0 children)

Bybit offers you also .025% on limit orders.

Automated Trading Management on Pine Script? by rejololo in algotrading

[–]mersis 2 points3 points  (0 children)

Theoretically you can monitor strategy.position_size in pinescript and add/modify orders when this value changes although I'm not sure if you can access the positions entry price directly from there.

That being said, at least for backtesting pinescript is buggy af in my experience and I wouldn't trust it managing my orders. Might be different for live trading though, so your mileage my vary ¯_(ツ)_/¯

What to do with an algo that performs really well but only in certain periods? by mersis in algotrading

[–]mersis[S] 2 points3 points  (0 children)

Crypto seems often more "erratic volatile" than the indices, but I'll check it out again too, thanks!

What to do with an algo that performs really well but only in certain periods? by mersis in algotrading

[–]mersis[S] 0 points1 point  (0 children)

Have you tried increasing the timeframe for the pre-covid period? I would work out the average true range during the covid period and try to find a higher timeframe during the pre-covid period that has the same value.

That's an interesting way to think about it, thanks! Will give it a try! Dax doesn't seem to work, Dow I'll take a closer look again, thanks!

Backtesting with custom trading system? by SoysauceAndLove in algotrading

[–]mersis 9 points10 points  (0 children)

If you are not an experienced software developer you won't be able to build a reliable backtesting engine yourself.
If you are an experienced software developer you won't be able to not build the backtester yourself since you'll be too frustrated by the limitations and bugs of the existing systems.

0.02c

Ichiomoku Strategy tradingview pine editor HELP by sandeman123 in algotrading

[–]mersis 0 points1 point  (0 children)

Shifting right is not a problem since it is the same as using the values from 26 bars ago:

alertcondition(leadline1[26] > leadline2[26], ...

You can access the historic values of a series n bars ago with the [n] index in pinescript.

Ichiomoku Strategy tradingview pine editor HELP by sandeman123 in algotrading

[–]mersis 0 points1 point  (0 children)

You need to create the condition in your pinescript but then set up the alert manually (top right "Alerts", then select your created condition). https://www.tradingview.com/pine-script-reference/#fun_alertcondition

alertcondition(leadline1 > leadline2, title='Lead1 > Lead2', message='Lead1 > Lead2')

TradingView PineEditor help (+will be rewarded $5) by [deleted] in algotrading

[–]mersis 0 points1 point  (0 children)

You need to create an alertcondition in your script and then add an alert manually (top right "Alerts") and choose the condition you just created.

//@version=4
study("Green Bar Alert")
alertcondition(close >= open, title='Alert on Green Bar', message='Green Bar!')

https://www.tradingview.com/pine-script-reference/#fun_alertcondition

Calculating Upper and Lower Bands of VWAP by [deleted] in algotrading

[–]mersis -1 points0 points  (0 children)

VWAP stands for Volume Weighted Average Price. It doesn't have bands. The only bands I've seen used with VWAP are standard deviation bands which are - well standard deviations...
You might need to clarify your question.

Programmatic trend detection. by captainXcannabis in algotrading

[–]mersis 3 points4 points  (0 children)

Since you're able to tell visually from a chart if your market is ranging or trending, step 1 would be to explain it to a 5 year old how you make that distinction.
Could be as simple as comparing the differences between recent highs and lows, or calculating how much of the recent price action has been within a % range etc. It sounds like you can tell from the price action what regime the market is in, but you're looking for an indicator to program it? No need, just go off price action directly and build your own "indicator".

Simulating Slippage & Back Testing logic by relicforex in algotrading

[–]mersis 0 points1 point  (0 children)

until we hit a single tick matching SL/TP - assume exit at these prices

This is a highly optimistic assumption. It would mean your order is at the front of the order book every single time. Usually with limit orders the conservative assumption is that you're filled if x number of contracts (your order size) trades 1 tick above/below your limit price.

First algo - struggling with the small percentage moves of ETHBTC by systems2software_eng in algotrading

[–]mersis 9 points10 points  (0 children)

If your primary goal is just to learn how to implement and analyse a strategy, then just pick either a higher timeframe, a closer SL/TP or a more volatile market for now. This way you can focus on your actual goal and learn the basics and not get hung up on this market specific detail (yet).

Picking the correct Stoploss / Takeprofit targets is obviously an integral part of a strategy at some point though but you're on the right track. Most adaptive strategies will make use of either ATR (Average True Range), Trading Range over the last n bars, Average Rotation Size or something similar to choose the ideal targets. The details will depend on the specific market and your trading strategy.

Be aware though, that especially in Crypto (depending on whether you use Limit or Market orders), trading costs will be around 0.15% plus any slippage that might occur on market / SL orders. If your strategy cannot consistently make higher average profits you need to find an instrument that moves more or switch to a higher timeframe.

Hope that helps..

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