The Litepresence Report on Cryptocurrency

Paladin69 said:
pres, is icy less effective the more ppl there are that use it? I planned on tipping u probably a lot more than 100 $150 users combined if this thing really works that well.
Click to expand...





At the minute I'm offering ICY really cheap... but for rent without open source code. I want to get real world data from multiple parties and do some real world analysis on that very question.


To get an idea of how it works...

The "spread" is the price range from the last buy to the last sell.

ICY spank places orders of anywhere from 250.00 to 350.00 LTC (at random); those orders are on the books anywhere from 25 to 35 seconds (at random) with anywhere between 4 and 10 seconds of latency (I have no control over this) between orders. The buy price is a random price in the lower half of the spread. Sell price is a random price in the upper half of the spread.

Every 25-35 seconds the process repeats; new entropy factors are generated, new ticker data is accumulated, new orders are placed. SPANK users are assured their orders are at or near the top of the book always.

.... so how could users with more than $100k of holdings make the MOST effective solution to ensuring that your orders get filled?

3 BTCe accounts each running 3 instances of spank. Each account would have instances running on different offsets... but the three instances on each individual account would have the same offset.

So at any time you'd have 3 6 or 9 orders on the books,.. from there orders could be proportioned to your holding size to maximize effectiveness. But this customization would require the user to buy rather than rent spank.

Before we get there... I want live data. Hence my 30 day special $39 offering which is 60% off the market order version of spank.


One thing that spank has going for it... VERY LOW trade frequency... one trade every 3 days on average for LTCUSD since Nov 1 2013... the less trades with the same gain, the wider the margin per trade. The wider the margin per trade, the less a fixed amount of slippage becomes an issue.

zeMan said:
Pres, Awesome job with SPANK! The Iceberg order is what we needed!
Click to expand...

Thanks!
 
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oaGD0nn.png




1st day sales of Icy Spank...

vqMuijV.png



if you're new to cryptotrader please use my affiliate link so I get commissions for you signing up:

https://cryptotrader.org/?r=72

much love,

litepresence
 
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The backtest looks like it skips a huge chunk of time...

2013-11-01 19:00 Simulation started. Balance: 10000.00 USD
2014-04-22 21:00 Iceberg Ask Number 69
 
I decided to take advantage of liquidity swaps. If I'm going to bet on the market direction, I'm going to have to sink more money into it. I'm starting to feel more bearish about it, so I might try to short again.
 
Paladin69 said:
The backtest looks like it skips a huge chunk of time...

2013-11-01 19:00 Simulation started. Balance: 10000.00 USD
2014-04-22 21:00 Iceberg Ask Number 69
Click to expand...


The log file only has so many lines. The bot ran during the period from 11-1 to 04-22... you just can't see the data. One of the limitations of crptotrader is the limited log file lines. You'll notice in live mode that over time you'll lose old trading data too. It doesn't effect trading... just reporting. I can code around that by making fewer reports or running backtests for fewer days to zoom in on detail log reports while in development.

So its giving you the initilization report and the most recent 100 or so debug lines. The bot probably had thousands of debug lines in that time from all the small trades.


Also in backtest mode it always places orders at candle closing price regarless of where I have coded the limits. "ticker" data is bonded to candle close in backtest mode.
 
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Also someone mentioned this...

<>did you let it initialize for 24 hours
<>before letting it use your money?

<me>how do you let it "initialize for 24 hours"? do you mean backtest for 24h?

<>lock your money in a limit order so the bot can't use it for 24 hours
<>and let it collect data
<>then let it go

<me>rly? pres never mentioned that
<me>is there a bug?

<>no
Click to expand...

no idea what he's talking about...
 
Certain strategy implementations require realtime aggregation of ticker data. For instance, if you want to wait for the estimated moving average over the past 30 ticks to be above the current price to buy, you must have data for the previous 30 ticks. When starting a bot, it may be that cryptotrader doesn't automatically give it the information from the market prior to the start of the bot. In other words, maybe BTC was $500 when you started the bot, it goes down to $495, your bot thinks it should buy, because all it knows is $500, so it thinks that is the average. But what it doesn't know is that it has been around $400 all day, and happened to spike to $500 the second you started the bot. Back down it goes from $495 to the real average of $400 - and you've bought too high.

Not sure if this is how cryptotrader works, cause I haven't done anything there or thought about it in a while, but I remember thinking about this before. I don't have any strategies that would trade any significant amount in the first 24 hours anyway, so it never really mattered to me.
 
Now that I think about it I remember pres mentioning initializing his bot somewhere in this thread, referring to dragonslayer.

When I was running dragonslayer I kept most of my litecoin away from it by setting a sell order that would never be filled, something like $1,000. With only a few litecoin available, the bot said something like 'less than $500 available, buying maximum coin.' Or maybe it was 'selling all coin.' That's what I referred to earlier that it wasn't built for an investor like me, only wanting to risk a small amount of money until I see how it works. It would say 'bull market' and then 5 minutes later 'bear market'.... this might be because it hadn't run long enough to initialize, didn't have any history of data to determine a real pattern. Assuming it would be able to determine a real pattern with ample data, of course.
 
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nayjevin said:
Certain strategy implementations require realtime aggregation of ticker data. For instance, if you want to wait for the estimated moving average over the past 30 ticks to be above the current price to buy, you must have data for the previous 30 ticks. When starting a bot, it may be that cryptotrader doesn't automatically give it the information from the market prior to the start of the bot. In other words, maybe BTC was $500 when you started the bot, it goes down to $495, your bot thinks it should buy, because all it knows is $500, so it thinks that is the average. But what it doesn't know is that it has been around $400 all day, and happened to spike to $500 the second you started the bot. Back down it goes from $495 to the real average of $400 - and you've bought too high.

Not sure if this is how cryptotrader works, cause I haven't done anything there or thought about it in a while, but I remember thinking about this before. I don't have any strategies that would trade any significant amount in the first 24 hours anyway, so it never really mattered to me.
Click to expand...

oh that makes sense... thanks!
 
Paladin69 said:
hmmmm...

https://cryptotrader.org/backtests/C9XkNLCuE72MSwtDT
Click to expand...


amongst botsmiths... we refer to these losses in terms of "win percentage"



Investopedia explains 'Win/Loss Ratio'


For example, if you made 30 trades and of them 12 were winners 18 were losers, your win/loss ratio would be 2:3. Your probability of success would be 40%.


The win/loss ratio is used in calculating the risk/reward ratio. It is not very useful on its own because it does not take into account the monetary value won or lost in each trade. For example, a win/loss ratio of 2:1, means the trader has twice as many winning trades than losing. Sounds good, but if the losing trades have dollar losses three-times as large as the dollar gains of the winning trades, the trader has a losing strategy.
Click to expand...


http://www.investopedia.com/terms/w/win-loss-ratio.asp


WIN/loss is not to be confused with PROFIT/loss:

Investopedia explains 'Profit/Loss Ratio'

Many books advocate at least a 2:1 ratio. For example, if a system had a winning average of $400 per trade and an average loss over the same time of $240 per trade then your profit/loss ratio would be 5:3 or 1.67:1.

The profit/loss ratio can be an overly simplistic way of looking at performance because it fails to take into account an individual's risk tolerance or the probability of gains for each trade.
Click to expand...

http://www.investopedia.com/terms/p/profit_loss_ratio.asp


Market order SPANK v1.0 earns 290X cash on 59 trades. At 70% that's about 41 winning trades and 18 losing trades.




simplified:

win / loss (we generally strive for 3:2 aka 6/10; spank scores 7/10)

is ratio of tally of profitable trades vs losing trades.

profit / loss (books recommend 2:1)

is the ratio of profits per average winning trade vs losses per average losing trade


Here are the W/L and P/L statements for SPANK from Nov 1 to April 30th in both cash and LTC terms:

[TD="bgcolor: #99ccff"] Cash loss [/TD]
[TD="bgcolor: #99ccff"] Losing Tally [/TD]
[TD="bgcolor: #99ccff"] Cash profits [/TD]
[TD="bgcolor: #99ccff"] Winning Tally [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -221,035.36 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 565,131.63 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -85,113.72 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 369,249.26 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -39,549.82 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 327,335.52 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -14,965.17 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 319,763.55 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -12,928.66 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 283,375.21 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -11,843.99 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 246,189.70 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -9,445.14 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 203,056.42 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -9,014.66 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 182,651.50 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -8,899.03 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 159,030.79 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -8,284.78 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 146,752.80 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -7,547.66 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 133,071.82 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -7,510.09 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 118,048.64 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -7,488.35 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 92,315.03 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -7,457.44 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 82,319.74 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -7,312.91 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 71,681.15 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -7,154.98 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 45,402.82 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -6,911.31 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 44,717.54 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -6,437.25 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 21,824.14 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -5,941.81 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 17,577.18 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -4,761.23 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 14,140.35 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -2,986.31 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 13,959.48 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -2,578.04 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 6,897.21 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -2,531.58 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 5,953.59 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -2,362.36 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 3,048.52 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -2,348.18 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1,902.96 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -1,761.74 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -1,314.74 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -1,050.36 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -953.34 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -902.33 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -164.97 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -142.3 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -142.25 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -49.89 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -42.83 [/TD]
[TD="bgcolor: #99ccff, align: right"] 1 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff, align: right"] -508,934.56 [/TD]
[TD="bgcolor: #99ccff, align: right"] 35 [/TD]
[TD="bgcolor: #99ccff, align: right"] 3,475,396.57 [/TD]
[TD="bgcolor: #99ccff, align: right"] 25 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff, align: right"] -14,540.99 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff, align: right"] 139,015.86 [/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"] In Cash Terms: [/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"]
[/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"] WIN / LOSS [/TD]
[TD="bgcolor: #99ccff, align: right"] 0.71 [/TD]
[TD="bgcolor: #99ccff"] To 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 41.67% [/TD]

[TD="bgcolor: #99ccff"]
[/TD]
[TD="bgcolor: #99ccff"] PROFIT/LOSS [/TD]
[TD="bgcolor: #99ccff, align: right"] 9.56 [/TD]
[TD="bgcolor: #99ccff"] To 1 [/TD]
[TD="bgcolor: #99ccff, align: right"] 856.03% [/TD]



[TD="bgcolor: #00ff00"] In cash terms [/TD]

[TD="bgcolor: #00ff00"] 41.6% of trades are winning [/TD]

[TD="bgcolor: #00ff00"] Winning trades are 856% bigger than losing trades [/TD]


hedge... hedge... hedge... SPANK! hedge... hedge... hedge... SPANK!



[TD="bgcolor: #ffff99"] LTC loss [/TD]
[TD="bgcolor: #ffff99"] Losing Tally [/TD]
[TD="bgcolor: #ffff99"] LTC gain [/TD]
[TD="bgcolor: #ffff99"] Winning Tally [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -25,228.76 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 102,846.01 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -6,309.52 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 38,931.84 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -5,268.04 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 21,826.99 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -2,775.24 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 17,575.20 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -620.01 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 16,624.56 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -406.52 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 16,413.73 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -217.6 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 11,967.78 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 11,733.64 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 10,198.39 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 10,189.62 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 8,068.55 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 5,912.64 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 3,067.82 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 2,886.53 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 1,896.92 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 1,721.19 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 1,654.77 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 1,388.61 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 1,162.29 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 963.81 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 615.75 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 122.15 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 4.63 [/TD]
[TD="bgcolor: #ffff99, align: right"] 1 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99, align: right"] -40,825.69 [/TD]
[TD="bgcolor: #ffff99, align: right"] 7 [/TD]
[TD="bgcolor: #ffff99, align: right"] 287,773.42 [/TD]
[TD="bgcolor: #ffff99, align: right"] 23 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] -5,832.24 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99, align: right"] 12,511.89 [/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"] In LTC terms: [/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"]
[/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"] WIN / LOSS [/TD]
[TD="bgcolor: #ffff99, align: right"] 3.29 [/TD]
[TD="bgcolor: #ffff99"] To 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 76.67% [/TD]

[TD="bgcolor: #ffff99"]
[/TD]
[TD="bgcolor: #ffff99"] PROFIT/LOSS [/TD]
[TD="bgcolor: #ffff99, align: right"] 2.15 [/TD]
[TD="bgcolor: #ffff99"] To 1 [/TD]
[TD="bgcolor: #ffff99, align: right"] 114.53% [/TD]


[TD="bgcolor: #00ff00"] In LTC terms [/TD]

[TD="bgcolor: #00ff00"] 76.6% of trades are winning [/TD]

[TD="bgcolor: #00ff00"] Winning trades are 114% bigger than losing trades [/TD]


*LTC transactions are in buy/sell pairs(hence 30 instead of 60)... as every sell is 0 gain or loss.

view spreadsheet here:

https://docs.google.com/spreadsheets/d/1M5Edldjg1FzcCTnBr4LTnlqtob2YUz51sBOR8corxhY/edit#gid=0


2014-02-28 15:00 Trades: 8 Day: 27.50 Freq: 3.4 Price: 13.44
2014-02-28 15:00 1000 Currency: $927/927 -7% ROI :confused:
2014-02-28 15:00 47 Assets: 0/69 46% ROI 0% Held :cool:
Click to expand...



You'll note... that although the bot lost -7% "cash" value in the bear market in question... it gained 46% in LTC shares during the period.

J3nfAbS.png



http://en.wikipedia.org/wiki/Short_(finance)#Loss-making_trade
Currency[edit]

Selling short on the currency markets is different from selling short on the stock markets. Currencies are traded in pairs, each currency being priced in terms of another. In this way, selling short on the currency markets is identical to going long on stocks.
Novice traders or stock traders can be confused by the failure to recognize and understand this point:


a contract
is always long in terms of one medium
and short another.



When the exchange rate has changed, the trader buys the first currency again; this time he gets more of it, and pays back the loan. Since he got more money than he had borrowed initially, he makes money. Of course, the reverse can also occur.
Click to expand...

When you take a "short" position on LTC... you are the one making the "loans" of your LTC's to the market. The bot is your "trader".


"Buy Low, Sell High" is one of 3 profitable moves a trader can make. These are generally "winning trades" and this is commonly understood to be the only way to "make money" trading among novice traders.
Its also known as "range trading".

nrYID0h.png


However there are also profitable "losing trades" you can make while "trend trading":

"Sell Low, Buy Lower" and "Buy High, Sell Higher" are the other types.


"Sell Low, Buy Lower" is generally what we call "shorting".

W9kYgIQ.png





Wolong spoke about this in his doge coin book which you posted. He called it "position building" through "price suppression".


"Buy High, Sell Higher" is what we would generally refer to as "pumping". Here we see SPANK "buying high" on March 4th about 6 hours prior to "selling higher".

IkCLRqk.png



In ideal circumstances sometimes you are even able to manage a "winning short" or a "winning pump". Winning trades however are most often taken in a volatile range or on an overall long position on a bullish asset.


hope this helps...


"Crypto Long, More Coinz Short"

LP

;)


IMAGES MAY EXTEND OFF SCREEN... RIGHT CLICK TO VIEW
 
Last edited:
http://alunacrypto.blogspot.com/201...ding-market-structure-cycle-manipulation.html


Aluna Crypto Currency


Cryptocurrency Trading Tips, Tutorials & Strategy Insights by Alvin Lee (@onemanatatime) | Fundamental Analysis | Technical Analysis | Market Psychology | Bitcoin | Altcoins | Quantum Holdings



SATURDAY, MAY 3, 2014

Paradigm Shift: Technical Analysis in the Altcoins & Bitcoin Market, & Introduction to Market Cycle, Structure & Manipulation



Remember this? I bet the first time you saw it in December you laughed this picture off, but it's okay so did I. And if this is the first time you're seeing this, don't dismiss it just yet!

​


Because, well, the harsh truth is that its all real. And this market cycle, believe it or not, is present in every market out there, including these Bitcoin & Altcoin markets.

​

If you haven't already, check out my previous posts earlier this year about trading Bitcoins and Altcoins, which highlight technical analysis basics, fundamental analysis frameworks, margin trading, and tips on developing a cryptocurrency trading strategy and TA. Here, I just want to point out the importance of understanding market structure, introduce you to market manipulation, and show you how technical analysis can be applied to your cryptocurrency trading.

As you read on, keep these following points in mind as these rules apply even more closely:

  • What goes up must come down
  • Buy on rumors, sell on news
  • All markets are linked to everything else


To take this one step further and understand the markets from an even wider perspective, the next thing to do is to put on your market manipulator hat. Check out these 2 really good resources covering this topic for a deeper understanding of what I'm trying to get at:



The whole point of learning about how market manipulators operate is not to actually manipulate the markets yourself or conduct pump and dumps, but to actually spot when others are trying to do so. This can help your trading strategy in various ways such as to:

  • Have a better understanding of the ebbs and flows of the market
  • Avoid getting caught in their squeezes
  • Identify a suspicious (potentially profitable) market
  • Know what the "smartest man in the room" is doing, and follow the "smart money"

From Wolong's ebook, he broke down the market cycle into 7 stages, namely:

  1. Position Building
  2. Suppressing prices
  3. Test Pump
  4. Actual Pump
  5. Shakeouts
  6. Re-allocation and distribution
  7. Exiting - The Dump



If you compare the psychology chart above and the Pump & Dump cycle pointed out by Wolong, to the market structure chart below, you can see how they have very similar structures even though they use different terms to explain the phases.



And from this market structure chart, you can see that the stages can be further simplified to 4 phases:

  1. Accumulation
  2. Markup (Pump)
  3. Distribution
  4. Decline (Dump)

So why is this important, or how does it apply to the cryptocurrency markets? By understanding the market cycle chart, you will be able to better pick altcoins by spotting accumulation zones to join the breakout and profit, and to make your exit when you reach distribution zones. For example:


Although many people disregard the profitability (or possibility) of using technical analysis to trade the Bitcoin and especially Altcoins markets, it is most definitely possible. I think the problem lies predominantly in the limitation that some of you have put on the term 'technical analysis'.

Every piece of information on that chart you use is part of technical analysis; but the bigger question is how to make sense of it all. To better understand TA, we should think of the price charts as simply a graph of human behaviour.

Although the tools to do so efficiently are sorely lacking at this point in time, here's just a few examples of TA used on Altcoins and Bitcoin.

The first ever Technical Analysis chart applied to altcoins on Dogecoin, from way back in January 2014:

Spotting an accumulation zone in Myriadcoin MYR in March:

Example of a markup on Blackcoin BC last month:


How a Dump looks like and when you should exit:

Bitcoin on a Logarithmic scale:



Once you can wrap you head around the following facts, and combine them with what I have covered in the previous posts, you should be well on your way to developing a profitable cryptocurrency trading strategy. So here's a recap of the key takeaways:


1) Markets are fundamentally fractal in nature; for every one up or down trend, you can zoom in/out too see the same wave cycles. Read more about Elliott Wave Theory here.





​

2) Price charts are merely a graph of human behaviour. It doesn't matter if you're looking at a 3h chart or a 30m chart, they all tell the same story. Make sure to always compare two different time frames to better understand the macro and micro trend.


​


3) All markets are linked to each other, and affect each other in a dynamic fashion to create one over-arching ecosystem. Don't forget those crash cycle charts I showed you at the beginning; they're everywhere.

4) All markets are manipulated. Ride the waves and profit with the whales; don't fight the macro trend.





Also, I'd like to take this opportunity to give you a little heads about Quantum Holdings.@AltcoinAce, @kazonomics, @TheCryptoEdge, and myself have been working on this really cool project to not only provide you with financial gains, but to also educate you to become a better trader.

​


The IPO is now live until the 5th of May 2014. Check out the announcement documentfor more details and how to register here. About 80+ BTC has been registered, of which 33.5 BTC has been paid. All registrations will be on a strictly first come first served basis based on payment confirmation, and email registration does not constitute as a confirmation.

We'll also be holding weekly video sessions where we teach you more about about trading cryptocurrencies, technical analysis, live trading, how to operate in the marketplace, as well as technical & coin development classes. So if you're interested to learn even more than what I've been teaching on my blog, don't forget to also sign up for these Quantum Sessions!

Follow our Twitter account @QTMHoldings for the latest updates.



With that, I'll just end off with a few words of wisdom.

...
Click to expand...


You want to visit the link for more "words of wisdom"
 
updates:
added a smaller 1000 initial investment backtest to ICY SPANK which boosts earnings closer to the original SPANK bot's:

SPANK market orders = 297X cash
Icy Spank w/ $10k initial = 253X cash
Icy Spank w/ only $1k initial investment = 296X cash

The difference being with $10k initial investment the bot is left to sell over 230,000 LTC in its final move in 250 LTC chunks every 30 seconds... so the process takes several 2h candles...

mo money mo problems :)
 
Paladin69 said:
Also someone mentioned this...



no idea what he's talking about...
Click to expand...


On "initializing" SPANK...



In the first 24 hours spank will only exibit 1 sigma accuracy or about 68% chance of doing what it would have done if had started running last month.

By day 3-4 it it reaches 2 sigma; about 95% accuracy; if it misses its criteria... it will only be by a candle or two.

At day 6 its 99% trading in the same candle it would have otherwise chosen with more data; 3 sigma


By 10 days its moving towards 99.9% or 4 sigma

6 sigma accuracy would theoretically occur at 60 days as its longest indicator is EMA 720 on 2h candles. If the bot is initialized in a low volatility period like right now (relative to say December 2013) then 6 sigma accuracy would occur much sooner.

...this is all in the realm of theoretical; I've have done no hard analysis... just lots of hands on backtesting and a good eye for numbers and trends.
 
PaulConventionWV said:
What kind of market conditions does spank work in? Is it good no matter what the price of BTC is doing at the time?
Click to expand...


It should be "compatible" with all market conditions in any currency pair on any exchange. Its "finely" tuned to LTCUSD.

Tested and profitable:

LTCUSD Nov 1 2013 to current (BEST PERFORMANCE)
LTCBTC Nov 1 2013 to current
NMCUSD Jan 1 2013 to current
PPCUSD Jan 1 2013 to current
NMCBTC Jan 1 2013 to current
XPMBTC Jan 1 2013 to current
BTCUSD March 2013 to current + multiple instances from 2010 to current Gox data.

RECOMMENDED and best performing, as tuned, for LTCUSD.

Profitable in any 60 day block of time in any currency pair tested so far.


I do intend to "retune" a future release to be more market neutral; that is, performing equal in any currency pair; the bulk of my tuning has been on the Nov1 to Current LTCUSD data set.


The bot has built in bull and bear market indicators to switch computational method and logic when the market long changes.
 
Last edited:

2842 HOUBI 10000 BTC 1h volume
464 STAMP 4000 BTC 1h volume
450 BTCe 1500 BTC 1h volume





BULLS ON PARADE!!!!


(mod note- NSFW)
http://i.imgur.com/t4iVoSF.jpg







posted 5 days ago:



aWzZbRm.png



posted 2 days ago:

TXVJ1pG.png


^^^ thanks for reading the litepresence report on crypto currency :)

Illustration+of+a+purple+smiley+face.png
 
Last edited:
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