Forex Scalping Trading Strategy: How To Scalp Like A PRO ...

I am a professional Day Trader working for a Prop Fund, Hope I can help people out and answer some questions

Howdy all, I work professionally for a proprietary trading fund, and have worked for quite a few in my time, hope I can offer some insights on trading etc you guys might have.
Bonus for you guys
Here are the columns in my trading journal and various explanations where appropriate:
Trade Number – Simply is this the first trade of the year? The 10th?, The 50th? I count a trade
that you opened and closed just one trade number. For example if you buy EUUSD today and
sell it 50 pips later in the day and close out the trade, then that is just one trade for recording
purposes. I do not create a second trade number to describe the exit. Both the entry and exit are
under the same trade number.


Ticket Number – This is ticket number / order ID number that your broker gives you for the trade
on your platform.


Day of the Week – This would be simply the day of the week the trade was initiated


Financial Instrument / Currency Pair – Whatever Financial Instrument or currency pair you are
trading. If you are trading EUUSD, put EUUSD. If you are trading the EuroFX futures
contract, then put in Euro FX. If you are trading the emini S&P, then put in Emini S&P 500. If
you are trading a stock, put in the ticker symbol. Etc.


Buy/Sell or Long/Short – Did you buy or sell to open the new trade? If you bought something to
open the trade, then write in either BUY or LONG. If you sold(shorted) something to open a
trade, then write in SOLD, or SHORT. This is a personal preference. Some people like to put in
their journals as BUY/SELL. Other people like to write in Long/Short. My preference is for
writing in long/short, since that is the more professional way to say it. I like to use the lingo
where possible.


Order Type – Market or Limit – When you entered the trade was it a market order or limit order?
Some people can enter a trade using a combination of market and limit orders. If you enter a
trade for $1 million half of which was market order and the other half was limit order, then you
can write in $500,000 Market, $500,000 Limit as a bullet points.


Position Size / Units / Contracts / Shares – How big was the total trade you entered? If you
bought 1 standard lot of a currency pair, then write in $100,000 or 1 standard lot. If you bought 5
gold futures contracts, then write in 5 contracts. If you bought 1,000 shares of stock, then write
in 1,000 shares. Etc.


Entry Price – The entry price you received entering your opening position. If you entered at
multiple prices, then you can either write in all the different fills you got, or specify the average
price received.


Entry Date – Date that you entered the position. For example January 23, 2012. Or you can
write in 1/23/12

.
Entry Time – Time that you opened the position. If it is multiple positions, then you can specify
each time for each various fill, or you can specify the time range. For example if you got
$100,000 worth of EUUSD filled at 3:00 AM EST, and another $100,000 filled at 3:05 and
another $100,000 filled at 3:25, then you can write all those in, or you can specify a range of 3:00
– 3:30 AM EST.


Entry Spread Cost (in pips) – This is optional if you want to keep track of your spread cost in
pips. If you executed a market order, how many pips did you pay in spread.


Entry Spread Cost (in dollars) – This is optional if you want to keep track of your spread cost in
dollars. If you executed a market order, how many dollars did you pay in spread.


Stop Loss Size – How big is your stop loss size? If you are trading a currency pair, then you
write in the pips. If you are trading the S&P futures contract, then write in the number of points.
If you are trading a stock, then write in how many cents or dollars your stop is away from your
entry price.


% Risk – If you were to get stopped out of the trade, how much % loss of your equity is that?
This is where you input your risk per trade expressed in % terms if you use such a position sizing
method. If you risked 0.50% of your account on the trade, then put in 0.50%


Risk in dollars – If you were to get stopped out of the trade, how much loss in dollars is that. For
example if you have a $100,000 account and you risked 1% on a trade, then write in $1,000
dollars


Potential Reward: Risk Ratio – This is a column that I only sometimes fill in. You write in what
the potential reward risk ratio of the trade is. If you are trading using a 100 pip stop and you
expect that the market can reasonably move 300 pips, then you can write in 3:1. Of course this is
an interesting column because you can look at it after the trade is finished and see how close you
were or how far removed from reality your initial projections were.


Potential Win Rate – This is another column that I only sometimes fill in. You write in what you
believe the potential win rate of this trade is. If you were to place this trade 10 times in a row,
how many times do you think you would win? I write it in as percentage terms. If you believe
the trade has a 50% chance to win, then write in 50%.


Type of Inefficiency – This is where you write in what type of inefficiency you are looking to
capture. I use the word inefficiency here. I believe it is important to think of trading setups as
inefficiencies. If you think in terms of inefficiencies, then you will think in terms of the market
being mispriced, then you will think about the reasons why the market is mispriced and why such
market expectations for example are out of alignment with reality. In this category I could write
in different types of trades such as fading the stops, different types of news trades, expecting
stops to get tripped, betting on sentiment intensifying, betting on sentiment reversing, etc. I do
not write in all the reasons why I took the trade in this column. I do that in another column. This
column is just to broadly define what type of inefficiency you are looking to capture.


Chart Time Frame – I do not use this since all my order flow based trades have nothing to do
with what chart time frame I look at. However, if you are a chartist or price action trader, then
you may want to include what chart time frame you found whatever pattern you were looking at.


Exit Price – When you exit your trade, you enter the price you received here.


Exit Date – The date you exited your trade.


Exit Time – The time you exited your trade.


Trade Duration – In hours, minutes, days or weeks. If the trade lasts less than an hour, I will
usually write in the duration in minutes. Anything in between 1 and 48 hours, I write in the hours
amount. Anything past that and I write it as days or weeks as appropriate, etc.
Pips the trade went against you before turning into a winner – If you have a trade that suffered a
draw down, but did not stop you out and eventually was a winner, then you write it how many
pips the trade went against you before it turned into a profitable trade. The reason you have this
column is to compare it to your stop loss size and see any patterns that emerge. If you notice that
a lot of your winning trades suffer a big draw down and get near your stop loss points but turn out
to be a profitable trade, then you can further refine your entry strategy to get in a better price.


Slippage on the Exit – If you get stopped out for a loss, then you write in how many pips you
suffered as slippage, if any. For example if you are long EUUSD at 1.2500 and have your stop
loss at 1.2400 and the market drops and you get filled at 1.2398, then you would write in -2 pips
slippage. In other words you lost 2 pips as slippage. This is important for a few different
reasons. Firstly, you want to see if the places you put your stop at suffer from slippage. If they
do, perhaps you can get better stop loss placement, or use it as useful information to find new
inefficiencies. Secondly, you want to see how much slippage your broker is giving you. If you
are trading the same system with different brokers, then you can record the slippage from each
one and see which has the lowest slippage so you can choose them.


Profit/Loss -You write in the profit and/or loss in pips, cents, points, etc as appropriate. If you
bought EUUSD at 1.2500 and sell it at 1.2550, you made 50 pips, so write in +50 pips. If you
bought a stock at $50 and you sell it at $60, then write in +$10. If you buy the S&P futures at
1,250 and sell them at 1,275, then write in +25 points. If you buy the GBP/USD at 1.5000 and
you sell it at 1.4900, then write in -100 pips. Etc. I color code the box background to green for
profit and red for loss.


Profit/Loss In Dollars – You write the profit and/or loss in dollars (or euros, or jpy, etc whatever
currency your account is denominated in). If you are long $100,000 of EUUSD at 1.2500 and
sell it at 1.2600, then write in +$1,000. If you are short $100,000 GBP/USD at 1.5900 and it
rises to 1.6000 and you cover, then write in -$1,000. I color code the box background to green
for profit and red for loss.


Profit/Loss as % of your account – Write in the profit and/or loss as % of your account. If a trade
made you 2% of your account, then write in +2%. If a trade lost 0.50%, then write in -0.50%. I
color code the box background to green for profit and red for loss.


Reward:Risk Ratio or R multiple: If the trade is a profit, then write in how many times your risk
did it pay off. If you risked 0.50% and you made 1.00%, then write in +2R or 2:1 or 2.0. If you
risked 0.50% and a trade only makes 0.10%, then write in +0.20R or 0.2:1 or 0.2. If a trade went
for a loss that is equal to or less than what you risked, then I do not write in anything. If the loss
is greater than the amount you risked, then I do write it in this column. For example lets say you
risk 0.50% on a stock, but overnight the market gaps and you lose 1.50% on a trade, then I would
write it in as a -3R.


What Type of trading loss if the trade lost money? – This is where I describe in very general
terms a trade if it lost money. For example, if I lost money on a trade and the reason was because
I was buying in a market that was making fresh lows, but after I bought the market kept on going
lower, then I would write in: “trying to pick a bottom.” If I tried shorting into a rising uptrend
and I take a loss, then I describe it as “trying to pick a top.” If I am buying in an uptrend and buy
on a retracement, but the market makes a deeper retracement or trend change, then I write in
“tried to buy a ret.” And so on and so forth. In very general terms I describe it. The various
ways I use are:
• Trying to pick a bottom
• Trying to pick a top
• Shorting a bottom
• Buying a top
• Shorting a ret and failed
• Wrongly predicted news
• Bought a ret and failed
• Fade a resistance level
• Buy a support level
• Tried to buy a breakout higher
• Tried to short a breakout lower
I find this category very interesting and important because when performing trade journal
analysis, you can notice trends when you have winners or losing trades. For example if I notice a
string of losing trades and I notice that all of them occur in the same market, and all of them have
as a reason: “tried to pick a bottom”, then I know I was dumb for trying to pick a bottom five
times in a row. I was fighting the macro order flow and it was dumb. Or if I notice a string of
losers and see that I tried to buy a breakout and it failed five times in a row, but notice that the
market continued to go higher after I was stopped out, then I realize that I was correct in the
move, but I just applied the wrong entry strategy. I should have bought a retracement, instead of
trying to buy a fresh breakout.


That Day’s Weaknesses (If any) – This is where I write in if there were any weaknesses or
distractions on the day I placed the trade. For example if you are dead tired and place a trade,
then write in that you were very tired. Or if you place a trade when there were five people
coming and out of your trading office or room in your house, then write that in. If you placed the
trade when the fire alarm was going off then write that in. Or if you place a trade without having
done your daily habits, then write that in. Etc. Whatever you believe was a possible weakness
that threw you off your game.


That Day’s Strengths (If any) – Here you can write in what strengths you had during the day you
placed your trade. If you had complete peace and quiet, write that in. If you completed all your
daily habits, then write that in. Etc. Whatever you believe was a possible strength during the
day.


How many Open Positions Total (including the one you just placed) – How many open trades do
you have after placing this one? If you have zero open trades and you just placed one, then the
total number of open positions would be one, so write in “1.” If you have on three open trades,
and you are placing a new current one, then the total number of open positions would be four, so
write in “4.” The reason you have this column in your trading journal is so that you can notice
trends in winning and losing streaks. Do a lot of your losing streaks happen when you have on a
lot of open positions at the same time? Do you have a winning streak when the number of open
positions is kept low? Or can you handle a lot of open positions at the same time?


Exit Spread Cost (in pips) – This is optional if you want to keep track of your spread cost in pips.
If you executed a market order, how many pips did you pay in spread.


Exit Spread Cost (in dollars) – This is optional if you want to keep track of your spread cost in
dollars. If you executed a market order, how many dollars did you pay in spread.


Total Spread Cost (in pips) – You write in the total spread cost of the entry and exit in pips.


Total Spread Cost (in dollars) – You write in the total spread cost of the entry and exit in dollars.


Commission Cost – Here you write in the total commission cost that you incurred for getting in
and out of the trade. If you have a forex broker that is commission free and only gets
compensated through the spread, then you do not need this column.


Starting Balance – The starting account balance that you had prior to the placing of the trade


Interest/swap – If you hold forex currency pairs past the rollover, then you either get interest or
need to pay out interest depending on the rollover rates. Or if you bought a stock and got a
dividend then write that in. Or if you shorted a stock and you had to pay a dividend, then write
that in.


Ending Balance – The ending balance of your account after the trade is closed after taking into
account trade P&L, commission cost, and interest/swap.


Reasons for taking the trade – Here is where you go into much more detail about why you placed
the trade. Write out your thinking. Instead of writing a paragraph or two describing my thinking
behind the trade, I condense the reasons down into bullet points. It can be anywhere from 1-10
bullet points.


What I Learned – No matter if the trade is a win or loss, write down what you believed you
learned. Again, instead of writing out a paragraph or two, I condense it down into bullet points. it
can be anywhere from 1-10 bullet points. I do this during the day the trade closed as a profit or
loss.


What I learned after Long Term reflection, several days, weeks, or months – This is the very
interesting column. This is important because after you have a winning or losing trade, you will
not always know the true reasons why it happened. You have your immediate theories and
reasons which you include in the previous column. However, there are times when after several
days, weeks, or months, you find the true reason and proper market belief about why your trade
succeeded or failed. It can take a few days or weeks or months to reach that “aha” moment. I am
not saying that I am thinking about trades I placed ten months ago. I try to forget about them and
focus on the present moment. However, there will be trades where you have these nagging
questions about they failed or succeeded and you will only discover those reasons several days,
weeks, or months later. When you discover the reasons, you write them in this column.
submitted by Fox-The-Wise to Forex [link] [comments]

What factors predict the success of a Steam game? (An analysis)

What factors predict the success of a Steam game?

I've seen quite a few discussions, comments and questions on /gamedev about what determines a game's success. How much does quality matter? Is establishing market awareness before launch the only thing that matters? Does a demo help or hurt? If your game has a poor launch, how likely is it to recover? Is it possible to roughly predict the sales of a game before launch?
In preparation for my game's launch, I spent a lot of time monitoring upcoming releases trying to find the answer to these questions. I compiled a spreadsheet, noted followers, whether it was Early Access or not, and saw how many reviews it received in the first week, month and quarter.
I'm sharing this data now in the hopes that it helps other developers understand and predict their games' sales.
First some notes on the data:
Game Price Launch Discount Week Guess Week actual 3 Month 3 Month/week Followers Early Access Demo Review Score
Pit of Doom 9.99 0 7 27 43 1.592592593 295 Y N 0.8
Citrouille 9.99 0.2 16 8 12 1.5 226 N N
Corspe Party: Book 14.99 0.1 32 40 79 1.975 1015 N N 0.95
Call of Cthulhu 44.99 0 800 875 1595 1.822857143 26600 N N 0.74
On Space 0.99 0.4 0 0 0 4 N N
Orphan 14.99 0 50 0 8 732 N N
Black Bird 19.99 0 20 13 34 2.615384615 227 N N
Gloom 6.99 0 20 8 17 2.125 159 N N
Gilded Rails 5.99 0.35 2 3 7 2.333333333 11 N Y
The Quiet Man 14.99 0.1 120 207 296 1.429951691 5596 N N 0.31
KartKraft 19.99 0.1 150 90 223 2.477777778 7691 Y N 0.84
The Other Half 7.99 0 2 3 27 9 91 N Y 0.86
Parabolus 14.99 0.15 0 0 0 16 N Y
Yet Another Tower Defense 1.99 0.4 20 22 38 1.727272727 396 N N 0.65
Galaxy Squad 9.99 0.25 8 42 5.25 3741 Y N 0.87
Swords and Soldiers 2 14.99 0.1 65 36 63 1.75 1742 N N 0.84
SpitKiss 2.99 0 3 1 2 2 63 N N
Holy Potatoes 14.99 0 24 11 22 2 617 N N 0.7
Kursk 29.99 0.15 90 62 98 1.580645161 2394 N N 0.57
SimpleRockets 2 14.99 0.15 90 142 272 1.915492958 3441 Y N 0.85
Egress 14.99 0.15 160 44 75 1.704545455 7304 Y N 0.67
Kynseed 9.99 0 600 128 237 1.8515625 12984 Y N 0.86
11-11 Memories 29.99 0 30 10 69 6.9 767 N N 0.96
Rage in Peace 12.99 0.1 15 10 42 4.2 377 N N 0.85
One Hour One Life 19.99 0 12 153 708 4.62745098 573 N N 0.81
Optica 9.99 0 0 2 3 1.5 18 N N
Cybarian 5.99 0.15 8 4 18 4.5 225 N N
Zeon 25 3.99 0.3 3 11 12 1.090909091 82 Y N
Of Gods and Men 7.99 0.4 3 10 18 1.8 111 N Y
Welcome to Princeland 4.99 0.1 1 15 55 3.666666667 30 N N 0.85
Zero Caliber VR 24.99 0.1 100 169 420 2.485207101 5569 Y N 0.73
HellSign 14.99 0 100 131 334 2.549618321 3360 Y N 0.85
Thief Simulator 19.99 0.15 400 622 1867 3.001607717 10670 N N 0.81
Last Stanza 7.99 0.1 8 2 4 2 228 N Y
Evil Bank Manager 11.99 0.1 106 460 4.339622642 8147 Y N 0.78
Oppai Puzzle 0.99 0.3 36 93 2.583333333 54 N N 0.92
Hexen Hegemony 9.99 0.15 3 1 5 5 55 Y N
Blokin 2.99 0 0 0 0 0 10 N N
Light Fairytale Ep 1 9.99 0.1 80 23 54 2.347826087 4694 Y N 0.89
The Last Sphinx 2.99 0.1 0 0 1 0 17 N N
Glassteroids 9.99 0.2 0 0 0 0 5 Y N
Hitman 2 59.99 0 2000 2653 3677 1.385978138 52226 N N 0.88
Golf Peaks 4.99 0.1 1 8 25 3.125 46 N N 1
Sipho 13.99 0 24 5 14 2.8 665 Y N
Distraint 2 8.99 0.1 40 104 321 3.086538462 1799 N N 0.97
Healing Harem 12.99 0.1 24 10 15 1.5 605 N N
Spark Five 2.99 0.3 0 0 0 0 7 N N
Bad Dream: Fever 9.99 0.2 30 78 134 1.717948718 907 N N 0.72
Underworld Ascendant 29.99 0.15 200 216 288 1.333333333 8870 N N 0.34
Reentry 19.99 0.15 8 24 78 3.25 202 Y N 0.95
Zvezda 5.99 0 2 0 0 0 25 Y Y
Space Gladiator 2.99 0 0 1 2 2 5 N N
Bad North 14.99 0.1 500 360 739 2.052777778 15908 N N 0.8
Sanctus Mortem 9.99 0.15 3 3 3 1 84 N Y
The Occluder 1.99 0.2 1 1 1 1 13 N N
Dark Fantasy: Jigsaw 2.99 0.2 1 9 36 4 32 N N 0.91
Farming Simulator 19 34.99 0 1500 3895 5759 1.478562259 37478 N N 0.76
Don't Forget Our Esports Dream 14.99 0.13 3 16 22 1.375 150 N N 1
Space Toads Mayhem 3.99 0.15 1 2 3 1.5 18 N N
Cattle Call 11.99 0.1 10 19 53 2.789473684 250 Y N 0.71
Ralf 9.99 0.2 0 0 2 0 6 N N
Elite Archery 0.99 0.4 0 2 3 1.5 5 Y N
Evidence of Life 4.99 0 0 2 4 2 10 N N
Trinity VR 4.99 0 2 8 15 1.875 61 N N
Quiet as a Stone 9.99 0.1 1 1 4 4 42 N N
Overdungeon 14.99 0 3 86 572 6.651162791 77 Y N 0.91
Protocol 24.99 0.15 60 41 117 2.853658537 1764 N N 0.68
Scraper: First Strike 29.99 0 3 3 15 5 69 N N
Experiment Gone Rogue 16.99 0 1 1 5 5 27 Y N
Emerald Shores 9.99 0.2 0 1 2 2 12 N N
Age of Civilizations II 4.99 0 600 1109 2733 2.464382326 18568 N N 0.82
Dereliction 4.99 0 0 0 0 #DIV/0! 18 N N
Poopy Philosophy 0.99 0 0 6 10 1.666666667 6 N N
NOCE 17.99 0.1 1 3 4 1.333333333 35 N N
Qu-tros 2.99 0.4 0 3 7 2.333333333 4 N N
Mosaics Galore. Challenging Journey 4.99 0.2 1 1 8 8 14 N N
Zquirrels Jump 2.99 0.4 0 1 4 4 9 N N
Dark Siders III 59.99 0 2400 1721 2708 1.573503777 85498 N N 0.67
R-Type Dimensions Ex 14.99 0.2 10 48 64 1.333333333 278 N N 0.92
Artifact 19.99 0 7000 9700 16584 1.709690722 140000 N N 0.53
Crimson Keep 14.99 0.15 20 5 6 1.2 367 N N
Rival Megagun 14.99 0 35 26 31 1.192307692 818 N N
Santa's Workshop 1.99 0.1 3 1 1 1 8 N N
Hentai Shadow 1.99 0.3 2 12 6 14 N N
Ricky Runner 12.99 0.3 3 6 13 2.166666667 66 Y N 0.87
Pro Fishing Simulator 39.99 0.15 24 20 19 0.95 609 N N 0.22
Broken Reality 14.99 0.1 60 58 138 2.379310345 1313 N Y 0.98
Rapture Rejects 19.99 0 200 82 151 1.841463415 9250 Y N 0.64
Lost Cave 19.99 0 3 8 11 1.375 43 Y N
Epic Battle Fantasy 5 14.99 0 300 395 896 2.26835443 4236 N N 0.97
Ride 3 49.99 0 75 161 371 2.304347826 1951 N N 0.74
Escape Doodland 9.99 0.2 25 16 19 1.1875 1542 N N
Hillbilly Apocalypse 5.99 0.1 0 1 2 2 8 N N
X4 49.99 0 1500 2638 4303 1.63115997 38152 N N 0.7
Splotches 9.99 0.15 0 2 1 0.5 10 N N
Above the Fold 13.99 0.15 5 2 6 3 65 Y N
The Seven Chambers 12.99 0.3 3 0 0 #DIV/0! 55 N N
Terminal Conflict 29.99 0 5 4 11 2.75 125 Y N
Just Cause 4 59.99 0 2400 2083 3500 1.680268843 50000 N N 0.34
Grapple Force Rena 14.99 0 11 12 29 2.416666667 321 N Y
Beholder 2 14.99 0.1 479 950 1.983298539 16000 N N 0.84
Blueprint Word 1.99 0 12 15 1.25 244 N Y
Aeon of Sands 19.99 0.1 20 12 25 2.083333333 320 N N
Oakwood 4.99 0.1 32 68 2.125 70 N N 0.82
Endhall 4.99 0 4 22 42 1.909090909 79 N N 0.84
Dr. Cares - Family Practice 12.99 0.25 6 3 8 2.666666667 39 N N
Treasure Hunter 16.99 0.15 200 196 252 1.285714286 4835 N N 0.6
Forex Trading 1.99 0.4 7 10 14 1.4 209 N N
Ancient Frontier 14.99 0 24 5 16 3.2 389 N N
Fear the Night 14.99 0.25 25 201 440 2.189054726 835 Y N 0.65
Subterraneus 12.99 0.1 4 0 3 #DIV/0! 82 N N
Starcom: Nexus 14.99 0.15 53 119 2.245283019 1140 Y N 0.93
Subject 264 14.99 0.2 25 2 3 1.5 800 N N
Gris 16.9 0 100 1484 4650 3.133423181 5779 N N 0.96
Exiled to the Void 7.99 0.3 9 4 11 2.75 84 Y N
Column Explanations
For the columns that are not self-explanatory:

Question 1: Does Quality Predict Success?

There was a recent blog post stating that the #1 metric for indie games' success is how good it is.
Quality is obviously a subjective metric. The most obvious objective measure of quality for Steam games is their % Favorable Review score. This is the percentage of reviews by purchasers of the game that gave the game a positive rating. I excluded any game that did not have at least 20 user reviews in the first month, which limited the sample size to 56.
The (Pearson) correlation of a game's review score to its number of reviews three months after its release was -0.2. But 0.2 (plus or minus) isn't a very strong correlation at all. More importantly, Pearson correlation can be swayed if the data contains some big outliers. Looking at the actual games, we can see that the difference is an artifact of an outlier. Literally. Valve's Artifact by far had the most reviews after three months and had one of the lowest review scores (53% at the time). Removing this game from the data changed the correlation to essentially zero.
Spearman's Rho, an alternative correlation model that correlates rank position and minimizes the effect of huge outliers produced a similar result.
Conclusion: If there is correlation between a game's quality (as measured by Steam review score) and first quarter sales (as measured by total review count), it is too subtle to be detected in this data.

Question 2: Do Demos, Early Access or Launch Discounts Affect Success/Failure?

Unfortunately, there were so few games that had demos prior to release (10) that only a very strong correlation would really tell us anything. As it happens, there was no meaningful correlation one way or another.
There were more Early Access titles (28), but again the correlation was too small to be meaningful.
More than half the titles had a launch week discount and there was actually a moderate negative correlation of -0.3 between having a launch discount and first week review count. However it appears that this is primarily the result of the tendency of AAA titles (which sell the most copies) to not do launch discounts. Removing the titles that likely grossed over a $1 million in the first week reduced the correlation to basically zero.
Conclusion: Insufficient data. No clear correlation between demos, Early Access or launch discount and review counts: if they help or hurt the effect is not consistent enough to be seen here.

Question 3: Does pre-launch awareness (i.e., Steam followers) predict success?

You can see the number of "followers" for any game on Steam by searching for its automatically-created Community Group. Prior to launch, this is a good rough indicator of market awareness.
The correlation between group followers shortly before launch and review count at 3 months was 0.89. That's a very strong positive correlation. The rank correlation was also high (0.85) suggesting that this wasn't the result of a few highly anticipated games.
Save for a single outlier (discussed later), the ratio of 3 month review counts to pre-launch followers ranged from 0 (for the handful of games that never received any reviews) to 1.8, with a median value of 0.1. If you have 1000 followers just prior to launch, then at the end of the first quarter you should expect "about" 100 reviews.
One thing I noticed was that there were a few games that had follower counts that seemed too high compared to secondary indicators of market awareness, such as discussion forum threads and Twitter engagement. After some investigation I came to the conclusion that pre-launch key activations are treated as followers by Steam. If a game gave away a lot of Steam keys before launch (say as Kickstarter rewards or part of beta testing) this would cause the game to appear to have more followers than it had gained "organically."
Conclusion: Organic followers prior to launch are a strong predictor of a game's eventual success.

Question 4: What about price?

The correlation between price and review count at 3 month is 0.36, which is moderate correlation. I'm not sure how useful that data point is: it is somewhat obvious that higher budget games have larger marketing budgets.
There is a correlation between price and review score of -0.41. It seems likely that players do factor price into their reviews and a game priced at $60 has a higher bar to clear to earn a thumbs up review than a game priced at $10.

Question 5: Do first week sales predict first quarter results?

The correlation between number of reviews after 1 week and number of reviews after 3 months was 0.99. The Spearman correlation was 0.97. This is the highest correlation I found in the data.
Excluding games that sold very few copies (fewer than 5 reviews after the first week), most games had around twice as many reviews after 3 months as they did after 1 week. This suggests that games sell about as many copies in their first week as they do in the next 12 weeks combined. The vast majority of games had a tail ratio (ratio of reviews at 3 months to 1 week) of between 1.3 to 3.2.
I have seen a number of questions from developers whose game had a poor launch on Steam and wanted to know what they can do to improve sales. While I'm certain post-launch marketing can have an effect on continuing sales, your first week does seem to set hard bounds on your results.
Conclusion: ALL SIGNS POINT TO YES

Question 6: Does Quality Help with a Game's "Tail"?

As discussed in the last question while first week sales are very strongly correlated with first quarter, there's still quite a wide range of ratios. Defining a game's Tail Ratio as the ratio of reviews after 3 months to after 1 week, the lowest value was 0.95 for "Pro Fishing Simulator" which actually managed to lose 1 review. The highest ratio was 6.9, an extreme outlier that I'll talk about later. It is perhaps not a coincidence that the worst tail had a Steam score of 22% and the best tail had a Steam score of 96%.
The overall correlation between the Tail Ratio and Steam score was 0.42.
Conclusion: Even though there is no clear correlation between quality and overall review count/sales, there is a moderate correlation between a game's review score and its tail. This suggests that "good games" do better in the long run than "bad games," but the effect is small compared to the more important factor of pre-launch awareness.

Question 7: Is it possible to predict a game's success before launch without knowing its wishlists?

While I was compiling the data for each game, sometime prior to its scheduled launch date, I would make a prediction of how many reviews I thought it would receive in its first week and add that prediction to the spreadsheet.
The #1 factor I used in making my prediction was group follower count. In some cases I would adjust my prediction if I thought that value was off, using secondary sources such as Steam forum activity and Twitter engagement.
The correlation between my guess and the actual value was 0.96, which is a very strong correlation. As you can see in the data, the predictions are, for the most part, in the right ballpack with a few cases where I was way off.
Based on my experience, multiplying the group follower count by 0.1 will, in most cases, give you a ballpark sense of the first week quarter review count. If a game doesn't have at least one question in the discussion forum for every 100 followers, that may indicate that there are large number of "inorganic" followers and you may need to adjust your estimate.
Conclusion: Yes, with a few exceptions, using follower data and other indicators you can predict first week results approximately. Given the strong correlation between first week and quarter sales, it should also be possible to have a ballpark idea of first quarter results before launch.

Final Question: What about the outliers you mentioned?

There were a few games in the data that stood out significantly in one way or another.
Outlier #1: Overdungeon. This game had 77 group followers shortly before launch, a fairly small number and based solely on that number I would have expected fewer than a dozen reviews in the first week. It ended up with 86. Not only that, it had a strong tail and finished its first quarter with 572 reviews. This was by a wide margin the highest review count to follower ratio in the sample.
Based on the reviews, it appears to basically be Slay the Spire, but huge in Asia. 90% of the reviews seem to be in Japanese or Chinese. If anyone has some insight to this game's unusual apparent success, I'm very curious.
This seems to be the only clear example in the data of a game with minimal following prior to launch going on to having a solid first quarter.
Outlier #2: 11-11 Memories Retold. This game had 767 group followers shortly before launch, ten times as many as Overdungeon. That's still not a large number for even a small indie title. It had a fair amount going for it, though: it was directed by Yoan Fanise, who co-directed the critally acclaimed Valiant Hearts, a game with a similar theme. It was animated by Aardman Studios of "Wallace and Gromit" fame. Its publisher was Bandai Namco Europe, a not inexperienced publisher. The voice acting was by Sebastian Koch and Elijah Wood. It has dozens of good reviews in both gaming and traditional press. It currently has a 95% positive review rating on Steam.
Despite all that, nobody bought it. 24 hours after it came out it had literally zero reviews on Steam. One week after it came out it had just 10. Three months later it had demonstrated the largest tail in the data, but even then it had only climbed to 69 reviews. Now it's at about 100, an incredible tail ratio, but almost certainly a commercial failure.
This is a solid example that good game + good production values does necessarily equal good sales.

Final notes:
The big take-aways from this analysis are:
Thanks for reading!
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