Is The Tradeskill real money?

No. The Tradeskill is 100% paper trading. Your account is funded with virtual cash only. You can never lose or withdraw real money, and it is not a broker.

How much does The Tradeskill cost?

It is completely free. There is no subscription and no hidden fees. You sign up with an email and get $20,000 in virtual cash to start practising.

How realistic is the market data?

The Tradeskill uses real, live market prices for crypto and US stocks. Simulated orders fill against those prices with realistic spreads and slippage, so the experience closely mirrors live trading.

Which assets can I trade on The Tradeskill?

30 major cryptocurrencies, including Bitcoin, Ethereum, Solana, BNB, XRP and Dogecoin, with live 24/7 pricing; 25 top US stocks and ETFs, including Apple, NVIDIA, Microsoft, Tesla, SPY and QQQ, during US market hours; plus major forex pairs and gold.

Is The Tradeskill good for beginners?

Yes. It is built for learning to trade. Guided steps, an automatic trade journal and AI feedback help you understand orders, risk and strategy with no real money at stake.

Trading Expectancy: Formula, Example and Why It Matters

What it means

Expectancy is the average result per trade. In R (multiples of the amount risked): E = (win rate × average win) − (loss rate × average loss).

A positive expectancy means the method made money on average over the sample; it does not mean the next trade will.

Why traders use it

Win rate alone is misleading. A method that wins 37% of the time at +2R and loses 1R otherwise has a positive expectancy; a method that wins 80% at +0.2R and loses 1R otherwise does not.

Chart examples

Expectancy from 30 example trades

11 wins of +2R and 19 losses of −1R: net +3R, or +0.10R per trade. Note the long flat and losing stretches even with a positive expectancy.Schematic diagrams drawn to explain the idea; they are not market data.

How to identify it objectively

1Record every trade in R (profit ÷ initial risk).
2Win rate = wins ÷ trades.
3E = win rate × average win R − loss rate × average loss R.
4Report it with the sample size.

Bullish use

1Expectancy applies to longs and shorts alike.
2Calculate it separately for long and short trades to see if one side carries the method.

Bearish use

1A negative expectancy means the rule loses on average over the sample.
2More trades only grow the loss.

What confirms it

A large sample (100+ trades) with costs included.
Similar expectancy out of sample.

What invalidates it

Positive in-sample, negative out-of-sample.
Costs not included.

How a hypothetical setup is built

Entry

Not an entry rule: a measurement of one.

Stop

Always record the planned stop so R can be calculated.

Target

Compare expectancy across target choices (for example 1.5R vs 2R).

A hypothetical illustration of how the concept is turned into a plan, not a recommendation. Practise it on a paper account first.

Historical testing

The diagram uses a made-up sequence of 30 trades (11 wins of +2R, 19 losses of −1R) to show the arithmetic; it is not a backtest of any method.

Limitations: when it fails

30 trades is far too few to trust; the example only shows the formula.
Expectancy can change as markets change.
Ignoring costs overstates it.

Knowledge check

Pick an answer to see the explanation. Nothing is saved.

1. Win rate 40%, average win 2R, average loss 1R. Expectancy?

2. Can a 30% win rate be profitable?

3. Why measure in R?

Practise it risk-free

Open the free chart, use replay to go back in time and look for this concept candle by candle with $20,000 in virtual money.