Hello, I have 10+ years of experience in financial markets, especially
statistical analysis of markets, so I can offer my forecasting skills as a service to people who want to approximate the price of any market into the future.
I have also developed some free demo tools, written mostly in
Python 3.5+, which is
FREE that I give out for free so that you can check my claims by yourself. Whatever I will sell to you will be much better that that!
Free Tools:What you Need To Know:First you need to know some things about my methods, I use LOG based absolute error measurements, not
RMS and bullshit like that, since that is heavily biased and I don't know why any statistician would use such things,
as explained here.
So when you see things like 0.1 LN, that means an error rate of that relative to the
natural logarithm. Since logs are additive, we can also calculate an average for them. So it's much better to work with that. I call this
LN Error.
I also have another benchmark which I call
Predictive Edge, which is based on
Theil’s U value. Basically it counts how much better our model is compared to random guessing. Anything over 0 is a theoretical edge over the market, so it should theoretically be profitable, giving a positive expectancy for a trader, and if it's below 0, then that model is not profitable.
Public Model:- Explanation: https://steemit.com/bitcoin/@profitgenerator/forecasting-adventures-9-final-research
- Data: Daily BTC/USD Data + Daily Transaction Fees USD
- Method: Transform the Price with the LN function, make the Regressor cumulative and then transform it by the LN function. Run the Model on the transformed data either backtest or forecast, and then transform back the fitted/forecasted values with the EXP() function.
- Model: ARIMAX(0,1,1){ LN(cumulative_transaction-fees-usd.csv)_1 } with constant
- Coefficients: You have to calculate them yourself from the historical data, since it varies by the data
- Estimated LN Error: 0.031060897872341 LN
- Estimated Predictive Edge: 0.012481538
Private Model:Coming Soon, Stay tuned!
I am doing research now, later I will provide my forecasting values for sale.
