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Price Probability Predictor.
Capital investments assisted by a probability field.
Cristian Păuna
Economic Informatics Doctoral School
Academy of Economic Studies, Bucharest, Romania
The 14th International Conference on Business Excellence.
Business Revolution in the Digital Era.
11-12 June 2020, Bucharest, Romania.
This paper was financed by Al gorithm Invest (algoinvest.biz)
This paper presents:
Price Probability Predictor, a reliable probability field
based on time price series applicable to any capital market
Mathematical proof of an inverse but strong correlation
between the Price Probability Predictor and the price action
A method based on the Price Probability Predictor to build
automated signals to entry and exit on any financial market
A method based on the Price Probability Predictor to build
limit conditions in order to stay away from the market risk
Real investment results obtained with the presented
methods to prove the efficiency and simplicity involved
Price Probability Predictor
is a function that can be applied
On real-time
price series to
make a profit
By anyone using
a personal
computer
To build a stable
investment
method
In any financial
market using
any timeframe
Can improve any
other capital
investment
strategy
Can improve any
automated
investment
software
Can increase the
capital efficiency
of any
investment plan
A strong and inverse correlation is proved between PPP and the price action.
-0.999 ≤ Pearson CC ≤ -0.537
for all equities included in the next capital markets:
DAX – Frankfurt Stock Exchange Deutscher Aktienindex
DJIA –US Wall Street Dow Jones IndustrialIndex
S&P – US Standard & Poor's Market Index
NASDAQ –US Nasdaq Stock Market Index
FTSE – UK Financial Times Stock Exchange
SMI–Swiss Stock Exchange Market Index
ASX – Australian Stock Exchange Market Index
NIKKEI –Japanese Stock Exchange Nikkei Index
CAC– France Cotation Assistee en Continue Index
CURRENCIES –EURUSD, EURJPY, GBPUSD
GOLD – Spot price XAUUAD, XAUEUR, XAUAUD
OIL –BRENT CRUDE OIL
Price Probability Predictor
is defined as:
Probability through
Price Cyclicality Function
Price Cyclicality Function
The probability field is defined as:
Probability through
Smoothed Heikin-Ashi price transform
Smoothed Heikin-Ashi transform
The probability field is defined as:
Probability through
Price Prediction Line and Trigonometric Price Line
The probability field is defined as:
Price Prediction Line
Trigonometric Price Line
A strong and inverse correlation is proved between PPP and the price action.
-0.999 ≤ Pearson CC ≤ -0.537
for all equities included in the next capital markets:
DAX – Frankfurt Stock Exchange Deutscher Aktienindex
DJIA –US Wall Street Dow Jones IndustrialIndex
S&P – US Standard & Poor's Market Index
NASDAQ –US Nasdaq Stock Market Index
FTSE – UK Financial Times Stock Exchange
SMI–Swiss Stock Exchange Market Index
ASX – Australian Stock Exchange Market Index
NIKKEI –Japanese Stock Exchange Nikkei Index
CAC– France Cotation Assistee en Continue Index
CURRENCIES –EURUSD, EURJPY, GBPUSD
GOLD – Spot price XAUUAD, XAUEUR, XAUAUD
OIL –BRENT CRUDE OIL
Price Probability Predictor
is defined as:
Automated entry signals
Automated exit signals and limit conditions
A
B
Instead of conclusions
1:4.96 (4.96€ profit for each1€ risk)
This result means 10:49.6, or 20:99.2, or 25:124
Capital evolution due to the A type signals built with the Price Probability Prediction.
Capital evolution due to the B type signals built with the Price Probability Prediction.
RRR: 1:2.32
RRR: 1:4.96
Period: 01.01.2019 - 31.12.2019
Period: 01.01.2019 - 31.12.2019
Instead of conclusions
Important note: if the probability for a price increase is low, that
does not mean that the probability for a price decrease is higher !
DAX30 D1
31.01.2020
64%
Instead of conclusions