Experiment FindingsPDF Available

WaitOnSignal Methodology. Experimental Findings.

Authors:
  • Algorithm Invest

Abstract

Being given a trading signal Ts based on the Price Prediction Line [1] (PPL) monotony, limited by the Price Cyclicality Function [2] (PCY) values, it was found that waiting on market (not to trade the current Ts trading signal) in some imposed price conditions, is significantly improving the profit and the trading efficiency. (DOI: 10.13140/RG.2.2.34582.45122)
WaitOnSignal Methodology.
Experimental Findings.



DOI: 10.13140/RG.2.2.34582.45122
Ts ! "#$"%  ! &%!
' #$(& ) ! %)%*
+) !+ %,  !Ts +!
+!ppli! "  ! %)%*&
+! pi!&)% ! )!))-!  
   % .& /& 01 ) %   %) ! %, 
%2%! ) !2 3!  !24
'3 )3!52 +! 678%!   
'3 )3!52 +!678%!   .9&/9:::&0919
;:<=%  )&;;=% +!!%+ +
3!,%%) !+%!> 8 " %!   #;$
3!+ 3!52 #$& %%) 5-?;#@$
3!+ +A;<+!!%) %
-% +)) %  )) %
References
#$  & A Price Prediction Model for Algorithmic Trading,  + B % C  ) D) % 
83!  !4EE %F D88G4@;H@
#$  & D "& Price Cyclicality Model for Financial Markets. Reliable Limit Conditions for Algorithmic
Trading&  +  C  ) 8  B! ) I  %    I  % 
!4EE D88G4@@H<@
#;$  & Capital and Risk Management for Automated Trading Systems&   ) ! <! D 
 )D) % I  %&J&DK&B %L-4!4EEE
#$   & TheDaxPredictor automated trading system online presentation& C  - 4
!4EEE!2 
#@$M& Frankfurt Stock Exchange Deutsche Aktienindex DAX30 Components&-4 !4EE+++ H
),)E2E2
Thesis
Full-text available
After several attempts to publish my Ph.D. thesis with different prestigious publishers, I have decided to make this work public and free of charge for anyone. Enjoy! Cristian Păuna
Article
Full-text available
Trading the financial markets is a common idea nowadays. Millions of market participants, individuals, companies or public funds are buying and selling different equities in order to obtain profit from the buy and sell price difference. Once the equity was established, the main question marks are when to buy, when to sell and how long to keep the opened positions. This paper will present a mathematical model for the cyclicality of the price evolution. The model can be applied for any equity in any financial market, using any timeframe. The method will gives us information about when is good to buy and when is better to sell. The price cyclicality model is also a method to establish when the price is approaching to change its behavior in order to build limit conditions to stay away the market and to minimize the risk. The fundamental news is already included in the price behavior. Being exclusively a mathematical model based on the price evolution, this method can be easily implemented in algorithmic trading. The paper will also reveal how the cyclicality model can be applied in automated trading systems and will present comparative results obtained in real-time trading environment.
Conference Paper
Full-text available
The most important part in the design and implementation process of automated trading systems in any financial investment company is the capital and risk management solution. Starting from the principle that the trading system must run fully automated, the design process gets several particular aspects. The global stop loss is a special approach for the risk management strategy that will ensures a positive expectancy in algorithmic trading. A case study based on an already optimized trading algorithm will be used to reveal how important the risk level optimization is, in order to improve the efficiency of the trading software. The main optimal criteria are as usual the profit maximization together with the minimization of the allocated risk, but these two requirements are not enough in this case. This paper will reveal an additional optimization criterion and the main directions to build a reliable solution for an automated capital and risk management procedure. Keywords: automated trading software (ATS), business intelligence systems (BIS), capital and risk management (CRM), algorithmic trading (AT), high frequency trading (HFT). (Available at: https://pauna.biz/Capital_and_Risk_Management)
A Price Prediction Model for Algorithmic Trading, under review at
  • C Păuna
C. Păuna, A Price Prediction Model for Algorithmic Trading, under review at Romanian Journal for Information Science and Technology (http://romjist.ro) ISSN: 1453-8245
TheDaxPredictor automated trading system online presentation
  • C Păuna
C. Păuna, TheDaxPredictor automated trading system online presentation, July 2018. Available at: https://pauna.biz/thedaxpredictor
Frankfurt Stock Exchange Deutsche Aktienindex DAX30 Components
  • Borse
Borse, Frankfurt Stock Exchange Deutsche Aktienindex DAX30 Components, 2018. Available: http://www. boersefrankfurt.de/index/dax