“Artificial Intelligence to Protect Investments”

“Artificial Intelligence to Protect Investments”

Today Paolo Savona, CONSOB (Italian Companies and Exchange Commission) Chairman, stated in an interview that they are going to use artificial intelligence to protect financial investments.

https://mobile.ilsole24ore.com/art/finanza-e-mercati/2019-06-19/savona-useremo-l8217-intelligenza-artificiale-a-tutela-del-risparmio/AC2MIaS#Echobox=1560930782

It is also the goal that MITIVEST start-uppers has been pursuing for years, willing to provide its Artificial Intelligence strategies to individual traders and future clients in general soon, having primary objective investment protection as well as profit achievement in a market neutral condition environment.

Multiple Spread Trading - an investment methodology neutral to financial market trends - is the MITIVEST safeguard against risk investment.

A real example of how Multiple Spread Trading (MST) algorithm has performed neutrally on the market is the recent news regarding the European Central Bank (ECB) on Quantitative Easing.

Yesterday, ECB’s monetary policy declaration increased sharply EUR volatility, potentially growing risk of substantial losses in a short time.

MST algorithm had forecast this week to use as EUR neutral currency basket the following structure:

Sell        0.96      EURUSD

Sell        0.29      EURGBP

Buy       0.46      EURAUD

Buy       0.96      EURJPY

Sell        0.33      EURCAD

The algorithm expects to carry out orders using this basket every time there is an excessive discrepancy from the overall balance point of these currencies, strictly maintaining money protection concerning disruptive events that could happen on EUR price.

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As we can see when ECB’s market mover was announced, our currency basket showed almost no impact on its overall value, protecting the investment from any loss regardless of the EUR movement direction. In such a market neutral environment, the algorithm allowed two profits, using simple momentary statistical excess recognition.


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