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Trade Against The 90% That Lose Money 22nd Dec
Retail traders are notoriously wrong at picking market direction/tops and bottoms. Most retail traders very naturally seem to adopt a counter-trend stance and this offers very accurate signals for individuals looking to trade against this group. This daily report is designed to help traders focus their efforts on higher probability pairs.
So what are the signals?
Strong Short 66% Retail Longs
Short 60% Retail Longs
Long 60% Retail Shorts
Strong Long 66% Retail Shorts
We are looking for 60%+ (Ideally for best opportunities 66%+) of retail traders to be trading either long or short a currency pair, we then look for opportunities to fade (trade against) this group. For example if 72.99% of traders are long the USD/CHF we look for opportunities to short that pair.
The pairs that we feel offer the highest opportunity for success are described in the Strong Short and Strong Long areas.
What’s New Today? No major shifts in retail trader positioning
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Today it seems to early.
The franc may continue to be strong due to some hidden reasons, maybe some banks hedging their potential losses in eastern Europe real estate markets.
However, when you think that for the price of one mansion in Swiss alps you can buy something like 400 apartments in Berlin, the Swiss Franc looks very dangerous place to hide indeed.
Perhaps even more than the indicator of the value of franc or euro or dollar it shows the difference in the relative buying power between the 2 different parts of population.
Anybody trading fx has to be careful not to put too much money into that or to use too much leverage.
Traders are looking for strength to come from somewhere else. If the upward revision in US GDP is enough, it may just smack the CHieF in its teeth, sending EURCHF on a rocket ride, CHFJPY back down to near-earth orbit and the EURJPY rising steadly higher.
The grind must end some time. Today may be the day. Keep your hats on and your knickers dry!
Why don't you list the probabilities for each trade in your table and how you compute them? That explanation would be quite a hoot-you could be Money McBags to vet it! Are these conditional probabilities? Do you assume a Gaussian price distribution? How to handle random fluctuations (thermal or otherwise) in your statistical model? What role does entropy and the ultimate heat death of the universe play your trading ideas?
(I'm just giving you the business, as the beaver might put it)
Shorting EURCHF has paid off.