<story><title>Time Series Prediction Using LSTM Deep Neural Networks</title><url>https://www.altumintelligence.com/articles/a/Time-Series-Prediction-Using-LSTM-Deep-Neural-Networks</url></story><parent_chain><item><author>jarym</author><text>Why does everyone naively try to predict price? No ‘traders’ are interested in predicting it - what traders do is identify good locations to enter or exit the market.&lt;p&gt;I.e. places with defined risk where you will know if you’re wrong if it goes against you by x% while you expect a y% gain if you’re right AND y&amp;gt;x is worth more than the number of times you’re wrong.&lt;p&gt;The types of Algos that work well for this are edge identification ones - I know this because I am (not as well as I’d like) successfully doing it.&lt;p&gt;LSTMs haven’t performed so well for me in this task but non-NN algos have. CNNs however were promising but didn’t match what I’d come up with - still searching for the holy grail that’ll make me rich!</text></item></parent_chain><comment><author>beagle3</author><text>.. because you buy at the price, and sell at the price (spread and fees ignored for now).&lt;p&gt;Which means, regardless of your philosophy, you are predicting a price change - a long signal is a prediction for positive price change; a short signal is a prediction for a negative price change. If that wasn’t true, your system would not be able to profit.&lt;p&gt;Predicting price change and predicting price are semantically equivalent, although a specific algorithm might be better at one than the other.</text></comment>
<story><title>Time Series Prediction Using LSTM Deep Neural Networks</title><url>https://www.altumintelligence.com/articles/a/Time-Series-Prediction-Using-LSTM-Deep-Neural-Networks</url></story><parent_chain><item><author>jarym</author><text>Why does everyone naively try to predict price? No ‘traders’ are interested in predicting it - what traders do is identify good locations to enter or exit the market.&lt;p&gt;I.e. places with defined risk where you will know if you’re wrong if it goes against you by x% while you expect a y% gain if you’re right AND y&amp;gt;x is worth more than the number of times you’re wrong.&lt;p&gt;The types of Algos that work well for this are edge identification ones - I know this because I am (not as well as I’d like) successfully doing it.&lt;p&gt;LSTMs haven’t performed so well for me in this task but non-NN algos have. CNNs however were promising but didn’t match what I’d come up with - still searching for the holy grail that’ll make me rich!</text></item></parent_chain><comment><author>cmroanirgo</author><text>&amp;gt; Why does everyone naively try to predict price? No ‘traders’ are interested in predicting it - what traders do is identify good locations to enter or exit the market.&lt;p&gt;I agree.&lt;p&gt;I&amp;#x27;ve built many systems in this area, but it wasn&amp;#x27;t until I started working in the Indian market (&amp;gt;10 yrs ago) that it became abundantly clear that trying to calculate the long&amp;#x2F;shorts signals using historical (&amp;#x2F;time series) data was a waste of time. (And yet my primary role was to provide tools that did exactly that).&lt;p&gt;Back then, in the indian market, you could see that most of the stocks, although skyrocketing upwards, all followed the slow vs fast moving averages to buy and sell! Back then, they weren&amp;#x27;t looking at RSI, stochastics, support lines, etc, etc. It was crazily predictable...but over time it was really interesting to see it become more haphazard and like western stocks. That is, the fundamentals came into play and  as you say, the traders began to use other metrics to buy and sell.</text></comment>