# Importance of Event Binary Features in Stock Price Prediction
## 3 Design and Development of the Stock Price Prediction Model
### Model 2: Event Binary Features Model
\begin{tabular}{l l c} \hline \hline
**Binary Features Description** & **Formula** & **Number of Features** \\ \hline Turn up/down point between & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathit{Grad}_{1}^{\mathrm{g}}<0 \mathit{and}\quad\mathit{Crad}6_{t}^{\mathrm{g}}\geq 0\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=5,10,20)\) & 30 \\ \hline Golden cross point between & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{MAK}_{1}^{\mathrm{g}}< \mathit{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}\geq\;\mathrm{MAK}_ {1}^{\mathrm{g}}\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=10,20,60,120)\) & 45 \\ moving average lines & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{MAK}_{1}^{\mathrm{g}}< \mathit{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}\geq\;\mathrm{MAK}_ {1}^{\mathrm{g}}\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=20,60,120)\) & 45 \\ moving average lines & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{MAK}_{1}^{\mathrm{g}}> \mathrm{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}\geq\;\mathrm{MAK}_ {1}^{\mathrm{g}}\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=60,120)\) & \\ \hline Dead cross point between moving average lines & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{MAK}_{1}^{\mathrm{g}}> \mathrm{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}\leq\;\mathrm{MAK}_ {1}^{\mathrm{g}}\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=10,20,60,120)\) & 45 \\ moving average lines & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{MAK}_{1}^{\mathrm{g}}> \mathrm{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}\leq\;\mathrm{MAK}_ {1}^{\mathrm{g}}\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=20,60,120)\) & 45 \\ moving average lines & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{MAK}_{1}^{\mathrm{g}}> \mathrm{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}\leq\;\mathrm{MAK}_ {1}^{\mathrm{g}}\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\right.\) & \((k=20,60,120)\) & \\ \hline \hline \end{tabular}  \ \begin{tabular}{l l} \hline \hline \end{tabular} 
\begin{tabular}{l l} \hline \(\mathit{If}\;\mathit{Open}_{t}^{\mathrm{g}}>\mathrm{Close}_{t}^{\mathrm{g}}\) & \(\mathit{True}\;if(\mathrm{MAK}_{1}^{\mathrm{g}}>\mathrm{Close}_{t}^{\mathrm{g}}\) and \(\mathrm{MAK}_{1}^{\mathrm{g}}<\;\mathit{High}_{t}^{\mathrm{g}}\)) & \\ \(\mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\) & \(12\) \\ moving average lines & \(\mathit{false}(=-1)\quad\mathit{Otherwise}\end{array}\) & \(,\) (\(k=5,10,20\)) & \\ \hline Upward/downward penetration & \(\left\{ \begin{array}{l}\mathit{true}\;if(\mathrm{MAK}_{1}^{\mathrm{g}}> \mathrm{Low}_{t}^{\mathrm{g}}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}< \;\mathit{Close}_{t}^{\mathrm{g}})\\ \mathit{false}\mathit{otherwise}\end{array} \right.\) & \(\mathit{false}\mathit{otherwise}\) & 12 \\ Upward/downward penetration & \(\left\{ \begin{array}{l}\mathit{true}\;if(\mathrm{MAK}_{1}^{\mathrm{g}}> \mathrm{Low}_{t}^{\mathrm{g}}\;and\;\mathit{MAK}_{1}^{\mathrm{g}}<\;\mathit{ Open}_{t}^{\mathrm{g}})\\ \mathit{false}(=-1)\quad\mathit{Otherwise}\end{array} \right.\) & \(,\) (\(k=5,10,20\)) & \\ \hline Golden cross point between & \(\left\{\begin{array}{l}\mathit{true}(=1)\quad\mathrm{VMA}_{1}^{\mathrm{g}}< \mathit{MAK}_{1}^{\mathrm{g}}\;and\;\mathit{VMA}_{1}^{\mathrm{g}}\geq\;\mathrm{VMA}_ {1}^{\mathrm{g}}\;\;,There are 46 price features used with binary features in Table 4. These consist of _MA_s, the gradient of _MA_s, the gradient of _VMA_s, and disparity. Each _MA_ and _VMA_ and the disparity, are calculated at intervals of 5/10/20/60/120 days. The configuration of the event binary features is shown in Table 5 (continued on the next page). There are 30 turn-up or down features, which means the phase at which the slope of _MA_ becomes negative or positive.