1. Prediction in Stock Trading
J.-S. Roger Jang (張智星)
MIR Lab, CSIE Dept.
National Taiwan University
2019/5/3

2. Types of Predictions in Stock Trading
Up/down prediction: Classification
Use historical data as groundtruth (GT)
Price prediction: Regression
Use historical data as GT
Timing prediction for “buy” and “sell” to maximize profit
Set up groundtruth  How?
Use historical data to do prediction
Historical data from 技術面、消息面、基本面…
Backtest (回測)

3. GT for “Buy” and “Sell”: Heuristic Approaches
Heuristic approaches to set up GT
慣量型
連漲三天 買！（因為還會上漲…）
連跌三天 賣！（因為還會下跌…）
逆勢型
連漲五天  賣！（因為快開始跌了…）
連跌五天  買！（因為快開始漲了…）
謹慎小心型
上漲超過買價的10%  賣！
下跌超過賣價的10%  買！
Performance can be evaluated by backtest.
Quiz!

4. GT for “Buy” and “Sell”: Optimal Approach
Problem definition
Given the price curve over a long period of time, find “buy” and “sell” points (where you can look into the future) such that the overall profit is maximized.
Assumptions
每一次都全買或全賣
根據開盤價格來買或賣，一定會成交
必須計算交易費
Approaches
Optimal search: Dynamic programming
Heuristic search: Genetic algorithms, simulated annealing, randomized search?

5. Set Up GT for Max. Profit in HW05
HW05: How can we set up GT for “buy” and “sell” points, such that the overall profit can be maximized?
MATLAB functions
Function submitted by you:
actionVec = myOptimAction(priceVec, transFeeRate);
Evaluation by our judge system
returnRate = profitEstimateOpen(priceVec, transFeeRate, actionVec);
Scoring is based on your ranking!
All price data is here!

6. Prediction of GT Derived by Optimal Methods
2019/5/3
For a given date
Predict all the future price using historical data
Run DP to predict all the “buy” and “sell” points based on the predicted price
Execute the predicted plan for tomorrow
Future price prediction
Time series prediction (regression)
One-step-ahead prediction
𝑥 𝑛 =𝑓( 𝑥 𝑛−𝑑 , 𝑥 𝑛−𝑑−1 ,…, 𝑥 𝑛−1 ), 𝑥 𝑛 ∈𝑅.
Accumulated prediction: 𝑥 1 , 𝑥 2 , 𝑥 3 , 𝑥 4 , 𝑥 5 , 𝑥 6 , 𝑥 7 , 𝑥 8 , 𝑥 9 , 𝑥 10
K-step-ahead prediction

7. Prediction of GT Derived by Heuristics
2019/5/3
For a given date
Predict “up for m days” or “down for n days”
Execute the predicted plan for tomorrow if the prediction tell us to “buy” or “sell”
Future price prediction
Prediction of up/down (classification)
One-step-ahead prediction:
𝑥 𝑛 =𝑓 𝑥 𝑛−𝑑 , 𝑥 𝑛−𝑑−1 ,…, 𝑥 𝑛−1 , 𝑥 𝑛 ∈ ±1 .
Accumulated prediction: 𝑥 1 , 𝑥 2 , 𝑥 3 , 𝑥 4 , 𝑥 5 , 𝑥 6 , 𝑥 7 , 𝑥 8 , 𝑥 9 , 𝑥 10
K-step-ahead prediction

8. References and Resources
2019/5/3
MATLAB
Time Series Forecasting Using Deep Learning
Time Series Prediction and Forecasting for Prognosis
Time Series Analysis …
Python
7 methods to perform Time Series forecasting
A comprehensive beginner’s guide to create a Time Series Forecast
11 Classical Time Series Forecasting Methods in Python