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Initial Situation

You are part of a company and your role is to forecast the future demand of a product. The product has a daily demand.
You are responsible to make sure that the demand is fulfilled to the best extent possible, the profitability of your company depends on it. In order to do so, you have to decide how much of the product (in pieces) should be available for the next day.

Every day, there are two stages you have to go through for making a forecast.
In a first stage the actual demand of past days will be presented.
In a second stage additionally a Machine Learning (ML) algorithm forecast will be available.

Task Description

Your task is to insert a numeric value as a forecast for the product amount that should be available the next day.
In the first stage of each forecasting step you give your initial forecast. You are allowed to take the additional information available into account.
In the second stage of each forecasting step you are allowed to enter a new forecast, after the ML algorithm's forecast is displayed.
It is up to you whether you stay with the initial value (by entering the same value again) or to adjust. Again, you are allowed to take all additional information you want into account.

In total you will plan for 30 days, so there are 30 successive forecasting steps to be made.

Payoff

Each participant starts with an initial payoff of {{ Constants.endowment }}. Your decisions should be as close as possible to the real demand in order to increase your payoff. Larger deviations from the real demand result in a smaller increase or add no value at all.

At the end of the game you will receive ... according to your absolute payoff in relation to other participants absolute payoff.

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