Accounting technology application learning objective 1

ACCT 300 Project 1- Using MS Access to create database and query information

It is necessary for accounting students to understand stock prices and their trending patterns. The intelligence about the stock market is not easy; many professionals dedicate their spend whole career lives on this understanding. According to behavior economics, animal spirit, fear, and euphoria can significantly impact stock. This assignment aims to train your understanding by practicing database skills with a fear and greed index and stock price datasets. In this project, you are required to complete two tasks: (1) create a database (SentimentImpactStockPrice) with two linked tables with two spreadsheet datasets and (2) develop four queries from the developed database. You need to upload the databases with these four queries to your Canvas assignment account. Please name your first database as “FirstNameLastName_SentimentImpactStockPrice” (e.g., JiahuaZhou_SentimentImpactStockPrice.accdb.

Task 1: Please follow the guidance below to (1) download two datasets, (2) feed the two spreadsheet datasets into MS ACCESS as two tables, and (3) integrate the two tables with the link of primary and foreign keys (Hint: MS ACCESS is more friendly with Excel Workbook, your downloaded file may be .csv, or other file forms. It is better to transform Excel Workbook. You can just click the file save as, and change the file type as Excel Workbook).

The first dataset specifically includes daily closing prices of Bitcoin, as well as daily volumes of Bitcoin, and the Fear and Greed Index values for the overall crypto market (I downloaded the in the canvas for you. You also can download it from ). This dataset presents a unique opportunity for researchers and analysts to explore the relationship between the prices and volumes of Bitcoin, as well as the sentiment of the overall crypto market. By conducting thorough analysis of this dataset, researchers and analysts can gain valuable insights into the behavior and trends of the cryptocurrency market. This includes examining the daily closing prices and volumes of Bitcoin, as well as the Fear and Greed Index values for the overall crypto market (this index is a composed indicator that includes various measurements, ). Through comprehensive analysis, potential patterns, trends, and correlations between price movements, trading volumes, and market sentiment can be identified. These insights can inform investment strategies and decision-making, providing a more nuanced understanding of the dynamics of the cryptocurrency market. This data presents a unique opportunity for researchers and analysts to uncover valuable information that can contribute to a deeper understanding of the cryptocurrency market and its potential implications for investment decision-making.

Please download a stock price dataset (You can choose one of the following stocks: Tesla, Google, JPMorgan Chase, GE) from .

You can name the first Table, tblGreedFearIndex (we usually name tables and attributes as several words without spaces between them), and the second table, tblStockPrice. You need to integrate these two tables with the link of primary key and foreign key.

Hint: The objective of this database is to observe the relationship between the greed index and stock price. We need to observe the movement of the index and stock price on the same date. Thus, date can be a unique attribute and act as the primary key in two tables. We can integrate these two tables by using Date. To simplify the demonstration, the following video only uses Google’s stock price and the Greed Index data as examples.

Course video:

Task 2: Develop the following with the database developed from Task 1. Before you start these queries, please understand the database’s data dictionary and tables’ relationship by clicking the Relationships” under the “Database Tools” button. With this information, you can know which tables you need for the following queries and select the necessary tables for your queries.

Query 1 (name it as qryExtremeFear): Please report Date, Value, BTC_Volume, Close, and Volume when the Value_Class (fear index) is Extreme Fear

Query 2 (name it as qry2020StockPerformance): Please report Date, Open, High, Low, Close from January 1, 2020, to December 31, 2020.

Query 3 (name it as qryHighVolatileStock): Please report Value, Value_Class when High >=1.5*Low and Close > Open.

Query 4 (name it as qryExtremeFearDays): Please list Close, Volume, BTC_Volume if Vlaue is smaller than 25 from March 2021 to September 2021, and also report how many days the Value_Class is Extreme Fear.

Note: You may use Count () function in this query. The count function is usually used in conjunction with the Group By clause to return the number of records of a data field.