Import data

## # A tibble: 45,090 × 10
##    stock_symbol date                 open  high   low close adj_close    volume
##    <chr>        <dttm>              <dbl> <dbl> <dbl> <dbl>     <dbl>     <dbl>
##  1 AAPL         2010-01-04 00:00:00  7.62  7.66  7.58  7.64      6.52 493729600
##  2 AAPL         2010-01-05 00:00:00  7.66  7.70  7.62  7.66      6.53 601904800
##  3 AAPL         2010-01-06 00:00:00  7.66  7.69  7.53  7.53      6.42 552160000
##  4 AAPL         2010-01-07 00:00:00  7.56  7.57  7.47  7.52      6.41 477131200
##  5 AAPL         2010-01-08 00:00:00  7.51  7.57  7.47  7.57      6.45 447610800
##  6 AAPL         2010-01-11 00:00:00  7.6   7.61  7.44  7.50      6.40 462229600
##  7 AAPL         2010-01-12 00:00:00  7.47  7.49  7.37  7.42      6.32 594459600
##  8 AAPL         2010-01-13 00:00:00  7.42  7.53  7.29  7.52      6.41 605892000
##  9 AAPL         2010-01-14 00:00:00  7.50  7.52  7.46  7.48      6.38 432894000
## 10 AAPL         2010-01-15 00:00:00  7.53  7.56  7.35  7.35      6.27 594067600
## # ℹ 45,080 more rows
## # ℹ 2 more variables: Column1 <lgl>, HPR <dbl>

State one question

When did each of the stocks increase and decrease the most on a percentage basis?

Plot data

Performance Line Plots

Results

## Stock Symbol: AAPL 
##   stock_symbol max_increase max_increase_date
## 1         AAPL    0.0869611        2015-08-24
##   stock_symbol max_decrease max_decrease_date
## 1         AAPL  -0.07257864        2020-03-20
## 
## Stock Symbol: ADBE 
##   stock_symbol max_increase max_increase_date
## 1         ADBE    0.1120156        2010-10-07
##   stock_symbol max_decrease max_decrease_date
## 1         ADBE  -0.07498947        2018-11-19
## 
## Stock Symbol: AMZN 
##   stock_symbol max_increase max_increase_date
## 1         AMZN    0.1221561        2010-07-23
##   stock_symbol max_decrease max_decrease_date
## 1         AMZN  -0.08561454        2015-07-24
## 
## Stock Symbol: CRM 
##   stock_symbol max_increase max_increase_date
## 1          CRM    0.1257775        2010-05-21
##   stock_symbol max_decrease max_decrease_date
## 1          CRM   -0.0932583        2012-05-10
## 
## Stock Symbol: CSCO 
##   stock_symbol max_increase max_increase_date
## 1         CSCO    0.0995261        2020-03-18
##   stock_symbol max_decrease max_decrease_date
## 1         CSCO  -0.07065341        2020-06-11
## 
## Stock Symbol: GOOGL 
##   stock_symbol max_increase max_increase_date
## 1        GOOGL   0.06507064        2022-11-30
##   stock_symbol max_decrease max_decrease_date
## 1        GOOGL  -0.08012822        2012-10-18
## 
## Stock Symbol: IBM 
##   stock_symbol max_increase max_increase_date
## 1          IBM   0.06003375        2020-03-17
##   stock_symbol max_decrease max_decrease_date
## 1          IBM  -0.06363565        2020-06-11
## 
## Stock Symbol: INTC 
##   stock_symbol max_increase max_increase_date
## 1         INTC    0.1278492        2020-03-13
##   stock_symbol max_decrease max_decrease_date
## 1         INTC  -0.06818866        2021-03-24
## 
## Stock Symbol: META 
##   stock_symbol max_increase max_increase_date
## 1         META    0.1124379        2012-11-14
##   stock_symbol max_decrease max_decrease_date
## 1         META  -0.09084421        2012-05-18
## 
## Stock Symbol: MSFT 
##   stock_symbol max_increase max_increase_date
## 1         MSFT    0.0810245        2022-02-24
##   stock_symbol max_decrease max_decrease_date
## 1         MSFT  -0.05924653        2020-03-20
## 
## Stock Symbol: NFLX 
##   stock_symbol max_increase max_increase_date
## 1         NFLX    0.1931938        2012-10-31
##   stock_symbol max_decrease max_decrease_date
## 1         NFLX   -0.1684199        2013-10-22
## 
## Stock Symbol: NVDA 
##   stock_symbol max_increase max_increase_date
## 1         NVDA    0.1491142        2011-01-12
##   stock_symbol max_decrease max_decrease_date
## 1         NVDA   -0.1320755        2011-08-12
## 
## Stock Symbol: ORCL 
##   stock_symbol max_increase max_increase_date
## 1         ORCL   0.08840015        2020-03-26
##   stock_symbol max_decrease max_decrease_date
## 1         ORCL  -0.06111018        2020-09-11
## 
## Stock Symbol: TSLA 
##   stock_symbol max_increase max_increase_date
## 1         TSLA    0.1993462        2010-11-10
##   stock_symbol max_decrease max_decrease_date
## 1         TSLA   -0.1975352        2012-01-13

Interpretation

AAPL (Apple Inc.):

Maximum Increase: AAPL experienced its highest monthly increase on August   24, 2015.
Reason: Strong quarterly earnings, new product launches, or positive market sentiment.
Maximum Decrease: The largest monthly decrease for AAPL occurred on March 20, 2020.
Reason: Broad market volatility due to the COVID-19 pandemic, supply chain disruptions, or declining iPhone demand.

ADBE (Adobe Inc.):

Maximum Increase: ADBE saw its peak monthly increase on October 7, 2010.
Reason: Robust revenue growth, successful product launches, or favorable market reception.
Maximum Decrease: The sharpest monthly decline for ADBE was observed on November 19, 2018.
Reason: Concerns over subscription growth rates, competitive pressures, or market corrections.

AMZN (Amazon.com Inc.):

Maximum Increase: AMZN recorded its highest monthly increase on July 23, 2010.
Reason: Strong quarterly earnings, expanding cloud computing services (AWS), or strategic acquisitions.
Maximum Decrease: The largest monthly decrease for AMZN occurred on July 24, 2015.
Reason: Missed earnings expectations, regulatory concerns, or profit-taking after stock price appreciation.

CRM (Salesforce.com Inc.):

Maximum Increase: CRM witnessed its highest monthly increase on May 21, 2010.
Reason: Impressive revenue growth, successful customer acquisitions, or strategic partnerships.
Maximum Decrease: The most substantial monthly decrease for CRM was observed on May 10, 2012.
Reason: Weaker-than-expected quarterly earnings, competitive pressures, or integration challenges.

CSCO (Cisco Systems Inc.):

Maximum Increase: CSCO experienced its highest monthly increase on March 18, 2020.
Reason: Increased demand for networking and cybersecurity solutions during the COVID-19 pandemic.
Maximum Decrease: The largest monthly decrease for CSCO occurred on June 11, 2020.
Reason: Concerns over slowing revenue growth, competitive pressures, or macroeconomic uncertainties.

GOOGL (Alphabet Inc. - Class A):

Maximum Increase: GOOGL saw its peak monthly increase on November 30, 2022.
Reason: Strong advertising revenue growth, successful product innovations, or market optimism.
Maximum Decrease: The sharpest monthly decline for GOOGL was observed on October 18, 2012.
Reason: Regulatory challenges, antitrust investigations, or concerns over slowing revenue growth.

IBM (International Business Machines Corporation):

Maximum Increase: IBM recorded its highest monthly increase on March 17, 2020.
Reason: Positive market reactions to strategic initiatives, cloud computing growth, or cost-cutting measures.
Maximum Decrease: The largest monthly decrease for IBM occurred on June 11, 2020.
Reason: Disappointing quarterly earnings, challenges in legacy business segments, or slower adoption of new technologies.

INTC (Intel Corporation):

Maximum Increase: INTC witnessed its highest monthly increase on March 13, 2020.
Reason: Optimism about Intel's new product roadmap, strength in data center segment sales, or industry trends.
Maximum Decrease: The most substantial monthly decrease for INTC was observed on March 24, 2021.
Reason: Production delays, competitive threats, or concerns over technological leadership.

META (Meta Platforms Inc.):

Maximum Increase: META experienced its highest monthly increase on November 14, 2012.
Reason: Strong user engagement metrics, successful monetization efforts, or positive market sentiment.
Maximum Decrease: The largest monthly decrease for META occurred on May 18, 2012.
Reason: Privacy scandals, regulatory scrutiny, or concerns over slowing user growth rates.

MSFT (Microsoft Corporation):

Maximum Increase: MSFT saw its peak monthly increase on February 24, 2022.
Reason: Robust cloud computing revenue growth, successful product launches, or digital transformation initiatives.
Maximum Decrease: The sharpest monthly decline for MSFT was observed on March 20, 2020.
Reason: Market sell-offs amid the COVID-19 pandemic, concerns over enterprise software sales, or profit-taking.

NFLX (Netflix Inc.):

Maximum Increase: NFLX recorded its highest monthly increase on October 31, 2012.
Reason: Strong subscriber growth, successful content releases, or market enthusiasm about Netflix's future.
Maximum Decrease: The largest monthly decrease for NFLX occurred on October 22, 2013.
Reason: Rising content costs, subscriber churn rates, or competitive pressures in the streaming market.

NVDA (NVIDIA Corporation):

Maximum Increase: NVDA witnessed its highest monthly increase on January 12, 2011.
Reason: Strong demand for NVIDIA's GPUs in gaming, data center, or AI applications.
Maximum Decrease: The most substantial monthly decrease for NVDA was observed on August 12, 2011.
Reason: Concerns over slowing PC sales, supply chain disruptions, or macroeconomic uncertainties.

ORCL (Oracle Corporation):

Maximum Increase: ORCL experienced its highest monthly increase on March 26, 2020.
Reason: Strong cloud services revenue growth, successful acquisitions, or transition to a cloud-centric business model.
Maximum Decrease: The largest monthly decrease for ORCL occurred on September 11, 2020.
Reason: Disappointing earnings results, competitive pressures, or challenges in retaining customers.

TSLA (Tesla Inc.):

Maximum Increase: TSLA saw its peak monthly increase on November 10, 2010.
Reason: Positive news about Tesla's electric vehicle production, successful product launches, or market enthusiasm.
Maximum Decrease: The sharpest monthly decline for TSLA was observed on January 13, 2012.
Reason: Production delays, quality issues, or broader market volatility.

Limitations

While this analysis provides insights into the monthly fluctuations of Holding Period Returns (HPR) for the 14 tech stocks, it is important to acknowledge the limitations of using daily HPR data. Daily fluctuations may be influenced by short-term market dynamics or trading irregularities, which may not reflect the underlying trends or external factors impacting stock performance.

In next week's assignments, the analysis will be enhanced by visualizing the HPR on a monthly basis, allowing for a more detailed understanding of long-term trends and identifying external factors affecting stock movements. Additionally, further research will be done to explore the specific drivers behind the observed increases and decreases in HPR for each stock, providing deeper insights for informed decision-making.