final stimulation project investment

Texas Wesleyan University

Portfolio Management Simulation Project FIN3325-01 Investments

Spring 2015 Dr. Wu

Student Name:

Table of Contents

Executive Summary 3 Introduction 4 Investment Objective and Strategy 4 Investment Style 5 Return Analysis 6 Risk Analysis 11 Investment Experience 12 Conclusion 13 Appendix 14 References 15

Executive Summary

During the Spring 2015 semester, I participated in the class of Finance 3325 –

Investments. One of the key requirements of the course was to complete an investment

simulation portfolio, covering a minimum of 50 trades and a maximum of 200 trades. The

simulation was to be completed through the server of StockTrak, the leading provider for virtual

trading applications. Transaction Fees through StockTrak were at $10, per each trade. The

simulation was open to all sorts of trading options. These included: Stocks, Bonds, Options,

Futures and Mutual Funds. To compare and contrast the success/failure through this project, a

realistic benchmark had to be selected. Beating the benchmark would create an incentive for

students, gaining extra points towards the final grade.

Introduction

During the nine weeks of this investment portfolio project, I became a small hedge fund

manager, where I organized and analyzed different techniques to create a successful portfolio. I

took charge of 53 different trades, which included 21 different companies. Some of these

companies were traded more than once during the portfolio. The Investor Portfolio Questionnaire

suggested I place certain focus on different investment types, such as small equity stocks, large

equity stocks and bonds. During the time period, my goal was to understand and learn more

about the investment techniques and strategies, while creating a profit on my portfolio. This was

to be completed with different Beta levels in mind. The result of my portfolio produced 6.66%

profit return, beating my benchmark.

Investment Objective and Strategy

In order for me to fulfill my goals during this nine-week period, I completed the Investor

Profile Questionnaire, provided through Charles Schwab. This questionnaire placed me at a level

where I should aim to invest moderately conservative. From this, the recommendation explained

that I allocate my money 50% through Bonds, Cash Investments 10%, Large Cap Equity 25%,

Small Cap Equity 5% and International Equity 10%. As seen in the first diagram below, this was

my initial suggested investment strategy. After starting the portfolio and investing in different

areas, I decided to take higher risk to understand the concepts. The strategy I ended up having for

my portfolio was: Large Equity Stocks: 48%, Mid Cap: 14%, Micro Cap: 5% and Nano Cap:

33%. The second graph below explains the breakdown. To use a general and straightforward

benchmark, I aimed at using the S&P 500.

With the breakdown of portfolio strategy shown above, this diversified my risk. Nano Cap

Stocks are small publicly traded companies, which have Market Capitalization below $50 Million.

Because of this, the small companies are “Prone to manipulation” (Investopedia, 2018), which makes

them very risky. Because of this, the Large Cap stocks, which have Market Capitalization above $10

Billion, were chosen to diversify the differences. Large Cap stocks are typically more secure as they

are the big global companies within the industry.

Investment Style

Through this portfolio, I used different techniques for analyzing information and making

decisions on my investments. For the majority of my investments, they were made based on recent

news, last 3-6 month trends, or any sudden increases/decreases in price. Through the start of the

portfolio, I made an investment based on a sudden price drop. After looking over the last 6 months

trend, I arrogantly ignored the news reports about bearish predictions for the future. As my first

investment in the portfolio, I learned my lesson to thoroughly investigate each transaction I decide to

make. I purchased 161 units of Walmart on February 23rd for $92.75, and after 9 weeks I was not

able to sell them for a profit. During this experience, I also learned the importance of viewing

multiple different sources of information for decision making. While certain sites provided bearish

reports, bullish reports were also present in other sites. Looking at moving day averages and previous

trends, I learned the importance of mixing articles with financial facts.

48%

14%5%

33%

Actual Portfolio Breakdown

Large Cap Mid Cap Micro Cap Nano Cap

50%

10%

25%

5% 10%

Suggested Breakdown

Bonds Cash Investments

Large Cap Small Cap

International Equity

After this error, my decision making was based on news through earning reports or sudden

releases of information such as when pharmaceutical companies announced the success of a new

drug. An example of a decision I made early on in the project, was with Zosano Pharma Corporation.

Zosano had a very high 50-day moving average at $5.80 in comparison to their 200-day moving

average of $4.00. Because of this, I invested at $9.95 and sold at $10.10 seven days later. I was still

nervous for my decision making in sales of stock. Had I waited a couple more days after Zosano hit

$10.10, I could have sold my stock around the $20.00 mark. Net Element, a financial technology

company who are also a Nano Cap stock, were brought up in the news. NETE had added another

high profile member to their Board Of Directors, and with their recent high trends I decided to

purchase stock at $9.20 on March 9th, then selling for $12.45 on March 13th.

Once I started gaining a little more confidence through these small areas of success, I started

watching the markets closely, especially when there were large drops or increases in the large market

indexes such as NASDAQ or S&P500. After analyzing some of the unusual drops that occurred for

no particular reason, I started ‘Buying The Dip’ on the large cap companies. Examples of this are

around the March 19-22 period, as I bought companies such as Amazon, Microsoft, Apple and the

ETF for NASDAQ. Over a short period of time, I was able to see profits for these particular

investment choices.

In my final strategy for making my investment decisions, I based them on the ‘short’

strategy. After viewing different news sources and information, I watched for unusual and sudden

increases in prices. Typically, these increases came within the pharmaceutical companies. The

sudden increases would come from success reports in a new drug being released or by being

approved by the Food & Drug Association. From these increases, I would short the stock, by then

covering them either on the same day or within 3 days.

Return Analysis

To start off the portfolio project, I was set off on the back foot quite heavily. After only

nine days there was a huge change in my portfolio, with -11% return. As shown in the graph

below, this created a large gap between my portfolio and the bench mark. Thankfully, 5 days

later (March 6th ), I was able to bring my portfolio to a positive return of 0.27%. After a steady

14 days, I hit the crossover point with my benchmark of S&P500 on March 20th. From here, I

took a minor dip, following my benchmark, before a major period of growth eventually taking

me to a positive return of 6.66% return.

On a weekly basis, I was able to analyze the 9 different weekly returns I got for both my

portfolio and the benchmark’s return. My results are seen in the below table and graph. Trend

lines are provided for both portfolio and market return.

Weeks Portfolio Return Market Return

Week 1 0.07% 2.33%

Week 2 -2.30% -0.85%

Week 3 0.44% 2.01%

Week 4 0.25% -1.89%

Week 5 -0.45% -2.15%

Week 6 0.47% -1.18%

Week 7 3.97% -0.05%

Week 8 0.07% 0.79%

Week 9 0.00% -1.34%

AVERAGE 0.28% -0.26%

After viewing the above tables and graphs, it can be seen that until Week 3 both the

portfolio and market were following similar trends. It was not until Week 4 that there was a

change in momentum for weekly returns, where my portfolio started growing at a faster rate. As

the trend lines provide, it shows the key difference between the positive portfolio trend and

negative market trend.

Throughout managing my portfolio, I was fortunate enough to have many different

successful transactions and investment choices. My top 5 best performing in my portfolio were

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9

R e

tu rn

%

Axis Title

Weekly Returns

Portfolio Return Market Return

Linear (Portfolio Return) Linear (Market Return)

the following companies: Net Element (35% Return), Verona Pharmaceuticals (12.58% Return),

NTN Buzztime (11.11% Return), Tenax Therapeutics (10.20% Return) and Check-Cap (9.17%

Return). All 5 of these investments that proved the best rate of return were Nano Cap stocks. All

these stocks had market capitalization below $50 Million. From the 5 most successful trades in

my portfolio, 4 of them were short trades, while 1 was a long. Below is a detailed table showing

the purchase and selling prices.

NETE proved to be a very successful long after only 4 days of purchasing. As explained

earlier in the paper, the new inclusion to the Board Of Directors helped boost the success of this

companies stock immensely. VRNA was a company that instantly jumped from $16.00 to $21.39

following the news of success in the pharmaceutical business. Because of this sudden increase, I

predicted a fall in price, which occurred in under 1 week. NTN was a company that jumped from

around $5.80 to $7.00 overnight following a good source of news, I predicted a drop, which

occurred after 3 days. TENX jumped from $4.60 to $8.86 overnight and was another company

that provided quick returns, in this case on the same day. CHEK was a company that was

gradually falling and had a negative trend line for the past 6 months. I predicted further drops,

which resulted the next day.

Also in my portfolio, I had some trades that proved to be unsuccessful. While some

trades were not completed with a buy and sell, they were purchased but remained in the portfolio

until the end simulation date. Some of these would have recovered if the time period of the

simulation was longer, such as Google. The top 5 worst performing in my portfolio were: Daxor

Corporation (-24.08% Return), Walmart (-6.22% Return), Google (-2.37% Return), McDonalds

(-1.77% Return) and Medical Transcription Billing Corporation (-1.04% Return). From these

worst performers, 3 were Large-Cap Stocks while the other 2 were Nano-Cap stocks. All of these

were purchased using the Long method. Below is a detailed table showing the purchase and

selling prices.

DXR proved to be the most unsuccessful trade I made during my simulation. After recent

good short-term performances I believed DXR would rise once more. Unfortunately, it did not

increase during the remainder of the simulation and remained until closing date. WMT was a

poor decision that I made early on in the simulation process. As explained earlier, I had believed

the sudden drop would recover quickly, which never did until the simulation closed. GOOG was

experiencing a bumpy journey over the past 6 months. After a small drop, I thought they would

recover to some of their highs which was around $1160. This never happened, and remained

untouched until the end of simulation. MCD was in a negative trend, but started to creep up

slowly around February 23rd, before suddenly taking a massive hit from February 26th onwards,

which never recovered into a profit. MTBC was a volatile company that I thought I could gather

a rather quick profit, awaiting earning reports, sources were sharing bullish trends.

Unfortunately, MTBC never matched the hype and resulted in a loss of 4 cents per share.

After research, small hedge fund startups seem to gather a fee around 1.25%, regardless

of performance (Baker, S.). Based on this information, I strongly believe I can make money for

them in terms of the risks provided. After starting with $1 Million, I was able to turn that into

$1.066 Million within 9 weeks, a 6.66% return. Although a longer period of time may mean

more risk in terms of volatility, I am confident that with my diversification techniques I will be

able to make money for the customer. Techniques also include, long and short strategies with

companies that range from Nano-Cap up to Large-Cap.

Risk Analysis

After analyzing the daily return on portfolio and daily return on the S&P 500, I was able

to gather the standard deviation figures for those 9 weeks. During this period, the standard

deviation for my portfolio resulted in 1.9539%, compared to the market’s 1.2053%. The higher

number representing my portfolio explains the increased volatility my portfolio had, in

comparison to the market. As taught through lectures, we understand that lower volatility tends

to have lower return, while higher risk typically provides higher return. This is explained through

my simulation, with figures that are greater than those of the market. When placing this volatility

into annualized statistics, my portfolio had 31.0172%, while the market had 19.1335%. These

figures were calculated by using the square root of the 252 trading days, multiplied by the daily

standard deviation rates. The Beta of a market is known as 1 and the risk free investments Beta

are known by 0. A Beta of 2 would mean that the results would fluctuate either 2 times higher or

2 times lower than what the market usually does. The Beta in my portfolio was 0.538 which

means that whenever that market moves by positively by 1 percent, my portfolio would move 0.5

percent or vice versa negatively.

St.D Daily St.D Annually

Portfolio 1.9539% 31.0172%

Market 1.2053% 19.1335%

Through lectures, we have learned that the higher figures are preferred for both the

Sharpe Ratio and Treynor Measure. For both of these calculations, higher figures represent

positive results. Throughout my portfolio, I had a Sharpe Ratio of: 0.08582, compared to the

markets -0.0318. While incurring a profit and positive return on my portfolio, my Sharpe Ratio

showed a positive figure when compared to the risk free investments. My Sharpe Ratio was

higher in comparison to the market. A higher Sharpe Ratio means that returns have been higher

compared to the risks. The Treynor Ratio for my portfolio was positive, while the market was

negative. My portfolio was at 0.00312, while the market was at -0.0004. The Treynor Ratio

represents the amount of reward compared to the volatility in the profile. My portfolio’s Treynor

Ratio is compared to the Beta of 0.53, while the market is compared to the Beta if 1. This means

that the reward to volatility return is better through my portfolio than compared to the market.

Sharpe Ratio Treynor Ratio

Portfolio 0.08582 0.00312

Market -0.0318 -0.0004

Jensen’s measure looks at the risks that a portfolio has and the return that comes from it.

It analyzes to see if the portfolio made enough return for the risk that was seen during the period.

It therefore compares the portfolio’s actual return vs the required return given the systematic

risks taken. In this case, the Jensen’s measure was negative (-0.006), meaning I underperformed

in comparison to the required rate of return, which is based on the systematic risk taken. If my

portfolio was at an optimal point, the Jensen’s measure would be positive, meaning excess return

compared to the required rate of return.

I think the Jensen’s measure is the best way of evaluating my portfolio. Jensen’s measure

compares the performance of my portfolio, seeing if it was completed at an optimal rate. With

this, it shows the rate of return I should be aiming for. After being able to review this

information, I understood that although I finished off my simulation with a positive return, I did

not make the most of the opportunities through the risk level that I took. It can be observed that

my performance could have been better and with higher return considering the risk levels that

were taken during the 9 weeks.

Investment Experience

Throughout my simulation, I believe I had a relatively successful portfolio, considering it

was my first time working with the stock markets while learning new terms and concepts on the

way. For me I feel most confident on the short strategy within the stock markets. While the long

strategy of NETE proved to be the most successful transaction in terms of return, I had a strong

amount of transactions that came through my short strategy. After analyzing stocks that shot up

in price immediately, I was able to initiate strong transactions in prediction of drop in price.

Another area where it was successful for my experience was when I invested in stocks after an

overall dip throughout the markets. After the prices had dropped, I purchased at a low and sold

again when the market strengthened. After initial hiccups in my investment strategies, I would

increase my research techniques for new stocks that I decide to invest in the future. In the future,

I would like to extend my investment experience to futures, options and bonds to further my

knowledge and understanding in these areas.

Conclusion

Overall, I viewed this simulation project as a success and a positive learning experience.

This 9-week portfolio provided me with a lot of new information and strategies to use further on

down the road. The simulation project helped me understand how the stock markets will operate

in a real-world environment, including all the fees and extras involved. To further increase my

success in a project like this, I will be able to use the different measures and ratios learned within

lectures, such as the Sharpe, Traynor and Jensens Alpha. With the inclusion of bonds, mutual

funds, options and futures, I am sure I will be able to greatly enhance my success going forward.

Appendix

February 23rd: McDonalds Corporation. Long Purchase @ $162.49.

• Purchase based on recovering form from recent dips. February 23rd: Wal-Mart Stores Inc. Long Purchase @ $92.75

• Huge recent dip, predicted a comeback, over coming months. Reference below. February 27th: Zosano Pharma Corp. Long Purchase @ $9.95

• New reports on drug improvements. Reference below. March 6th: Medical Transcripion Billing Corp. Long Purchase @ $3.85

• MTBC to host earnings call. Reference below. March 9th: Net Element. Long Purchase @ $9.20

• New member joins Board Of Directors. Reference below. March 19th: Amazon.com Inc. Long Purchase @ $1544.38

• Recent dips in market provides opportunity to buy low. March 19th: Microsoft Corporation. Long Purchase @ $92.40

• Recent dips in market provides opportunity to buy low. March 19th: Nasdaq Inc. Long Purchase @ $83.46

• Recent dips in market provides opportunity to buy low. March 19th: Netflix Inc. Long Purchase @ $310.32

• Recent dips in market provides opportunity to buy low. March 20th: Apple Inc. Long Purchase @ $175.36

• Recent dips in market provides opportunity to buy low. March 20th: Alphabet Inc. Long Purchase @ $1,098.96

• Recent dips in market provides opportunity to buy low. March 27th: Red Hat Inc. Long Purchase @ $159.09

• Bullish reports from analysts regarding RHT future. Reference below. March 27th: Verona Pharma. Short Proceeds @ $22.50

• Sudden increase in prices due to positive news reports. Reference below. March 28th: RH. Short Proceeds @ $93.04

• Sudden increase in prices due to positive financial results. Reference below. March 28th: RSP Permain Inc. Short Proceeds @ $44.75

• Sudden increase in prices provides opportunity to short.

March 28th: Verona Pharma. Short Proceeds @ $21.00

• Sudden increase in prices provides opportunity to short. March 29th: Apple Inc. Long Purchase @ $170.79

• Recent dips in market provides opportunity to buy low. March 29th: Netflix Inc. Long Purchase @ $293.45

• Recent dips in market provides opportunity to buy low. March 29th: NTN Buzztime Inc. Short Proceeds @ $7.00

• Instant boost in price creates opportunity to short. April 2nd: Apple Inc. Long Purchase @ $168.89

• Recent dips in market provides opportunity to buy low. April 2nd: NTN Buzztime Inc. Short Proceeds @ $6.30

• Opportunity in shorting further is still there.

April 2nd: RH. Short Proceeds @ $ 89.94

• Opportunity in shorting further is still there. April 4th: Alibaba Group Holding. Long Purchase @ $168.23

• Recent dips in market provides opportunity to buy low. April 4th: Check-Cap. Short Proceeds @ $5.00

• Positive financial results creates boom in prices, opportunity to short. Reference below. April 4th: RSP Permain Inc. Short Proceeds @ $43.76

• Opportunity in shorting further is still there. April 4th: Tenax Therapeutics Inc. Short Proceeds @ $9.16

• Reports after shift from loss to profit, creates boom in prices. Reference below. April 5th: Longfin Corp. Short Proceeds @ $17.30

• Volatile market creates great opportunity for quick returns in short.

References

Wal-Mart: Stock decline, with news reports suggesting negative trends. https://www.cnbc.com/2018/02/23/walmarts-plunge-this-week-shows-investors-should-be- skeptical-of-big-growth-after-deals.html Zosano Pharma: New reports on drug progression leads to my decision of long purchasing some shares. https://finance.yahoo.com/news/zosano-pharma-announces-issuance-u- 133000338.html MTBC: Earnings call to be hosted for the performances of MTBC. https://finance.yahoo.com/news/medical-transcription-billing-corp-host-113000003.html Net Element: New member joins Board Of Directors. https://finance.yahoo.com/news/net-element-appoints-jon-dr-133000070.html Red Hat: Bullish reports regarding the future of RHT. https://finance.yahoo.com/news/analysts-bullish-red-hat-ahead-193427823.html Verona Pharma: Positive news reports after clinical trial for VRNA.

https://finance.yahoo.com/news/verona-pharma-reports-positive-top-060000768.html RH: Positive financial results leads to quick boom in prices. https://finance.yahoo.com/news/rh-report-fourth-quarter-fiscal-200500113.html Chek-Cap: Positive financial results leads to quick boom in prices. https://finance.yahoo.com/news/check-cap-reports-fourth-quarter-120000161.html Tenx: News reports provides shift from loss to profit for the organization. https://finance.yahoo.com/news/tenax-therapeutics-inc-nasdaq-tenx-142318183.html