Team 6
Bingjian Huang
Kimberly Chau
Paul Medvinsky
Final Report
Overview
The main strategy that we pursued in our portfolio was a midcap pure growth strategy.
Our asset universe consisted solely of stocks from the s&p midcap 400-pure growth index. We
used fundamental analysis as the selection criteria for the stocks and the single index model in
an attempt to find the positive excess return (alpha) on each selected stock. Technical Analysis
was used after the purchase to determine whether to keep the stock or sell it.
Diversification and Portfolio Size
Unsystematic risk is the risk we can diversify by adding enough stocks into a portfolio. In
this case, we constructed a portfolio with optimal diversification, rather than naïve
diversification. Therefore, potential benefits from diversification arise when correlation is less
than perfectly positive. We would prefer having some stocks with a negative correlation to curb
risk. We chose between 10-20 stocks in the first stock selection to construct our base portfolio
and then we added 10 more stocks in the portfolio based on our performance. On average, we
had around 15 stocks in our portfolio. Our main purpose is not only for diversification, but also
to find out 20 stocks with highest positive excess return (alpha) through single index model.
Figure 1 Coefficient Correlation Matrix Table
Investment Strategy & Investment Style
80% of our fund was allocated to equities. Our asset universe was constructed from s&p
midcap 400-pure growth index across seven sectors in order to achieve the purpose of
diversification. 20% of our fund was reserved in cash.
To ascertain what stocks we would be looking at, we looked at individual sectors and
compiled a list of a few stocks from cross sectors. Then, we researched some stocks from the
healthcare, construction, technology, and consumer materials sectors in order to make our list.
In our case, Financial Statement Analysis was used for the stock selection in order to see
if a company generated healthy incomes in the past, compared with its competitors in the same
industries. So what we focused on were the liquidity and interest coverage ratios since they are
important in evaluating the riskiness of a firm's securities. For liquidity ratios, it includes the
current ratio, quick ratio, and cash ratio. For interest coverage ratio, a high coverage ratio
indicates that the likelihood of bankruptcy is low because annual earnings are significantly
greater than annual interest obligations. Moreover, we also used leverage ratio because
financial leverage helps boost ROE only if ROA is greater than the interest rate on the firm's
debt. The price to book value, price to sales, and P/E were also useful ratios for us. We used
the forward PE ratio, comparing the PE of the whole industry to determine if the stock has
potential to grow.
After finding out promising stocks in different industries, we made a coefficient matrix
table to see how those selected stocks correlate to each other, so as to diversify our portfolio
based on their correlation coefficients. In fact, financial statements can tell us if a company is
healthy or not, but nothing on return. Low correlation stocks were preferable in the portfolio.
Initially, we used the single index model to identify the stocks with ex-ante risk-adjusted excess
return (alpha). However, we found out that it was hard to tell the statistical significance of the
alpha. So we didn’t incorporate it after a few trades.
Technical Analysis was also a huge factor in our assessments after the stock’s selection.
We used relevant strength to pinpoint how strong our stock’s price is compared to others in
that industry. We looked at chart patterns to determine points of support and resistance. We
looked at primary, secondary, and tertiary trends to figure out when the best time to buy a
stock is so that we didn’t buy it when it’s in a historically downtrend state. Also, 20 day moving
averages were utilized to determine points of purchase.
Performance and Asset Allocation
However, things did not turn out the way we expected. Our portfolio’s average return is
-0.02% and the Sharpe ratio is -0.032.
Without a doubt, diversification is the main core of our stock selections. In the first
trading day, we picked stocks based on their financial statement ratios, comparing them to
their competitors. After that, we ran the coefficient matrix table to see how they correlated to
each other for the past 3 months. So our portfolio initially contained 20 stocks.
Surprisingly, the overall performance of our portfolio underperformed in the first
trading day. We kept track of our portfolio and found out there was one stock extremely
volatile, STRA. It went down 5% within the first 2 hours and went down another 8% before
closing. Besides that, the volatilities of the other stocks were almost offset by each other. Based
on the first day observation, we
realized that the diversification
and the correlation matrix table
worked, but it didn’t help us with
the volatility of individual stocks.
Thus, the covariance matrix table
was used after that to identify the
correlation and standard deviation
of
each
two
stocks.
Most
importantly, lack of risk management strategies made our portfolio become much worse than it
should have been.
In the end, our portfolio
underperformed
the
benchmark,
Guggenheim S&P Midcap 400 Pure
Growth (RFG) according to the ratios
on the table. Even though the
standard deviation and the Beta of our portfolio are lower than the benchmark, 0.335% of high
residual risk undermined our efforts of reducing the overall volatility of our portfolio. Our
portfolio did not generate a positive average return; average return of our portfolio is -0.02%,
compared to 0.059% of the benchmark. According to M-Square, the Sharpe ratio of our
portfolio with the benchmark’s standard deviation was -0.833, which is lower than the
benchmark’s. Based on the Treynor ratio, the Treynor ratio of our portfolio is -0.0094 which is
lower than -0.0044 of the benchmark.
Figure 2 Portfolio Attributions
According to Portfolio Attribution Table, 0.085% of extra return was due to asset
allocation and -0.06% of the extra loss was due to selection. We did make a good decision on
asset allocation. Most of our fund was invested in equity and cash, which generated the highest
return among equity, bonds and cash. However, we suffered
-0.06% of extra loss due to
selection within 2 months. Lack of risk management techniques and skills in stock selection at
the beginning of the game made us underperform the index.
Risk Management and Lessons from Trading
After suffering losses, we realized the
importance of risk management strategies such
as stop orders and position limits. We have also
ignored the fact that pure growth stocks are
extremely volatile so that our portfolio was at
risk if stop losses weren’t set. Thus, we checked
the volatilities of each individual stock by using
Bollinger Bands whose bands are plotted two
standard deviations away from a simple moving
average. By looking at Bollinger bands of a
stock, it was easier to tell how wide the stock’s
movement would be so that we were able to take the stocks with high volatility out of our
portfolio. After that, we reselected stocks based on the research reports from ValueLine,
Mergent and S&P500. We refocused on the midcap pure growth stocks with moderate
volatility. And then we set up stop loss for each of stocks in order to protect our investment. An
example of a risky decision which we will longer make is the stock core logic Inc. “CLGX.” Core
Logic deals with residential and commercial title insurance. With the recent turnaround of the
real estate market and the stock making higher highs since January, we thought that this stock
would be a good bargain. Here is the chart for this stock and the arrow points to the price of
purchase. We bought the stock at this point
based on the fact that we were expecting a
turnaround. We set up a stop loss at $24.95
and decided to take our losses.
Position limits are another important
strategy for protecting our investments. Thus,
we diversified our portfolio by keeping around
10-15 stocks at a time. We allocated around $380,000 to each stock. However, we also kept
some reserves in cash, usually around $2 million in cash.
Likewise, we initially made a mistake on our investment policy statement regarding the
stock selection. In reality, dividend
yield is one of the measurements
for pension fund managers in
stock selection. Even though,
dividends were obviously not
received in this portfolio, there
was a positive correlation in our
asset universe between positive
price movements and dividend
yields. In other words, holding a
valued
stock
with
potential
growth and higher dividend yields
is better than the one without dividend yields. Dividend yield should have been one of our
measurements in stock selection even though we didn’t consider it. As a matter of fact, half of
the stocks in our portfolio which generated low or zero dividend yields tended to perform badly
over the past 3 months.
Why We Should be Retained
Admittedly, our ignorance in risk management and stock selection resulted in huge
losses in the beginning and made our Sharpe ratio go down to negative eight. However, as you
can tell from this chart, we learned from our mistakes pretty quickly. After suffering huge losses
on the first few days, we realized the importance of stock volatilities and reconstructed our
portfolio under the consideration of correlation and covariance of two different stocks. In
order to prevent substantial losses, risk management techniques such as stop orders and
position limits were brought into play. Our stock performance was getting better and better, as
evident by the increasing Sharpe Ratio of our portfolio over the time period. The Sharpe Ratio
of our portfolio actually went up from -8 to -0.65 as of Feb 25. For instance, on March 15, all of
our stocks were rallying on that day. Instead of picking more stocks to invest, we decided to
increase the weight of the bullish stocks like PKG and RMD by 50% and reduce the weights of
those stocks back to what it used to be after the rally. We ended up with substantial gains on
rally days. This portfolio only ran for a period of 3 months. However, midcap pure growth
equities do well over a long-term period and are very volatile in the short term; therefore we
should be retained for a longer period of time.
Asset Universe (34 stocks)
S&P MidCap 400 Pure Growth
1. Consumer Discretionary
AMC Networks Inc.-A
American Eagle Outfitters
ANN Inc.
Ascena Retail Group Inc.
Carters Inc
Chico's Fas Inc
Dick's Sporting Goods Inc
Foot Locker Inc
Hanesbrands Inc
HSN Inc
Jarden Corp
PVH Corp
Service Corp Intl
Tractor Supply Co
Under Armour Inc A
AMCX
AEO
ANN
ASNA
CRI
CHS
DKS
FL
HBI
HSNI
JAH
PVH
SCI
TSCO
UA
2. Energy
HollyFrontier Corporation
HFC
3. Financials
Signature Bank NY
SBNY
4. Health Care
Regeneron Pharmaceuticals Inc
ResMed Inc
United Therapeutics Corp
REGN
RMD
UTHR
5. Industrials
Alaska Air Group Inc
AMETEK Inc
Clean Harbors Inc
Lennox International Inc
Terex Corp
Valmont Industries Inc
Wabtec
ALK
AME
CLH
LII
TEX
VMI
WAB
6. Information Technology
Alliance Data Systems Corp
NeuStar
SolarWinds Inc
Trimble Navigation Ltd
ADS
NSR
SWI
TRMB
7. Materials
NewMarket Corp
Packaging Corp of America
Royal Gold Inc
NEU
PKG
RGLD