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Research on Choices of Investment Strategies

Research on Choices of Investment Strategies
Lin Song
Shandong University of Finance and Economics
Ji'nan, China
AbstractThe argument of whether the market is efficient
has lasted for a long time and it is essential for an investor to
determine what kind of investment strategy to choose facing
different market effectiveness. It is valuable to determine
which kind of strategy to use in different market stages.
We would like to evaluate the performance of passive
strategy, so we choose NASDAQ index ETF and HSI ETF as
the representatives. The method of regression and tracking
error are used and it is easy to get the conclusion that returns
of ETFs follows the change of whole market and only a small
amount of return could be earned.
Then, we should establish a mutual fund to evaluate the
performance of aggressive strategy. To eliminate the influence
of the extreme value and manipulation, the best choice is to
construct a fund of fund using 4 dominant mutual funds and
basing on Markowitz's portfolio theory, we construct a FOF
and calculate daily return and evaluate risk with VaR.
After comparing the performance of the passive strategy
and aggressive strategy, we find that the return of ETF and
FOF display an opposite trend. This finding is consistent with
behavior finance theory which holds the point of view that the
effectiveness of the market changes with economic cycle.
In the end, it is easy to get the following conclusions: first,
when the market enters the effective stage, passive strategy is
economical and ideal; second, when the market is inefficient,
aggressive strategy could bring extra return. These conclusions
fill the gap between academy and industry and prove the
research of behavior finance.
Keywords: positive strategy, negative strategy, VaR, portfolio
The idea of research on choices of investment strategies
derive from an interesting argument between the academic
circles and industry. As we all know, academic research
always assumes that the market is completely perfect while
in practice, from the perspective of industry, price cannot
reflect all the information in the market and an aggressive
investment strategy could always bring a positive premium
return. Consequently, based on the arguments above, two
kinds of investment ideas emerged.
According to the Efficient Market Hypothesis, or EMH,
all the information is reflected into the market prices of the
stock and equity. A premium investment strategy will not
generate an excess return and no extra alpha will be gained.
All the investors in the financial market will not earn excess
return and face a same scenario. Thus, just following the
market trend where index funds track a stock market index of
the market and resisting the temptation to react or predict the
next move in the stock market is an ideal investment
Stock prices cannot reflect all the information of the
market, so the role of managers is attached much more
importance. It aims to exceed the average return of the stock
market by in-depth analysis and expertise and by taking full
advantage of short-term price fluctuations. Managers should
know when to move into or out of stocks, bond, or any asset.
These portfolio managers try to determine when and where
prices will change by studying qualitative and quantitative
Thus, it is valuable to research on which strategies can
perform better in the real world. Using NASDAQ ETF to
evaluate the performance of Passive investment strategy and
establishing a FOF to display Aggressive investment
We want to evaluate the performance of the passive
The first step is to collect the data of NASDAQ index
and HSI as benchmark from 01/01/2019.
Then we would like to analyze the trend and give overall
description of NASDAQ index and HIS.
Third, we pick suitable ETF and evaluate the return
related to market index.
Finally, we use the method of tracking error to test the
performance of passive strategy.
A. Data collection
It is easy to download the daily return of NASDAQ index
and HSI from Yahoo finance and then using the daily return
to calculate the monthly return and evaluate the performance
of NASDAQ index and HSI with daily close-prices and
monthly price limit.
Advances in Social Science, Education and Humanities Research, volume 416
4th International Conference on Culture, Education and Economic Development
of Modern Society (ICCESE 2020)
Copyright © 2020 The Authors. Published by Atlantis Press SARL.
This is an open access article distributed under the CC BY-NC 4.0 license - 1354
B. Description of the market index
1) Trend analysis
At the end of the first quarter of this year, the yields on
March and 10-year U.S. Treasury bonds inverted, causing widespread discussion in the market about the U.S. economic
recession. ("Fig. 1")
Fig. 1. Trend of NASDAQ Index.
Federal Reserve cut interest rates as scheduled in July,
and the Nasdaq index showed a rising trend. Since September, the Fed has cut interest rates again by
0.25%, hence the Nasdaq index shows volatile growth.
Fig. 2. Trend of HSI.
At the beginning, the valuation level of Hong Kong
stocks was already in a historically low level, and the
implementation of the central government's stimulating
economic policies encouraged the market. ("Fig. 2")
There were several adverse signals in the market in the
second quarter. The first was a major setback in Sino-U.S.
Trade talks, and the two sides faced the risk of reciprocal
The second was that China's macroeconomic data after
May showed signs of a significant slowdown. This also
means that the macro economy is facing a very unfavorable
situation. Under the influence of these factors, the Hong
Kong stock market has experienced a substantial retracement.
As the Sino-U.S. Trade war disrupted the market, the
long-term and short-term yields of U.S. Treasury bonds fell,
U.S. stocks fell, Hong Kong stocks continued to fall to low
2) Performance of ETF
ETF can be conceptually regarded as a first set of index
spot, in combination with the commodity characteristics of
ETF itself that can be operated both long and short.
According to efficient market theory, investors do not get
excess returns from securities analysis and should buy and
hold index funds. That is what we called negative investment
strategies. Hence, we choose two indexes ETF which follow
the NASDAQ index and Hang Seng index
To make the chart more directly, we used two-week data
here to present both ETFs.
Advances in Social Science, Education and Humanities Research, volume 416
Fig. 3. NASDAQ ETF (QQQ) Two-week Chart.
According to the figure above ("Fig. 3"), QQQ ETF
performed quite well in this year. The volume of QQQ was
around $3 million and it nearly reached $6million at the
middle of the first month of 2019, which means the liquidity
of this ETF was quite attractive. Besides, the changes of
price were also quite smooth and steady. It plays an
important role in giving conservative investors great
confidence to buy in this ETF.
Fig. 4. HSI ETF (Tracker Fund of Hong Kong).
Since the ETF is related to the original index, due to the
bad performance of Hang Seng Index this year, the overall
trend of its ETF, Tracker Fund of Hong Kong, waves
violently. Not only the price of Tracker Fund of Hong Kong,
but its volume fluctuated al lot as well. The volume on April
26th fell at the rock bottom at around 10 million HKD, but
reached the peak point of this year 2 weeks later. And the
price was surprisingly following the trend of the volume.
("Fig. 4")
A. Comparison of two ETFs
We Use the bi-weekly transaction data of two ETFs to
calculate the return of these two funds, as shown in the figure
below. Then we compare these two ETF, the average return
of the NASDAQ index ETF and Hang Seng index ETF are
0.97% and -0.05% respectively. And the deviation of them
are 0.1355 and 0.1571 respectively in general, due to market
fluctuations, the returns of the two funds are not high.
Advances in Social Science, Education and Humanities Research, volume 416
B. Tracking error
Tracking error, which reports the difference between the
return an investor receives and that of the benchmark they
were attempting to imitate, is commonly used as a metric to
measure ETF's performance. As we know, tracking error is
the standard deviation of the difference between the returns
of an investment or portfolio and its benchmark, which can
be expressed as Tracking error=Standard Deviation of (P-B).
Calculated the active return as the daily return of QQQ
minus the return of Nasdaq index. From the line chart below,
it indicates that the active return of QQQ fluctuated greatly,
which between 4% and -5%. ("Fig. 5")
Then we use the formula to get its tracking error which
was 1.12%. It is rigorous to set the confident level as 95% to
calculate its parametric and non-parametric tracking error
was 1.84% and 1.74%, respectively. ("Fig. 6")
Fig. 5. Active return for QQQ.
Fig. 6. Active return for Tracker Fund of Hong Kong.
The active return of this ETF was quite flat all over the
year, except on Oct 31st was downtrend at -2.8%. Besides,
its tracking error, parametric and non-parametric tracking
error were respectively at 0.26%, 0.43% and 0.30%, which
are far smaller than the number of QQQ. It shows that
Tracker Fund of Hong Kong had a better performance in the
past year.
A. Mutual fund construction
1) Selection of funds: According to the Zacks Mutual
Fund Rank, which is not only focus on past performance but
on the future success of the fund, picked out 4 most
promising aggressive funds ("Fig. 7").
Fig. 7. Four most promising aggressive funds.
These four funds seek long-term capital appreciation by
investing in a diversified group of emerging businesses like
healthcare and technology. These businesses usually have a
high probability of accelerating earnings growth that depend
on factors such as reformed management, new products and
services or structural changes in the economy. In this way,
FOF is fully diversified.
2) FOF construction: Given the 4 individual assets are
picked, download the daily close prices of 4 individual
funds from Yahoo Finance between 2018/12/17 and
2019/12/14. To establish the FOF, daily return should be
calculated with the formula:
Daily return = (close price-open price)/open price
Advances in Social Science, Education and Humanities Research, volume 416
To establish a FOF, we use the following formulas:
After calculation of the covariance matrix, draw the
efficient frontier to construct the optimal portfolio. Use total
of 20 scenarios to draw the efficient frontier. Considered the
shape of the fitted line, display the first half of the fitted
picture ("Fig. 8"):
Fig. 8. Portforlio Frontier.
After the establishment of the optimal portfolio, testing
the risk of this portfolio is an essential part to evaluate the
efficiency of the aggressive strategy ("Fig. 9"):
Credit VaR = q(CL) EL
We use Excel to calculate the 1-day 0.99-VaR and 10-
day 0.99-VaR:
Fig. 9. 1-day VaR.
Advances in Social Science, Education and Humanities Research, volume 416
Then, we summarize the calculation data of constructed
FOF ("Fig. 10"):
Fig. 10. Summary
Step1: We use the function of OFFSET to match the data
time to create standard time-series data ("Fig. 11").
Step2: Then, we insert the daily return of FOF return and
ETF return in chronological order.
Fig. 11. OFFSET
Step3: We draw a picture to show the difference of these
two portfolios and the discrepancy is filled with light blue
("Fig. 12").
Fig. 12. Comparison of returns of FOF&ETFs.
A. Findings of research
From the above picture, it is obvious that returns of FOF
and ETFs show a totally different changing trend: when the
return of FOF is high, the return of ETFs keeps on a
relatively low level; if the return of FOF is very low, the
return of ETFs increases dramatically.
This conclusion is consistent with the findings of
behavioral finance. According to the behavior finance, the
efficiency of market change with the economic cycle. The
market efficiency and inefficiency takes place in turn,
This finding contacts the efficient market hypothesis in
academic area and the real world in industry. Passive
strategy is recommended when the economy into the period
of efficient market and the aggressive strategy could earn a
higher return when the market is not efficient enough.
B. Brief bridge of behavior finance
Behavior finance study for the behavior of the
practitioners in the financial market. In traditional economic
theory, all the investors are rational and they always make
decisions based on their needs and demanding. But in reality,
things are different, not all the investors are rational, but
complicated. Thus, behavior finance could explain what
happened in the real world and the bias.
Behavior finance fills the gap between the efficiency
market hypothesis and the real world. It explains the market
chaos and the economic crisis in industry and this
discrepancy could be explained by behavior finance.
The findings of behavior finance are consistent with the
above research:
When the market is efficiency, according to the
efficiency market hypothesis, all the information has been
reflected in the stock prices. Thus, technical analysis is
useless, just following the change of the market is a wise
choice for all the investors, no extra return and premium can
be realized. Consequently, passive strategy not only money-
saving and it is easy to implement for all the investors with
different background and information.
When the market is inefficiency, like some political
impact and some government regulation, the assets prices
deviate from the real value. This situation offers good
opportunities for smart investors to earn an extra value with
more inside-information and qualified technical analysis
ability. Under such circumstance, aggressive strategy can
distinguish the naïve investors and the wise investors.
Although passive strategy in such situation follows the
market and earns an average return of the whole market,
aggressive one provides the possibility to earn far more
profits than imagine.
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  • V Ivashina
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Ivashina, V., & Lerner, J. (2019). The Genesis of Private Capital. In Patient Capital: The Challenges and Promises of Long-Term Investing (pp. 99-123). Princeton; Oxford: Princeton University Press.