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Prediction on US/China Trade war to be verified in 2021

Main points of contention

  • Marxist ideological foundation versus a Judeo-Christian philosophical foundation
    • “In god we trust” versus a centrally controlled and designed market model
    • China’s inability to open up markets internationally due to challenges in finding a sustainable way to separate market from government
    • viewing the Party as above the market leading to difference in way IP ownership is viewed
  • The Chinese dream versus the American dream
    • China’s dumping strategy which lead to the severe imbalance of trade and thus steady US job losses over the past years
    • China’s strategy of acquiring US technology via forceful knowledge transfer due to its point of view on markets which resulted in the blacklisting of Huawei
    • China’s intention to establish leadership over two thirds of the world’s population thus challenging US dominance leading to the election of a hawkish US president

Assessment of situation

  • The issue is deeply structural and resolution will be unlikely during Trump’s current term of service
  • Companies within impacted industries will continue experiencing negative headwinds well beyond 2019
  • US companies will gradually shift production to the US and other parts of the world as President Reagan’s hypothesis on China’s successful transition to a market economy gets invalidated
  • World splits into two distinct economic blocs
  • Chinese economy will face continued pressure given the following concerns
    • aging population
    • lack of room for further domestic growth
    • none granting of WTO market status
  • US untangles its free market economy from the Chinese centrally controlled market economy as the latter slips into recession

Related references

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Book summary: Everybody lies by Seth Stephens-Davidowitz

Signals from Search

  • What people search for is in itself a signal
  • The order of keywords in which they search is also a signal
  • Quality of google search data is better than in Facebook because
    • You are alone with no fear of being judged
    • You have an incentive to be honest

On Big data

  • the needle is still the same size but the haystack has been getting bigger
  • Be judicious by cutting down the sample size of the data to be used

Data science

  • Trust your intuition as the initial signal but verify quantitatively to avoid narrative bias
  • Correlation is most often sufficient for utilization purposes – often the explanation of why the model works comes after the fact
  • critically assess the actual data underlying the narrative. At times it might tell a very different story than narrative presented
  • Clustering of groups of people helps predicts behavior – Netflix and baseball
  • AB testing to discover causations

Social Impact

  • great business are found on:
    • secrets about nature
    • secrets about people
  • Modeling
    • Physics – utilize neat equation
    • Human behavior – probabilistically via Naive Bayes classification

Managing angry people

  • Lecturing them will provoke their anger
  • Provoking their curiousity will cause their attention to be diverted causing anger to subside

Related readings

  • Zero to one, Peter Thiel
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Book summary – The Signal and the noise

Risk versus uncertainty

  • Risk can be mathematically modeled to yield a probability
  • uncertainty cannot be mathematically modeled

Conditions for quality data

Why google’s Search data is better than Facebook profile data

  • subject feels she has privacy privacy
  • subject feels she is not judged
  • subject sees tangible benefit from being honest

The hedgehog versus the fox

  • The hedgehog approaches reality through a narrative/ideology while the fox thinks in terms of probabilities
  • The hedgehog goes very deep in an area while the fox employs multiple different models
  • The fox is a better forecaster than the hedgehog
  • The fox is more tolerant of uncertainty

Big data

  • More data does not yield better results and predictions
  • Deciding the right kind of data from the abundance available
  • To do prediction it is important to start from intuition and to keep model simple
  • qualitative data should be weighted and considered
  • Be self aware of your own biases

Prediction

  • Similarity scores – clustering in Netflix and baseball
  • Be wary of confirmation biases
  • Be wary of overfitting using small sample size – Tokyo earthquakes and global warming
  • Correlation does not equal causation
  • short hand heuristics to reduce the computational space – for example chess

Related references

  • Irrational exuberance, Robert Shiller
  • Expert political judgement, Philip E. Tetlock
  • Future shock, Alvin and Heidi Toffler
  • Principles of forecasting, J Scott Armstrong
  • Predicting the unpredictable, Hough
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Loss aversion reversion to mean anti pattern

  • Six consecutive days of price deterioration.
  • 16th May to 22nd May 2019
  • No-significant rebounds were observed during this period
  • Company reported expected losses for the forthcoming two quarters
  • There were significant concerns about ability of company to stay solvent
  • Concerns over trade war is a strong negative head wind.

 

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Post 2019 US/China Trade War companies for consideration

The following is a list of microchip related companies to consider once the dust settles

  • AVGO – Broadcom
  • NVDA – Nvidia
  • QCOM – Qualcomm
  • INTC – Intel
  • MU – Micron
  • AMD – Advanced micro devises
  • XLNX – Xilinx
  • MCHP – Microchip Technology Inc

The following is a list of Consumer technology companies to consider once the dust settles

  • WB – Weibo
  • BIDU – Baidu
  • TCHEY – Tencent
  • BABA – Alibaba
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Insights from Ilya

  • It does not pay to take on risk when the overall macro economic trend is negative.
  • When the yield curve occurs, a recession typically happens within 12-18 months
  • Bonds yield has not returned to its previous highs from its current levels of 3-4.5%
  • Stock still offers the highest rates of returns in the long term horizon
  • Shares of companies that do not produce a necessity tends to spike in late stages of a bull market
  • Portfolio allocation horizon
    • short term portion of portfolio which you will need to access within 1 to 2 years should be placed in medium term bonds
    • mid term portion of portfolio which you will need to access within 3-5 years that will likely experience at least one recession should be place partially in stocks and partially in bonds
    • long term portion of portfolio which you will need to access within 10 years that will likely experience at least a few recessions should be placed fully in stocks
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Learnings from the market today

During a trade war situation, negative news about one Chinese company listed NASDAQ or NYSE will cause negative price movement of other Chinese companies
  • 17th May 2019 – Baidu poor earnings (-16% price decline) causes Weibo share price decline (-11% price decline)
Negative news about a negative law suit outcome for a semi conductor causes negative price movement of other semi conductor companies
  • Apple evades legal claims by Qualcomm causes price decline in NVDIA (-4%) and MU (-10.6%)
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Key trading mistakes during execution

Mistakes

  1. Do not hold a position against general macro events like (Trade) Wars
    • Lesson learned: impact of loss aversion and reversion to mean is muted when trade war is occurring
  2. Don’t double down on your mistakes
    • Lesson learned: it is cheaper to admit mistake and cut losess
  3. Committing too much to a position leaving not much liquidity for later. This forces freeing up liquidity at a loss when new buying signals surface.
    • Lesson learned: it is cheaper to under allocate portfolio to a position upfront.
  4. Entering too late into a buy signal by more than 48 hours.
    • Lesson learned: it is cheaper to forget about it when you are late
  5. Entering too early into a buy signal.
    • Lesson learned: it is cheaper to figure out the support level before entering into position.
  6. Don’t enter into position when there are no buy signals.
    • Lesson learned: it is cheaper to wait for a wave than to get carried away by the anxiety that there will never be a buy signal again in this lifetime.
  7. Not verifying assumptions
    • Lesson learned: Seek evidences to challenge your own assumptions. Lessons could be learned when you dig deeper into pass records to for deeper insights.

Additional insights

  1. Sudden news about macro economic events (Donald Trump tweeting) does follow a lose aversion and reversion to mean pattern.
  2. Gradual news about macro economic events (US passing tariffs on China and banning Huawei) will have a long term negative impact.
  3. Price of REITs are:
    • relatively insensitive to trade wars
    • hyper sensitive to Federal Reserve (expected) interest rate changes
  4. Only execute loss aversion and reversion to mean trades on positions that exhibit bullish trends both at the individual stock level as well as at the SnP level.

Related references

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3rd June post effects of 13th May 2019 US/China Trade war on US markets

The following is a list of 19 companies either in the tech sector or with market capitalization above USD20 billion that experienced more than 10% drop in share price on the May, 13th 2019.   Below is the breakdown in terms of price performance on 15th May 2019.
  • 2 companies (10.5% of sample) not related to trade war
  • 2 companies (10.5% of sample) fully recovered
  • 7 companies (36.8% of sample) at least 50% recovery
  • 10 companies (52.63%) not recovered by at least 50%
Below is the breakdown in terms of price performance on 3rd June May 2019.
  • 2 companies (10.5% of sample) not related to trade war
  • 2 companies (10.5% of sample) fully recovered
  • 15 companies (52.63%) not recovered by at least 50%

Related references

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Macro economic analysis on US/China 2018/2019 Trade war

The 196 pages of Chinese goods to be taxed by the US governments are spread across 6 categories. Where US manufacturers cannot find alternative sources of supplies, price increase of end product will be expected. Based on what was observed in December. The ability of the US government to sustain the trade war is predicated upon the Feds keeping interest rate low.

Taxed categories include

  • agricultural produce
  • textiles
  • chemical compounds
  • hardware parts
  • mechanical parts
  • electronic parts
The December 2018 US market financial meltdown can be attributed to US government tariffs to reduce demand for foreign material supplies from China coupled with Feds interest rate hike to limit capital needed to boost domestic production. The trade war seems to serve three purposes:
  • Drive up demand for domestic supplies
  • To keep inflation in check the economy grows (traditionally a role played by Fed Interest Rates)
  • Keep China in check.

Related references