Markets Watch

What MSA is watching

The markets have seem to reached a consensus that the Fed will cut rates on Sep 18 yet they disagree with the magnitude of the cut. Recent remarks from Fed officials indicate that policymakers are aware of the risk from the job market but they may prefer a “slower to lower” approach considering the robustness of the US economy and the possibility of a hard landing. Some considered that a 50bps cut may be too hasty while others warn about the deterioration of the payrolls. UST market fluctuates around the short-end like 2yr which is largely impacted by FFR. US equity benchmarks lost winning streaks with the mega-caps suffered sharp decline.

  • More updates to follow after Friday’s Jackson Hole speech by Powell.

Gone but not forgotten…

Global stocks selloff during the week of Aug 5: It’s a bit of JPY, a bit of fear of US recession, and a bit of summer madness

  • unwinding JPY Carry Trade
  • the great terror looms: fear of hard-landing for US economy
  • crowded big-tech trade in the US

My two cents about the stock selloff on Aug 5:

If what my previous experience taught me about how the markets work makes sense, then here’s my two cents, I think Global Markets operate and trade on views, fueled by sentiments, and views result from assumptions.

The big take from this rout, is that there are 3 assumptions embedded so deep that they have been taken for granted by the markets practitioners for years - the key assumptions that investors across the globe were profiting from have been shaken.

In hindsight, we have: (1) the US economy is unstoppable; (2) AI will quickly revolutionize business everywhere; (3) Japan will never hike interest rates, or not enough to really matter. Indeed, they do sound too opportunistic.

Assumptions MarketReality
A hard-landing for US economy is unlikely Feeble July NFP
Bid Nvidia shares up 1,100% in less than 2 years Weaker Big Tech’s quarterly earnings
Load up on junk loans bunded into bonds or borrow JPY and invest assets paying 11% in Mexico BoJ hiked rates for the 2nd time this year

Central Bank Watch

CB Decision Date Current CCY Next
Riksbank (SEK) Aug 19 3.75% SEK
Norges Bank (NOK) Aug 15 4.5% NOK
Banxico -0.25% Aug 08 10.75% MXN Sep 26
RBA unchanged Aug 06 4.35% AUD Sep 24
Bank of England -0.25% Aug 01 5.0% GBP Sep 19
Federal Reserve unchanged July 31 5.5% USD Sep 18
Bank of Japan +0.25% July 31 0.25% JPY Sep 20
Bank of Canada -0.25% July 24 4.5% CAD Sep 04
European Central Bank unchanged July 18 4.25% EUR Sep 12

Economic Data Watch

Country InterestRate InflationRate JoblessRate
US US 5.50 3.00 4.30
Canada Canada 4.50 2.70 6.40
Mexico Mexico 10.75 5.57 2.80
China China 3.35 0.50 5.00
Japan Japan 0.25 2.80 2.50
EuroA EuroArea 4.25 2.60 6.50
UK UK 5.00 2.00 4.40

Market Data Watch

Note

This charting section is still in developing as the data server needs further calibration.

Code 
import yfinance as yf
/Users/nimbp21/.virtualenvs/r-reticulate/lib/python3.8/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020
  warnings.warn(
Code 
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime, timedelta

# Set the today variable
today = datetime.today().date()
start_date = today - timedelta(days=14)

# List of tickers
tickers = ["SPY", "USDJPY=X", "^N225", "BZ=F"]

# Create a figure and a set of subplots
fig, axs = plt.subplots(2, 2, figsize=(10, 7))
fig.suptitle('Price Changes - Last 14 Days', fontsize=16)

for ax, ticker in zip(axs.flat, tickers):
    # Fetch data
    try:
        data = yf.Ticker(ticker).history(start=start_date, end=today)
        if data.empty:
            ax.text(0.5, 0.5, f'No data for {ticker}', ha='center', va='center')
            ax.set_title(ticker)
        else:
            # Plot the closing price
            ax.plot(data.index, data['Close'], label=ticker)
            # Customize the date format on the x-axis
            ax.xaxis.set_major_formatter(mdates.DateFormatter('%b %d'))
            ax.xaxis.set_major_locator(mdates.DayLocator())
            ax.set_xlabel('Date')
            ax.set_ylabel('Closing Price')
            ax.set_title(ticker)
            ax.legend()
            ax.grid(False)
            ax.tick_params(axis='x', rotation=45)  # Rotate dates for better readability
    except Exception as e:
        ax.text(0.5, 0.5, f'Error loading data\n{e}', ha='center', va='center')
        ax.set_title(ticker)

# Adjust layout to prevent clipping
plt.tight_layout(rect=[0, 0, 1, 0.95])
plt.show()