1 Introduction & Summary

This is a performance review of a selection of tickers and is expected to be run and published on a weekly basis to help with identifying entry and/or exit opportunities in the markets.

Extraction of data is from https://finance.yahoo.com/ and the report is prepared by Irvine Udinge. The data covers 365 days from date of extraction unless explicitly mentioned otherwise.

1.1 Definition of symbols

  • HSI - Hang Seng Index. A freefloat-adjusted market-capitalization-weighted stock-market index in Hong Kong.
  • GSPC - S&P 500. A stock market index tracking the stock performance of 500 large companies listed on stock exchanges in the United States.
  • DJI - Dow Jones Industrial Average. A stock market index of 30 prominent companies listed on stock exchanges in the United States.
  • IXIC - NASDAQ Composite. A stock market index that includes almost all stocks listed on the Nasdaq stock exchange.
  • RUT - Russel 2,000. A small-cap stock market index that makes up the smallest 2,000 stocks in the Russell 3000 Index (a capitalisation-weighted stock market index that seeks to be a benchmark of the entire U.S stock market).
  • GDAXI - GER40/DAX. A stock market index consisting of the 40 major German blue chip companies trading on the Frankfurt Stock Exchange. It is a total return index.
  • FTSE - Financial Times Stock Exchange 100 Index. A share index of the 100 companies listed on the London Stock Exchange with the highest market capitalisation.
  • STOXX50E - EURO STOXX 50. A stock index of Eurozone stocks designed by the STOXX, an index provider owned by Deutsche Börse Group. The index is composed of 50 stocks from 11 countries in the Eurozone.
  • FCHI - CAC 40. A benchmark French stock market index which represents a capitalization-weighted measure of the 40 most significant stocks among the 100 largest market caps on the Euronext Paris.
  • AXJO - S&P/ASX 200. A market-capitalization weighted and float-adjusted stock market index of stocks listed on the Australian Securities Exchange.
  • N225 - Nikkei 225/Nikkei Stock Average. A stock market index for the Tokyo Stock Exchange. It has been calculated daily by the Nihon Keizai Shimbun newspaper since 1950.
  • FT5=F - E-mini FTSE China 50 Index Future, A real-time, tradable index comprising the largest 50 A Share companies by full market capitalisation of the securities listed on the Shanghai and Shenzhen stock exchanges.
  • NSEI - Nifty 50. A benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange.
  • FVX - Treasury Yield 5 Years. The yield received for investing in a US government issued treasury security that has a maturity of 5 years. The 5 Year treasury yield is used as a reference point in valuing other securities, such as corporate bonds.
  • TNX - Treasury Yield 10 Years. The yield that the government pays investors that purchase the specific security.
  • VIX - Chicago Board Options Exchange’s CBOE Volatility Index. A popular measure f the stock market’s expectation of volatility based on S&P 500 index options.

Data dates back 365 days from date of publishing - unless stated otherwise.

2 Analysis & Charts

2.1 Review of General Performance

## [1] "IRX"

2.1.1 Candlestick charts from 2007

2.1.2 SMA over the past two years

2.2 Annual performance of instruments

2.3 Assessing Volatility Through Analysing the True Range

2.3.1 Boxplots

2.3.2 Bar Charts

2.4 Analysing Comparative Performance

2.4.1 Past two year returns

2.4.2 Zooming in on Drawdowns

## $`S&P500`

## 
## $`Dow Jones`

## 
## $Nasdaq100

## 
## $Russel1k

## 
## $DAX

## 
## $FTSE100

## 
## $EURO50

## 
## $CAC40

## 
## $HangSeng

## 
## $ASX200

## 
## $Nikkei225

## 
## $Nifty50

## 
## $`5 Yr TY`

## 
## $`US Dollar`

## 
## $`Volatility Ind.`

2.5 Annualised Returns, Standard Deviation & Sharpe

Risk can be measured through assessing the volatility of returns. Sharpe allows us to create a link between the volatility and the returns from an instrument. This helps to understand the extent to which returns are generated from undertaking risk.

The formulato calculate Sharpe Ratio is as follows: Sharpe Ratio = (Rp – Rf)/ σp

The visualisation below aids in obtaining a quick understanding of the performance of the tickers under review from an annualised perspective (for the current year).

2.6 Return and Risk

To strike a balance between the risk and the returns of an instrument is crucial as this will help with matching the portfolio against the desired strategy expected to be implemented. Below is an analysis of annualised return and risk.

2.6.1 Annualised returns since 2007

### Annualised returns past two years

2.6.2 Return and risk from kurtosis and skweness

Kurtosis is a measure of how tailed the data is relative to a normal distribution. I consider any measurement above 3 in the analysis below as heavily tailed and would contain multiple outliers. Low kurtosis indicates a more uniform distribution, thereby making returns more predictable.

Skweness refers to how the data adheres to the symmetrical bell curve (normal distribution). Symmetrical distribution occurs when the mean, median and mode are all on one position. The distribution is positively skewed when the mode appears before the mean. I consider a general adherence to +/- 0.5 as acceptable skweness.

2.6.2.1 Since 2007

2.6.2.2 Over past two years

2.7 Distribution of Returns

Other than looking at the oscillation alone, we will now look at the actual return which will normally be smaller and will be computed from the Opening and Closing prices. This will be used to determine the level of volatility that can be expected when:

  • There is significant economic news; and

  • On an ordinary day.

This information can be crucial when swing trading.

2.7.1 Boxplot of returns

2.7.2 Histogram of Returns

A long tail indicates higher volatility and a short one indicates that low volatility can be expected from the instrument.

2.7.3 Q-Q Plots for the Returns

Another way of looking at the returns is to have an line that intuitively has to be adhered to.

2.8 Exploring Correlation of Returns

Almost always, correlation of the indices is based on geographic location. The US indices move in one block whilst those in the Eurozone move together especially since (as of April 2021) the Euro STOXX 50 is dominated by France (representing 36.6% of all total assets) and Germany (33.2%). Asia Pacific is usually the least volatile and Hong Kong is usually in its own league.

2.8.1 Correlation by Hierachial Ordering - longer period

2.8.2 Correlation by Hierachial Ordering - shorter period

2.9 Exploring correlation using Performance Analytics

2.10 Exploring Autocorrelation of Returns

Estimation of returns is difficult to perform. Just like white noise, the expectation is usually that there will be no guarantee of knowing which way the pendulum will swing.

2.11 Exploring daily returns

More often than not, a retracement usually occurs over an extended move by the indices. This is evidenced by lack of maintenance of a specific pattern when daily returns are plotted.