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| Field | Definition |
| Date | Last trading day of the month (YYYY-MM-DD) |
| Close | Index closing price on that date |
| High | Highest intramonth index price |
| Low | Lowest intramonth index price |
| Open | Index opening price on the first trading day of the month |
| Volume | Total shares (or contracts) traded during the month |
| Index_Name | Internal identifier for the index (e.g. FTSE_100, DAX_40, S&P_500) |
| Ticker | Exchange ticker symbol (e.g. ^GSPC for S&P 500, ^IXIC for Nasdaq) |
| Country | Country in which the index is domiciled |
| Region | Geographical region (e.g. “Europe,” “Asia-Pacific,” “North America”) |
| Continent | Continent (e.g. “Europe,” “Asia,” “Africa”) |
| Currency | Local currency code (e.g. USD, GBP, HKD) |
| Latitude | Latitude of the index’s primary exchange (for mapping) |
| Longitude | Longitude of the index’s primary exchange |
| Year | Calendar year extracted from Date |
| Quarter | Quarter of the year (1–4) in which Date falls |
| Month | Month number (1–12) |
| Week | ISO week number of the year |
| Day | Day of the month (1–31) |
| Day_of_Week | Numeric code for weekday (0 = Monday … 6 = Sunday) |
| Day_Name | Name of the weekday (“Monday,” “Tuesday,” etc.) |
| Daily_Return | (Closet/Closet−1)−1(\text{Close}_t / \text{Close}_{t-1}) – 1, the percent change from prior month’s close |
| Cumulative_Return | Total compounded return since the series start (e.g. as a multiplier or percentage) |
| MA_50 | 50-month moving average of Close, smoothing medium-term trend |
| MA_200 | 200-month moving average of Close, highlighting long-term trend |
| Volatility_10D | Standard deviation of the last 10 monthly returns (proxy for 10-period risk) |
| Volatility_30D | Standard deviation of the last 30 monthly returns |
| Normalized_Value | Index value rescaled so every series starts at the same base (e.g. 100) for percentage-based comparisons across different indices |

What Are Stock Market Indexes?
A stock market index is a benchmark that measures the performance of a specific group of stocks. These stocks are usually chosen based on:
Indexes are indicators of how a market or sector is performing and are commonly used by investors to track trends, compare performance, or invest passively via index funds.
| Weighting Type | Description | Example Index |
| Price-weighted | Stocks with higher prices influence the index more | Dow Jones Industrial Average (DJIA) |
| Market cap-weighted | Larger companies (by market cap) have more influence | S&P 500 , NASDAQ Composite |
| Equal-weighted | Every stock has the same weight regardless of size | Invesco S&P 500® Equal Weight ETF (RSP) |
| Fundamental-weighted | Based on earnings, revenue, or book value | FTSE RAFI US 1000 Index |
Index Calculation
The value of an index is computed using the formula:
Index Value = (Sum of weighted stock prices) / Divisor

| Index Name | Country/Region | Key Features |
| S&P 500® | USA | 500 large-cap U.S. companies; market cap-weighted |
| Dow Jones Industrial Average | USA | 30 blue-chip U.S. stocks; price-weighted |
| NASDAQ Composite | USA | Tech-heavy, over 3,000 stocks |
| FTSE 100 | UK | 100 largest companies on the London Stock Exchange |
| DAX 40 | Germany | 40 major German companies |
| Nikkei 225 | Japan | 225 top Japanese companies; price-weighted |
| Shanghai Composite | China | All stocks listed on the Shanghai Stock Exchange |
| Sensex | India | 30 largest companies on the Bombay Stock Exchange |
| MSCI World Index | Global | Developed market stocks from 23 countries |
| Use Case | Explanation |
| Market Snapshot | Reflects the health or performance of a market/sector |
| Benchmarking | Used by investors to compare how their portfolios are performing |
| Passive Investing | Basis for index funds and ETFs, allowing low-cost exposure |
| Economic Indicator | Often used by economists and policymakers to track economic sentiment |
If the S&P 500® rises by 1.5% today:
| Feature | Description |
| Indexes | Represent performance of a group of stocks |
| Used For | Market tracking, benchmarking, investment |
| Types | Based on weighting and selection criteria |
| Tracked By | Analysts, economists, investors worldwide |
By normalizing all index values to a base of 100 in mid-2020, performance gaps become more evident.
Normalized Performance Insights:
This normalized view confirms percentage-based outperformance and highlights where investors saw the greatest compounded growth relative to starting levels.
A comparison of cumulative returns across global indexes shows a wide divergence in performance from 2020 to 2025. Markets such as Germany’s DAX (+94%), the U.S. Nasdaq (+84%) and S&P 500 (+83%), and South Africa’s JSE Top 40 (+81%) posted robust gains, outperforming peers. In contrast, the FTSE 100 gained just 40%, while Hong Kong’s Hang Seng showed negligible progress with only a 0.6% gain over the same period.
These results reflect a mix of regional economic momentum, structural factors, and investor sentiment.
While Germany and the U.S. benefited from strong post-pandemic recoveries and technology sector growth, the Hang Seng struggled under the weight of domestic policy uncertainty and global geopolitical pressures.
The FTSE 100’s relatively flat trajectory underscores broader concerns over UK economic performance and Brexit-related fallout.
Notably, South Africa’s JSE Top 40 has demonstrated resilience despite broader emerging market volatility. It stands out for having regained and surpassed previous highs, with a relatively shallow drawdown (~17.6%) compared to Hong Kong, which experienced a ~50% peak-to-trough decline and remains far below its former levels.
Analysis of short- and long-term moving averages reveals divergent regional signals. A “golden cross” (where the 50-day moving average rises above the 200-day) typically signals bullish momentum, while a “death cross” (50-day MA below 200-day) points to a bearish outlook.
As of May 2025:
This suggests that, at present, short-term momentum favors European and South African equities, while U.S. markets show signs of consolidation or weakness. The structure of these moving average crossovers supports a narrative of regional rotation, where investor interest is shifting from U.S. to international markets.
Volatility analysis (measured as the standard deviation of 30-day returns) indicates the following:
The data confirms that Asia-Pacific remains the most turbulent region for investors, while Europe exhibits lower risk. Hong Kong’s elevated volatility reflects its exposure to both regional political uncertainty and speculative trading behavior.
Trading volume, a measure of market liquidity and investor conviction, shows stark regional variation:
Liquidity Analysis:
All index data are in local currencies. For international investors, currency fluctuations can significantly affect returns. For example:
Between 2020 and 2025, most major currencies (USD, EUR, JPY) moved within a ±5% band, limiting distortions. However, during certain months, sharp FX swings could have affected short-term performance, particularly in portfolios unhedged against currency risk.
Correlated movements in indexes suggest that sentiment travels across borders. For example:
This phenomenon, sometimes described as “sentiment contagion,” reflects how investor mood in one market can spill over into others through global fund flows and risk sentiment adjustments.
Analysis of calendar-based patterns revealed well-known seasonal trends:
For example, December and January frequently show green on monthly heatmaps across multiple countries, while June, July, and August often reflect stagnation or mild losses.
| Index Name | Annualised Return | Annualised Volatility |
| CAC 40 | 10.65% | 16.25% |
| DAX 40 | 15.89% | 16.42% |
| Dow Jones | 10.83% | 15.97% |
| EURO STOXX 50 | 13.35% | 16.80% |
| FTSE 100 | 7.58% | 11.38% |
| Hang Seng Index | 0.13% | 24.84% |
| JSE Top 40 | 13.55% | 15.32% |
| NASDAQ Composite | 14.21% | 19.25% |
| Nikkei 225 | 11.73% | 15.26% |
| S&P 500 | 14.08% | 15.54% |
From 2020 to 2025, global equity performance has diverged significantly across regions. Long-term winners like Germany and South Africa have built sustained momentum, while Hong Kong remains mired in stagnation. Technical indicators currently favor European and emerging markets over U.S. stocks, and volatility patterns support a more risk-averse stance in Asia-Pacific.
Cyclical patterns, sentiment contagion, and trading volume all reinforce the broader takeaway: while macro conditions may appear similar, local market structure, liquidity, and investor psychology continue to drive country-level differentiation.
Recommended Index: FTSE 100
Why:
So initially:
After one year, that grows by 7.58%:
Now convert back to KES under each of the three currency scenarios:
Same as GBP return because exchange rate didn’t change.
Your investment grows in GBP, but stronger KES hurts your returns when converting back.
Weaker KES amplifies your return when converting back.
Summary for Short-Term Investor
| Scenario | Ending Value (KES) | Return (%) |
| KES Unchanged | 1,076,000 | +7.6% |
| KES Appreciates 10% | 968,400 | -3.16% |
| KES Depreciates 10% | 1,183,300 | +18.3% |
NASDAQ Composite
Snp500
Recommended Index: S&P 500 or NASDAQ Composite
Why S&P 500:
Why NASDAQ:
So initially:
After one year:
Now convert back to KES under each of the three currency scenarios:
1. KES Remains Unchanged (129.40)
Same as USD return since the exchange rate is unchanged.
2. KES Appreciates by 10% (New Rate = 116.46)
KES strength cuts into your USD gains.
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3. KES Depreciates by 10% (New Rate = 142.34)
Weakening KES significantly boosts your returns.
Summary for Long-Term Investor (S&P 500)
| Scenario | Ending Value (KES) | Return (%) |
| KES Unchanged | 1,141,056 | +14.1% |
| KES Appreciates 10% | 1,026,919 | +2.7% |
| KES Depreciates 10% | 1,255,200 | +25.5% |
Recommended Index: Hang Seng Index
Why:
So initially:
After one year:
Now convert back to KES under each of the three currency scenarios:
1. KES Remains Unchanged (16.57)
Flat result—neither the market nor the currency moved meaningfully.
2. KES Appreciates by 10% (New Rate = 14.913)
KES strength wipes out any gains, leading to a near 10% loss.
3. KES Depreciates by 10% (New Rate = 18.227)
Even tiny gains in HKD get amplified when the KES weakens.
Summary for Trader (Hang Seng Index)
| Scenario | Ending Value (KES) | Return (%) |
| KES Unchanged | 1,000,813 | +0.08% |
| KES Appreciates 10% | 901,176 | –9.88% |
| KES Depreciates 10% | 1,101,330 | +10.13% |
| Investor Type | Recommended Index | Rationale |
| Short-Term Investor | FTSE 100 | Low volatility, capital stability |
| Long-Term Investor | S&P 500 / NASDAQ | Strong long-term returns, broad exposure |
| Trader | Hang Seng Index | High volatility = more trading opportunities |

(S&P 500 index Example)
The simplest route is an ETF (exchange-traded fund), which bundles the 500 largest U.S. companies in a single ticker.
You need an online platform that:
Recommended brokers:
Compare each on trading fees, deposit/withdrawal charges, and platform usability.
S&P 500 ETFs distribute dividends roughly every quarter. You can:
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