Stock price variance
through September 30, 2022
Variance of daily price changes has now begin to rise again. The top of the class of stocks, those with more liquidity and market capitalization have increases in stock price variance. There was a period of stability but now we are rising again. The academic literature would say that this is not good for stock prices, and requires them to fall. The problem is that higher variance and uncertainty requires a higher future expected return. This is the situation with individual stocks (both those with a profit and those without).
We do see the variance 'cost' of investing in profitless or money losing companies increasing further. It is now more than 3x more risky to hold a stock in a company that loses money. This ratio was closer to 2.5x in the past.
Finally, the riskiness of the SPY (the S&P 500 Index ETF) is elevated but has stabilized. This makes it slightly better relative to individual stocks. This is what we would expect to see. We expect the market capitalization weighted SPY to have a better risk-return than a passive set of equally weighted stocks. This is true when comparing the SPY against money losing companies but not true (at least not to a significant level) when comparing SPY to profitable firms in the aggregate.
We have seen significantly elevated price variance in the S&P 500 Index ETF, and the two populations of stocks that we track, since the beginning of the bear market. Greater variability in share prices is correlated to lower stock prices at first glance.
We also see that stocks of companies that lose money (negative net income) have significantly more adjusted closing price variance than stocks in companies that make a profit (positive net income). The expected return in the market for stocks of companies that lose money is higher, but that extra return comes with a very high 'price tag' in price variance. We see this in our own personal portfolio where our one speculative stock trades with significantly more volatility as 'believers' come on board and exit.
These findings are based on the full population of US-listed stocks that pass data validation, and are held equally, in our model. That diversification of over 1,000 stocks should remove stock-specific shocks and focus on population statistics.
Why is the S&P 500 Index ETF also seeing great variance? We hypothesize that this is caused by a lack of liquidity and an increase in speculative bets on the overall indices. It is easier to bet against the market by betting against an index (with a futures contract or option with massive leverage) as opposed to betting against hundreds of stocks simultaneously. It is not impossible, as there are those who arbitrage these two investments, but it is simpler and easier to trade one instrument than 1,000 and we believe large institutional investors do just this with the SPY, the ES_F and other index bets.
Our model looks at two US company populations: positive and negative net income. Our 'control set' is the S&P 500 Index ETF.
1. US-listed stocks with positive net income.
May 17: 1.4 x 10-4
May 20: 1.4 x 10-4
May 31: 1.4 x 10-4
June 1 : 1.4 x 10-4
June 8: 1.4 x 10-4
June 10: 1.5 x 10-4 (up a tick). Expected return 4.75%; 2,013 stocks (dropped significantly)
Min & max expected return 0.01, 0.15 (rounded to 2 decimal places)
June 24: 1.6 x 10-4 (up a tick)
July 6: 1.6 x 10-4
July 11: 2004 stocks (profitable, removed test for positive cash flow, dropped floor cap to $5M)
July 11: 1.9 x 10-4 (up three ticks)
July 26: 1.9 x 10-4 (2,010 stocks)
July 27: 1.9 x 10-4 (2,014 stocks)
July 29: 1.9 x 10-4 (2,014 stocks)
August 7: 1.9 x 10-4 (2,020 stocks)
August 11: 1.8 x 10-4 (2,165 stocks)
Aug 12: 1.9 x 10-4
Aug 19: 1.9 x 10-4
Aug 25: 1.9 x 10-4 (2,141 stocks)
Aug 29: 1.9 x 10-4 (2,156 stocks)
Sept 2: 2.1 x 10-4 (1,722 stocks) - tighter data validation to select higher liquidity stocks*.
Sept 6: 2.0 x 10-4 (1,641 stocks) - even tighter data validation
Sep 11: 2.1 x 10-4 (1,568 stocks) - tightened data validation further (to increase liquidity)
Sep 14: 2.2 x 10-4 (1,564 stocks) (up a tick)
Sept 15: 2.2 x 10-4 (1,564 stocks)
Sept 22: 2.2 x 10-4 (1,554 stocks)
Sept 23: 2.1 x 10-4 (1,267 stocks) - increased minimum market capitalization and minimum daily traded volume.
Sept 27: 2.1 x 10-4 (1,269 stocks)
Sept 30: 2.1 x 10-4 (1,272 stocks) - list of stocks is growing (no change to underlying data validation).
2. US-listed stocks with negative net income.
May 17: 4.3 x 10-4
May 20: 4.2 x 10-4
May 31: 4.2 x 10-4
June 1 : 4.2 x 10-4
June 8: 4.3 x 10-4 (it finally went up a tick)
June 10: 4.4 x 10-4 (up another tick)
Expected return: 6.24%
1,501 stocks (increased significantly)
Min & max expected return 0.0109, 0.1454
June 24: 4.7 x 10-4 (up three ticks)
1,505 stocks (negative net income - global companies listed on US stock exchanges):
July 6: 4.8 x 10-4 (up a tick)
Expected return of the full set of 1,505 stocks: 6.11%
July 11: 1,444 stocks (unprofitable, floor cap $5M)
July 11: 5.3 x 10-4 (up five ticks)
July 26: 5.4 x 10-4 (up one tick - 1,440 stocks)
July 27: 5.5 x 10-4 (up one tick - 1,489 stocks)
July 29: 5.4 x 10-4 (down a tick - 1,493 stocks)
August 7: 5.5 x 10-4 (up a tick - 1,492 stocks)
August 11: 5.2 x 10-4 (1,658 stocks)
Aug 12: 5.2 x 10-4
Aug 19: 5.3 x 10-4
Aug 25: 5.2 x 10-4 (1,672 stocks)
Aug 29: 5.3 x 10-4 (1,664 stocks)
Sept 2: 5.7 x 10-4 (1,197 stocks) - we tightened up the data validation (these are higher liquidity stocks)
Sep 6: Did not run
Sep 11: 6.6 x 10-4 (871 stocks) - We tightened up data validation further (more liquidity required)
Sept 14: 6.1 x 10-4 (455 stocks) - we tightened up data validation (required a $1B market cap minimum).
Sept 15: 6.1 x 10-4 (456 stocks)
Sept 22: 6.0 x 10-4 (429 stocks) - down a tick
Sept 23: 6.0 x 10-4 (423 stocks)
Sept 27: 6.1 x 10-4 (419 stocks) - Fewer stocks as we maintain an aggressive market cap floor (maybe stocks are falling below)?
Sept 30: 6.2 x 10-4 (430 stocks) - more stocks with no change to underlying data validation.
3. $SPY, or the S&P 500 Index ETF:
May 17: 1.2 x 10-4
May 20: 1.3 x 10-4
May 31: 1.3 x 10-4
June 1 : 1.3 x 10-4
June 8: 1.3 x 10-4
June 10: 1.4 x 10-4 (up a tick)
June 24: 1.6 x 10-4 (up two ticks)
2,040 stocks (US companies, US listed, with positive net income and positive CFFO):
July 6: 1.6 x 10-4
Expected return of the full set of 2,040 tickers: 4.75%
July 11: 1.6 x 10-4
July 26: 1.6 x 10-4
July 27: 1.6 x 10-4
July 29: 1.7 x 10-4 (up a tick)
August 7: 1.7 x 10-4
Aug 10: 1.7 x 10-4
Aug 12: 1.7 x 10-4
Aug 19: 1.7 x 10-4
Aug 25: 1.7 x 10-4
Aug 29: 1.8 x 10-4
Sept 2: 1.8 x 10-4
Sept 6: 1.8 x 10-4
Sept 11: 1.8 x 10-4
Sept 14: 1.9 x 10-4 (up a tick)
Sept 15: 1.9 x 10-4
Sept 22: 1.9 x 10-4
Sept 23: 1.9 x 10-4
Sept 27: 1.9 x 10-4
Sept 30: 1.9 x 10-4
Conclusion: The $SPY has the lowest price variance, then companies with positive net income, then companies with negative net income. In today's market, variances are rising. However, the SPY is increasing in variance while the overall groupings of stocks (highly diversified portfolios) are maintaining their variance levels.
Assumptions: portfolios are evenly weighted, for 253 trading days, using adjusted closing stock prices.
Note (*): We tightened data validation into September 2022 to help us select stocks that can be easily purchased and sold for our Chicago Quantum Net Score model portfolio / managed accounts / hedge fund. This is currently only paper-traded as we work through the proper formulation, methods and processes. We required a higher share price, and more shares traded. There is no market capitalization floor.
We do see the variance 'cost' of investing in profitless or money losing companies increasing further. It is now more than 3x more risky to hold a stock in a company that loses money. This ratio was closer to 2.5x in the past.
Finally, the riskiness of the SPY (the S&P 500 Index ETF) is elevated but has stabilized. This makes it slightly better relative to individual stocks. This is what we would expect to see. We expect the market capitalization weighted SPY to have a better risk-return than a passive set of equally weighted stocks. This is true when comparing the SPY against money losing companies but not true (at least not to a significant level) when comparing SPY to profitable firms in the aggregate.
We have seen significantly elevated price variance in the S&P 500 Index ETF, and the two populations of stocks that we track, since the beginning of the bear market. Greater variability in share prices is correlated to lower stock prices at first glance.
We also see that stocks of companies that lose money (negative net income) have significantly more adjusted closing price variance than stocks in companies that make a profit (positive net income). The expected return in the market for stocks of companies that lose money is higher, but that extra return comes with a very high 'price tag' in price variance. We see this in our own personal portfolio where our one speculative stock trades with significantly more volatility as 'believers' come on board and exit.
These findings are based on the full population of US-listed stocks that pass data validation, and are held equally, in our model. That diversification of over 1,000 stocks should remove stock-specific shocks and focus on population statistics.
Why is the S&P 500 Index ETF also seeing great variance? We hypothesize that this is caused by a lack of liquidity and an increase in speculative bets on the overall indices. It is easier to bet against the market by betting against an index (with a futures contract or option with massive leverage) as opposed to betting against hundreds of stocks simultaneously. It is not impossible, as there are those who arbitrage these two investments, but it is simpler and easier to trade one instrument than 1,000 and we believe large institutional investors do just this with the SPY, the ES_F and other index bets.
Our model looks at two US company populations: positive and negative net income. Our 'control set' is the S&P 500 Index ETF.
1. US-listed stocks with positive net income.
May 17: 1.4 x 10-4
May 20: 1.4 x 10-4
May 31: 1.4 x 10-4
June 1 : 1.4 x 10-4
June 8: 1.4 x 10-4
June 10: 1.5 x 10-4 (up a tick). Expected return 4.75%; 2,013 stocks (dropped significantly)
Min & max expected return 0.01, 0.15 (rounded to 2 decimal places)
June 24: 1.6 x 10-4 (up a tick)
July 6: 1.6 x 10-4
July 11: 2004 stocks (profitable, removed test for positive cash flow, dropped floor cap to $5M)
July 11: 1.9 x 10-4 (up three ticks)
July 26: 1.9 x 10-4 (2,010 stocks)
July 27: 1.9 x 10-4 (2,014 stocks)
July 29: 1.9 x 10-4 (2,014 stocks)
August 7: 1.9 x 10-4 (2,020 stocks)
August 11: 1.8 x 10-4 (2,165 stocks)
Aug 12: 1.9 x 10-4
Aug 19: 1.9 x 10-4
Aug 25: 1.9 x 10-4 (2,141 stocks)
Aug 29: 1.9 x 10-4 (2,156 stocks)
Sept 2: 2.1 x 10-4 (1,722 stocks) - tighter data validation to select higher liquidity stocks*.
Sept 6: 2.0 x 10-4 (1,641 stocks) - even tighter data validation
Sep 11: 2.1 x 10-4 (1,568 stocks) - tightened data validation further (to increase liquidity)
Sep 14: 2.2 x 10-4 (1,564 stocks) (up a tick)
Sept 15: 2.2 x 10-4 (1,564 stocks)
Sept 22: 2.2 x 10-4 (1,554 stocks)
Sept 23: 2.1 x 10-4 (1,267 stocks) - increased minimum market capitalization and minimum daily traded volume.
Sept 27: 2.1 x 10-4 (1,269 stocks)
Sept 30: 2.1 x 10-4 (1,272 stocks) - list of stocks is growing (no change to underlying data validation).
2. US-listed stocks with negative net income.
May 17: 4.3 x 10-4
May 20: 4.2 x 10-4
May 31: 4.2 x 10-4
June 1 : 4.2 x 10-4
June 8: 4.3 x 10-4 (it finally went up a tick)
June 10: 4.4 x 10-4 (up another tick)
Expected return: 6.24%
1,501 stocks (increased significantly)
Min & max expected return 0.0109, 0.1454
June 24: 4.7 x 10-4 (up three ticks)
1,505 stocks (negative net income - global companies listed on US stock exchanges):
July 6: 4.8 x 10-4 (up a tick)
Expected return of the full set of 1,505 stocks: 6.11%
July 11: 1,444 stocks (unprofitable, floor cap $5M)
July 11: 5.3 x 10-4 (up five ticks)
July 26: 5.4 x 10-4 (up one tick - 1,440 stocks)
July 27: 5.5 x 10-4 (up one tick - 1,489 stocks)
July 29: 5.4 x 10-4 (down a tick - 1,493 stocks)
August 7: 5.5 x 10-4 (up a tick - 1,492 stocks)
August 11: 5.2 x 10-4 (1,658 stocks)
Aug 12: 5.2 x 10-4
Aug 19: 5.3 x 10-4
Aug 25: 5.2 x 10-4 (1,672 stocks)
Aug 29: 5.3 x 10-4 (1,664 stocks)
Sept 2: 5.7 x 10-4 (1,197 stocks) - we tightened up the data validation (these are higher liquidity stocks)
Sep 6: Did not run
Sep 11: 6.6 x 10-4 (871 stocks) - We tightened up data validation further (more liquidity required)
Sept 14: 6.1 x 10-4 (455 stocks) - we tightened up data validation (required a $1B market cap minimum).
Sept 15: 6.1 x 10-4 (456 stocks)
Sept 22: 6.0 x 10-4 (429 stocks) - down a tick
Sept 23: 6.0 x 10-4 (423 stocks)
Sept 27: 6.1 x 10-4 (419 stocks) - Fewer stocks as we maintain an aggressive market cap floor (maybe stocks are falling below)?
Sept 30: 6.2 x 10-4 (430 stocks) - more stocks with no change to underlying data validation.
3. $SPY, or the S&P 500 Index ETF:
May 17: 1.2 x 10-4
May 20: 1.3 x 10-4
May 31: 1.3 x 10-4
June 1 : 1.3 x 10-4
June 8: 1.3 x 10-4
June 10: 1.4 x 10-4 (up a tick)
June 24: 1.6 x 10-4 (up two ticks)
2,040 stocks (US companies, US listed, with positive net income and positive CFFO):
July 6: 1.6 x 10-4
Expected return of the full set of 2,040 tickers: 4.75%
July 11: 1.6 x 10-4
July 26: 1.6 x 10-4
July 27: 1.6 x 10-4
July 29: 1.7 x 10-4 (up a tick)
August 7: 1.7 x 10-4
Aug 10: 1.7 x 10-4
Aug 12: 1.7 x 10-4
Aug 19: 1.7 x 10-4
Aug 25: 1.7 x 10-4
Aug 29: 1.8 x 10-4
Sept 2: 1.8 x 10-4
Sept 6: 1.8 x 10-4
Sept 11: 1.8 x 10-4
Sept 14: 1.9 x 10-4 (up a tick)
Sept 15: 1.9 x 10-4
Sept 22: 1.9 x 10-4
Sept 23: 1.9 x 10-4
Sept 27: 1.9 x 10-4
Sept 30: 1.9 x 10-4
Conclusion: The $SPY has the lowest price variance, then companies with positive net income, then companies with negative net income. In today's market, variances are rising. However, the SPY is increasing in variance while the overall groupings of stocks (highly diversified portfolios) are maintaining their variance levels.
Assumptions: portfolios are evenly weighted, for 253 trading days, using adjusted closing stock prices.
Note (*): We tightened data validation into September 2022 to help us select stocks that can be easily purchased and sold for our Chicago Quantum Net Score model portfolio / managed accounts / hedge fund. This is currently only paper-traded as we work through the proper formulation, methods and processes. We required a higher share price, and more shares traded. There is no market capitalization floor.
What this data means to us is that regardless of market conditions, stocks of companies that are profitable (positive net income) and as of May 20, 2022 also have positive cash flow from operations have lower daily price variance than stocks of companies with negative net income.
R&D readout:
— Chicago Quantum (@chicago_quantum) May 23, 2022
New: From May 16 to May 20 annual closing price variance increased for the S&P 500 Index ETF while it decreased for two large sets of individual stocks, held evenly.
The S&P 500 has become more volatile.https://t.co/5ADw2v5KMn pic.twitter.com/a2wEMRPBfT
Thank you goes to Finviz, Yahoo Finance and Intrinio.