| 8/14/2018 | 4 |
| 8/15/2018 | -15.75 |
| 8/16/2018 | 3.25 |
| 8/20/2018 | -3.25 |
| 8/21/2018 | -5.75 |
| 8/24/2018 | 4.75 |
| 8/27/2018 | 4.25 |
| 8/28/2018 | 0.5 |
| 8/30/2018 | -3.5 |
| Total: | -11.5 |
Starting March, Medved's proprietary algorithm made 95 /ES points.
Thursday, August 30, 2018
-$600, Day Trading Algorithm
Friday, August 24, 2018
-$6,280 #soybean
according to the plan. The lesson here is - don't increase the size of a losing position.
Soybean Naked Put
New Entry
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type |
| 8/24/2018 9:38 | SINGLE | SELL | -1 | TO OPEN | /ZSX8 1/50 NOV 18 | /OZSX8 | 800 | PUT | 8.125 | 8.125 | LMT |
My old position will be closed later today ; the expected loss is ~ $6,000.
Wednesday, August 22, 2018
Leverage Using The Kelly Criterion
I will start this post by reminding that trading with leverage carries significant risk. Day traders use leverage to win big, however, usually they lose big and end up in misery To avoid this fate please read"Why Day Traders Lose Money".
This post is about the algorithmic use of leverage in day trading. The goal is to optimize growth of the trading capital. The related problem is tossing a favorable coin (binominal game). The known solution to favorable binomial games is The Kelly criterion. Kelly's solution involves a mathematical idealization that the capital can be dived infinitely, i.e. an infinitesimally small bet is possible which is not the case in real trading. In this post, an example of how Kelly can be used to control trading SP500 Emini futures is provided.
Part II of Statistical Mechanics of Algorithmic Day Trading describes a generic algorithm for trading SP500 which ensures a positive expectation of return. Averaged over years 2007 to 2017 this algorithm has win ratio w = 0.38 and payout p= 2.7. Kelly is given by k = w-(1-w)/p = 0.15. Thus, for the optimal grows of the trading capital, the bot has to risk f, 0.15, fraction of the capital. Recall that the bot uses 1/4 of daily Standard Deviation of SP500 as the stop loss. Accordingly, to start trading one Emini contract it is necessary to have $280= 1/4*1.25%*SP500*50 as the minimal bet and $280/k=$1800 as the initial trading capital at the beginning of 2007. The actual capital used to start the simulation was $5000 which is about 3x of the precalculated starting capital. The two goals were achieved by this increase: 1) to decrease the volatility of the trading capital; 2) to allow up to 66% loss of the capital while maintaining f < k. Now the algorithm is really simple:
if (f < k/6) number of contracts = number of contracts* 2;
if (f > k/2) number of contracts = number of contracts / 2;
The result of the trading from the long side ($5,000 to $5,000,000 in about two years) is shown below.
DISCLAIMER
The presented here results are a theoretical study which was conducted out of curiosity. The algorithms described here are for entertainment only.
Part II of Statistical Mechanics of Algorithmic Day Trading describes a generic algorithm for trading SP500 which ensures a positive expectation of return. Averaged over years 2007 to 2017 this algorithm has win ratio w = 0.38 and payout p= 2.7. Kelly is given by k = w-(1-w)/p = 0.15. Thus, for the optimal grows of the trading capital, the bot has to risk f, 0.15, fraction of the capital. Recall that the bot uses 1/4 of daily Standard Deviation of SP500 as the stop loss. Accordingly, to start trading one Emini contract it is necessary to have $280= 1/4*1.25%*SP500*50 as the minimal bet and $280/k=$1800 as the initial trading capital at the beginning of 2007. The actual capital used to start the simulation was $5000 which is about 3x of the precalculated starting capital. The two goals were achieved by this increase: 1) to decrease the volatility of the trading capital; 2) to allow up to 66% loss of the capital while maintaining f < k. Now the algorithm is really simple:
if (f < k/6) number of contracts = number of contracts* 2;
if (f > k/2) number of contracts = number of contracts / 2;
The result of the trading from the long side ($5,000 to $5,000,000 in about two years) is shown below.
DISCLAIMER
The presented here results are a theoretical study which was conducted out of curiosity. The algorithms described here are for entertainment only.
Sunday, August 19, 2018
Mathematics behind of "Why Day Traders Lose Money"
Mathematical statistics explains three major reasons behind the frustrating reality that nearly all day traders lose money.
1. Instead of "cut your losses early and let your winners run" a trader usually is inclined to "take the profit early and let the losers run". This type of behavior is dictated by emotions while statistical analysis showed that taking profit early leads to a negative expectation. "Let the losers run and averaging losers" in day trading is a recipe of "how to lose your deposit quick".
2. The second reason has to deal with the mathematical fact that for a trader who has a limited capital having a strategy with a positive expectation is a necessary condition to win but it is not a sufficient one. Proper position sizing is required to be a profitable trader.
Let us describe the problem in simple terms. As I posted earlier, day trading can be approximated by a toss of a biased coin. Now imagine that a trader has $1000 and knows a strategy equal to a coin biased as follows - 2/3 heads and 1/3 tails. If this trader every time goes all in on heads than, at some point, all wins and the initial $1000 will be lost. There is a limit to the fraction of the capital this trader can bet on a single toss to avoid the ruin and there is the optimal bet which allows growing the capital with the fastest rate. The mathematical solution to this problem is known as the Kelly criterion. For the coin used in the example above, the Kelly gives 2/3-1/3=1/3 as the optimal fraction of the capital to bet. This solution involves a mathematical idealization that the capital can be dived as many times as it requires and an infinitesimally small bet is possible. Unfortunately, unless a trader has enough money to start with say 100 emini contracts, the Kelly criterion can't be used directly by a small-scale day trader. However, this criterion still can be used to prevent a day trading strategy from running into a ruin.
To summarize, the problem of the optimal bet in the leveraged trading on time frames with the quasi-normal distribution of the return (day or shorter time frames) is still, at least to me, an open question.
I will try to look into this problem.
Update: Leveraged Trading Using The Kelly Criterion.
3. The third reason is the cost of trading which includes trading fees and a slippage. The quasi-normal distribution of the daily return results in close to zero expectation of trading. That is many wins and losses eventually just cancel each other while, as time passes by, the cost of trading steadily adds to the loss. For this reason, many quant strategies that look good on paper do not deliver in real life. Here one has to :
a) daytrade using only liquid trading instruments;
b) choose a broker with a better fee structure;
c) use the realistic cost of trading in calculating the expected return of a trading model.
Let us describe the problem in simple terms. As I posted earlier, day trading can be approximated by a toss of a biased coin. Now imagine that a trader has $1000 and knows a strategy equal to a coin biased as follows - 2/3 heads and 1/3 tails. If this trader every time goes all in on heads than, at some point, all wins and the initial $1000 will be lost. There is a limit to the fraction of the capital this trader can bet on a single toss to avoid the ruin and there is the optimal bet which allows growing the capital with the fastest rate. The mathematical solution to this problem is known as the Kelly criterion. For the coin used in the example above, the Kelly gives 2/3-1/3=1/3 as the optimal fraction of the capital to bet. This solution involves a mathematical idealization that the capital can be dived as many times as it requires and an infinitesimally small bet is possible. Unfortunately, unless a trader has enough money to start with say 100 emini contracts, the Kelly criterion can't be used directly by a small-scale day trader. However, this criterion still can be used to prevent a day trading strategy from running into a ruin.
To summarize, the problem of the optimal bet in the leveraged trading on time frames with the quasi-normal distribution of the return (day or shorter time frames) is still, at least to me, an open question.
I will try to look into this problem.
Update: Leveraged Trading Using The Kelly Criterion.
3. The third reason is the cost of trading which includes trading fees and a slippage. The quasi-normal distribution of the daily return results in close to zero expectation of trading. That is many wins and losses eventually just cancel each other while, as time passes by, the cost of trading steadily adds to the loss. For this reason, many quant strategies that look good on paper do not deliver in real life. Here one has to :
a) daytrade using only liquid trading instruments;
b) choose a broker with a better fee structure;
c) use the realistic cost of trading in calculating the expected return of a trading model.
Friday, August 17, 2018
Take Profit & White Swans
INTRODUCTION
The probability distribution of SP500 daily return was calculated and posted in Part I. The calculations showed that the Efficient Market Hypothesis is a good approximation, i.e. most of the time the daily return of SPX index is a variable with close to zero expectation which equates day trading to gambling against a house. The house has the statistical advantage due to the trading fees. In Part II, it was shown that both for longs and shorts a positive expectation can be achieved using "cut your losses early and let your winners run" approach.
On algorithmic level this approach was formulated as follows:
1. Every trading day: if no position open SPX position at the close of the trading session;
2. Next day: if return < StopLoss than close the position.
When the only parameter in this algorithm (StopLoss) is optimized the algorithm is expected to outperform the total return of SP500 (see Part II). Here we modified the algorithm by introducing the TakeProfit variable.
ALGORITHM
1. Every trading day: if no position open SPX position at the close of the trading session;
2. Next day: if ( return < StopLoss ) { close the position}
else{
if ( return > TakeProfit ) {close the position}
}
Based on the results in Part II the StopLoss variable wass set as follows:
StopLoss = 1/4*StandardDeviation,
The TakeProfit variable was varied using the following formula:
TakeProfit = x*StandardDeviation.
The calculated return averaged over years 2007 to 2017 is shown below.
Keep in mind that historical Standard Deviation of SPX index is about 1.25%. The result means that taking profit before 1.25% is expected to decrease the long-term return of the algorithm almost 4 times for shorts and 2 times for longs. Moreover, taking profit before 3 SD still significantly decreases the performance.
BLACK & WHITE SWANS
Let us simplify Swan definition to a session close with an abnormal daily return. For example, the normal distribution with the mean and the standard deviation of SPX index predicts 24 days (since 1950) with the daily return 3 SD (3.75% ) or more. There were 102 days when SP500 printed 3.75% or more. For a 10x leverage day trader, a 3 SD move against the position is a Black Swan by any means. The Black Swan side of the distribution is taken care of by "cut your losses early" part of the algorithm. At the same time "let your winners run" part accumulates White Swan events providing that the Take Profit parameter is large enough.
CONCLUSIONS
In algorithmic day trading, the take profit parameter has to be 3 or more standard deviations.
Taking profit early - less than 1 SD - results in day trading with a negative expectation.
On algorithmic level this approach was formulated as follows:
1. Every trading day: if no position open SPX position at the close of the trading session;
2. Next day: if return < StopLoss than close the position.
When the only parameter in this algorithm (StopLoss) is optimized the algorithm is expected to outperform the total return of SP500 (see Part II). Here we modified the algorithm by introducing the TakeProfit variable.
ALGORITHM
1. Every trading day: if no position open SPX position at the close of the trading session;
2. Next day: if ( return < StopLoss ) { close the position}
else{
if ( return > TakeProfit ) {close the position}
}
Based on the results in Part II the StopLoss variable wass set as follows:
StopLoss = 1/4*StandardDeviation,
The TakeProfit variable was varied using the following formula:
TakeProfit = x*StandardDeviation.
The calculated return averaged over years 2007 to 2017 is shown below.
Keep in mind that historical Standard Deviation of SPX index is about 1.25%. The result means that taking profit before 1.25% is expected to decrease the long-term return of the algorithm almost 4 times for shorts and 2 times for longs. Moreover, taking profit before 3 SD still significantly decreases the performance.
BLACK & WHITE SWANS
Let us simplify Swan definition to a session close with an abnormal daily return. For example, the normal distribution with the mean and the standard deviation of SPX index predicts 24 days (since 1950) with the daily return 3 SD (3.75% ) or more. There were 102 days when SP500 printed 3.75% or more. For a 10x leverage day trader, a 3 SD move against the position is a Black Swan by any means. The Black Swan side of the distribution is taken care of by "cut your losses early" part of the algorithm. At the same time "let your winners run" part accumulates White Swan events providing that the Take Profit parameter is large enough.
CONCLUSIONS
In algorithmic day trading, the take profit parameter has to be 3 or more standard deviations.
Taking profit early - less than 1 SD - results in day trading with a negative expectation.
Generic Algorithm of Day Trading
INTRODUCTION
In Part I, the probability distribution (density) of SP500 daily return was calculated. It was shown that a directional day trade is not much different from a toss of a fair coin - 0.47 shorts, 0.53 longs. At best a directional daytrader has a close to zero expected value of return. It can be said that the ensemble of the directional daytraders exists only to generate trading fees while their wins and losses eventually cancel each other.
To make day trading profitable one needs to shift the probability distribution to have a positive expected value of return. The figure below demonstrates how the proverbial "cut your losses early and let your winners run" can be tested in a quantitative fashion. I believe that this is how instead of fear of uncertainty one acquires a conviction.
ALGORITHM
1. Every trading day: if no position open SPX position at the close of the trading session;
2. Next day: if return < StopLoss than close the position.
The only parameter in this algorithm is the value of StopLoss. Let us choose this parameter as follows:
StopLoss = x*StandardDeviation
In simple words, Standard Deviation characterizes the width of the probability distribution (for example, in normal distribution a chance of going beyond 2*StandardDeviation is about 5%). Using SPX historical (see Part I) one can calculate that 1.25% is Standard Deviation for the probability distribution of SPX daily returns expressed in %,
The results of the algorithmic trading from the long side (the cost of trading was set to 0.01%) were estimated for x={1, 1/2, 1/4} and are shown below:
The table below shows more details for x =1/4:
The last column of the table above shows the difference between the return of the algorithm and the total return of SPY.
One can envision that the algorithm should be fine for trading from the short side as well. The table below shows the result for x=1/4 and trading from the short side:
One can envision that the algorithm should be fine for trading from the short side as well. The table below shows the result for x=1/4 and trading from the short side:
CONCLUSIONS
The results presented here indicate that directional betting in day trading is of no importance.
In fact, the best result is achieved when the proposed algorithm is used simultaneously both from the long and short sides.
Managing losses based on the width of the probability distribution is the key to expect profit when trades will be averaged over.
The optimized "cut your losses early and let your winners run" approach should be a generic part of any trading algorithm on the time frames with the symmetrical or quasi-symmetrical distribution of returns.
DISCLAIMER
The presented here results are a theoretical study which was conducted out of curiosity. The algorithm described here can't be used as a guide for real trading.
There could be significant differences, especially at the open, in the published values of the SPX index and the tape values of Emini futures or SPY ETF. Consequently, the presented results are not directly applicable to Emini/SPY.
P.S.
Hope this reading was helpful for your trading comprehension. Part III will be about swan-like events. Probably you have noticed that the years 2008 & 2009 stand apart in the performance tables.
Finally, after day job hours, I develop real trading algorithms.
The results presented here indicate that directional betting in day trading is of no importance.
In fact, the best result is achieved when the proposed algorithm is used simultaneously both from the long and short sides.
Managing losses based on the width of the probability distribution is the key to expect profit when trades will be averaged over.
The optimized "cut your losses early and let your winners run" approach should be a generic part of any trading algorithm on the time frames with the symmetrical or quasi-symmetrical distribution of returns.
DISCLAIMER
The presented here results are a theoretical study which was conducted out of curiosity. The algorithm described here can't be used as a guide for real trading.
There could be significant differences, especially at the open, in the published values of the SPX index and the tape values of Emini futures or SPY ETF. Consequently, the presented results are not directly applicable to Emini/SPY.
P.S.
Hope this reading was helpful for your trading comprehension. Part III will be about swan-like events. Probably you have noticed that the years 2008 & 2009 stand apart in the performance tables.
Finally, after day job hours, I develop real trading algorithms.
Probability Distribution of The Daily Return
“Number rules the universe.”― Pythagoras
Introduction
A reader will find out that Statistical Mechanics of Day Trading doesn't use Price Patterns and Technical Analysis as a way to describe the price behavior. A human being in a natural environment is rewarded for pattern recognition skill as it helps to discover the relationship between cause and effect. Hence the psychological expectation that a price pattern (cause) - price action (effect) relationship does exist. This expectation is a trap, many traders look for the Holy Grail in the realm of TA with a great persistence but nearly always end up in fear and distress. These emotions - Fear of Missing Out (FOMO), Fear of Uncertainty and Destruction (FUD) - can be avoided altogether when instead of the psychological expectation trading is based on the mathematical expectation. The probability distribution of the daily return of SP500 is presented in this part of Statistical Mechanics of Day Trading. It was shown that day trading of SP500 is similar to a coin toss which slightly favors betting from the long side.
Probability Distribution of the daily return of SP500 index.
SP500 historical data were taken from finance.yahoo.com. Since Jan. 3, 1950 till Jul. 13,2018 there were 17,254 trading days. To obtain the probability distribution (the probability density of a daily return, p(r)), the histogram of the daily returns in % was calculated and normalized by dividing over 17,362. Figures 1 to 3 show the result. Figure 1 shows the major part of the distribution. Figures 2 and 3 show rare events - tails or black & white swans - that SP500 experienced since 1950.
Figure 1.
The maximum of p(r) is around 0.2% which reflects SP500's tendency to be in a bull market.
Figure 2.
Introduction
A reader will find out that Statistical Mechanics of Day Trading doesn't use Price Patterns and Technical Analysis as a way to describe the price behavior. A human being in a natural environment is rewarded for pattern recognition skill as it helps to discover the relationship between cause and effect. Hence the psychological expectation that a price pattern (cause) - price action (effect) relationship does exist. This expectation is a trap, many traders look for the Holy Grail in the realm of TA with a great persistence but nearly always end up in fear and distress. These emotions - Fear of Missing Out (FOMO), Fear of Uncertainty and Destruction (FUD) - can be avoided altogether when instead of the psychological expectation trading is based on the mathematical expectation. The probability distribution of the daily return of SP500 is presented in this part of Statistical Mechanics of Day Trading. It was shown that day trading of SP500 is similar to a coin toss which slightly favors betting from the long side.
Probability Distribution of the daily return of SP500 index.
SP500 historical data were taken from finance.yahoo.com. Since Jan. 3, 1950 till Jul. 13,2018 there were 17,254 trading days. To obtain the probability distribution (the probability density of a daily return, p(r)), the histogram of the daily returns in % was calculated and normalized by dividing over 17,362. Figures 1 to 3 show the result. Figure 1 shows the major part of the distribution. Figures 2 and 3 show rare events - tails or black & white swans - that SP500 experienced since 1950.
Figure 1.
The maximum of p(r) is around 0.2% which reflects SP500's tendency to be in a bull market.
Figure 2.
Figure 3.
Probability P(r).
The integral of p(r) from minus infinity to r, P(r), gives the probability of having a daily return less than r. P(r) is shown in Figure 4.
In particular, the chance of a negative daily return is given by P(0) which is 0.47. Accordingly, the chance of a positive daily return is 0.53.
The integral of r*p(r) from r1 to r2 divided by ( P(r2)-P(r1)), R(r1,r2), gives the daily return averaged over [r1,r2].
In particular, the average negative return is given by R(-inf.,0) which is -0.65%. The positive return is given by R(0,inf.) which is 0.64%.
PART I : Conclusion & Discussion
Day trading of SP500 can be viewed as a daily toss of the unfair coin -0.47 tails, 0.53 heads - with the even payout, 0.6%. This imaginary coin is slightly in favor of trading from the long side. As of today, SP500 is at $2800 which translates into $46 of the expected daily win for trading Emini futures from the long side. Bid-Ask differential and the cost of trading for a retail trader amounts to $31 per one Emini futures roundtrip; 250 trading days *$(46-31)/($2800*50)=2.7% per year before tax. Thus the expected return, 2.7%, is well below the rate of $ devaluation, 4.5%. On the other note, a black swan can ruin a multiyear profitable streak.
R(-inf.,inf.)=0.033% is the expected average return for day trading from the long side.
PART I : Conclusion & Discussion
Day trading of SP500 can be viewed as a daily toss of the unfair coin -0.47 tails, 0.53 heads - with the even payout, 0.6%. This imaginary coin is slightly in favor of trading from the long side. As of today, SP500 is at $2800 which translates into $46 of the expected daily win for trading Emini futures from the long side. Bid-Ask differential and the cost of trading for a retail trader amounts to $31 per one Emini futures roundtrip; 250 trading days *$(46-31)/($2800*50)=2.7% per year before tax. Thus the expected return, 2.7%, is well below the rate of $ devaluation, 4.5%. On the other note, a black swan can ruin a multiyear profitable streak.
Highly liquid SP500 market behaves very much in an agreement with the efficient market hypothesis. Highly liquid SP500 market behaves very much in an agreement with the efficient market hypothesis. It was shown that day trading of SP500 is similar to a coin toss with even payout and with a small favor for betting from the long side. In the next part, a generic methodology of algorithmic day trading for a retail investor will be derived based on the calculated probability distribution. A reader will find out that the return of the proposed algorithmic trading is expected to beat $ dollar devaluation by a significant margin while profiting from the swan events.
#WTI #RBOB Simple #Crack Spread Pair #Trade
How to calculate and trade Simple Crack Spread using RBOB and WTI Futures.
Friday, June 22, 2018
Scaled in @17.4; tis a berry painful trade. I Feel Like I'm Taking Crazy Pills
Wednesday, June 20, 2018
The U.S. gasoline price decreased. Let us wait for a summer spike in gasoline price and try to do some scalping at the same time.
Scaled in @18.71
Monday, June 18, 2018
Scaled out @20.27 for $100 ; the basis is @20.87 now.
Friday, June 15, 2018
Scaled in @20.17.
Friday, June 22, 2018
Scaled in @17.4; tis a berry painful trade. I Feel Like I'm Taking Crazy Pills
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type | Crack |
| 17.431 | ||||||||||||
| 6/22/2018 11:31 | FUTURE | SELL | -1 | TO OPEN | /CLQ8 | 18-Aug | FUTURE | 68.06 | 68.06 | MKT | ||
| 6/22/2018 11:31 | FUTURE | BUY | 1 | TO OPEN | /RBQ8 | 18-Aug | FUTURE | 2.0355 | 2.0355 | MKT |
Wednesday, June 20, 2018
The U.S. gasoline price decreased. Let us wait for a summer spike in gasoline price and try to do some scalping at the same time.
Scaled in @18.71
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type | Crack_Spread |
| 18.7126 | ||||||||||||
| 6/20/2018 12:18 | FUTURE | SELL | -1 | TO OPEN | /CLQ8 | 18-Aug | FUTURE | 65.51 | 65.51 | MKT | ||
| 6/20/2018 12:18 | FUTURE | BUY | 1 | TO OPEN | /RBQ8 | 18-Aug | FUTURE | 2.0053 | 2.0053 | LMT |
Monday, June 18, 2018
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type | Crack_spread |
| 20.2728 | ||||||||||||
6/18/2018 10:23 | FUTURE | BUY | 1 | TO CLOSE | /CLQ8 | 18-Aug | FUTURE | 64.92 | 64.92 | MKT | ||
6/18/2018 10:23 | FUTURE | SELL | -1 | TO CLOSE | /RBQ8 | 18-Aug | FUTURE | 2.0284 | 2.0284 | LMT |
Friday, June 15, 2018
Scaled in @20.17.
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type | Crack_Spread | |
| 20.1696 | |||||||||||||
| 6/15/2018 10:46 | FUTURE | BUY | 1 | TO OPEN | /RBQ8 | 18-Aug | FUTURE | 2.0338 | 2.0338 | MKT | |||
| 6/15/2018 10:46 | FUTURE | SELL | -1 | TO OPEN | /CLQ8 | 18-Aug | FUTURE | 65.25 | 65.25 | MKT | |||
Thursday, June 14, 2018
In line with my expectation, Q8 Crack spread is cheaper today. Having a long position here is a good idea as at summer seasons this pair is prone to sudden spikes.
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type | Crack_Spread |
| 20.968 | ||||||||||||
| 6/14/2018 11:05 | FUTURE | BUY | 1 | TO OPEN | /RBQ8 | 18-Aug | FUTURE | 2.079 | 2.079 | MKT | ||
| 6/14/2018 11:05 | FUTURE | SELL | -1 | TO OPEN | /CLQ8 | 18-Aug | FUTURE | 66.35 | 66.35 | MKT |
Why do I buy cheap OTM puts?
SLV credit puts spreads is the core of my Income Portfolio. A typical spread is -1 16 Put hedged with +1 13 Put. Almost always I have a feeling that cheap OTM puts are a useless waste of money. I have to suppress this emotion because back in 2008 SLV printed $8.5. If a financial crisis like in 2008 will happen again and the SLV price will drop say to $10 the baseline for me will shift $3 down but the income strategy will keep yielding interest. It turns out that Mark Spitznagel has a similar approach to risk hedging.
Small-scale Trading That Works Similar to Income from Real Estate Investing
Part I: Upstream against Currency Devaluation
For all practical purposes, 1964 marks the last year when regular quarters minted in the USA were suitable for value storing by a regular person. 54 years later, in 2018, 1964 Washington silver quarter costs about $3. Isn't it an interesting and dangerous question - to whom 11/12 of the original value was transferred?Another important observation is that those- before 1964- folks were paid interest without losing the real value. A modern investor has to operate in the monetary environment constructed to deplete the principal value of a cash account by virtue of the hidden currency devaluation. Let us estimate the rate of USD devaluation using the value of 1964 Washington silver quarter - (1-x) ^54=1/12. The answer is x = 0.045. It means that -
No matter what they say in their official reports, the calculation showed that the value of $1 decreases with the rate of ~4.5% per year.
Now, the formula to calculate the real return on a cash account reads:
Real ROI = (1 - Tax Rate/100) x ROI - Currency Devaluation Rate,
where ROI stands for the return on investment. Say if your tax rate is 25% than Real ROI for the cash account becomes positive if you make > 6% per year.
Part II: Residential Real Estate Investing.
Middle-class individuals often choose to invest in real estate as a way to receive interest without losing the real value. For example, currently a 1400 square feet, 2 bedrooms, 2 1/2 bath condo in Miami-Dade, Florida costs ~$200,000. If rented out, such a property generates cash flow of $1300 rent per month, minus management fee of about $200-300 per month, and minus property tax which is about $2,000 per year. Altogether it is about 5% ROI per year.
Real ROI = (1 - Tax Rate/100) x (ROI - Depreciation Rate),
Let us use IRS allowed number, 3.636%, for the depreciation rate. In this case, if your tax rate is 25% than Real ROI in the described above residential property is ~1% per year. For investors in Miami-Dade residential properties, it means that in 2018 all future rental incomes are nearly priced in the current price. Well, at least the wealth is protected from the silent erosion by $ devaluation. Real Estate Investing in Miami-Dade was way more attractive back in 2010-4 when the same condo yielded between 6 and 4%.
Part III: Small-scale Stock Investing.
 |
| SP500, Historical data. |
Real estate investing is a capital-intensive business while according to some recent publications in media outlets, many people in the USA have no $500 of free cash. Now let us think of a person who wants to accumulate wealth by small-scale savings while collecting interest. Since this individual has to beat $ devaluation (see Part I), small-scale investing in stocks of a dividend-paying company looks like a natural choice here. This choice, however, creates an additional risk cause a lot of companies tend to lose business and at some point, nearly all of them will go bankrupt.Thus it is better for our small investor to buy a dividend-paying index fund. For example, in 2018 before tax SPY pays ~1.8% of interest. Similar to real estate investing, the chronical problem here is the overstretched valuation of the attractive companies which typically goes hand in hand with debt expansion cycles. A debt expansion cycle is usually followed by a prolonged period of bad ROI. From 1970 to 1980 SP500 dropped from ~$700 to $300 while, for example, WTI oil skyrocketed from $20 to ~$120. It is difficult to predict when and at what price the next top in SP500 will happen, but the phenomenon of lost decades is amply demonstrated by the historical chart of SP500 index.
Part IV: Small-scale commodity investing.
Commodity investing is another way to fight currency devaluation. Beware that the entry point has to be close enough to the lows of a commodity cycle. Typically a long period of oversupply and of depressed prices is followed by a period when the demand becomes larger than mining supply. The price will stay depressed until the overground stocks are depleted. Usually, there is enough time to gather information and make an investment decision.
Silver
At the beginning of 21st century, the rise of digital photography had eliminated about half of the industrial demand for silver. After it, the investment demand was oversaturated in the bubble of 2011. The price of silver was depressed since then. With the widespread adoption of electronic gadgets the situation has changed and in 2017 for the first time in many years, the total demand for silver is larger than mining supply. Silver ETF, SLV, is an ideal choice for a small-scale commodity investing. Interest can be collected by selling out of the money calls against SLV stocks (SLV has liquid options). At the same time, this approach allows profiting from price appreciation in the rising phase of the mining cycle. That easily beats currency devaluation. Here is an example of value investing in SLV stocks using just $3600.
Uranium
"In 2018 Uranium supply is getting short, Uranium demand is growing while the number of the active mines is dropping worldwide. When the overground stocks of Uranium will go, the price will explode. Here one can get a solid return on the investment while participating in the liquid market. Indeed, for the next several years, aggressive trading strategies like stock replacement by debit call spread may yield a spectacular return ...."
Stocks of Uranium ETF, URA, is suitable for small-scale value investing in Uranium market. Again, Call options can be used here to collect interest. Unlike SLV, URA is not a pure commodity ETF. As a collection of mining stocks, this ETF pays quite significant dividends.
Silver
At the beginning of 21st century, the rise of digital photography had eliminated about half of the industrial demand for silver. After it, the investment demand was oversaturated in the bubble of 2011. The price of silver was depressed since then. With the widespread adoption of electronic gadgets the situation has changed and in 2017 for the first time in many years, the total demand for silver is larger than mining supply. Silver ETF, SLV, is an ideal choice for a small-scale commodity investing. Interest can be collected by selling out of the money calls against SLV stocks (SLV has liquid options). At the same time, this approach allows profiting from price appreciation in the rising phase of the mining cycle. That easily beats currency devaluation. Here is an example of value investing in SLV stocks using just $3600.
Uranium
"In 2018 Uranium supply is getting short, Uranium demand is growing while the number of the active mines is dropping worldwide. When the overground stocks of Uranium will go, the price will explode. Here one can get a solid return on the investment while participating in the liquid market. Indeed, for the next several years, aggressive trading strategies like stock replacement by debit call spread may yield a spectacular return ...."
Stocks of Uranium ETF, URA, is suitable for small-scale value investing in Uranium market. Again, Call options can be used here to collect interest. Unlike SLV, URA is not a pure commodity ETF. As a collection of mining stocks, this ETF pays quite significant dividends.
#Ponzi #Crypto vs #Uranium
The recent post, "#Uranium is going to beat #crypto returns", may sound a little bit provocative, but let us check the realities of these two very different mining worlds.
The blockchain technology is not that young anymore, but no economically significant applications were reported yet.
At present, it is not obvious how to get rid of the inherent slowness and expensiveness of a blockchain transaction. Meanwhile, people are experiencing crypto-mania and it is an acute form of mania. The reason is that the opportunity of an abnormal gain has a strong emotional response in the reptilian part of the human brain. This reptilian brain has all chemical means to stop commonsense. When a critical mass of free lunch believers is achieved, it becomes a self-propelling mania, because human beings have the basic instinct to act in a herd. No one is going to ask who is the patsy, that ultimate bagholder on the other side of the trade. While the answer is pretty obvious, people don't mind to buy some hilarious #ICO. For example, PonziCoin does exist in the crypto universe. I dare to predict that the eventual return on this ICO will be minus 100%. Ponzi is a common trait of ICOs. Hence minus 100% return is going to be the universal constant in the ICO world.
As for #Uranium, there is no reason to think that the uranium cycle is different from any other commodity cycle for that matter. In 2018 U supply is getting short, demand is growing while the number of active mines is dropping worldwide. When the overground stocks will go, the price will explode. Here one can get a solid return on investment while participating in the liquid market. Indeed, for the next several years, aggressive trading strategies like stock replacement by debit call spread may yield abnormal returns and beat the darlings of the crypto world.
The blockchain technology is not that young anymore, but no economically significant applications were reported yet.At present, it is not obvious how to get rid of the inherent slowness and expensiveness of a blockchain transaction. Meanwhile, people are experiencing crypto-mania and it is an acute form of mania. The reason is that the opportunity of an abnormal gain has a strong emotional response in the reptilian part of the human brain. This reptilian brain has all chemical means to stop commonsense. When a critical mass of free lunch believers is achieved, it becomes a self-propelling mania, because human beings have the basic instinct to act in a herd. No one is going to ask who is the patsy, that ultimate bagholder on the other side of the trade. While the answer is pretty obvious, people don't mind to buy some hilarious #ICO. For example, PonziCoin does exist in the crypto universe. I dare to predict that the eventual return on this ICO will be minus 100%. Ponzi is a common trait of ICOs. Hence minus 100% return is going to be the universal constant in the ICO world.
As for #Uranium, there is no reason to think that the uranium cycle is different from any other commodity cycle for that matter. In 2018 U supply is getting short, demand is growing while the number of active mines is dropping worldwide. When the overground stocks will go, the price will explode. Here one can get a solid return on investment while participating in the liquid market. Indeed, for the next several years, aggressive trading strategies like stock replacement by debit call spread may yield abnormal returns and beat the darlings of the crypto world.
Thursday, August 16, 2018
Why do people trade at all?
Real life encounters with traders tell quite a different story.
1. In our local park, my kids easily make tons of new friends. That's how I came to know a weekend daddy. This old man first lost his business; next, his wife ran away with a significant chunk of his wealth and to a younger man. The guy told me that he trades his retirement account cause he doesn't feel secure about coming years and that his trading was inspired by "a bald guy on CNBC". Shortly I learned that this nice person with huge black circles under the eyes trades FANG stocks and that he understands only simple trading from the long side. The year was 2016 and he was a happy trader who had recovered all his losses caused by the nosedive of Apple stocks back in 2015.
2. Every other Saturday at 7:30 AM I play beach volleyball with other people from our physics and chemistry departments. Here I talked with a Ph.D. whose wife and kid stay in India while in the USA he shares a room with another guy from India. This young person invested ~$1000 in shares of crypto-mining companies and now is reduced to HODL. In his 30's this man who already published ~20 papers is desperately looking for an additional income as his salary is not enough to fulfill basic needs.
I know in person several other guys who can be classified as 1 or 2 or something in between.
My conclusion is that people trade mainly because their financial situation is an unstable one. Indeed "Almost half of US families can't afford basics like rent and food; some 66% of jobs in the US pay less than $20 an hour."
No wonder that a trader in financially weak position often buys a dream of a miraculous return on a small investment while giving up a part of his/her real wealth. For example, it can be Facebook shares or bitcoins. In this case, Wall Street works as a wealth transfer machine where > 90% of retail traders end up losing money.
I think before getting involved with risky trading styles one should try small-scale income trading that works similar to cash flow from real estate assets.
anatomy of silver gold pair trade
Gold is a monetary metal, i. e. gold is money. Gold can be used as a safe storage of value when fiat currencies are being devalued day by day. Also, rising gold price usually means that faith in banking and governmental institutions is falling and investors are looking for safe haven. Gold has few industrial uses.
Silver is used both as a monetary and industrial asset. Consequently, there is the strong silver-gold correlation. However, because silver also has many industrial uses it is affected by the business cycle.
A trader can try to profit form the interplay of monetary and industrial factors. From historical perspective Silver/Gold ratio is rather high, i.e ~ 80 : 
One /SI contract is a digital equivalent of 5,000 oz of silver. At the moment it can be hedged with ~ 62 oz of gold.
One /GC contract is a digital equivalent of 100 oz of gold. 60 delta /GC call against /SI contract gives a fully hedged position.
Naturally, a contrarian wants to short gold and long silver here but let us think some fundamentals first.
1. Physical investment (coins, et cetera) is depressed ( negative ).
2. Industrial demand is rising (positive).
3. Rising interest rates (negative).
Eventually, 2 will change 1 into positive and a new secular bull market will be born. However, 3 provides a very strong negative pressure and prices like $10 per oz may happen first. In this case, the proposed trading strategy is:
accumulate long silver while hedging the position with gold calls until rate environment remains negative.
The factors that favor this strategy are:
1. High Silver/Gold ratio;
2. Theta decay in gold calls;
3. Increasing industrial demand for silver.
4. Long-term devaluation of $USD.
4/27/18 Here is the entry where silver was lightly underhedged:
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type |
| 4/27/2018 11:12 | SINGLE | SELL | -1 | TO OPEN | /GCM8 1/100 JUN 18 | /OGM8 | 1330 | CALL | 10.6 | 10.6 | LMT |
| 4/27/2018 11:10 | FUTURE | BUY | 1 | TO OPEN | /SIN8 | 18-Jul | FUTURE | 16.52 | 16.52 | LMT |
If the gold price is on a move /GC delta has to be updated accordingly.
5/1/18
PM complex moved down. -40 /GC delta of the original trade became -20. Posted is the trade which made /GC delta back to -40.
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type |
| 5/1/2018 10:52 | SINGLE | BUY | 1 | TO CLOSE | /GCM8 1/100 JUN 18 | /OGM8 | 1330 | CALL | 4.6 | 4.6 | LMT |
| 5/1/2018 10:49 | SINGLE | SELL | -1 | TO OPEN | /GCQ8 1/100 JUL 18 | /OGN8 | 1325 | CALL | 14.1 | 14.1 | LMT |
For chart lovers I have a graphical representation of the trade:
5/2/18
Today (5/2/18) after FED meeting the silver-gold pair trade went positive. It is nothing wrong if one wants to take ~$300 and run. However, I want to l keep the trade open for now.
5/9/18
Flat. The trade generated $600 profit before commissions. /GC hedge and Silver/Gold ratio played out to my expectation.
| Exec Time | Spread | Side | Qty | Pos Effect | Symbol | Exp | Strike | Type | Price | Net Price | Order Type |
| 5/9/2018 8:54 | FUTURE | SELL | -1 | TO CLOSE | /SIN8 | 18-Jul | FUTURE | 16.55 | 16.55 | LMT | |
| 5/9/2018 8:32 | SINGLE | BUY | 1 | TO CLOSE | /GCQ8 1/100 JUL 18 | /OGN8 | 1325 | CALL | 15.6 | 15.6 | LMT |
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The recent post, " # Uranium is going to beat #crypto returns " , may sound a little bit provocative, but let us check the reali... -
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