Posts Tagged ‘Average’

McGinley Dynamic: The Reliable Unknown Indicator

Written by admin. Posted in Technical Analysis

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The McGinley Dynamic is a little-known yet highly reliable indicator invented by John R. McGinley, a chartered market technician and former editor of the Market Technicians Association’s Journal of Technical Analysis. Working within the context of moving averages throughout the 1990s, McGinley sought to invent a responsive indicator that would automatically adjust itself in relation to the speed of the market.

His eponymous Dynamic, first published in the Journal of Technical Analysis in 1997, is a 10-day simple and exponential moving average with a filter that smooths the data to avoid whipsaws.

Key Takeaways

  • John R. McGinley is a chartered market technician known for his work with technical market strategies and trading techniques.
  • The McGinley Dynamic is a moving average indicator he created in the 1990s that looks to automatically adjust itself to the pace of the financial markets.
  • The technique helps address the tendency to inappropriately apply moving averages.
  • It also helps to account for the gap that often exists between prices and moving average lines.

Simple Moving Average (SMA) vs. Exponential Moving Average (EMA)

A simple moving average (SMA) smooths out price action by calculating past closing prices and dividing by the number of periods. To calculate a 10-day simple moving average, add the closing prices of the last 10 days and divide by 10. The smoother the moving average, the slower it reacts to prices.

A 50-day moving average moves slower than a 10-day moving average. A 10- and 20-day moving average can at times experience the volatility of prices that can make it harder to interpret price action. False signals may occur during these periods, creating losses because prices may get too far ahead of the market.

An exponential moving average (EMA) responds to prices much more quickly than a simple moving average. This is because the EMA gives more weight to the latest data rather than older data. It’s a good indicator for the short term and a great method to catch short-term trends, which is why traders use both simple and exponential moving averages simultaneously for entry and exits. Nevertheless, it too can leave data behind.

The Problem With Moving Averages

In his research, McGinley found moving averages had many problems. In the first place, they were inappropriately applied. Moving averages in different periods operate with varying degrees in different markets. For example, how can one know when to use a 10-day, 20-day, or 50-day moving average in a fast or slow market? In order to solve the problem of choosing the right length of the moving average, the McGinley Dynamic was built to automatically adjust to the current speed of the market.

McGinley believes moving averages should only be used as a smoothing mechanism rather than a trading system or signal generator. It is a monitor of trends. Further, McGinley found moving averages failed to follow prices since large separations frequently exist between prices and moving average lines. He sought to eliminate these problems by inventing an indicator that would hug prices more closely, avoid price separation and whipsaws, and follow prices automatically in fast or slow markets.

McGinley Dynamic Formula

This he did with the invention of the McGinley Dynamic. The formula is:


MD i = M D i 1 + Close M D i 1 k × N × ( Close M D i 1 ) 4 where: MD i = Current McGinley Dynamic M D i 1 = Previous McGinley Dynamic Close = Closing price k = . 6  (Constant 60% of selected period N) N = Moving average period \begin{aligned} &\text{MD}_i = MD_{i-1} + \frac{ \text{Close} – MD_{i-1} }{ k \times N \times \left ( \frac{ \text{Close} }{ MD_{i-1} } \right )^4 } \\ &\textbf{where:}\\ &\text{MD}_i = \text{Current McGinley Dynamic} \\ &MD_{i-1} = \text{Previous McGinley Dynamic} \\ &\text{Close} = \text{Closing price} \\ &k = .6\ \text{(Constant 60\% of selected period N)} \\ &N = \text{Moving average period} \\ \end{aligned}
MDi=MDi1+k×N×(MDi1Close)4CloseMDi1where:MDi=Current McGinley DynamicMDi1=Previous McGinley DynamicClose=Closing pricek=.6 (Constant 60% of selected period N)N=Moving average period

The McGinley Dynamic looks like a moving average line, yet it is actually a smoothing mechanism for prices that turns out to track far better than any moving average. It minimizes price separation, price whipsaws, and hugs prices much more closely. And it does this automatically as a factor of its formula.

Because of the calculation, the Dynamic Line speeds up in down markets as it follows prices yet moves more slowly in up markets. One wants to be quick to sell in a down market, yet ride an up-market as long as possible. The constant N determines how closely the Dynamic tracks the index or stock. If one is emulating a 20-day moving average, for instance, use an N value half that of the moving average, or in this case 10.

It greatly avoids whipsaws because the Dynamic Line automatically follows and stays aligned to prices in any market—fast or slow—like a steering mechanism of a car that can adjust to the changing conditions of the road. Traders can rely on it to make decisions and time entrances and exits.

The Bottom Line

McGinley invented the Dynamic to act as a market tool rather than as a trading indicator. But whatever it’s used for, whether it is called a tool or indicator, the McGinley Dynamic is quite a fascinating instrument invented by a market technician that has followed and studied markets and indicators for nearly 40 years. In creating the Dynamic, McGinley sought to create a technical aid that would be more responsive to the raw data than simple or exponential moving averages.

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Daily Analysis 20230309

Written by itho suryoputro. Posted in Daily Analysis

March 09th, 2023

Good morning,

Dow finishes slightly lower as traders consider a faster Fed tightening cycle

The Dow Jones Industrial Average finished slightly lower Wednesday as the market fought to overcome Tuesday’s selloff, spurred by comments from Federal Reserve Chairman Jerome Powell hinting at higher interest rates for longer.

Dow…..32798 -58.1 -0.18%
Nasdaq11576 +45.7 +0.40%
S&P 500.3992 +5.6 +0.14%

FTSE…….7930 +10.4 +0.13%
Dax……..15632+72.3 +0.46%
CAC……..7325 -14.5 -0.20%

Nikkei…..28444 +135.03+0.25%
HSI……. .20051 -483.2 -2.35%
Shanghai.3283 -1.9 -0.06%

IDX…..6776.37 +9.61 +0.14%
LQ45….939.03 +3.30 +0.35%
IDX30…489.26 +2.32 +0.48%

IDXEnergy…2046.37 -6.48 -0.32%
IDX BscMat 1177.60 -15.24 -1.28%
IDX Indstrl..1164.92 -6.39 -0.50%
IDXNONCYC..732.02 +0.79 +0.11%
IDX Hlthcare1529.90 -10.30 -0.67%
IDXCYCLIC…833.29 -8.32 -0.99%
IDX Techno.5423.28 -5.80 -0.11%
IDX Transp.1811.63 +11.54 +0.64%
IDX Infrast….835.37 +2.62 +0.31%
IDX Finance1398.12 +2.22 +0.16%
IDX Banking1133.34 +5.19 +0.46%
IDX Property….685 -0.00 -0.00%

Indo10Yr.6.9766 +0.0249+0.36%‼️
ICBI….348.6693 -0.520 -0.05%‼️
US2Yr5.0701‼️+0.0590 +1.18%
US5Yr 4.3453‼️+0.0300 +0.70%
US10Yr3.9890‼️+0.0140 +0.36%
US30Yr.3.8791‼️+0.0030 +0.08%
VIX……. 19.11 -0.48 -2.45%

USDIndx105.6690+1.3950+1.33%‼️
Como Indx.267.02 -2.56 -0.95%
(Core Commodity CRB)
BCOMIN…158.74 +0.83 +0.53%

IndoCDS..105.25 – -%
(5-yr INOCD5) (07/11)

IDR…..15437.50 +70.50 +0.46%‼️
Jisdor.15451.00 +92.00. +0.60%‼️

Euro……1.0548 -0.0001 -0.01%

TLKM….25.70 +0.35 +1.38%
(3971)
EIDO……22.23 +0.12 +0.54%
EEM……38.90 +0.16 +0.41%

Oil….76.66 -0.92 -1.19%
Gold1818.60 -1.40 -0.08%
Timah 25334 – -%
(Closed 03/01)
Nickel..23913.00 -304.00 -1.26%
(Closed 03/08)
Silver…..20.15 -0.05 -0.24%
Copper.402.70 +5.20 +1.31%

Nturl Gas.2.593 -0.0650 -2.45%

Ammonia 4406.67 -16.66 -0.38%
China
(Domestic Price)(03/07)

Coal price.179.50 +0.25 +0.25%
(Mar/Newcastle)
Coal price.182.25 -1.00 -0.55%
(Apr/Newcastle)
Coal price.186.20 -0.30 -0.16%
(May/Newcastle)
Coal price.192.80 +0.15 +0.08%
(Jun/Newcastle)

Coal price.123.35 -1.15 -0.92%
(Mar/Rotterdam)
Coal price 117.80 +0.30 +0.26%
(Apr/ Rotterdam)
Coal price 118.50 -1.00 -0.83%
(May/Rotterdam)
Coal price 119.30 -0.70 -0.58%
(Jun/Rotterdam)

CPO(May)…4181 -25 -0.59%
(Source: bursamalaysia.com)

Corn……..625.50 -8.75 -1.38%
SoybeanOil..59.06 +0.42 +0.72%
Wheat…….687.50 -10.50 -1.50%

Wood pulp…5730.00 -30 -0.52%
(Closed 03/07)

©️Phintraco Sekuritas
Broker Code: AT
Desy Erawati/ DE
Source: Bloomberg, Investing, IBPA, CNBC, Bursa Malaysia
Copyright: Phintraco Sekuritas

DJI closing merah tipis, Nasdaq udah rebound. Europe tipis2 kebanyakan ijo, Asia juga tipis2 kecuali Hangseng yang merah dalem. Ada harapan rebound kalo gini

Oil gas lanjut merah, coal ijo, metal2 merah kecuali copper, kita tunggu momentum reboundnya basic materials versi tambang mineral

IHSG – kemaren NFS, semoga lanjut asing masuk terus, udah cukup lah koreksi ke fibo 50. Technically stoch masih down, MACD down, MFI sw, w% downtrend done, ada gap di 6688, mungkin juga dibawa dip tutup gap baru naik lagi sih, tapi berdarah2 banget itu kalo kejadian. Belum saatnya aggressive belanja. Cari contrarian aja

Industrials keseret ASII dan UNTR yang koreksi abis loncat. Energy Property sama Technology yang upcoming

 

Average Daily Rate (ADR): Definition, Calculation, Examples

Written by admin. Posted in A, Financial Terms Dictionary

Average Daily Rate (ADR): Definition, Calculation, Examples

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What Is the Average Daily Rate (ADR)?

The average daily rate (ADR) is a metric widely used in the hospitality industry to indicate the average revenue earned for an occupied room on a given day. The average daily rate is one of the key performance indicators (KPI) of the industry.

Another KPI metric is the occupancy rate, which when combined with the ADR, comprises revenue per available room (RevPAR), all of which are used to measure the operating performance of a lodging unit such as a hotel or motel.

Key Takeaways

  • The average daily rate (ADR) measures the average rental revenue earned for an occupied room per day.
  • The operating performance of a hotel or other lodging business can be determined by using the ADR.
  • Multiplying the ADR by the occupancy rate equals the revenue per available room.
  • Hotels or motels can increase the ADR through price management and promotions.

Understanding the Average Daily Rate (ADR)

The average daily rate (ADR) shows how much revenue is made per room on average. The higher the ADR, the better. A rising ADR suggests that a hotel is increasing the money it’s making from renting out rooms. To increase the ADR, hotels should look into ways to boost price per room.

Hotel operators seek to increase ADR by focusing on pricing strategies. This includes upselling, cross-sale promotions, and complimentary offers such as free shuttle service to the local airport. The overall economy is a big factor in setting prices, with hotels and motels seeking to adjust room rates to match current demand.

To determine the operating performance of a lodging, the ADR can be measured against a hotel’s historical ADR to look for trends, such as seasonal impact or how certain promotions performed. It can also be used as a measure of relative performance since the metric can be compared to other hotels that have similar characteristics, such as size, clientele, and location. This helps to accurately price room rentals.

Calculating the Average Daily Rate (ADR)

The average daily rate is calculated by taking the average revenue earned from rooms and dividing it by the number of rooms sold. It excludes complimentary rooms and rooms occupied by staff.


Average Daily Rate = Rooms Revenue Earned Number of Rooms Sold \text{Average Daily Rate} = \frac{\text{Rooms Revenue Earned}}{\text{Number of Rooms Sold}}
Average Daily Rate=Number of Rooms SoldRooms Revenue Earned

Example of the Average Daily Rate (ADR)

If a hotel has $50,000 in room revenue and 500 rooms sold, the ADR would be $100 ($50,000/500). Rooms used for in-house use, such as those set aside for hotel employees and complimentary ones, are excluded from the calculation.

Real World Example

Consider Marriott International (MAR), a major publicly traded hotelier that reports ADR along with occupancy rate and RevPAR. For 2019, Marriott’s ADR increased by 2.1% from 2018 to $202.75 in North America. The occupancy rate was fairly static at 75.8%. Taking the ADR and multiplying it by the occupancy rate yields the RevPAR. In Marriott’s case, $202.75 times 75.8% equates to a RevPAR of $153.68, which was up 2.19% from 2018.

The Difference Between the Average Daily Rate (ADR) and Revenue Per Available Room (RevPAR)

The average daily rate (ADR) is needed to calculate the revenue per available room (RevPAR). The average daily rate tells a lodging company how much they make per room on average in a given day. Meanwhile, RevPAR measures a lodging’s ability to fill its available rooms at the average rate. If the occupancy rate is not at 100% and the RevPAR is below the ADR, a hotel operator knows that it can probably reduce the average price per room to help increase occupancy.

Limitations of Using the Average Daily Rate (ADR)

The ADR does not tell the complete story about a hotel’s revenue. For instance, it does not include the charges a lodging company may charge if a guest does not show up. The figure also does not subtract items such as commissions and rebates offered to customers if there is a problem. A property’s ADR may increase as a result of price increases, however, this provides limited information in isolation. Occupancy could have fallen, leaving overall revenue lower.

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Average Inventory: Definition, Calculation Formula, Example

Written by admin. Posted in A, Financial Terms Dictionary

Average Inventory: Definition, Calculation Formula, Example

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What Is Average Inventory?

Average inventory is a calculation that estimates the value or number of a particular good or set of goods during two or more specified time periods. Average inventory is the mean value of inventory within a certain time period, which may vary from the median value of the same data set, and is computed by averaging the starting and ending inventory values over a specified period.

Key Takeaways

  • Average inventory is a calculation that estimates the value or number of a particular good or set of goods during two or more specified time periods.
  • Average inventory is the mean value of an inventory within a certain time period, which may vary from the median value of the same data set.
  • Average inventory figures can be used as a point of comparison when looking at overall sales volume, allowing a business to track inventory losses.
  • Moving average inventory allows a company to track inventory from the last purchase made.
  • Inventory management is a key success factor for companies as it allows them to better manage their costs, sales, and business relationships.

Understanding Average Inventory

Inventory is the value of all the goods ready for sale or all of the raw materials to create those goods that are stored by a company. Successful inventory management is a key focal point for companies as it allows them to better manage their overall business in terms of sales, costs, and relationships with their suppliers.

Since two points do not always accurately represent changes in inventory over different time periods, average inventory is frequently calculated by using the number of points needed to more accurately reflect activities across a certain amount of time.

For instance, if a business was attempting to calculate the average inventory over the course of a fiscal year, it may be more accurate to use the inventory count from the end of each month, including the base month. The values associated with each point are added together and divided by the number of points, in this case, 13, to determine the average inventory.

The average inventory figures can be used as a point of comparison when looking at overall sales volume, allowing a business to track inventory losses that may have occurred due to theft or shrinkage, or due to damaged goods caused by mishandling. It also accounts for any perishable inventory that has expired.

The formula for average inventory can be expressed as follows:

Average Inventory = (Current Inventory + Previous Inventory) / Number of Periods

Average inventory is used often in ratio analysis; for instance, in calculating inventory turnover.

Moving Average Inventory

A company may choose to use a moving average inventory when it’s possible to maintain a perpetual inventory tracking system. This allows the business to adjust the values of the inventory items based on information from the last purchase.

Effectively, this helps compare inventory averages across multiple time periods by converting all pricing to the current market standard. This makes it similar to adjusting historical data based on the rate of inflation for more stable market items. It allows simpler comparisons on items that experience high levels of volatility.

Example of Average Inventory

A shoe company is interested in better managing its inventory. The current inventory in its warehouse is equal to $10,000. This is in line with the inventory for the three previous months, which were valued at $9,000, $8,500, and $12,000.

When calculating a three-month inventory average, the shoe company achieves the average by adding the current inventory of $10,000 to the previous three months of inventory, recorded as $9,000, $8,500 and $12,000, and dividing it by the number of data points, as follows:

Average Inventory = ($10,000 + $9,000 + $8,500 + $12,000) / 4

This results in an average inventory of $9,875 over the time period being examined.

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