marinero4972/CyberV_ASR · Datasets at Hugging Face

text stringlengths 21 388
[31.86s -> 45.65s] Retained means to keep. Corporations retain their earnings from year to year to be used for different purposes. What is retained earnings used for? 1. To pay out dividends.
[45.65s -> 55.73s] 2. Reinvest earnings into other business ventures. 3. Finance other areas of their operations.
[57.52s -> 65.10s] Earnings is the amount of money earned through the regular course of business after all expenses are deducted.
[67.86s -> 76.05s] Where is retained earnings reported? Retained earnings is reported in the stockholders equity section on the balance sheet.
[77.78s -> 92.40s] So how do we calculate retained earnings? Here is the equation. Beginning retained earnings plus net income minus dividends equals ending retained earnings.
[92.82s -> 98.58s] The ending retained earnings is the value that is reported on the balance sheet.
[98.96s -> 111.79s] Now, let's review. What is retained earnings? It is the amount of income earned through regular course of business that is retained from year to year.
[111.79s -> 124.18s] Here is the equation revisited. Beginning retained earnings plus net income minus dividends equals ending retained earnings.
[127.98s -> 142.96s] For more free videos, online courses, and accounting training, visit accountinguniv.com. And remember to subscribe and like. More videos coming your way soon.
[0.00s -> 4.18s] In this video, we're going to discuss multi-factor models in investing.
[4.18s -> 18.58s] So the most widely known model for estimating the expected return of a security is the capital asset pricing model, where it's modeling the expected return as a function of a single factor, which is capturing systematic returns.
[18.58s -> 32.78s] risk this is beta so we talk about the beta of a security we're saying how many units of risk are in this security with respect to changes in the overall market so the systematic risk remember that's risk that cannot be
[32.78s -> 41.20s] diversified away. It's saying how much does this securities return a function of changes in the overall market?
[41.20s -> 55.50s] Okay, so the market goes up. Let's say we've got a beta 1.5. We say, okay, the market goes up by 1%. Then this security goes up by 1.5%. Now, the single factor model is nice for its simplicity.
[55.50s -> 69.71s] we might think about this systematic risk it includes so many different things it includes expectations about the overall economy and what the GDP is going to be it includes expectations about what the inflation rate is going to be what interest
[69.71s -> 83.92s] rates are going to be. All these different macroeconomic factors are part of this systematic risk. And so you might consider and say, hey, maybe different types of securities react in different ways.
[83.92s -> 98.13s] to changes in interest rates, to changes in inflation. For example, might a bank respond differently to changes in interest rates than a grocery store? Sure, that's reasonable to think that. And so when we just use a single...
[98.13s -> 112.34s] factor that measures systematic risk that's a great start but some people have said well look we can actually think about breaking this systematic risk into its component parts so that we might more accurately predict the expected
[112.34s -> 126.54s] return of the security and when we do that when we have multiple factors here so we have we could have this factor we have another factor we have another factor for interest rates and so forth we have different factors we call that a multi-factor model
[126.54s -> 134.50s] So I want to give you just an easy example. So let's say that we are going to estimate a two-factor model for a fictional company called Happy Bank.
[134.50s -> 147.84s] And our two factors, we're going to make this really simple. We're just going to have inflation and interest rates. Those will be the only two factors in the model. And so we go and we estimate the model with regression analysis and we get the following result.
[147.84s -> 162.13s] And so we've got this 0.11 here. That's going to be the expected excess return for Happy Bank. So that's 11%. That's the expected excess return. But now we've got to think about our two factors. We've got a factor here and we've got a factor here.
[162.13s -> 176.43s] And each of these factors, so it's a coefficient estimate is what we call this in a regression. So this 0.2 is telling us that if we have a one percentage point increase in inflation.
[176.43s -> 190.74s] Okay, so we have an unexpected 1 percentage point increase in inflation. Then that would lead to a 0.2 percentage point increase in the expected return. Okay, now conversely, now we have an...
[190.74s -> 204.94s] negative sign with our other factor so that means that if we were to have an unexpected 1% increase one percentage point increase in interest rates then that would predict that we would have a decrease of
[204.94s -> 219.15s] 0.4 percentage points in the expected return. Okay, so we don't have to have just two factors here. We could have a third factor that measures GDP. We could have a fourth factor. We could have a fifth factor.
[219.15s -> 229.84s] most famous of the multi-factor models is the Fama French model. And then also we've got Fama French Carhartt and so forth. And we'll talk about all of those in the videos to come.
[0.00s -> 14.42s] In this video, I want to walk you through a CFA level one exam style question on Jensen's alpha or simply alpha, which is a topic very much related to the capital asset pricing model. So if this is something you
[14.42s -> 21.90s] want to get right in the exam, do keep watching and let's get solving. So this is the question which I want us to have a go at.
[21.90s -> 35.79s] if you watch the previous two videos you will recall these figures for portfolio x y and z we've got some performance information including return standard deviation and beta we also have the return on the market portfolio 2.3 percent
[35.79s -> 50.06s] its standard deviation and a risk-free rate of return equal to 0.5 and we're asked about which portfolio offers the best performance as measured by jensen's alpha now jensen's alpha is
[50.06s -> 64.48s] basically something that we probably had already exposure to. I've definitely recorded previous videos on this, although I didn't call it alpha as such. It was all about whether a stock is generating returns.
[64.48s -> 75.39s] in excess or below the rate of return required under the CAPM model, given its level of systematic risk. So basically...
[75.39s -> 88.88s] this thing called alpha, which we also call Jensen's alpha, is equal to the return on the portfolio, either expected or, you know, historically experienced minus
[88.88s -> 101.52s] what the CAPM model would predict is the required rate of return. And that's obviously a function of the risk-free rate plus the beta of that specific portfolio times RM.
[101.52s -> 107.92s] minus rf where rm is the rate return on the market portfolio and rf is once again
[107.92s -> 122.03s] the risk-free rate of return and obviously if this relationship is positive if a portfolio is generating more than what's required by uh under the cap and model let me
[122.03s -> 134.50s] perhaps just finish this off with a nice square bracket at the end to close this off and make the formula complete well if this relationship is positive then a stock would be described as lying above
[134.50s -> 147.86s] the sml the security market line if the relationship is negative it's yielding less than what's required and that would respectively lead us to conclude that the stock is either
[147.86s -> 161.42s] undervalued if it's above or the sml or undervalued if it's below the sml and we've had previous questions on that comparison and whether stocks are under or overvalued okay so
[161.46s -> 172.53s] Let's compute this for portfolio X to start with. Its return is 2%. What would be predicted by the CAPM model?
[172.53s -> 186.42s] The RF is 0.5% plus the beta on this specific portfolio being 0.8 times the rate of return on the market, which is 2.3.
[186.93s -> 199.62s] minus 0.5 percent close the bracket okay i'm going to take my phone with the calculator and quickly do this not really sharing my phone screen with you as there is nothing um
[199.62s -> 205.26s] terribly exciting happening in terms of the computations so let me start with
[205.55s -> 218.93s] this 2.3 minus 0.5 that's obviously 1.8 times the beta of 0.8 okay plus 0.5 okay and i see
[219.86s -> 233.04s] A result equal to, let me write this down over here, it's going to be 0.06% and it's positive. So this suggests a little bit of alpha, very small.
[233.04s -> 243.31s] but a little bit of excess performance on a sort of risk-adjusted basis where we, as risk, we take into account systematic risk only.
[243.31s -> 255.02s] Good. So better than the required rate of return from the CAPM model. How about Y? Well, over here we're going to have...
[255.02s -> 269.01s] the return of four and a half percent minus the same thing as before 0.5 plus and the only thing that changes here is the beta which is going to be specific to the teach portfolio 1.6 other than that
[269.20s -> 276.58s] We've got 2.3 minus 0.5, just like before. So I know the term here in the...
[276.58s -> 290.86s] in the bracket is 1.8 so that's 1.8 times the new beta of 1.6 let's add 0.5 to that 3.38 okay and this is definitely going to yield something
[290.86s -> 299.02s] positive i see a positive difference of 1.12 percent so this stock definitely
[299.02s -> 312.29s] yields more than what would be required under the CAPM model given its level of systematic risk as measured by beta. So we would say that this stock is lying above the SML, the security market line.
[312.29s -> 324.40s] And we would also conclude that it is undervalued. Now, what about Z? For portfolio Z, we've got 6.2%. Once again, minus...
[324.40s -> 338.64s] square bracket 0.5 percent plus a beta of 2.5 and uh same thing as before in the bracket 2.3 minus 0.5 close both brackets
[339.41s -> 353.04s] So, this is 1.8 multiplied by a beta of 2.5 plus 0.5, okay, minus...
[354.51s -> 359.55s] And for this one, I see a result which is even higher.
[359.55s -> 371.22s] it's positive and it's 1.2 percent so that's a measure of the excess return above what's required and that will lead me to conclude that portfolio z is
[371.50s -> 380.46s] The one which performs best. It's got the best performances measured by Jensen's alpha. So, answer C.
[0.43s -> 12.67s] Helo, selamat hari. Dalam video sebelum ini, saya telah membincangkan beberapa teori portfolio dan harga aset utama dari teori portfolio moden pada tahun 1952
[12.67s -> 26.86s] ke Kepem pada tahun 60-an. Hari ini saya akan bergerak ke tahun 1970 dengan menunjukkan kepada anda teori yang mempengaruhi aset, teori harga arbitraj.
[26.86s -> 36.02s] Mari kita mengetahui bersama-sama apa itu APT dan bagaimana APT boleh digunakan dalam peningkatan aset.
[37.30s -> 49.17s] Pada tahun 1976, Stephen Ross mengembangkan Teori Pricing Arbitrasi. Dia mempunyai pendekatan multifaktor untuk menjelaskan harga aset.
[50.38s -> 61.33s] Sebelum kita bergerak ke kisah tentang APT, mari kita ambil masa untuk memahami konsep arbitrage. Kemudian anda akan dapat menghargai
[61.33s -> 75.10s] mengapa model yang dikembangkan oleh Stephen Ross dipanggil APT. Menurut definisi Valdi, Kane dan Marcus pada tahun 2011, arbitrage adalah penggunaan.
[75.10s -> 87.10s] peningkatan keselamatan dengan cara sebegitu bahawa keuntungan tanpa risiko boleh diperoleh. Menurut Herschel dan Nozinger dalam 2010, arbitrage
[87.10s -> 96.94s] hanyalah pembelian dan penjualan aset yang sama pada harga yang berbeza untuk menangkap peningkatan yang salah
[100.08s -> 113.78s] Peraturan Satu Harga mengatakan bahawa dua aset yang sama sepatutnya mempunyai harga pasaran yang sama. Peluang pembayaran akan muncul jika aset yang sama dihantar untuk harga yang berbeza.
[113.78s -> 124.35s] di dua lokasi yang berbeza. Perbelanjaan satu harga dilaksanakan oleh pembayar RBI yang akan mengambil kesempatan harga dalam kawasan ini.
[124.35s -> 136.21s] Penjual akan membeli aset di tempat yang murah dan menjual di tempat yang tinggi. Melalui mekanisme penjualan ini, harga akan berpindah kembali ke kawasan.
[136.30s -> 149.22s] Peluang arbitrage berlaku apabila pelabur dapat memperoleh keuntungan tanpa membuat pelaburan net.
[149.22s -> 160.19s] pelabur boleh menggunakan proses daripada jualan pendek untuk membeli long dan oleh itu transaksi boleh dibuat tanpa pelaburan
[160.19s -> 165.65s] Ini menjadikan transaksi transaksi yang tidak berguna
[168.46s -> 180.88s] APT adalah teori untuk menjelaskan keuntungan stok berdasarkan sensitiviti kepada banyak faktor risiko. Ia mengandung model linier.
[180.88s -> 192.13s] keuntungan dalam pelaburan boleh dijelaskan dengan lebih daripada satu faktor. Menurut APT, pasar adalah sempurna efisien jika
[192.13s -> 200.85s] tidak mungkin untuk menghasilkan keuntungan arbitrage tanpa risiko dengan membeli dan menjual aset yang sama
[202.42s -> 213.36s] APT mengatakan bahawa terdapat banyak faktor yang menyebabkan kembali, berbeza dengan KPM di mana risiko yang terkait sahaja adalah beta.
[213.68s -> 227.79s] APT tidak mengatakan apa faktornya. Contohnya, keuntungan stok perniagaan syarikat mungkin terpaksa oleh perubahan dalam harga minyak. Kebanyakan syarikat transport, seperti pesawat,
[227.79s -> 240.72s] akan mempunyai sensitiviti negatif kepada perubahan harga minyak. Beberapa syarikat akan lebih sensitif kepada faktor tertentu daripada syarikat lain. Contohnya, syarikat minyak
[240.72s -> 246.16s] boleh menjadi lebih sensitif kepada faktor minyak daripada industri pengguna
[249.04s -> 260.46s] APT adalah model yang lebih jeneralisasi daripada CAPM dan kurang restriktif dalam pengiraannya. Ada lima pengiraan yang ditandakan di sini.
[263.12s -> 274.16s] Ini menunjukkan model APT. Dalam formula ini, keuntungan sebenar pada aset dikalkulasi. ER bermakna keuntungan yang diharapkan
[274.16s -> 287.73s] F adalah setan faktor umum yang mempengaruhi keuntungan pada aset Beta adalah sensitiviti faktor pada keuntungan aset E adalah terma kesilapan
[287.89s -> 301.20s] Di sini, formula menunjukkan bahawa APT adalah proses stokastik yang menghasilkan keuntungan aset yang boleh dikatakan sebagai fungsi linear setiap faktor risiko
[302.77s -> 313.58s] The APT can also be expressed in terms of expected risk premium. Expected risk premium is the actual return minus risk free rate.
[313.58s -> 327.22s] APT mengatakan bahawa premium risiko yang diharapkan pada stok harus bergantung pada premium risiko yang diharapkan terkait dengan setiap faktor dan sensitiviti stok kepada setiap faktor
[328.62s -> 334.06s] Mari kita gunakan formula APT dalam contoh ini
[342.80s -> 350.48s] Apa jawapan anda? Jawapan adalah C
[354.93s -> 362.80s] Mari kita cuba contoh lain. Di sini kita mempunyai portfolio A dan B. Apa yang akan anda lakukan?
[372.94s -> 385.28s] Jika anda mahu mengambil kesempatan arbitrage, anda harus mengambil posisi pendek dalam portfolio B dan posisi panjang dalam A. Mengapa begitu?
[385.28s -> 394.35s] kerana A di bawah nilai dan B di atas nilai apabila mereka terhadap risiko yang sama F
[398.86s -> 403.50s] Saya harap anda dapat memahami sesi ini. Jumpa lagi dan selamat tinggal.
[0.00s -> 9.76s] In this video we are going to discuss cost-based pricing strategy and one very important concept associated with cost-based pricing strategy.
[9.76s -> 21.60s] now in another video we talked about different types of cost based pricing strategy like the cost plus pricing and markup pricing but in this video we are going to talk about break even pricing
[21.60s -> 34.51s] break-even pricing is a very important concept in pricing strategy because break-even pricing is the price at which you are able to recoup all your cost right so your profit is zero
[34.51s -> 47.12s] the revenue that you are going to get is equal to the cost that you are incurring so if you can find out your break-even price then you know that a price higher than the break-even price would lead to profit
[47.12s -> 60.42s] and a price lower than the breakeven price would lead to a loss. Now let's do some calculations to understand this concept a little bit more. Now we know that profit equals to
[60.42s -> 72.54s] total revenue minus total cost now we know that total revenue is a multiplication of your price times quantity which we will turn p times q here
[72.54s -> 84.46s] We also know that your total cost consists of fixed cost and variable cost where the variable cost is the unit variable cost multiplied by the quantity.
[84.94s -> 98.06s] Whereas the fixed cost is represented just by the fixed cost Now since we have profit equals total revenue minus total cost Our equation comes out like this

[31.86s -> 45.65s] Retained means to keep. Corporations retain their earnings from year to year to be used for different purposes. What is retained earnings used for? 1. To pay out dividends.

[45.65s -> 55.73s] 2. Reinvest earnings into other business ventures. 3. Finance other areas of their operations.

[57.52s -> 65.10s] Earnings is the amount of money earned through the regular course of business after all expenses are deducted.

[67.86s -> 76.05s] Where is retained earnings reported? Retained earnings is reported in the stockholders equity section on the balance sheet.

[77.78s -> 92.40s] So how do we calculate retained earnings? Here is the equation. Beginning retained earnings plus net income minus dividends equals ending retained earnings.

[92.82s -> 98.58s] The ending retained earnings is the value that is reported on the balance sheet.

[98.96s -> 111.79s] Now, let's review. What is retained earnings? It is the amount of income earned through regular course of business that is retained from year to year.

[111.79s -> 124.18s] Here is the equation revisited. Beginning retained earnings plus net income minus dividends equals ending retained earnings.

[127.98s -> 142.96s] For more free videos, online courses, and accounting training, visit accountinguniv.com. And remember to subscribe and like. More videos coming your way soon.

[0.00s -> 4.18s] In this video, we're going to discuss multi-factor models in investing.

[4.18s -> 18.58s] So the most widely known model for estimating the expected return of a security is the capital asset pricing model, where it's modeling the expected return as a function of a single factor, which is capturing systematic returns.

[18.58s -> 32.78s] risk this is beta so we talk about the beta of a security we're saying how many units of risk are in this security with respect to changes in the overall market so the systematic risk remember that's risk that cannot be

[32.78s -> 41.20s] diversified away. It's saying how much does this securities return a function of changes in the overall market?

[41.20s -> 55.50s] Okay, so the market goes up. Let's say we've got a beta 1.5. We say, okay, the market goes up by 1%. Then this security goes up by 1.5%. Now, the single factor model is nice for its simplicity.

[55.50s -> 69.71s] we might think about this systematic risk it includes so many different things it includes expectations about the overall economy and what the GDP is going to be it includes expectations about what the inflation rate is going to be what interest

[69.71s -> 83.92s] rates are going to be. All these different macroeconomic factors are part of this systematic risk. And so you might consider and say, hey, maybe different types of securities react in different ways.

[83.92s -> 98.13s] to changes in interest rates, to changes in inflation. For example, might a bank respond differently to changes in interest rates than a grocery store? Sure, that's reasonable to think that. And so when we just use a single...

[98.13s -> 112.34s] factor that measures systematic risk that's a great start but some people have said well look we can actually think about breaking this systematic risk into its component parts so that we might more accurately predict the expected

[112.34s -> 126.54s] return of the security and when we do that when we have multiple factors here so we have we could have this factor we have another factor we have another factor for interest rates and so forth we have different factors we call that a multi-factor model

[126.54s -> 134.50s] So I want to give you just an easy example. So let's say that we are going to estimate a two-factor model for a fictional company called Happy Bank.

[134.50s -> 147.84s] And our two factors, we're going to make this really simple. We're just going to have inflation and interest rates. Those will be the only two factors in the model. And so we go and we estimate the model with regression analysis and we get the following result.

[147.84s -> 162.13s] And so we've got this 0.11 here. That's going to be the expected excess return for Happy Bank. So that's 11%. That's the expected excess return. But now we've got to think about our two factors. We've got a factor here and we've got a factor here.

[162.13s -> 176.43s] And each of these factors, so it's a coefficient estimate is what we call this in a regression. So this 0.2 is telling us that if we have a one percentage point increase in inflation.

[176.43s -> 190.74s] Okay, so we have an unexpected 1 percentage point increase in inflation. Then that would lead to a 0.2 percentage point increase in the expected return. Okay, now conversely, now we have an...

[190.74s -> 204.94s] negative sign with our other factor so that means that if we were to have an unexpected 1% increase one percentage point increase in interest rates then that would predict that we would have a decrease of

[204.94s -> 219.15s] 0.4 percentage points in the expected return. Okay, so we don't have to have just two factors here. We could have a third factor that measures GDP. We could have a fourth factor. We could have a fifth factor.

[219.15s -> 229.84s] most famous of the multi-factor models is the Fama French model. And then also we've got Fama French Carhartt and so forth. And we'll talk about all of those in the videos to come.

[0.00s -> 14.42s] In this video, I want to walk you through a CFA level one exam style question on Jensen's alpha or simply alpha, which is a topic very much related to the capital asset pricing model. So if this is something you

[14.42s -> 21.90s] want to get right in the exam, do keep watching and let's get solving. So this is the question which I want us to have a go at.

[21.90s -> 35.79s] if you watch the previous two videos you will recall these figures for portfolio x y and z we've got some performance information including return standard deviation and beta we also have the return on the market portfolio 2.3 percent

[35.79s -> 50.06s] its standard deviation and a risk-free rate of return equal to 0.5 and we're asked about which portfolio offers the best performance as measured by jensen's alpha now jensen's alpha is

[50.06s -> 64.48s] basically something that we probably had already exposure to. I've definitely recorded previous videos on this, although I didn't call it alpha as such. It was all about whether a stock is generating returns.

[64.48s -> 75.39s] in excess or below the rate of return required under the CAPM model, given its level of systematic risk. So basically...

[75.39s -> 88.88s] this thing called alpha, which we also call Jensen's alpha, is equal to the return on the portfolio, either expected or, you know, historically experienced minus

[88.88s -> 101.52s] what the CAPM model would predict is the required rate of return. And that's obviously a function of the risk-free rate plus the beta of that specific portfolio times RM.

[101.52s -> 107.92s] minus rf where rm is the rate return on the market portfolio and rf is once again

[107.92s -> 122.03s] the risk-free rate of return and obviously if this relationship is positive if a portfolio is generating more than what's required by uh under the cap and model let me

[122.03s -> 134.50s] perhaps just finish this off with a nice square bracket at the end to close this off and make the formula complete well if this relationship is positive then a stock would be described as lying above

[134.50s -> 147.86s] the sml the security market line if the relationship is negative it's yielding less than what's required and that would respectively lead us to conclude that the stock is either

[147.86s -> 161.42s] undervalued if it's above or the sml or undervalued if it's below the sml and we've had previous questions on that comparison and whether stocks are under or overvalued okay so

[161.46s -> 172.53s] Let's compute this for portfolio X to start with. Its return is 2%. What would be predicted by the CAPM model?

[172.53s -> 186.42s] The RF is 0.5% plus the beta on this specific portfolio being 0.8 times the rate of return on the market, which is 2.3.

[186.93s -> 199.62s] minus 0.5 percent close the bracket okay i'm going to take my phone with the calculator and quickly do this not really sharing my phone screen with you as there is nothing um

[199.62s -> 205.26s] terribly exciting happening in terms of the computations so let me start with

[205.55s -> 218.93s] this 2.3 minus 0.5 that's obviously 1.8 times the beta of 0.8 okay plus 0.5 okay and i see

[219.86s -> 233.04s] A result equal to, let me write this down over here, it's going to be 0.06% and it's positive. So this suggests a little bit of alpha, very small.

[233.04s -> 243.31s] but a little bit of excess performance on a sort of risk-adjusted basis where we, as risk, we take into account systematic risk only.

[243.31s -> 255.02s] Good. So better than the required rate of return from the CAPM model. How about Y? Well, over here we're going to have...

[255.02s -> 269.01s] the return of four and a half percent minus the same thing as before 0.5 plus and the only thing that changes here is the beta which is going to be specific to the teach portfolio 1.6 other than that

[269.20s -> 276.58s] We've got 2.3 minus 0.5, just like before. So I know the term here in the...

[276.58s -> 290.86s] in the bracket is 1.8 so that's 1.8 times the new beta of 1.6 let's add 0.5 to that 3.38 okay and this is definitely going to yield something

[290.86s -> 299.02s] positive i see a positive difference of 1.12 percent so this stock definitely

[299.02s -> 312.29s] yields more than what would be required under the CAPM model given its level of systematic risk as measured by beta. So we would say that this stock is lying above the SML, the security market line.

[312.29s -> 324.40s] And we would also conclude that it is undervalued. Now, what about Z? For portfolio Z, we've got 6.2%. Once again, minus...

[324.40s -> 338.64s] square bracket 0.5 percent plus a beta of 2.5 and uh same thing as before in the bracket 2.3 minus 0.5 close both brackets

[339.41s -> 353.04s] So, this is 1.8 multiplied by a beta of 2.5 plus 0.5, okay, minus...

[354.51s -> 359.55s] And for this one, I see a result which is even higher.

[359.55s -> 371.22s] it's positive and it's 1.2 percent so that's a measure of the excess return above what's required and that will lead me to conclude that portfolio z is

[371.50s -> 380.46s] The one which performs best. It's got the best performances measured by Jensen's alpha. So, answer C.

[0.43s -> 12.67s] Helo, selamat hari. Dalam video sebelum ini, saya telah membincangkan beberapa teori portfolio dan harga aset utama dari teori portfolio moden pada tahun 1952

[12.67s -> 26.86s] ke Kepem pada tahun 60-an. Hari ini saya akan bergerak ke tahun 1970 dengan menunjukkan kepada anda teori yang mempengaruhi aset, teori harga arbitraj.

[26.86s -> 36.02s] Mari kita mengetahui bersama-sama apa itu APT dan bagaimana APT boleh digunakan dalam peningkatan aset.

[37.30s -> 49.17s] Pada tahun 1976, Stephen Ross mengembangkan Teori Pricing Arbitrasi. Dia mempunyai pendekatan multifaktor untuk menjelaskan harga aset.

[50.38s -> 61.33s] Sebelum kita bergerak ke kisah tentang APT, mari kita ambil masa untuk memahami konsep arbitrage. Kemudian anda akan dapat menghargai

[61.33s -> 75.10s] mengapa model yang dikembangkan oleh Stephen Ross dipanggil APT. Menurut definisi Valdi, Kane dan Marcus pada tahun 2011, arbitrage adalah penggunaan.

[75.10s -> 87.10s] peningkatan keselamatan dengan cara sebegitu bahawa keuntungan tanpa risiko boleh diperoleh. Menurut Herschel dan Nozinger dalam 2010, arbitrage

[87.10s -> 96.94s] hanyalah pembelian dan penjualan aset yang sama pada harga yang berbeza untuk menangkap peningkatan yang salah

[100.08s -> 113.78s] Peraturan Satu Harga mengatakan bahawa dua aset yang sama sepatutnya mempunyai harga pasaran yang sama. Peluang pembayaran akan muncul jika aset yang sama dihantar untuk harga yang berbeza.

[113.78s -> 124.35s] di dua lokasi yang berbeza. Perbelanjaan satu harga dilaksanakan oleh pembayar RBI yang akan mengambil kesempatan harga dalam kawasan ini.

[124.35s -> 136.21s] Penjual akan membeli aset di tempat yang murah dan menjual di tempat yang tinggi. Melalui mekanisme penjualan ini, harga akan berpindah kembali ke kawasan.

[136.30s -> 149.22s] Peluang arbitrage berlaku apabila pelabur dapat memperoleh keuntungan tanpa membuat pelaburan net.

[149.22s -> 160.19s] pelabur boleh menggunakan proses daripada jualan pendek untuk membeli long dan oleh itu transaksi boleh dibuat tanpa pelaburan

[160.19s -> 165.65s] Ini menjadikan transaksi transaksi yang tidak berguna

[168.46s -> 180.88s] APT adalah teori untuk menjelaskan keuntungan stok berdasarkan sensitiviti kepada banyak faktor risiko. Ia mengandung model linier.

[180.88s -> 192.13s] keuntungan dalam pelaburan boleh dijelaskan dengan lebih daripada satu faktor. Menurut APT, pasar adalah sempurna efisien jika

[192.13s -> 200.85s] tidak mungkin untuk menghasilkan keuntungan arbitrage tanpa risiko dengan membeli dan menjual aset yang sama

[202.42s -> 213.36s] APT mengatakan bahawa terdapat banyak faktor yang menyebabkan kembali, berbeza dengan KPM di mana risiko yang terkait sahaja adalah beta.

[213.68s -> 227.79s] APT tidak mengatakan apa faktornya. Contohnya, keuntungan stok perniagaan syarikat mungkin terpaksa oleh perubahan dalam harga minyak. Kebanyakan syarikat transport, seperti pesawat,

[227.79s -> 240.72s] akan mempunyai sensitiviti negatif kepada perubahan harga minyak. Beberapa syarikat akan lebih sensitif kepada faktor tertentu daripada syarikat lain. Contohnya, syarikat minyak

[240.72s -> 246.16s] boleh menjadi lebih sensitif kepada faktor minyak daripada industri pengguna

[249.04s -> 260.46s] APT adalah model yang lebih jeneralisasi daripada CAPM dan kurang restriktif dalam pengiraannya. Ada lima pengiraan yang ditandakan di sini.

[263.12s -> 274.16s] Ini menunjukkan model APT. Dalam formula ini, keuntungan sebenar pada aset dikalkulasi. ER bermakna keuntungan yang diharapkan

[274.16s -> 287.73s] F adalah setan faktor umum yang mempengaruhi keuntungan pada aset Beta adalah sensitiviti faktor pada keuntungan aset E adalah terma kesilapan

[287.89s -> 301.20s] Di sini, formula menunjukkan bahawa APT adalah proses stokastik yang menghasilkan keuntungan aset yang boleh dikatakan sebagai fungsi linear setiap faktor risiko

[302.77s -> 313.58s] The APT can also be expressed in terms of expected risk premium. Expected risk premium is the actual return minus risk free rate.

[313.58s -> 327.22s] APT mengatakan bahawa premium risiko yang diharapkan pada stok harus bergantung pada premium risiko yang diharapkan terkait dengan setiap faktor dan sensitiviti stok kepada setiap faktor

[328.62s -> 334.06s] Mari kita gunakan formula APT dalam contoh ini

[342.80s -> 350.48s] Apa jawapan anda? Jawapan adalah C

[354.93s -> 362.80s] Mari kita cuba contoh lain. Di sini kita mempunyai portfolio A dan B. Apa yang akan anda lakukan?

[372.94s -> 385.28s] Jika anda mahu mengambil kesempatan arbitrage, anda harus mengambil posisi pendek dalam portfolio B dan posisi panjang dalam A. Mengapa begitu?

[385.28s -> 394.35s] kerana A di bawah nilai dan B di atas nilai apabila mereka terhadap risiko yang sama F

[398.86s -> 403.50s] Saya harap anda dapat memahami sesi ini. Jumpa lagi dan selamat tinggal.

[0.00s -> 9.76s] In this video we are going to discuss cost-based pricing strategy and one very important concept associated with cost-based pricing strategy.

[9.76s -> 21.60s] now in another video we talked about different types of cost based pricing strategy like the cost plus pricing and markup pricing but in this video we are going to talk about break even pricing

[21.60s -> 34.51s] break-even pricing is a very important concept in pricing strategy because break-even pricing is the price at which you are able to recoup all your cost right so your profit is zero

[34.51s -> 47.12s] the revenue that you are going to get is equal to the cost that you are incurring so if you can find out your break-even price then you know that a price higher than the break-even price would lead to profit

[47.12s -> 60.42s] and a price lower than the breakeven price would lead to a loss. Now let's do some calculations to understand this concept a little bit more. Now we know that profit equals to

[60.42s -> 72.54s] total revenue minus total cost now we know that total revenue is a multiplication of your price times quantity which we will turn p times q here

[72.54s -> 84.46s] We also know that your total cost consists of fixed cost and variable cost where the variable cost is the unit variable cost multiplied by the quantity.

[84.94s -> 98.06s] Whereas the fixed cost is represented just by the fixed cost Now since we have profit equals total revenue minus total cost Our equation comes out like this